Integrating functional connectivity in designing networks of protected areas under climate change: A caribou case-study

Sarah Bauduin; Steven G Cumming; Martin-Hugues St-Laurent; Eliot J B McIntire

doi:10.1371/journal.pone.0238821

. 2020 Sep 30;15(9):e0238821. doi: 10.1371/journal.pone.0238821

Integrating functional connectivity in designing networks of protected areas under climate change: A caribou case-study

Sarah Bauduin ^1,², Steven G Cumming ¹, Martin-Hugues St-Laurent ^3,^*, Eliot J B McIntire ^1,⁴

Editor: Laurentiu Rozylowicz⁵

PMCID: PMC7526922 PMID: 32997673

Abstract

Land-use change and climate change are recognized as two main drivers of the current biodiversity decline. Protected areas help safeguard the landscape from additional anthropogenic disturbances and, when properly designed, can help species cope with climate change impacts. When designed to protect the regional biodiversity rather than to conserve focal species or landscape elements, protected areas need to cover a representative sample of the regional biodiversity and be functionally connected, facilitating individual movements among protected areas in a network to maximize their effectiveness. We developed a methodology to define effective protected areas to implement in a regional network using ecological representativeness and functional connectivity as criteria. We illustrated this methodology in the Gaspésie region of Québec, Canada. We simulated movements for the endangered Atlantic-Gaspésie caribou population (Rangifer tarandus caribou), using an individual-based model, to determine functional connectivity based on this large mammal. We created multiple protected areas network scenarios and evaluated their ecological representativeness and functional connectivity for the current and future conditions. We selected a subset of the most effective network scenarios and extracted the protected areas included in them. There was a tradeoff between ecological representativeness and functional connectivity for the created networks. Only a few protected areas among those available were repeatedly chosen in the most effective networks. Protected areas maximizing both ecological representativeness and functional connectivity represented suitable areas to implement in an effective protected areas network. These areas ensured that a representative sample of the regional biodiversity was covered by the network, as well as maximizing the movement over time between and inside the protected areas for the focal population.

Introduction

Habitat change is recognized as the main driver of the current declines of terrestrial species [1–3]. Securing habitats by creating or expanding protected areas networks is part of the solution to counter biodiversity loss [4]. A regional protected areas network could be considered ultimately effective insofar as it can sustain the region’s biodiversity into some reasonably foreseeable future. Such effectiveness is not guaranteed [5, 6] and could be limited by many factors [7]. We consider three such factors: ecological representativeness [8], functional connectivity among protected areas within the network [9] and resilience to climate change [10].

Ecological representativeness measures the degree to which the various non-anthropogenic habitats or ecosystem types (sensu [11]) within a focal region are available within a protected areas network in proportion to their regional abundance [12, 13]. When protected area locations are skewed towards certain habitats [14, 15], usually for economic or social reasons, ecological representativeness will be low, and habitats considered to be of high-value for some species may be underrepresented [8]. Conversely, when ecological representativeness is high, it is reasonable to assume that the habitat requirements for many species will be satisfied within the protected areas network. This assumption is usual in conservation, and representativeness is one of the core concepts in systematic conservation planning [13, 16].

A high degree of ecological representativeness may be a necessary condition for an effective protected areas network, but it is not sufficient. There are species whose requirements are not automatically satisfied by ecological representative networks, such as endemic or threatened species [17]. Another exception, which we explore here, would be wide-ranging species with habitat requirements varying among seasons or life history stages. Functional connectivity is “the degree to which the landscape facilitates or impedes movement among resource patches” [18] or, in this case, among protected areas within a protected areas network. Functional connectivity is species- or population-specific [19, 20]. A protected areas network with high functional connectivity facilitates the movement between different protected areas for individuals of a given species, increasing their access to resources and, ultimately, the rates of recruitment or survivorship [21]. Increasing functional connectivity may thus increase population size and decrease extinction risk for the vulnerable species [21]. These effects would increase the effectiveness of a protected areas network.

Climate change is a major driver of ecosystem change and its negative impacts on biodiversity have increased rapidly over the past century [1, 3, 22, 23]. Climate change disrupts environmental patterns and species’ habitats globally [24, 25]. As a result, species distributions and individual movement patterns are impacted [26, 27]. Because of the “cost of waiting,” managers should proactively account for future climate change effects when implementing new protected areas networks [28] or expanding existing networks. The effectiveness of a fixed protected areas network designed for current conditions may decrease in the future if ecological representativeness or functional connectivity decline. Enhancing or maintaining functional connectivity inside protected areas networks is thus one approach to helping species cope with climate change [10, 29]; individuals would be better able to access resources available in distant protected areas, or even to migrate from less to more favorable areas. Therefore, the ability of a protected areas network to sustain functional connectivity under climate change is another dimension of effectiveness.

Many methods exist for designing protected areas networks to achieve ecological representativeness. In the systematic conservation planning literature [13], variations of the site selection problem are posed, where one seeks a subset of available sites that, in aggregate, achieve some measure of ecological representativeness at a near-minimum of total area or cost. Variations of these approaches exist that can also partially satisfy other conservation objectives such as topological connectivity, where selected sites are spatially aggregated to some degree [e.g. 30].

The aim of our paper is to present a new method to include functional connectivity in the design process, while also accounting for its persistence under climate change. Our method applies individual-based movement models to simulate maps of habitat use by a population, under present conditions and under hypothetical future conditions reflecting climate change scenarios. From these maps, we derive numerical indices of functional connectivity that allow alternate protected areas network designs to be compared. These are coupled with a novel variant of the site-selection algorithm that constructs protected areas networks of specified total area that can achieve a high degree of ecological representativeness while also satisfying secondary constraints on hydrological connectivity and intactness; the variant is detailed in Schmiegelow et al. [31] and an example of application can be consulted in Saucier [32].

Our goal was to identify protected areas network designs that simultaneously achieve high degrees of ecological representation and functional connectivity under present conditions and future climates. Achieving this is a multi-objective optimization problem [33, 34] that does not admit a unique solution. Instead, one may define a tradeoff surface by those points or “feasible solutions” where no single objective can be increased without decreasing at least one other. Such points are said to be Pareto optimal; points on the interior of this surface are suboptimal in that other solutions exist that are better in terms of all the dimensions considered [35]. Our design methodology used randomization to generate a large sample of feasible solutions for a given protected areas network design problem. Using these samples, we could approximately define the tradeoff-surface and identified a set of feasible, near-equivalent solutions in the vicinity of any specified point on that surface.

We illustrated our method in the Gaspésie region (Québec, Canada) using the endangered Atlantic-Gaspésie population of woodland caribou (Rangifer tarandus caribou) as our focal population. This isolated herd, which has been identified as one of 12 Designatable Caribou Units considered irreplaceable components of Canada's biodiversity [36], has been declining since the late 19^th century and has reached a critical abundance level [37]. To measure functional connectivity with respect to this population, we applied an individual-based model of animal movement previously developed for this population [38]. The Québec government is currently engaged in expanding the existing network of protected areas in this region to attain a proportional area target of 12% [39]. To place our work in the context of this ongoing conservation planning exercise, we employed a variant of our design methodology that constructs protected areas networks by adding new protected areas to the existing network. We identified areas that were of high relative importance in achieving ecological representation in the Gaspésie region and functional connectivity for the Atlantic-Gaspésie caribou under present conditions and future climates.

Methods

Overview

We present a method to identify potential areas to prioritize to create an effective protected areas network in a given region, conserving both the regional biodiversity, represented by biophysical surrogates as well as focal, highly mobile endangered species, while also accounting for climate change. We illustrated this method in the Gaspésie region of Québec, Canada (Fig 1) using an individual-based model we developed previously [38] and for which we used telemetry data collected on several individuals. We had an Animal Welfare certificate (#52-13-112) for the capture and manipulation of these caribou, but for the current manuscript, no additional capture session was conducted.

Fig 1 — The Gaspésie National Park (i.e. the black area designated by a white star) encompass most of the range and all the breeding habitats used by the Atlantic-Gaspésie caribou population. Right inset: Province of Québec (Canada) with study area outlined.

We built candidate protected areas (hereafter referred to as CPAs) in the region and integrated random subsets of these with the existing protected areas (Fig 1) to create a large sample of candidate networks of the desired total area. Each candidate network was then evaluated for effectiveness. High priority conservation areas were identified as the CPAs that occur most frequently in the most effective networks. The complete workflow is summarized in Fig 2.

Fig 2 — Schematic of workflow for assembling candidate protected areas networks (bottom panel) from candidate protected areas (middle panel), which are constructed as hydrologically connected groups of intact hydrological catchments (top panel) rooted at the headwaters (shown in blue).

Study area

The Gaspésie natural region (latitude extent: 47.98 to 49.20º N, longitude extent: 64.11 to 67.57º W; Fig 1) is a physiographically defined area of approximately 25,000 km² at the eastern end of the Gaspésie Peninsula, in eastern Québec [39]. Except for narrow coastal bands, it belongs to the balsam fir–white birch bioclimatic domain [40]. The climate is maritime with abundant precipitation. Wildfire is infrequent; the main natural disturbance is spruce budworm (Choristoneura fumiferana) outbreaks [40]. Approximately 90% of the region is covered by forests and 80% of these are on public lands [39]. Forest harvesting and the associated extensive road network are the main proximate human disturbances to date. Only 34% of the Gaspésie natural region is free of measurable human footprint [39].

An existing protected areas network covers 5.5% (1371 km²) of the region (Fig 1). This falls short of the target of an ecologically representative 12%, set by the government of Québec [41]. A scenario proposed by the Ministère du Développement Durable, de l’Environnement et de la Lutte aux Changements Climatiques (“the Ministry”, henceforth) defined 20 new protected areas that would increase the percentage of area protected to 12.3% (3080 km²) [39; Fig 1].

The Gaspésie National Park (802 km²) is the largest protected area in the region [42]. This park helps conserve 42 endangered and vulnerable species of plants and animals [39], including the Atlantic-Gaspésie caribou population. Because of its designated status as endangered [43], its capacity to move widely [44] and the vulnerability of its habitat [45], we chose this caribou population as our focal population to define functional connectivity. The population is designated because of its small size (currently ~70 individuals [37]) and the observed long-term decline [46]. These caribou rely on alpine tundra [47, 48] as a predator-free refuge against coyotes (Canis latrans) and black bears (Ursus americanus) [49], a habitat possibly threatened by climate change [50, 51]. Caribou also use mid-elevation, old fir forests during winter [47,48]. The fir forests around the park are affected by forest harvesting, and also possibly by climate change [52].

Building protected areas networks

We adapted the BEACONs (Boreal Ecosystems Analysis for Conservation Networks) approach to create protected areas networks by adding new protected areas to the existing ones [31, 32]. This approach uses mapped hydrological catchments as spatial units, rather than using the cells of an arbitrary grid or other tessellation (Fig 2). This allows the design of protected areas that simultaneously achieve terrestrial and hydrological connectivity [53, 54]. Although functional connectivity for aquatic species was not a major concern in our study area [39], it is increasingly recognized as a desirable goal in general [55]. The use of hydrological catchments does impose some limits on the shape and size of protected areas, due to the size of catchments and the method of stream network traversal; however, the size of the catchments was small, implying high spatial resolution to the design. CPAs are assembled as contiguous, hydrologically connected sets of catchments satisfying minimum size and intactness criteria (Fig 2). Using an initial “seed” catchment as starting point, a modified breadth-first traversal of the stream network is carried out. Catchments are added as they are encountered, provided they satisfy a catchment-level intactness criteria. The process continues until the target size is achieved, or all pathways are blocked by headwater or non-intact catchments.

We used a custom 1:50,000 catchment layer for Gaspésie [56] (Fig 2). The catchment’s average size was 2.3 km² (SD = 1.3 km²). We defined catchment intactness using existing 250 x 250m raster maps of the human footprint in Gaspésie [39]. These maps defined six disturbance types: forestry activities, roads and trails, agriculture, power-line rights-of-way, urban areas, and “other”. Only the first two of these disturbance types were widespread in our study area. From the six disturbance rasters, we derived a 250 x 250m raster of cell-level intactness, using a value of 0 for cells where no disturbance of any type was present, and a value of 1 otherwise. Catchment-level intactness was then calculated as the mean cell-level intactness over all cells within a catchment, or equivalently, as the proportion of non-intact cells. We defined our catchment-level intactness criteria as the median catchment intactness over all catchments on public lands, outside of existing protected areas (median value = 0.026) (Fig 2). In order to create feasible designs given land ownership in Gaspésie, we set the intactness of catchments completely overlapping private lands [39] to zero so that they would be excluded from the CPA construction (Fig 2).

Our measures of cell and catchment-level intactness give equal weight to each disturbance type. This was not applied, in general, at the species level. The response to different disturbance types is known to differ among species, as shown by Toews et al. ([57]) in Alberta for wolves (C. lupus), meso-carnivores and large ungulates, or more precisely within our study area for caribou, coyotes and bears that respond differently to recent harvesting, forest roads and hiking trails [58]. However catchment intactness as a design criteria was intended to be relevant to biodiversity more broadly, not to any particular species. Equal weighting of disturbance types reflects different responses to disturbances across species, and is thus a conservative assumption.

We prioritized the inclusion of headwater catchments in protected areas, because of their hydrological importance and to reduce the potential for upstream river contamination inside protected areas [59]. Accordingly, we used all intact headwater catchments as seeds. We used the mean size of the new protected areas proposed by the Ministry (Fig 1; mean = 85.5 km², SD = 61. 4 km²; [39]) as the target size. We then applied the construction process to each seed catchment, with target size and catchment intactness criteria as defined above. The procedure returns a list of the catchments selected and their total area. If this total area satisfied the target size, the result was accepted as a candidate protected area. The construction adds entire catchments one at a time, so target sizes are generally exceeded rather than satisfied exactly (Fig 2). Because the mean catchment area (2.3 km²) was small relative to the target size, we consider such discrepancies negligible. The minimum size of the Ministry’s proposed new protected areas was 31.2 km² [39], which is only 36.5% of our target size. To make our size criteria more comparable to theirs, we also accepted, as candidate protected areas, constructions smaller than the target size but larger than this minimum. Candidate protected areas satisfy, by construction, the criteria of size, intactness and hydrological connectivity [31]. They are not designed to satisfy ecological representativeness or functional connectivity criteria. These criteria pertain to networks of protected areas, not to individual protected areas.

We used the set of selected candidate protected areas to generate a sample of 500,000 candidate protected areas networks (Fig 2). Each candidate network was constructed by adding a random sequence of candidate protected areas to the existing network, until the summed area of unique catchments exceeded the Ministry’s area target of 3080 km² (Fig 2). The candidate protected areas included within a given candidate network may overlap with each other or with elements of the existing network, but this does not affect the candidate network area. It is easy to show that the properties of hydrological connectivity and intactness are conserved by aggregating overlapping candidate protected areas. Thus, the only material consequence of such overlap is that spatially disjunct network elements may exceed the minimum size criteria, and may be fewer than expected based on the number of candidate protected areas that were added. However, other things being equal, larger protected areas are preferred [60], and the number of spatially separated components is not one of our network design criteria, so we do not consider this overlap of relevance to the present study.

Network ecological representativeness

Ecological representativeness is measured at the candidate network level [31], in terms of four environmental attributes: elevation, surficial deposit, drainage class and potential vegetation type [39] (Fig 2). Potential vegetation was defined by the Ministère des Forêts, de la Faune et des Parcs du Québec (MFFP) as the vegetation present on a site or potentially present, in the absence of disturbance [41]. Surficial deposit, drainage class and potential vegetation type had been used for a gap analysis conducted to inform the proposed expansion of the existing protected areas network [39]. The four attributes define habitats independent of human activities such as harvesting history. All four attributes were available for the entire study and were provided by the Ministry. Catchment-level attributes were calculated by intersecting a shapefile of the catchment layers with the various raster grids and taking means for continuous attributes and frequency tables for categorical attributes.

We measured candidate network representativeness using nonparametric, two-sample univariate dissimilarity measures. For each attribute, we obtained its distributions over all catchments within the candidate network, and over all other catchments within the study region. For continuous attributes (e.g., elevation), we calculated a two-sample Kolmogorov-Smirnov statistic. For categorical attributes (e.g. surficial deposit, drainage class, and potential vegetation type), we calculated the Bray-Curtis statistic. These statistics ranged from 0 to 1, measuring a candidate network’s deviation from perfect representation with respect to an attribute, and were equal to 0 only when the two distributions are identical. The univariate statistics for multiple attributes were combined into a univariate distance metric by calculating a Euclidean norm [31, 32]. We took the inverse of this distance metric as the ecological representativeness score for each candidate network, so that a larger score indicates a greater degree of representativeness.

We also calculated the representativeness score of the Ministry’s proposed network. To do this, the protected areas within this network were approximated to the resolution of hydrological catchments. Because these catchments were relatively small, we assumed approximation errors to be negligible. We note that this measure of ecological representativeness does not depend on the specific choice of ecological attributes or on the specifics of our design methodology; it can be applied to any existing protected areas network using whatever ecological attributes are of interest.

Network functional connectivity

We defined candidate network functional connectivity for the Atlantic-Gaspésie caribou population using a spatially explicit individual-based movement model (IBM) adapted from Bauduin et al. [38, 61] (Fig 2). This model simulates caribou movement as a two-state behavioral model process with a habitat-mediated random walk in habitats of high quality and a foray loop movement in habitats of low quality. The IBM includes the attraction of individuals’ mating areas during mating season. Habitat quality is modeled using a Resource Selection Function (RSF; [62, 63]) model developed for this specific population of caribou [58] and based on four habitat types relevant to this population (i.e., alpine tundra, mature fir stands, regenerating stands and stands of other tree species, primarily broad-leaved species) as well as three classes of transportation routes (paved roads, gravel/secondary roads, and hiking trails). These landscape components represent resources or barriers for the caribou (e.g., alpine tundra and mature fir stands for food resources and shelter from predators, paved roads as movement barriers) or proxies for the presence of their predators (e.g., regenerating stands where bears and coyotes frequently occur).

The original model was re-estimated from newly available GPS locations [44, 64]. Model movement behavior is partially driven by spatial variation in habitats as described by the RSF. Following Bauduin et al. [38, 61], we generated five different habitat maps to represent the current landscape and four landscapes for 2080 forecast under different climate change scenarios. The current landscape was derived from the ecoforestry maps from Québec’s 4^th decennial forest inventory program (source: MFFP). The future landscapes represented a range of potential climate change impacts (none: CC₀; minimum: CC_Min; moderate: CC_Med; high: CC_High) on vegetation dynamics and natural disturbances, combined with predicted cumulative timber management for 2080. Primary impacts were reduced areas of tundra [50, 65] and of fir forest [52], and a decreased severity of spruce budworm outbreaks [66, 67] leading to less area with young fir stands. A complete description of the four climate scenarios and of the construction of the corresponding 2080 landscapes is given in Bauduin et al. [61] (and in the S1 Material). A fifth scenario represented current conditions.

For each landscape, we created 20 individuals in each of the three caribou subpopulations (see [38]; current population estimates are 20, 35 and 15, [37]) and ran 10,000 replicates of four-year model simulations. For each scenario and replicate, we calculated and mapped the number of caribou visits per 1-ha landscape cell (see S2 Material). For each candidate network, under each scenario, we measured network functional connectivity by taking the mean, over replicates, of the number of caribou visits in cells within the network’s protected areas. This represented the simulated movement patterns within and between the protected areas. The differences in results between climate scenarios were relatively small. We considered evaluating differences between them to be unimportant relative to our core message concerning the inclusion of functional connectivity in a protected areas network design. Accordingly, and because no climate change scenario was defined as more likely than another, we used the mean functional connectivity over the four climate change scenarios as an index of network connectivity under future conditions (S2 Material). We calculated the functional connectivity of the Ministry’s network under current and future conditions in the same way.

Identifying priority conservation areas

By plotting the distributions of indicators (i.e., ecological representativeness, current and future functional connectivity), the outlines of the tradeoff surface may be visualized. To identify one specific location on this surface, we incrementally decreased a quantile threshold Q from 1 to 0 by steps of 0.001 to find the maximum Q for which at least 500 networks had indicator values above the Q-th quantile for each of the three indicators. This identified a subsample of 0.1% of the candidate networks that were highly ranked under all three criteria. This represents a level of tradeoff which, informally, values all three attributes equally. We then identified the candidate protected areas included in the network subsample, calculated their selection frequencies, and mapped their locations color-coded by selection frequency. These selection frequencies may be interpreted as priorities for including candidate protected areas within a new or expanded protected areas network [30]. Similarly, spatial clusters of high priority areas may highlight regions of high importance relative to network conservation goals. We set a selection frequency threshold for high priority catchments by plotting the selection frequencies in decreasing rank order, and identifying an inflection point on this curve. We then added the locations of high priority catchments to the above-mentioned map. To evaluate the sensitivity of the priority conservation areas selection to the choice of conservation goals, we applied the preceding analysis to two alternate rankings of the same set of 500,000 candidate networks. In the first instance, we ranked the networks by ecological representation alone. Then, we ranked them according to their joint functional connectivity under current and future conditions.

Results

Protected areas networks

We constructed 690 unique candidate protected areas satisfying our size and intactness criteria. Their mean size was 86.8 km² (SD = 4.0 km²), only very slightly larger than the target size of 85.5 km². The 500,000 candidate protected areas networks (candidate networks) included a mean of 25 (SD = 2.2) candidate protected areas added to the 62 existing protected areas. The mean candidate network area was 3138.5 km² (SD = 24.6 km²), again slightly larger than the target of 3080 km². Network ecological representativeness scores ranged from 2.76 to 7.63 (mean = 4.71, SD = 0.64) (Fig 3). Network functional connectivity ranged from 4.21e⁺⁰⁵ to 4.79e⁺⁰⁵ (mean = 4.38e⁺⁰⁵, SD = 9.42e⁺⁰³) under current conditions (Fig 3A), and from 4.41e⁺⁰⁵ to 5.00e⁺⁰⁵ (mean = 4.58e⁺⁰⁵, SD = 9.51e⁺⁰³) under mean future conditions (Fig 3B). There was a negative relationship between ecological representativeness and functional connectivity, under both current (slope = -3922, p < 0.001, Fig 3A) and mean future conditions (slope = -3779, p < 0.001, Fig 3B).

The Ministry’s proposed network (Fig 1) had an ecological representativeness score of 4.65 (Fig 3A), which was slightly lower than our sample mean. Its current and future functional connectivity were 4.59e⁺⁰⁵ and 4.76e⁺⁰⁵, respectively, both above our sample means (Fig 3A and 3B). However, our methodology yields many candidate networks that surpass the Ministry’s proposed design in both representativeness and functional connectivity (Fig 3A and 3B). We conclude that the Ministry’s design is suboptimal with respect to these three indicators of network effectiveness.

Priority conservation areas

The quantile Q = 0.925 (92.5%-ile) yielded a subsample of 501 candidate protected areas scoring above the corresponding sample quantiles of all three indicators simultaneously (Fig 3). The ecological representativeness quantile was 5.68. The quantiles for current and future functional connectivity were 4.53 x 10⁵ and 4.73 x 10⁵, respectively. All 501 selected designs had higher ecological representativeness scores than did the Ministry’s. Most of these 501 designs did not exceed the Ministry’s functional connectivity scores, but some did (Fig 3): 78/501 designs had higher functional connectivity under both current and future conditions. That is to say, we identified some designs for the given tradeoff that outperformed the Ministry’s design with respect to all three indicators.

All but one of the 690 candidate protected areas were included in at least one of the 501 selected networks. Selection frequencies were highly skewed (Fig 4). At the inflection point (32,35) on the graph, 32/689 candidate protected areas were included in at least 35/501 selected networks (Fig 4). These 32 priority candidate protected areas were fairly widely distributed over the study region (Fig 5), with some spatial clustering in the southwest of the Gaspésie National Park, and in the areas adjacent to the extreme west of the park (Fig 1), which includes the important high elevation caribou breeding habitats. The spatial distributions of high priority catchments under alternate conservation objectives were markedly different (S3 Material). In designs emphasizing ecological representation, priority areas were more widely distributed, but mostly in the south of the Gaspésie National Park, and none were adjacent to the Park (S3.1 Fig in S3 Material). In designs emphasizing only functional connectivity for caribou, all priority areas were adjacent to the Park (S3.2 Fig in S3 Material).

Fig 4 — These candidate networks included 689 of the 690 candidate protected areas (CPAs). The selection frequencies (y-axis) of these 689 CPAs are plotted in decreasing rank order (x-axis). Only 32/689 CPAs were included in more than 35/501 selected networks. This inflection point of the curve is indicated by the light grey lines perpendicular to the axes.

Fig 5 — The 689 Candidate Protected Areas (CPAs) included in the subsample of 501 near-Pareto-optimal networks are shown in orange scale, coloured by selection frequency, from low (light orange) to high (dark orange). The 32 CPAs included in more than 35/501 networks (Fig 4) are outlined with a thick line. The existing protected areas are shown in black.

Discussion

We present a methodology to define an effective protected areas network based on the tradeoff between ecological representativeness and functional connectivity over time, including the potential impacts of climate change. Our methodology yields a proposed subset of protected areas that may be close to ideal from an environmental or conservation point of view, but which does not fully respect all constraints of the use of public lands. For example, the Gaspésie region is highly disturbed by human activities. Considering all the social and economic constraints would have reduced too much the area for potential new protected area implementations, giving little space for designing different network scenarios or exploring the limits of what is possible. However, this methodology could easily include more features in the choice of the best network scenarios, and the proposed top protected areas would then be represented as the best tradeoff between all selected features. It would be possible, given data availability, to add constraints in the choice of the networks with, for example, the ecological representativeness of the future landscape under climate change, the functional connectivity of several species important for the ecosystem [68], the economic cost of excluding human activities from the proposed areas, the potential benefit with tourism if protected areas act as parks [69], or any of the other factors affecting the Ministry’s design. Target features and constraints can be defined by local managers to help meet local biodiversity goals, and could easily be implemented in our method to improve the design of regional protected areas networks.

Network ecological representativeness

Gap analyses are a common tool to quantify ecological representativeness of extant networks and to identify underrepresented features [e.g. 8, 70]. Here, we adapted an alternate two-stage approach that was recently developed in Canada [31, 32] to support systematic conservation planning in the boreal region. The first stage of that method used geospatial analysis tools to construct potential or candidate protected areas, which were then assembled into networks. A multivariate distribution matching methodology identified networks that minimized gaps. Gaps were quantified as dissimilarities, with respect to the distributions of a chosen set of environmental covariates, between the network and the rest of the study region.

Network functional connectivity

Many studies have included connectivity in conservation planning using measures of distance or the cost of movement between protected areas [71] or applying graph and circuit theory techniques [72, 73]. A novel feature of this study was that we derived network functional connectivity measures from movement simulations using an individual-based model [38, 61] that reproduced known characteristics of the focal population within the study region. The model accounted for process-based complex movement behaviors (e.g., seasonal site fidelity, foray loop movement) that would be difficult to represent in static habitat-based models. Being process-based, the models reflect behavioral responses to environmental conditions and should be preferred to make predictions under future conditions compared to models based on only observed habitat where the suppositions underlying current empirical relationships may no longer hold [74].

Accounting for climate change

It is more efficient to take future climate change impacts into account now instead of reacting to them only once changes occur [28]. To account for climate change, we defined the future functional connectivity criteria using simulated movements on hypothetical landscapes resulting from different climate change scenarios. Network effectiveness will likely depend on the realized landscape outcome which is presently unknown. Therefore, networks selected using an average functional connectivity over a wide range of climate change impacts would be suboptimal for any particular climate change scenario. However, they might perform reasonably well under a large range of possible future environmental conditions. The differences in movement predicted for the different climate change scenarios resulted from the assumptions made about the future environmental conditions. We used this relatively simple approach as the functional connectivity differences among the scenarios were not particularly large. This suggests that using coupled climate change and vegetation change dynamic models may not dramatically improve the choice of protected areas in this region. Furthermore, since no climate-sensitive model of vegetation dynamics was available for Gaspésie natural region, using the scenario approach with averaging of results seemed to be a reasonable compromise to account for uncertainty in future conditions. Our approach could readily be adapted to cases with much greater divergence among expected future conditions, at the price of increasing the dimensionality of the tradeoff surface. Management decisions in that case would ideally be based on weighting the relative costs of possible solutions and the probabilities associated with each alternate outcome.

Case study

The lack of functional connectivity during the last 20 years between the different major mountain summits of the Gaspésie National Park has led to a division of the caribou population into two genetically distinct sub-populations and is now jeopardizing the persistence of this isolated population [75]. Consequently, using an approach that could identify key elements to preserve in order to maintain functional connectivity could benefit the conservation of an endangered caribou population, especially under a changing climate.

In the Gaspésie region, there is only one caribou population occurring primarily inside the Gaspésie National Park [37, 48]. Consequently, in our analyses, networks with high functional connectivity tended to include many protected areas adjacent to or near this park. On the other hand, to achieve high ecological representativeness, protected areas needed to be more or less evenly distributed over the entire region to capture habitat diversity. There was therefore a negative relationship between representation and connectivity in our case study, as others have found [e.g. 76]. It is, in general, not possible to simultaneously optimize for multiple design criteria. Our sampling-based design methodology allows us to approximate a multidimensional tradeoff surface. Given the management decision about the choice of tradeoff, we can identify a large number of solutions that are close to this point. Our methodology showed how to design new protected areas for a regional network that satisfy multiple, divergent criteria to (nearly) the highest degree possible. Other tradeoffs between the two objectives of representation and caribou conservation could be defined. The two extremes (S3 Material), in which only one criterion is emphasised, produce very different spatial distributions of priority candidate protected areas. Our chosen tradeoff produced an intermediate result, indicating that new protected areas in the south of the study region are needed to improve ecological representation, and that an expansion of Gaspésie National Park would best improve functional connectivity for caribou. However, the designs considered in Fig 5 are not intended or represented as optimal for caribou conservation per se.

The protected areas network expansion proposed by the Québec government to achieve the 12% coverage target that we used as a comparison was different than the sample of candidate protected areas suggested from the selected best networks identified here (Figs 1 and 5). The Ministry’s network achieved a lower ecological representativeness than our selected networks. However, they had to respect design criteria and constraints, like socio-economic issues or the inclusion of rare ecosystems that we did not consider. This could explain the suboptimal ecological representativeness achieved by their network. Regarding functional connectivity, their network seems well connected from the Atlantic-Gaspésie caribou point of view. The performance of their scenario is surprisingly quite good for this feature, considering it was not explicitly part of their design. The networks we selected may not achieve such a high functional connectivity because our specific choice of intactness criteria resulted in some areas being excluded from any of our network solutions. In particular, we excluded some non-intact areas close to the Gaspésie National Park that were included in the Ministry’s design.

Supporting information

S1 Material. Construction of the potential future landscapes.

(DOCX)

Click here for additional data file.^{(38.5KB, docx)}

S2 Material. Caribou movements in the current and future landscapes.

(DOCX)

Click here for additional data file.^{(193.4KB, docx)}

S3 Material. Description of the optimal protected areas networks.

(DOCX)

Click here for additional data file.^{(671.8KB, docx)}

Acknowledgments

We thank the Canadian BEACONs Project (http://www.beaconsproject.ca) for developing and sharing methods and software for protected areas design, and for providing the custom hydrological catchments. We also thank BEACONs members M. Houle, K Lisgo and P. Vernier for their help with the use of the BEACONs toolkit. We thank the Ministère de l’Environnement et de la Lutte aux Changements Climatiques du Québec (D. Boisjoly, F. Brassard and S. Benoit) and the Ministère des Forêts, de la Faune et des Parcs du Québec for the data and documents provided. We finally thank K. Malcolm and three anonymous reviewers for their constructive comments on an earlier version of this manuscript.

Data Availability

Data cannot be completely shared publicly because of the Endangered Status of the Atlantic-Gaspésie caribou population, so data that could help track and find these animals won't be made available publicly. However, the modeled data we used to quantify the balance between ecological representativeness and functional connectivity will be made available in a public repository (DRYAD #https://doi.org/10.5061/dryad.612jm641c) upon acceptance. However, the telemetry data collected on these endangered caribou population can be made available upon request by qualified researchers if they contact Prof. Martin-Hugues St-Laurent at Université du Québec à Rimouski (martin-hugues_st-laurent@uqar.ca) or services.clientele@mffp.gouv.qc.ca. Being co-owner of the data (along with the Québec Ministry of Forests, Wildlife and Parks), please note that I’ll then have to transfer the request to the authorities of the QMFWP to obtain their permission too.

Funding Statement

Funding for this project was provided by: - the Québec Fonds Verts (S.G.C., E.J.B.M.) (URL: http://www.environnement.gouv.qc.ca/ministere/fonds-vert/) - the Ouranos Consortium (S.G.C., E.J.B.M.) (URL: https://www.ouranos.ca/) - the Centre d’étude de la forêt (S.B.) (URL: http://www.cef-cfr.ca/) - Natural Sciences and Engineering Research Council Discovery Grants (E.J.B.M., S.G.C.) (URL: https://www.nserc-crsng.gc.ca/NSERC-CRSNG/) - the Canada Research Chair’s program (E.J.B.M.) (URL: https://www.chairs-chaires.gc.ca) -the French National Research Agency (ANR‐16‐CE02‐0007, S.B.) (URL: https://anr.fr/en/).

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PLoS One. doi: 10.1371/journal.pone.0238821.r001

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Laurentiu Rozylowicz

19 Mar 2020

PONE-D-20-04608

Coping with climate change when designing networks of protected areas by accounting for functional connectivity: a case-study with caribou

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Reviewer #1: Thank you for the opportunity to review this manuscript. While this is an interesting spatially explicit study on a topic of high conservation relevance and immediate urgency, I have several concerns. My main concern with this study is that it places considerable emphasis on ecological representativeness, which is basically the landscape variability in the study area. Whereas the stated goal (e.g., right from the title) is to help devise an optimal protected area network for endangered caribou specifically.

I understand the desire to represent the broader landscape in the protected area network. I also see the appeal of providing a spatially informed means to enable trade-offs between ecological representativeness and functional connectivity for caribou. I think this is a noble scope. Overall however I see this approach as lacking comprehensive consideration of caribou population needs, resulting in an analytical framework and reporting that do not adequately address the life history challenges of caribou in the study population. Perhaps the Individual Based Model (IBM) encapsulates a wealth of ecologically relevant information, but that needs to be detailed herein. In particular, what were the set of rules set for the IBM? Where do food availability and predation risk fit in here? Are these encapsulated in the functional connectivity component?

The authors must provide details on what caribou in their study populations actually prefer. I suspect that caribou like and do better in specific landscape features that do not reflect landscape diversity (representativeness). In fact they reflect quite the opposite, e.g. tundra or old-growth forest. There is therefore a discrepancy between ecological representativeness as quantified in this study and representativeness for caribou. The term "functional connectivity" used by the authors in relation to caribou does not imply consideration of core areas, breeding areas, essential foraging and resting habitat, refugia from predation etc. It simply pertains to movements between resource patches. I would like to see an emphasis on the resources that the caribou require and a detailed explanation of how the IBM via its rule set leads to the emergence of resource patch distributions.

Overall, my sense is that the paper is trying to come up with a protected area network for an endangered species; but not necessarily incorporating either best knowledge or a straightforward approach to facilitate desired landscape planning and conservation outcomes for this species. The attempt to include ecological representativeness of the broader landscape is a heavy burden that does a disservice to the protected area network outputs. I ponder on how this can be an effective strategy for an endangered caribou population with ~70 individuals total fragmented into 3 subpopulations.

I suggest a much more aggressive and caribou-tailored conservation strategy, including a protected area design framework tailored more specifically - exclusively - to the caribou population. This would maximize protected area representativeness for caribou, and would also eliminate the emphasis on the rather vague notion of broader ecological representativeness. Ecological representativeness as quantified with the 4 attributes the authors considered (elevation, surficial deposit, drainage class and potential vegetation type), has questionable conservation relevance. It also distracts from the goal of optimal protected area design for an endangered species. The 4 attributes, with the exception of vegetation type and perhaps elevation, are coarse scale and it is unclear how related they are, if at all, to biological diversity, richness and abundance of the various taxa in the study region. Furthermore, elevation does not seem an appropriate attribute as applied here, because the ecological representativeness model defines headwaters as catchment seeds, thereby biasing modelling outputs to high elevation (which do no not necessarily represent the broader landscape).

I have included additional comments in the attached .pdf.

Reviewer #2: Please see attached comments.

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Reviewer #1: No

Reviewer #2: No

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PLoS One. 2020 Sep 30;15(9):e0238821. doi: 10.1371/journal.pone.0238821.r002

Author response to Decision Letter 0

15 Jun 2020

Coping with climate change when designing networks of protected areas by accounting for functional connectivity: a case-study with caribou

(MS # PONE-D-20-04608)

Responses to reviewers’ comments

Please find below our responses to the reviewer’s comments; the line numbers in our responses refer to the revised version (clean copy) of our manuscript.

Please note that we have also uploaded a version of our revised manuscript with all modifications highlighted in “Track Change”.

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OUR RESPONSE: We formatted the title, authors and affiliations following PLOS guidelines.

REQUIREMENTS #2. We note that you have indicated that data from this study are available upon request. PLOS only allows data to be available upon request if there are legal or ethical restrictions on sharing data publicly. For more information on unacceptable data access restrictions, please see http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions

OUR RESPONSE: We uploaded the relevant data we used in our calculation in a DRYAD repository (https://doi.org/10.5061/dryad.612jm641c). However, as the Atlantic-Gaspésie caribou population is currently endangered under the Canadian Species at Risk Act, we decided not to upload the telemetry location of the caribou in order to protect them from being tracked, disturbed, displaced or even poached by people. We hope you’ll understand that decision, but as the vice-president of the Atlantic-Gaspésie caribou recovery team, I cannot accept to increase the level of risk on those animals, sorry. However, the data can be made available upon request by qualified researchers if they contact Prof. Martin-Hugues St-Laurent at Université du Québec à Rimouski (martin-hugues_st-laurent@uqar.ca). Being co-owner of the data (along with the Québec Ministry of Forests, Wildlife and Parks), I’ll then have to transfer the request to the authorities of the QMFWP to obtain their permission.

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OUR RESPONSE: We detailed our decision regarding these points in the cover letter.

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OUR RESPONSE: We have included an updated Supporting Information file, with captions just below the figures, i.e., not in a separate file as per instructions.

REVIEWER #1

COMMENT #1. Thank you for the opportunity to review this manuscript. While this is an interesting spatially explicit study on a topic of high conservation relevance and immediate urgency, I have several concerns. My main concern with this study is that it places considerable emphasis on ecological representativeness, which is basically the landscape variability in the study area. Whereas the stated goal (e.g., right from the title) is to help devise an optimal protected area network for endangered caribou specifically.

OUR RESPONSE: Our goal was not to “devise an optimal network for caribou explicitly”. We but to incorporate aspects of caribou movement into a relatively standard protected areas design methodology based on ecological representation, intactness and hydrological connectivity. The ideas of optimality arise only in the evaluation of trade-offs between an index of representation and of functional connectivity for caribou, as explained in the Methods. We added an explicit statement at lines 370-382. We may have failed to clearly explain our objective, but we cannot identify in the text the source of misunderstanding. We hope the revised, abbreviated title does not mislead in this respect.

COMMENT #2. I understand the desire to represent the broader landscape in the protected area network. I also see the appeal of providing a spatially informed means to enable trade-offs between ecological representativeness and functional connectivity for caribou. I think this is a noble scope. Overall however I see this approach as lacking comprehensive consideration of caribou population needs, resulting in an analytical framework and reporting that do not adequately address the life history challenges of caribou in the study population. Perhaps the Individual Based Model (IBM) encapsulates a wealth of ecologically relevant information, but that needs to be detailed herein. In particular, what were the set of rules set for the IBM? Where do food availability and predation risk fit in here? Are these encapsulated in the functional connectivity component?

OUR RESPONSE: The IBM includes many details of the behaviour and ecology of this caribou population, which we now briefly describe at lines 267-308 in the “Network functional connectivity” section. The model simulates caribou movement according to some elements of the landscape which account for both caribou resources/habitats/barriers/etc. as well as their predator’s habitats. These are predicted from a map of landcover, disturbance history and transportation networks using a Resource Selection Function model developed for this population, as cited in the revised version of the manuscript.

COMMENT #3. The authors must provide details on what caribou in their study populations actually prefer. I suspect that caribou like and do better in specific landscape features that do not reflect landscape diversity (representativeness). In fact they reflect quite the opposite, e.g. tundra or old-growth forest. There is therefore a discrepancy between ecological representativeness as quantified in this study and representativeness for caribou. The term "functional connectivity" used by the authors in relation to caribou does not imply consideration of core areas, breeding areas, essential foraging and resting habitat, refugia from predation etc. It simply pertains to movements between resource patches. I would like to see an emphasis on the resources that the caribou require and a detailed explanation of how the IBM via its rule set leads to the emergence of resource patch distributions.

OUR RESPONSE: We completely agree there is a discrepancy between landscape diversity and habitat preferences for the caribou. This is visible in Figures 2 (negative relationships between caribou functional connectivity and ecological representativeness). That is why the best solution for protected areas networks are trade-off between these components as they cannot be both maximized. The entire of this study was to address this discrepancy by augmenting a conventional representation-based design with species-specific movement behaviour; we tried to explain this in the Introduction. As stated in our response to Comment #2, the functional connectivity was defined using the IBM which is based on habitat selection for several landscape elements: core areas = habitat of high quality; mating areas; and foraging and resting habitats. The functional connectivity is derived from simulated movements over the landscape where spatially and temporally varying movement behaviour integrates all these elements. A description of the rules governing the IBM which include all these elements was added in the manuscript in the “Network functional connectivity” section (lines 267-308).

COMMENT #4. Overall, my sense is that the paper is trying to come up with a protected area network for an endangered species; but not necessarily incorporating either best knowledge or a straightforward approach to facilitate desired landscape planning and conservation outcomes for this species. The attempt to include ecological representativeness of the broader landscape is a heavy burden that does a disservice to the protected area network outputs. I ponder on how this can be an effective strategy for an endangered caribou population with ~70 individuals total fragmented into 3 subpopulations

OUR RESPONSE: As we agreed above in responding to Comment #3, and as stated in the Introduction (see the lines 109-119 and 130-132) ecological representativeness and caribou “needs” are not the same, hence their negative relationship (Figures 2) and the need for a trade-off between them to obtain protected areas networks providing a range of levels of both characteristics.

The near-optimal networks presented in Figure 4 include many areas around the Gaspésie National Park to favor caribou persistence, as well as more distant areas across Gaspésie to account for ecological representativeness.

As explained in Introduction, this study attempts to add caribou considerations to an actual representation-based design to expand an existing protected areas network (see lines 128-130). Our aim was to show how such designs could be enhanced for caribou by including aspects of their space use and movement behavior. As stated above, we do not represent this work as an optimal conservation plan for this species or population (see lines 454-455).

COMMENT #5. I suggest a much more aggressive and caribou-tailored conservation strategy, including a protected area design framework tailored more specifically - exclusively - to the caribou population. This would maximize protected area representativeness for caribou, and would also eliminate the emphasis on the rather vague notion of broader ecological representativeness. Ecological representativeness as quantified with the 4 attributes the authors considered (elevation, surficial deposit, drainage class and potential vegetation type), has questionable conservation relevance. It also distracts from the goal of optimal protected area design for an endangered species. The 4 attributes, with the exception of vegetation type and perhaps elevation, are coarse scale and it is unclear how related they are, if at all, to biological diversity, richness and abundance of the various taxa in the study region. Furthermore, elevation does not seem an appropriate attribute as applied here, because the ecological representativeness model defines headwaters as catchment seeds, thereby biasing modelling outputs to high elevation (which do no not necessarily represent the broader landscape).

OUR RESPONSE: The goal of this study was to propose different protected areas networks that could be implemented in real life by the Government of Quebec. When implementing new protected areas in Gaspésie, the government’s goal is not only to protect the caribou population but also to protect the “common” elements of regional biodiversity, hence our analysis using other elements (i.e., ecological representativeness). If the goal would have been focused only on the caribou population, an extension of the Gaspésie National Park where the caribou are located would have been the answer.

The selection of biodiversity surrogates in representation analysis is a vast topic but the use of surrogates is very widespread. Our specific choices of surficial deposit, drainage class and potential vegetation were made in conformance with the Provincial government’s design process which we are evaluating and augmenting, as explained in section Network ecological representativeness. To these we added elevation, precisely to counter any elevational bias in catchments selection due to rooting the benchmark construction at headwater catchments. We don’t think it requires pointing out in the text that general method we present does not depend on the choice of surrogates.

ADDITIONAL COMMENTS IN THE EDITED PDF DOCUMENT

COMMENT #6 - Title. Please shorten the title, in its current form it is a bit of a mouthful. Titles of up to 15 words are generally preferable.

OUR RESPONSE: The title has been abbreviated to 12 words, as follows: “Protected areas networks, functional connectivity and climate change: a caribou case-study.”

COMMENT #7 - Authors. Order of authors is different here than at the bottom of pg 1 of this document. Please adjust for consistency.

OUR RESPONSE: This was an error when submitting the manuscript. We corrected that in the resubmitted version, thanks for noticing.

COMMENT #8 – L27. “…and likely help…” change to “and when designed adequately likely help…”.

OUR RESPONSE: Done.

COMMENT #9 – Lines 28-30. Statement is a bit too generic and needs changing. In fact, some protected areas are fairly small in size and/or designated for focal species conservation rather than for biodiversity protection. E.g., an endangered plant species, or a plant at the limit of its distribution range.

OUR RESPONSE: We adapted the sentence.

COMMENT #10 – Line 50. Order keywords alphabetically.

OUR RESPONSE: Done.

COMMENT #11 – Lines 92-93. “Therefore, the ability of a protected areas network to sustain functional connectivity under is another dimension of effectiveness”. What “under” means here? Needed?

OUR RESPONSE: The intended reading was “under climate change”. This has been corrected.

COMMENT #12 – Lines 98-100. Please add more background information on current state of knowledge and methodologies for protected area designation. Illustrate these with examples from varied taxa supported by references to literature.

OUR RESPONSE: We regret that it has not been possible to conduct such a review. We recognize that it could have been very interesting but it would have greatly increased the length of our manuscript. We thus decided that this suggestion could be left unanswered.

COMMENT #13 – Lines 115-117. Insert references at the end of this sentence.

OUR RESPONSE: We have added a subject-matter relevant reference for Pareto optimality at lines 108-112, with reference to the following article:

Kennedy, M.C., Ford, E.D., Singleton, P., Finney, M. and Agee, J.K., 2008. Informed multi‐objective decision‐making in environmental management using Pareto optimality. Journal of Applied Ecology, 45(1), pp.181-192.

COMMENT #14 – Line 185. Why were highly disturbed types, e.g. "urban areas" and "agriculture", assigned the same weights as some of the other disturbances? This seems likes a major flaw. Forestry activities, roads and trails can trigger temporal avoidance but animals can still use these areas; whereas they would not be able to use urban areas and presumably avoid agricultural areas also.

OUR RESPONSE: The intactness of the catchment was defined using these 6 disturbances and these elements were included to build intact protected areas to conserve biodiversity as such, not only caribou. Giving different weights to the different disturbances seemed subjective as some disturbances can have a large impact on some species but a minor impact on other species. For example, agricultural fields have a large impact on caribou but less impact on meso-carnivores. Even urban areas can be less avoided by some species (e.g., birds, insects) relative to either heavily forested areas or highways and their surroundings. At worst, our criteria could be regarded as too conservative. We added a sentence in the text to clarify this point (see lines 213-221 and the last paragraph of the discussion). Regarding the application of our method to the study area, please note that agricultural fields and urban areas are very rare and all distributed along the coast, not in the middle of the peninsula where caribou can be found. Finally, please note that the caribou IBM effectively uses empirical weights for the effect of different feature classes via the RSF model (see Bauduin et al. 2016; Ecological Modelling).

COMMENT #15 – Lines 192-195. Could you instead simply clip the rasters at the end? This way you could still have a model output for private land, in case private land acquisition becomes feasible for protected area expansion.

OUR RESPONSE: This action needed to be done at this initial stage so that catchments on private lands, which are not available for inclusion in the Province’s proposed expansion, are not included in the construction of candidate protected areas.

COMMENT #16 – Line 198. Ok, but I thought your model organism was caribou. How are caribou responding to headwater catchments? Does empirical data show that they utilize these headwaters, and if so, to what intensity compared to downstream areas in the catchments?

OUR RESPONSE: The construction of the candidate protected areas is done to protect biodiversity in its most “untouched” way and is not focused on our case study and the caribou. Using headwater catchment is done to ensure terrestrial and hydrological connectivity and conserve biodiversity features (like fish and aquatic invertebrates) that may depend on it.

This specific feature of the benchmark design is not aimed at terrestrial organisms and is unrelated to our case study. We added a few sentences to highlight this point and avoid confusion (lines 219-221).

Again we stress, any benefit to caribou is an emergent property of networks, not an attribute of individual catchments. Similarly, network characteristics address other goals than caribou.

COMMENT #17 – Lines 207-209. What does a protected area of this size contribute to the conservation of a wide-ranging species such as caribou in your study system? Are caribou migratory in your system and have you incorporated this life history characteristic in your simulation framework? What are the main causes of caribou decline in your area and how does the intactness metric relate/account for them? E.g. do areas with higher intactness have better nutritional availability and lower risk of calf mortality through predation? Use references to justify.

OUR RESPONSE: Connectivity and ecological representation are characteristics of the network, not of any specific component. The presence of small protected areas as such within a network does not disqualify it. The definition of the protected areas is the first step to create an effective network of protected areas that may be implemented in real life. It should not be defined for the caribou only. We added a few sentences to highlight this point and avoid confusion (lines 218-221).

Moreover, the caribou population in Gaspésie is not wide-ranging in their current state. These animals make relatively short-distance seasonal migrations from the top of the mountains to adjacent or nearby forested areas below the tundra (Mosnier et al. 2003).

COMMENT #18 – Lines 232-233. Who decides which resolution is "adequate"? What is that resolution?

OUR RESPONSE: We meant that the resolution was high enough compared to the size of the catchment to be meaningful at the catchment level. We removed this info about resolution to avoid confusion and because it is not relevant.

COMMENT #19 – Lines 233-234. What is a "standard spatial data operation"? Describe briefly what you did.

OUR RESPONSE: We added some text to spell it out (see lines 243-247).

COMMENT #20 – Lines 235 +(and the following). Use past tense throughout.

OUR RESPONSE: Done.

COMMENT #21 – Line 269. …subpopulation. Add a S at subpopulation..

OUR RESPONSE: Done.

COMMENT #22 – Lines 271-272. Why four-year simulations and not annual? With such low population sizes, it seems that environmental factors e.g. inter-annual variability in winter severity could really impact the population.

OUR RESPONSE: The IBM simulating caribou movement includes an attraction of the mating area but only during mating season. To be able to capture the movement towards and away these areas, with just a few individuals, we needed to run the simulation longer than one year. The IBM model has many stochastic processed and to capture the whole range of movement possibility, the simulation needed to run a few years with so few individuals to adequately assay functional connectivity. We did not simulate caribou movement for more than 4 years because of computer capacities and considering that we reached similar responses after more than a few years.

COMMENT #23 – Line 272. I thought the spatial grain was 250 x 250 m?

OUR RESPONSE: The resolution 250 x 250m is used to define the intactness. The resolution of 1-ha applies to the IBM. The resolution of these two rasters are different but they are the best ones available for their respective use. Rasters are summarized at the catchment level for the intactness and at the network level for the caribou connectivity. There is no interaction nor conflict between the two resolutions.

COMMENT #24 – Lines 274-275. Does your model differentiate repeat movements within the same protected area, from movements in different protected areas? The former represents protected core area fidelity, whereas the latter addresses connectivity.

OUR RESPONSE: We did not look at this because the protected core area is the Gaspésie National Park and individuals rarely leave the park (see Mosnier et al. 2003; Morin 2018; but also based on the GPS telemetry data collected by MH St-Laurent during the last years and used in Lesmerises et al. 2017, 2018a,b and 2019). In this instance, as it turned out, our connectivity refers more the to the facilitation of seasonal movements rather than exchange of individuals among core areas.

COMMENT #25 – Lines 280. How was this assessed? Because of your large sample sizes in number of replicates, P-values associated with mean comparisons are not reliable. Did you use effect sizes?

OUR RESPONSE: No means tests were conducted. Every candidate protected area (CPA) was evaluated by repeated simulation of the IBM under each of the four climate scenarios. This resulted in four functional connectivity metrics per CPA. We evaluated overall function connectivity of a CPA by taking the mean of these four metrics. We slightly revised to clarify (see lines 312-318).

COMMENT #26 – Lines 285-287. Unclear here, please provide more details.

OUR RESPONSE: We hope the revised text is easier to understand. It would be difficult to be more precise without introducing a bunch of notations.

COMMENT #27 – Line 292. “inflexion” should be “inflection”.

OUR RESPONSE: Done.

COMMENT #28 – Lines 314-315. Replace “well below” by "which was slightly lower than" and remove “well” at line 318.

OUR RESPONSE: Done.

COMMENT #29 – Line 315. our sample mean was 4.71, correct? Not that different than 4.65.

OUR RESPONSE: It is true the value of 4.65 is not much smaller than the sample mean so we used your proposition as “slightly lower”.

COMMENT #30 – Line 434. Add reference to Fig. 1 too.

OUR RESPONSE: Done.

COMMENT #31 – Fig. 3 (caption). Provide better axes labels to reflect "protected area" and "protected area network".

OUR RESPONSE: Done (now Figure 4). The x-axis represents all the protected areas used in the selected networks, ranked in their order of selection in the network. The y-axis is their frequency.

REVIEWER #2

This manuscript proposes an approach to identifying protected area networks using simulation modeling that seek to balance multiple ecological criteria. The authors focus on ecological representativeness and functional connectivity as their metrics for optimization, with the former relating to broad landscape features and the latter focusing on an endangered species in Canada – the Atlantic-Gaspésie caribou population. They consider potential networks of protected areas under both current conditions and future conditions of climate change and timber management. The paper appears methodologically sound, though several of the descriptions should be clarified and supported with figures to make the approach clearer to readers. With the addressing of the issues below, I think this paper would make a worthy contribution to PLoS ONE.

COMMENT #32. The primary improvement needed for this paper is clarification of the methodology and support with additional figures. This paper really is focused around the details of its methods as it proposes a detailed methodology for conducting optimization. However, there are multiple places where methods are difficult to determine based on the information as currently organized, especially for those unfamiliar with the BEACONs approach. Given the spatial nature of the proposed simulation approach it is especially difficult to visualize the steps of the method from the description given. I had to read the methods multiple times to wrap my head around the steps the authors take to simulate candidate protected area networks.

As best I can tell, the procedure that was used was to:

1. Identify a set of initial “seed” catchments

a. Defined here as all intact headwater catchments

2. For each seed catchment, add contiguous catchments that are hydrologically connected and meet minimum size and intactness criteria

a. Stop adding catchments when target size is achieved or no more catchments that meet the criteria are available to be added

b. Define the set of catchments associated with a given seed as a “candidate protected area” if its total area is greater than 31.2 sq km.

3. From the full set of candidate protected areas, generate “candidate protected area networks” by randomly selecting candidate protected areas and adding them to the existing protected area network until the total area exceeds 3080 sq km.

a. Repeat this step 500,000 times to generate many possible candidate protected area networks.

The paper would greatly benefit from clearly stating the above steps and from addition of one or two figures clarifying these steps. How protected area networks are generated is central to the methods and validity of the paper. I recommend the steps above be clearly indicated in the text and perhaps in a flowchart, with one or two figures displaying the corresponding spatial depictions:

� All seed catchments across the study area, shown in relation to existing protected areas.

� One candidate protected area, with each of the included catchments shown distinctly as outlines.

� The full set of existing and candidate protected areas, displayed with transparency or some other way of indicating where overlap occurs.

� A multi-panel plot showing how one candidate protected area network is compiled as an accumulation of the randomly selected candidate protected areas. Each step in the compilation does not need to be shown, but a representative selection of steps throughout the process should be displayed to give the reader an understanding of how networks were created. By including the total aggregate area of the protected area network at each displayed step, it will be easy for the reader to understand how the total area threshold was met and how overlap between candidate protected areas did not alter the candidate network area.

o This will greatly clarify L.213-222. The discussion of overlap and its consequences (or lack thereof) was confusing without some frame of reference on which to base the statements. Showing where multiple candidate protected areas overlap (e.g., by displaying them with transparency in the figure) may help explain what is meant here. If this is made clear in the figure, then L.213-222 could be removed or greatly simplified. As long as the methods are clear that where candidate protected areas overlap only the aggregate area was considered (as indicated in the associated figure), that should be sufficient for the reader to understand what was done and why.

The above figures would likely benefit from use of color. Since PLoS ONE is online-only this will not result in extra charges.

OUR RESPONSE: The reviewer’s description of the three stages or the procedure is correct.

To address the recommendations, we have developed a new Figure (Figure 2) which illustrates these steps with explanation and shows also the initial catchments with headwater catchments distinguished. We have also expanded the explanations somewhat throughout the Methods and developed a colour version of the former Figure 4 (now Figure 5).

COMMENT #33. Another helpful figure would be to depict functional connectivity. This is one of the two metrics employed in paper and yet the reader is left without a clear depiction of how functional connectivity actually works on the landscape. This also is relevant to L.414-416 in the Discussion. The paper states that a lack of functional connectivity during the last 20 years has led to division into sub-populations and heightened risk of extinction for caribou. This makes me wonder whether functional connectivity was overestimated in the models as it currently is hindered on the landscape. Without seeing any functional connectivity plots it is not possible to know how reasonable the model results for current and future functional connectivity might be. If the final functional connectivity map is considered protected information, since the caribou are an endangered population, a single iteration of the simulation could be shown as an example. This would at least give a sense of the model results. With this should be an indication of the location of the three caribou subpopulations references in L.269, as this will help the reader interpret the reasonableness of the functional connectivity results.

OUR RESPONSE: We added the figures of the summed caribou movements on the current landscapes and as averaged over the four different future landscapes to S3 – Supporting Information, as this is not the focus of the study. The results also appear in Bauduin, S., McIntire, E.J.B., St-Laurent, M.H., Cumming, S.G., 2018. Compensatory conservation measures for an endangered caribou population under climate change. Sci. Rep. 8, 1–10. https://doi.org/10.1038/s41598-018-34822-9, as cited [55].

COMMENT #34. Modifications are also needed for Figure 4 to provide consistency and clarity with the results. Based on the text in L.474, a continuous color ramp of greyscale values was used, but only a single grey is shown in the figure legend. Also, as it currently stands the legend seems to indicate that the frequently selected candidate protected areas are shown in white, while in actuality these are the dark areas with a black outline. Changing this square to have a darker grey fill with a black outline would clarify this. Use of color, which does not cost extra in PLoS publications, would also be helpful here. Finally, the text refers to frequently selected candidate protected areas being adjacent to important caribou breeding habitats (L.337-338). Since these important breeding areas are referenced, they should be shown in Fig. 4 or Fig. 1.

OUR RESPONSE: We fixed the mistakes on the legend for Figure 4 (now Figure 5) and used color for better clarity, thanks for noticing.

The important caribou breeding habitats are the high-elevation areas within Gaspésie National Park (see Mosnier et al. 2008), and are thus effectively shown in Figure 1. We have rephrased the text formerly at lines 365-367 to remove the ambiguity.

Other methodological clarifications are also needed to allow the reader to assess the validity of the proposed methods:

COMMENT #35. L.165-179. Prior to this point the reader has only been introduced to the existing protected areas and those proposed by MELCC, as shown in Fig. 1. It was not initially clear whether the approach to building protected areas networks outlined here would apply only to the proposed protected areas or to all lands in the study area. This should be clarified.

OUR RESPONSE: The approach is applied to the entire study area, but in this specific application is additive to an existing protected areas network, up to the area target. We added a new paragraph at the beginning of the Method (a section called “Overview”) to introduce the goal of the study and present an overview of the method, adding here the new Figure 2 presenting the workflow, as suggested in your Comment #32.

COMMENT #36. L.183-184. Roads and trails are likely to be much smaller than a 250 x 250m raster pixel. Was any pixel overlapped by a road or trail considered to be a road or trail?

OUR RESPONSE: Yes, as stated on the original manuscript in the following paragraph. We have reorganised slightly to avoid confusion and make this easier to understand.

COMMENT #37. L.184-185. The six disturbance types were given equal weight. Is there a reason to think that forestry activity and power line rights-of-way are as disruptive as roads or urban areas? In the absence of studies on caribou selection and avoidance equal weighting might be a reasonable assumption, but some support should be given from the literature for why caribou would be expected to respond strongly to things like forestry, rights-of-way and agriculture.

OUR RESPONSE: The measure of intactness is not directed primarily at caribou. It is rather one of the design criteria for protected areas networks, possibly a conservative one in that. The empirical data for the effects of specific disturbance types on caribou behaviour are incorporated into the Resource Selection Function which partially drives the caribou movement model (more details provided at lines 301-314). These responses effect the functional connectivity, which is used to select among candidate networks, each of which satisfies the network design criteria of e.g. representation, intactness and hydrological connectivity. We do not think any additional text is needed at this point in the manuscript. See also our answer to Comment #4 above.

COMMENT #38. L.185. Please give an example or two of what would be part of the “other” category.

OUR RESPONSE: We cannot provide these details as data we were provided did not specify. As stated, most of the disturbances were forest harvesting operations of roads and trails. Forest inventory data from other parts of Canada would suggest that minor residual areas of disturbance would be things like borrow pits for road construction, or clearings for infrastructure like electrical transformer stations.

COMMENT #39. L.191-192. Is there any evidence that the median intactness outside of existing protected areas is functionally relevant for caribou movement? In other words, is having < 0.5% of a catchment intact really enough to allow for caribou movement? I have some doubts about this. Without a study of caribou movement with respect to intactness it will be difficult to determine what is possible, but at least it would be good to indicate why this is a reasonable assumption. Was any sort of sensitivity analysis conducted to see how this threshold affected the resulting networks?

OUR RESPONSE: See above our response to Comment #37.

COMMENT #40. L.205-206. I do not understand what this means. Please clarify. For example, what does “protected area-level intactness criteria” mean? Is the point that intactness was only assessed at the catchment level, not for the resulting protected area? If so, this is not clear; I had to read it many times to come to this possible interpretation.

OUR RESPONSE: In some applications, it is useful to have separate intactness criteria at the catchment and CPA level: for example, in building large areas in regions with significant localised disturbances, one can allow a small number of highly impacted catchments within a CPA so as to that allow construction of a large CPA that is otherwise mostly intact. However, we did not use this feature in the present study, so the catchment and CPA-level criteria are effectively the same. To simplify the exposition we removed the reference to this unused feature of the construction software.

COMMENT #41. L.233-234. “Catchment-level attributes were calculated using standard spatial data operations.” What does that mean? I do spatial analysis frequently, but I am uncertain what the authors consider “standard spatial data operations.” This needs clarification. If the point is simply to introduce the approaches of the following paragraph then delete this sentence, as it does not describe ‘standard measures.’ If it means something like calculating the mean or median across pixels, then state that instead.

OUR RESPONSE: See above our response to Comment #19 made by Reviewer #1.

COMMENT #42. L.260. Consider updating to state that habitat generation was “to represent the current landscape and four landscapes for 2080 under future timber management and different climate change scenarios.” As currently stated, it is unclear how the current conditions map would differ from the scenario with no climate change impacts (L. 268) because it seems that only climate scenarios were changed. Based on the supplementary materials, however, it seems clear that timber management would lead to changes between the CC0 and current conditions map, even in the absence of climate effects. This should be indicated in the main text so those who do not read the supplement can still follow the basic approach.

OUR RESPONSE: We added a clause to clarify this point in the revised manuscript (see lines 315-328).

COMMENT #43. L.257. For readers not familiar with the approach of Bauduin et al. 2016 it would be helpful to give a brief summary of what the model does. For example (I made this up based on the information given here, not having read Bauduin et al. 2016), “The model simulates movements of individual caribou at an XX timescale with movement probability driven by habitat attraction/repulsion and an individual’s internal state [maybe an extra detail or two needed here]. Model outputs report the number of visits per landscape cell.” Such statements would give the reader the context to understand what was done and evaluate its relevance to the representation of functional connectivity. This could also be integrated with the content of L.269-272.

OUR RESPONSE: We added a summary of the main features of the IBM (see lines 268-281).

COMMENT #44. No indication is given for what software were used to conduct the simulations, making replication difficult. This should be clarified. While the authors explain why the input caribou data cannot be shared due to endangered species considerations, it does seem feasible to share code or other materials that would allow others to apply their modeling approach.

OUR RESPONSE: The BEACONs tool chain consists of two substantial pieces of custom software: the program that constructs candidate protected areas from a catchment shapefile and ancillary GIS layers, and a system that constructs and ranks candidate networks from the “Builder” output. Neither has yet been published other than as MSc theses: the reviewer may wish to refer to www.beaconsproject.ca for some background material. BEACONS has recently secured some resources to rework these tools as an R package, which would make them public, but this will take some time, and is not the responsibility of our former graduate student Dr. Bauduin. The custom R software used in the present analysis has been provided as supplementary data in the DRYAD depository.

COMMENT #45. The methods for generating future landscapes under climate change and management laid out in the supplementary materials also need some additional clarification. My primary concern is about how uncertainty was accounted for in generation of future landscapes. As best I can tell, future landscapes were only generated once for each climate scenario. However, at multiple steps in the process random selection and application of probabilities was applied (e.g., mature fir mortality due to spruce budworm, selection of fir stands outside of protection areas and conversion to other classes). If this is the case, the effects in future landscapes could be an artifact of these random selections and probabilities. Notably, the treatment of alpine habitat differed from that of fir habitat, as the former used fixed buffer distances, indicating that alpine habitat was always treated the same. This could result in different levels of variability across habitat classes. What impact did the random selection and use of probabilities have on outcomes? This paper generally does a good job of exploring many iterations of simulations to reflect potential variability, but here it is not clear that this was done. Some sort of sensitivity analysis or discussion would be nice.

OUR RESPONSE: The reviewer is correct. Only one future landscape was developed per scenario. The randomisation was at the level of individual mapped forest polygons which numbered in the hundreds of thousands. There’s no reason to expect that a specific random sample would introduce bias. Similarly, while developing these future landscapes, there was no discernible impact on caribou or protected area conclusions whether one set of mature fir polygons was removed or another set of mature fir polygons. Another level of replicated simulations would be very time consuming, and of doubtful interest or impact.

Other aspects of the Supporting Information in which clarity is needed:

COMMENT #46. Alpine tundra paragraph: What were the buffered areas replaced with? I assume the classes along their borders. What happened if there was a mix of mature and regenerating fir stands along the boundary of alpine tundra.

OUR RESPONSE: Recall (see Supporting Information S1): The three vegetation types of interest were the alpine tundra, the mature fir stands and the regenerating stands; also recall: these are defined in more detail in other, published papers that we cite. Any pixels that ceased to be alpine tundra were simply part of the remainder of the rule sets i.e., there was no difference in these pixels or other “non-tundra-affected” pixels. To summarize here, for non-protected areas, this would follow the forest harvesting and climate change rule sets: 1) if ministry of forests project an increase (or decrease) in mature fir in a zone (there were 5 zones in our study area), then took the aspatial ministry forecasted proportion of “increase in mature fir” and turned a random set of polygons into mature fir (or turned mature fir into ‘other’), 2) for climate effects, we then impose mortality on the mature fir stands according to the intensity of the climate effects (0% up to 50% for the most severe scenario). In the protected areas, we imposed the natural disturbance effects (increase in age of some fir polygons, and some mortality) and then the climate effects (as per above). Thus, there could be new mature fir or removal (and same for regenerating stands), but the fact that it was tundra before didn’t change our implementation of rules: these simply because polygons on the landscape that could have been turned into mature fir.

COMMENT #47. Mature fir stands and regenerating stands section/Impact of climate change section: Here for the first time there is mention of an “other” category. Above only three habitats were mentioned as being used to generate habitat quality maps: alpine tundra, mature fir, and regenerating stands. How many habitat types were there actually? This needs to be made clear at the outset of the description. Also, what was lumped into the “other” category? The descriptions further in the supplement make it seem like it could contain fir trees from 30-50 years old, but this likely is very different functionally than if it consists of urban areas, agricultural areas, etc.

OUR RESPONSE: We added a mention earlier of the “other” types, which could also help for you previous comment. Habitat types (young fir stands, urban areas, agricultural areas, etc.) were distinguished (or not) depending on whether they were distinct in the RSF model used as input to the IBM. Minor changes were made to the manuscript at lines 194-200 but also to the Supporting Information. The categories were initially detailed in Gaudry 2013 (MSc Thesis – Université du Québec à Rimouski) and also in Bauduin et al. 2016 (Ecological Modelling), 2018 (Scientific Reports). The “other” category gathered the following landcover types: deciduous, spruce and mixed stands (all age classes confounded) and < 50-year-old balsam fir stands, as these were shown to be significantly less used than available (see Ouellet et al., 1996 and Mosnier et al., 2003).

COMMENT #48. Mature fir stands and regenerating stands section/Impact of climate change section: If potential habitat was determined to be lost, why were mortality probabilities set at < 1? It seems odd that this would happen. I understand doing this when habitat quality decreases, but not if it is lost. Without suitable habitat why should any fir forest be expected to remain, especially ≥ 50% of the time?

OUR RESPONSE: By “loss of habitat” we mean “changes such that the habitat becomes unfavourable for the tree species presently dominant at the site”. This does not mean all individuals of the species immediately die. The time horizon we chose, 2080, is only 60 years from now. Even if the habitats are predicted to become unsuitable by then, it is not realistic to think existing canopies or regenerating trees of the species present will have all died. We account for partial morality of 0.01, 0.1 and 0.5 given the severity of climate change, but we do not expect more than 50% of mortality in a system where wildfire is nearly absent.

COMMENT #49. Mature fir stands and regenerating stands section/Impact of disturbances inside protected areas section: Good job identifying the potential for fire and windthrow to change with climate alteration as well as why these factors were not considered further. I would like to see more of this in the paper.

OUR RESPONSE: These were simplifying assumptions given the fact that the impact of these two disturbances is expected to be small relative to spruce budworm outbreaks. However, we have no study to support this. Developing integrated climate sensitive models of vegetation dynamics, insect defoliation, fire and human activities are beyond the scope of this study; such models may one day exist to provide more reliable inputs to future studies.

COMMENT #50. Mature fir stands and regenerating stands section/Impact of disturbances outside protected areas: What was done in the remaining 28% of forest outside of protected areas (if BFEC units cover 72% of the forest outside protected areas)? There is no description given for how habitat in these areas was treated.

OUR RESPONSE: The 28% of forest outside protected areas were not public forests, there were either private forests (included in the analyses with the same rules as the public ones) or non-forested areas. Thus the BFEC do not have any rights to plan and operate commercial timber harvesting on private lands without the authorization of the owners (citizens).

COMMENT #51. Mature fir stands and regenerating stands section/Impact of disturbances outside protected areas: It would be great to have a little more detail about how forestry plans for harvest are expected to increase the amount of old forest. This seems a bit counterintuitive if “the landscape is managed for timber production” as is stated above. I’m sure there’s a rationale for it, but for readers unfamiliar with the Québec context it would be great to explain briefly (e.g., by focusing timber harvest on currently regenerating stands and allowing older stands to grow unharvested…or whatever they are doing).

OUR RESPONSE: This refers to silvicultural treatments implemented as part of ecosystem-based management strategies designed to generate old forest conditions relatively early in the development of regenerating harvested stands. Our scenarios respect the plans as given.

COMMENT #52. Another area where the manuscript should be strengthened is in the framing about protected areas and their designation, which is established at the beginning of the Introduction. The authors should be clearer about the choices they make and definitions they employ in their paper and should set these in the context of other possibilities with regards to conservation decisions. Protected area networks may be established for a variety of reasons. One important reason is maintenance of biodiversity, which is the case this paper focuses on (L.55-57). But others are more species-specific or culturally driven (e.g., IUCN categories III - VI), which may lead to other criteria for effectiveness. It is fine for the paper to focus on biodiversity protection as a primary goal of protected area networks, but this should be explicitly stated and complemented with at least a sentence or two recognizing other purposes for protected areas. The paper focuses strongly on effectiveness. Statements such as that “A high degree of ecological representativeness is a necessary condition for an effective protected areas network” (L.69-70), that “These effects would increase the effectiveness of a protected areas network” (L.79-80), and that the generated set of protected areas “may be close to ideal from an environmental or conservation point of view” (L.345) assume a certain criterion for determining an effective protected areas network, ignoring other potential goals. Thus, biodiversity maintenance is presented as if it were the only possible definition for effectiveness, rather than one of multiple possible definitions. I recommend a more explicit statement early in the Introduction (e.g., ‘we define an “effective” regional protected areas network as one that can sustain the region’s biodiversity into some reasonably foreseeable future”) and discussion of other possible definitions. Some of this is touched on in the Discussion (e.g., L. 347-359) but it would be better to set this up in the Introduction as well.

OUR RESPONSE: We understand the interest in adding information to the manuscript in order to recognize the importance of other potential goals for the creation of protected areas. However, reporting all the goals for which we can protect land is beyond the scope of our manuscript. Regarding the importance of the biodiversity maintenance as one focus of our analysis, we do believe that this was already presented in the original manuscript, and still there in the revised version. The second sentence of the Introduction states: “Securing habitats by creating or expanding protected areas networks is part of the solution to the challenge of biodiversity loss [4].” We think this situates the study exactly as recommended by the reviewer. The third sentence of the introduction states: “A regional protected areas network could be considered ultimately effective insofar as it can sustain the region’s biodiversity into some reasonably foreseeable future.” reads to us effectively as a definition, as requested.

MINOR COMMENTS:

COMMENT #53. L. 65-66. This assumes populations are stable or growing. The presence of species in ecological traps may artificially inflate representativeness, leading to assumption that “habitat requirements…will be satisfied within the protected areas network” when this is not actually the case. It might be nice to at least point out this possibility, even while acknowledging that this is nonetheless a typical assumption, as the paper does in L.68. In fact, this is a strange statement given the following paragraph, which details why it is not the assumption is not necessarily reasonable. It seems like it would make more sense for the paragraph on representativeness to make the case for why representativeness matters for conservation (e.g., see second paragraph of Dietz et al. 2015 Biological Conservation and references therein).

OUR RESPONSE: In the 1st paragraph of the Introduction we set up the thee aspects of protected areas network design that we address: representation, species-specific needs, climate change, which we then elaborate upon one at time. The second paragraph deals with the 1st of these, namely representation, includes the caveat “most species”. We have revised this paragraph to refer to make clear that by “habitat” we refer to or ecological types, citing Dietz et al. 2015, and changed “most” to “many”. The exceptions are discussed in the next paragraph, and we add another example, namely endangered species, as studied in Venter et al. 2014.

COMMENT #54. L.362. A citation is needed for this statement.

OUR RESPONSE: Rather than fully discuss and references these controversial points, we have simply dropped the two lines in question. The claims they make go beyond our results are not necessary to their interpretation.

Low ecological representativeness may compromise the effectiveness or efficiency of protected areas networks. Ideally, managers would work towards achieving a better representation of the regional biodiversity when implementing new protected areas. However, to achieve biodiversity protection, protected areas networks should aim to represent the landscape in its pre-industrial form and not to protect habitat types resulting from human disturbances

COMMENT #55. L.366. Again, a citation is needed. In some cases, species thrive under habitat types resulting from human disturbances. It is a decision based on the sensitivity of focal species to human disturbance that should drive such decisions.

OUR RESPONSE: Please see our response to Comment #54 above.

COMMENT #56. L.376-377. This raises an important point about the potential to consider tradeoffs. This is not really done in the paper, however, as the focus is only on areas where both representativeness and functional connectivity are mutually high. One way this could be addressed is to make similar plots to Fig. 4 in the supplementary materials that are focused on just one of the indicators. Then the reader could better see where tradeoffs occur.

OUR RESPONSE: The focus not at all on [protected] areas where representativeness and functional connectivity are mutually high. It is on designing networks which, in aggregate, achieve both objectives. We discuss this in in the Introduction (lines 108-116) and in the section “Identifying priority conservation areas” (lines 311-324). The tradeoff curve could be shown explicitly by drawing a bounding curve over the clouds of points in Figures 3a and 3b; this could be done by quantile non-parametric additive models: but we feel this would obscure our main message which is that a better network designs are possible: better in both that representation and functional connectivity are improved relative to the Ministry’s proposal at that time.

GRAMMATICAL ISSUES TO ADDRESS:

� L.81. “among the main current drivers” reads a bit awkwardly. Suggest replacing with “a major driver.” // OUR RESPONSE: Done.

� L.90. Move comma within quotation marks. // OUR RESPONSE: Done.

� For clarity and better readability, I recommend moving “Because of…existing networks” (L.89-91) to before “The effectiveness of…” in L.84. and deleting “One important…functional connectivity” (L.91-92). // OUR RESPONSE: Done.

� L.111-121 are in present tense, L.122-134 in past tense. These should be consistent. // OUR RESPONSE: Done. We have put most such instances into the past tense.

� L.152. “currently” is unnecessary. Delete. // OUR RESPONSE: Done.

� L.212. Remove extra “s” in “areass." // OUR RESPONSE: Done.

� L.252. Replace “or” with “of.” // OUR RESPONSE: Done.

� L. 256. Remove “by simulating.” // OUR RESPONSE: Done.

� L.269. Add an “s” to “subpopulation.” // OUR RESPONSE: Done.

� L.292. Remove “the” between “protected areas” and “most frequently selected.” // OUR RESPONSE: Done.

� L.374. Replace “ammeding” with “amending.” // OUR RESPONSE: Done.

� L.418. Remove “to” after “benefit.” // OUR RESPONSE: Done.

� L.427. Add “us” between “allows” and “to approximate.” // OUR RESPONSE: Done.

� L.465. Add an “s” to “represent.” // OUR RESPONSE: Done.

Supporting Information

� Last sentence of first paragraph. Replace “caution” with “cautious.” // OUR RESPONSE: Done.

� Alpine tundra paragraph:

o Consider replacing “for the horizon 2090” with “by 2090.” // OUR RESPONSE: Done.

o Add “using” between “…in Gaudry 2013)” and “interior buffering.” // OUR RESPONSE: Done.

o Consider adding “soils” between “serpentine” and “(Sirois and Grandtner 1992)” and changing “is less subject” to “are less subject.” // OUR RESPONSE: Done.

� Mature fir stands and regenerating stands section / Impact of disturbances inside protected areas section:

o Consider replacing “turned” with “reclassified” in the second to last sentence. // OUR RESPONSE: Done.

� Mature fir stands and regenerating stands section / Impact of disturbances outside protected areas:

o Remove “for” in “Windthrow is similarly managed for.” // OUR RESPONSE: Done.

o Replace “at” with “as” in “classed at mature.” // OUR RESPONSE: Done.

o Insert “were” between “Once the landscapes” and “built with the.” // OUR RESPONSE: Done.

o Consider rephrasing to something like “For the four climate change scenarios…the alpine tundra area was 100%, 59%, 39%, and 14%, respectively, compared to current conditions. This will indicate what the percentages indicate (a comparison with current). Also, “remained at” indicates stasis while the numbers reported reflect decreases in area. Similar phrasing should be used for changes in area of mature fir stands and regenerating stands. // OUR RESPONSE: Done.

o Consider deleting “fir stands area increased” as this seems to still be explaining why old stand area increased. // OUR RESPONSE: The first part of the sentence refers to OLD stands (not fir in particular) and the second part of the sentence refers to FIR stands (not particularly the old ones). We split the sentence in two for better clarity.

o Consider adding “regenerating” after “However,” as this sentence seems to be just about regenerating stands since old stands mostly increased. // OUR RESPONSE: The sentence referred to FIR stands, not regenerating stands. We coupled this part with the previous sentence that was split to show the two contrasting impacts on fir stands.

Attachment

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PLoS One. doi: 10.1371/journal.pone.0238821.r003

Decision Letter 1

Laurentiu Rozylowicz

9 Jul 2020

PONE-D-20-04608R1

Protected areas networks, functional connectivity and climate change: a caribou case-study

PLOS ONE

Dear Dr. St-Laurent,

The reviewers are positive about revised paper, however, there is a need for some minor changes (methodology, figures, discussion).

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We look forward to receiving your revised manuscript.

Kind regards,

Laurentiu Rozylowicz, Ph.D.

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: (No Response)

Reviewer #3: (No Response)

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2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #2: Yes

Reviewer #3: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

Reviewer #3: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #2: Yes

Reviewer #3: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #2: Yes

Reviewer #3: Yes

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6. Review Comments to the Author

Reviewer #2: Thank you for your efforts to revise the manuscript in response to my previous review. The result is a clearer work that communicates the important approach you have taken. There remain, however, a few issues that should be addressed prior to acceptance of the manuscript. I hope that these will be easy to update and that the manuscript can then be accepted.

L.197-198. Both reviewers questioned giving an equal weight to each disturbance type, which suggests other readers will as well. Having read the authors’ responses to our comments, I now understand the authors’ reasoning behind this decision and suggest that a few sentences be added to clarify this for other readers. For example (adapting from the response to Comment 14): “…This gives equal weight to each disturbance type. While this is likely unrealistic for any given species, catchment intactness was intended to be relevant to biodiversity more broadly. Equal weighting reflects differing responses across species. For example, agricultural fields have a large impact on caribou but less impact on meso-carnivores (references). Even urban areas can be less avoided by some species (e.g., birds, insects) relative to either heavily forested areas or highways and their surroundings (references). Equal weighting thus represents a conservative assumption.”

I greatly appreciate the authors adding Fig 2 and making modifications to Fig 5 and the Methods description in response to my comments. This greatly helped in clarifying the approach used in their model. I still am a little confused, however, by what size threshold was used in creating candidate protected areas. In combination with Fig 2, L.209-213 indicate that starting with the seed catchments – which should be intact headwater catchments (presumably only on public land, see next point) – additional catchments along the stream network that met the intactness criteria of > median intactness were added sequentially until the target size of 85.5 sq km was met or slightly exceeded. At that point the set of combined catchments was considered a candidate protected area. The sentence from L.213-215 then seems redundant, simply restating what was just described so I suggest removing it. But then L.216-218 indicate that candidate protected areas with a total area above 31.2 sq km were selected. This is where I am confused. If the target size was 85.5 sq km and catchments were added until this was met or exceeded, what was the 31.2 sq km size used for? Should not all candidate protected areas have exceeded this size? I do not see this clearly explained. This needs to be clarified as the difference between these two target sizes affects the ability of readers to understand the criteria used and to replicate the study.

L.209. Fig 2 says intact headwater catchments on public land were used as seeds, but this line does not specify that the seeds had to be on public land. If this was a constraint it should be indicated here as well.

L.316,321. These references to Fig 2 seem a little strange to me as what is being described is not clearly pictured in Fig 2. There is some text that indicates seeking tradeoffs, but mostly I found myself looking for explanations of what was meant by “a subsample of 0.1% of the candidate networks that were highly ranked under all three criteria” and “using as the frequency threshold the inflection point in the proportional frequency curve,” neither of which seem to be indicated in Fig 2. I suggest removing these references to the figure as they really are not necessary here.

L.354. A reference is given to S3 Supporting Information to support the statement that “Most of these 501 designs did not exceed MELCCs functional connectivity scores, but some did.” However, MELCC is never mentioned in Supplementary Information S3, nor are specific values of the displayed protected areas or even a labelled color ramp of values given that would allow the reader to evaluate the claim made in the paper, so this reference seems inappropriate. Instead, S3 reports statistics based on a single optimality criterion only, which is not discussed anywhere in the main text. While I suggested making figures like this in my previous review, they need to be at least briefly introduced in the text and then given further description in the supplement, or else removed entirely.

L.396-399. I am unclear what is meant by “We attempted to address some of the potential shortcomings of such a coarse filter approach by amending a fine filter approach that accommodates very different criteria, which is builds in an almost orthogonal dimension to the conservation problem.” Which fine filter approach is meant? I first thought it was a reference to the caribou IBM, but considering that this is all under a heading of “Network ecological representativeness” and the caribou model fits under the next section, “Network functional connectivity,” I am left unclear by what the authors consider the fine filter approach? This is the only place in the manuscript where this term shows up other than the key words. What is meant by the fine filter and coarse filter approach need to be clearly described. Likewise, the potential shortcomings of the coarse filter approach should be described, at least in brief. Then it should be explained how the fine filter approach accommodates a different criteria and builds in an orthogonal dimension to the problem. As it stands, none of this is clear to me.

L.486. MDDELCC should be defined in the figure caption so that the figure can stand on its own. This is especially important because while the acronym MELCC is regularly used in the paper, MDDELCC does not show up anywhere in the main text or supplements, nor is there an MDDELCC 2014 reference in the References. The citation for this needs to be clarified.

L.505. Use of color in this figure improves clarity over the initial version. However, the greenscale color ramp used to show selection frequency of candidate protected areas in Figure 5 is subtle enough that it remains difficult to discern differences among many of the protected areas. It would be helpful to use a different color ramp with greater contrast. This also applies to the figures in Supplementary Information S3.

Finally, a number of typos or grammatical issues remain in the manuscript that should be addressed prior to publication. These include:

L.21. Change “disturbanes” to “disturbances”

L.133. Change “potental” to “potential”

L. 135. Change “and well as” to “as well as a”

L. 135. Remove extra space between “while” and “also”

L. 140. I suggest changing “has been” to “was”

L.167. Change “it” to “this caribou population” to clarify for those reading quickly that “it” does not refer to the park, as the subject of the previous sentence was Gaspésie National Park.

L.177. Change “completing” to “complementing”

L.271. Remove the comma from “model, process”

L.289. Remove the second “with” from “combined with with predicted”

L.438-439. Rephrase to “two genetically distinct sub-populations”

L.489. This should be changed to either “assembling a candidate protected areas network” or to “assembling candidate protected areas networks”. It was not clear to me which the authors intend.

L.491. Change “middel" to “middle”

L.491. Change “hydroligically” to “hydrologically”

L.496. Insert a comma after “connectivity”

Reviewer #3: ADDITIONAL COMMENTS IN THE EDITED PDF MANUSCRIPT

COMMENT #1: The research reported in this manuscript seems highly relevant to conservation planning for the Atlantic-Gaspésie caribou population. However, I think the new title of the manuscript should be changed a little bit. Hence, I suggest revising the title. A suggested title is “Integrating functional connectivity in designing networks of protected areas under climate change: a caribou case-study”.

COMMENT #2: L.348 I suggest you change the name “Identifying priority conservation areas” from the results to “Priority conservation areas” as it is the same as the title from the methods (L.310) and can be confusing.

COMMENT #3: L.504 “inflection” instead of “inflexion”

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While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2020 Sep 30;15(9):e0238821. doi: 10.1371/journal.pone.0238821.r004

Author response to Decision Letter 1

21 Aug 2020

Integrating functional connectivity in designing networks of protected areas under climate change: a caribou case-study

(MS # PONE-D-20-04608.R2)

Responses to reviewers’ comments

Please find below our responses to the reviewer’s comments; the line numbers in our responses refer to the revised version (clean copy) of our manuscript.

Please note that we have also uploaded a version of our revised manuscript with all modifications highlighted in “Track Change”.

REVIEWER #2

COMMENT #1. Thank you for your efforts to revise the manuscript in response to my previous review. The result is a clearer work that communicates the important approach you have taken. There remain, however, a few issues that should be addressed prior to acceptance of the manuscript. I hope that these will be easy to update and that the manuscript can then be accepted.

OUR RESPONSE: Thanks for the time invested in reviewing our manuscript and helping us, your comments were greatly appreciated.

COMMENT #2. L.197-198. Both reviewers questioned giving an equal weight to each disturbance type, which suggests other readers will as well. Having read the authors’ responses to our comments, I now understand the authors’ reasoning behind this decision and suggest that a few sentences be added to clarify this for other readers. For example (adapting from the response to Comment 14): “…This gives equal weight to each disturbance type. While this is likely unrealistic for any given species, catchment intactness was intended to be relevant to biodiversity more broadly. Equal weighting reflects differing responses across species. For example, agricultural fields have a large impact on caribou but less impact on meso-carnivores (Toews et al. 2018). Even urban areas can be less avoided by some species (e.g., birds, insects) relative to either heavily forested areas or highways and their surroundings. Equal weighting thus represents a conservative assumption.”

OUR RESPONSE: We have added some text to this section, adapted from your suggestions (lines 206-211).

COMMENT #3. I greatly appreciate the authors adding Fig 2 and making modifications to Fig 5 and the Methods description in response to my comments. This greatly helped in clarifying the approach used in their model. I still am a little confused, however, by what size threshold was used in creating candidate protected areas. In combination with Fig 2, L.209-213 indicate that starting with the seed catchments – which should be intact headwater catchments (presumably only on public land, see next point) – additional catchments along the stream network that met the intactness criteria of > median intactness were added sequentially until the target size of 85.5 sq km was met or slightly exceeded. At that point the set of combined catchments was considered a candidate protected area. The sentence from L.213-215 then seems redundant, simply restating what was just described so I suggest removing it. But then L.216-218 indicate that candidate protected areas with a total area above 31.2 sq km were selected. This is where I am confused. If the target size was 85.5 sq km and catchments were added until this was met or exceeded, what was the 31.2 sq km size used for? Should not all candidate protected areas have exceeded this size? I do not see this clearly explained. This needs to be clarified as the difference between these two target sizes affects the ability of readers to understand the criteria used and to replicate the study.

OUR RESPONSE: We have revised the text to clarify and to motivate the distinction between the target and minimum sizes (Lines 218-227).

COMMENT #4. L.209. Fig 2 says intact headwater catchments on public land were used as seeds, but this line does not specify that the seeds had to be on public land. If this was a constraint it should be indicated here as well.

OUR RESPONSE: We specify in the preceding paragraph that “intact catchments” were defined so as to exclude catchments on private lands. We have modified Fig. 2 to remove the reference to this case-study-specific detail, so that the caption is now consistent with the text at the former L. 209. This avoids repeating the same detail in three places.

COMMENT #5. L.316,321. These references to Fig 2 seem a little strange to me as what is being described is not clearly pictured in Fig 2. There is some text that indicates seeking tradeoffs, but mostly I found myself looking for explanations of what was meant by “a subsample of 0.1% of the candidate networks that were highly ranked under all three criteria” and “using as the frequency threshold the inflection point in the proportional frequency curve,” neither of which seem to be indicated in Fig 2. I suggest removing these references to the figure as they really are not necessary here.

OUR RESPONSE: We agree and have removed the two references to Figure 2 (lines 325 and 327). This information actually refers more to Figure 3 but as Figure 3 presents results, we won’t refer to it in the Methods. The subsection in question (Lines 324-332) has been revised to improve clarity.

COMMENT #6. L.354. A reference is given to S3 Supporting Information to support the statement that “Most of these 501 designs did not exceed MELCCs functional connectivity scores, but some did.” However, MELCC is never mentioned in Supplementary Information S3, nor are specific values of the displayed protected areas or even a labelled color ramp of values given that would allow the reader to evaluate the claim made in the paper, so this reference seems inappropriate. Instead, S3 reports statistics based on a single optimality criterion only, which is not discussed anywhere in the main text. While I suggested making figures like this in my previous review, they need to be at least briefly introduced in the text and then given further description in the supplement, or else removed entirely.

OUR RESPONSE: The material in S3 Supporting Information is indeed unrelated to the statement in question (lines 353-356 in the previous version). We now refer instead to Figure 3, which does support the statement (lines 368-370 of the revised version), and made also some revisions to the paragraph to improve notation and clarity (lines 365-384). With regards to S3, it is now motivated in the Methods (Lines 334-338), and references in the Results (Lines 379-384) and Discussion (Lines 470-472); the text of S3 itself has also been expanded, as requested

COMMENT #7. L.396-399. I am unclear what is meant by “We attempted to address some of the potential shortcomings of such a coarse filter approach by amending a fine filter approach that accommodates very different criteria, which is builds in an almost orthogonal dimension to the conservation problem.” Which fine filter approach is meant? I first thought it was a reference to the caribou IBM, but considering that this is all under a heading of “Network ecological representativeness” and the caribou model fits under the next section, “Network functional connectivity,” I am left unclear by what the authors consider the fine filter approach? This is the only place in the manuscript where this term shows up other than the key words. What is meant by the fine filter and coarse filter approach need to be clearly described. Likewise, the potential shortcomings of the coarse filter approach should be described, at least in brief. Then it should be explained how the fine filter approach accommodates a different criterion and builds in an orthogonal dimension to the problem. As it stands, none of this is clear to me.

OUR RESPONSE: The references to fine and course filter approaches were superfluous and have been deleted.

COMMENT #8. L.486. MDDELCC should be defined in the figure caption so that the figure can stand on its own. This is especially important because while the acronym MELCC is regularly used in the paper, MDDELCC does not show up anywhere in the main text or supplements, nor is there an MDDELCC 2014 reference in the References. The citation for this needs to be clarified.

OUR RESPONSE: Our use of “MDDELCC” as a citation key to Bouchard (2014) was incorrect. In the revised caption of Figure 1, we now use the journal’s numerical citation format. The acronym MDDELCC no longer appears in the caption or the Figure’s legend. We note that the responsible ministry has changed names several times since this project was initiated. We now refer throughout to “the Ministry”, as per the revised Introduction (Lines 161-162).

COMMENT #9. L.505. Use of color in this figure improves clarity over the initial version. However, the greenscale color ramp used to show selection frequency of candidate protected areas in Figure 5 is subtle enough that it remains difficult to discern differences among many of the protected areas. It would be helpful to use a different color ramp with greater contrast. This also applies to the figures in Supplementary Information S3.

OUR RESPONSE: We changed the color ramp for Figure 5 (Lines 529-532) and for the Figures in S3 Supporting Information.

COMMENT #10. Finally, a number of typos or grammatical issues remain in the manuscript that should be addressed prior to publication. These include:

• L.21. Change “disturbanes” to “disturbances”

OUR RESPONSE: Corrected.

• L.133. Change “potental” to “potential”

OUR RESPONSE: Corrected.

• L. 135. Change “and well as” to “as well as a”

OUR RESPONSE: Corrected.

• L. 135. Remove extra space between “while” and “also”

OUR RESPONSE: Corrected.

• L. 140. I suggest changing “has been” to “was”

OUR RESPONSE: Done.

• L.167. Change “it” to “this caribou population” to clarify for those reading quickly that “it” does not refer to the park, as the subject of the previous sentence was Gaspésie National Park.

OUR RESPONSE: Done.

• L.177. Change “completing” to “complementing”

OUR RESPONSE: Done.

• L.271. Remove the comma from “model, process”

OUR RESPONSE: Corrected.

• L.289. Remove the second “with” from “combined with with predicted”

OUR RESPONSE: Corrected.

• L.438-439. Rephrase to “two genetically distinct sub-populations”

OUR RESPONSE: Done.

• L.489. This should be changed to either “assembling a candidate protected areas network” or to “assembling candidate protected areas networks”. It was not clear to me which the authors intend.

OUR RESPONSE: This comment refers to the caption of Figure 2. Our intended meaning was the second you mentioned “assembling candidate protected areas networks”. The caption has been revised (Lines 512-515).

• L.491. Change “middel" to “middle”

OUR RESPONSE: Corrected.

• L.491. Change “hydroligically” to “hydrologically”

OUR RESPONSE: Corrected.

• L.496. Insert a comma after “connectivity”

OUR RESPONSE: Corrected.

REVIEWER #3

COMMENT #11 – Title. The research reported in this manuscript seems highly relevant to conservation planning for the Atlantic-Gaspésie caribou population. However, I think the new title of the manuscript should be changed a little bit. Hence, I suggest revising the title. A suggested title is “Integrating functional connectivity in designing networks of protected areas under climate change: a caribou case-study”.

OUR RESPONSE: We have revised the title much as you suggested.

COMMENT #12. L.348 I suggest you change the name “Identifying priority conservation areas” from the results to “Priority conservation areas” as it is the same as the title from the methods (L.310) and can be confusing.

OUR RESPONSE: We have modified the section heading according to your suggestion (line 363).

COMMENT #13. L.504 “inflection” instead of “inflexion”.

OUR RESPONSE: Done (line 527)

Attachment

Submitted filename: Responses to Reviewers_PONE-D-20-04608_R1.pdf

Click here for additional data file.^{(199KB, pdf)}

PLoS One. doi: 10.1371/journal.pone.0238821.r005

Decision Letter 2

Laurentiu Rozylowicz

25 Aug 2020

Integrating functional connectivity in designing networks of protected areas under climate change: a caribou case-study

PONE-D-20-04608R2

Dear Dr. St-Laurent,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Laurentiu Rozylowicz, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0238821.r006

Acceptance letter

Laurentiu Rozylowicz

4 Sep 2020

PONE-D-20-04608R2

Integrating functional connectivity in designing networks of protected areas under climate change: a caribou case-study

Dear Dr. St-Laurent:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

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on behalf of

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Material. Construction of the potential future landscapes.

(DOCX)

Click here for additional data file.^{(38.5KB, docx)}

S2 Material. Caribou movements in the current and future landscapes.

(DOCX)

Click here for additional data file.^{(193.4KB, docx)}

S3 Material. Description of the optimal protected areas networks.

(DOCX)

Click here for additional data file.^{(671.8KB, docx)}

Attachment

Submitted filename: PONE-D-20-04608_review.pdf

Click here for additional data file.^{(1.8MB, pdf)}

Attachment

Submitted filename: Review of PONE-D-20-04608.docx

Click here for additional data file.^{(23.5KB, docx)}

Attachment

Submitted filename: Responses to Reviewers_PONE-D-20-04608.pdf

Click here for additional data file.^{(339.8KB, pdf)}

Attachment

Submitted filename: Responses to Reviewers_PONE-D-20-04608_R1.pdf

Click here for additional data file.^{(199KB, pdf)}

Data Availability Statement

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PERMALINK

Integrating functional connectivity in designing networks of protected areas under climate change: A caribou case-study

Sarah Bauduin

Steven G Cumming

Martin-Hugues St-Laurent

Eliot J B McIntire

Roles

Abstract

Introduction

Methods

Overview

Fig 1. The Gaspésie natural region with existing protected areas (black) and additions (grey) proposed by the Québec government [39].

Fig 2.

Study area

Building protected areas networks

Network ecological representativeness

Network functional connectivity

Identifying priority conservation areas

Results

Protected areas networks

Fig 3.

Priority conservation areas

Fig 4. A subsample of 501 candidate protected areas networks selected from near one point on the tradeoff curve (Fig 3).

Fig 5.

Discussion

Network ecological representativeness

Network functional connectivity

Accounting for climate change

Case study

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Laurentiu Rozylowicz

Roles

Author response to Decision Letter 0

Decision Letter 1

Laurentiu Rozylowicz

Roles

Author response to Decision Letter 1

Decision Letter 2

Laurentiu Rozylowicz

Roles

Acceptance letter

Laurentiu Rozylowicz

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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