In-stream habitat availability for river dolphins in response to flow: Use of ecological integrity to manage river flows

Shambhu Paudel; John L Koprowski; Usha Thakuri; Ajay Karki

doi:10.1371/journal.pone.0241099

. 2021 Jul 21;16(7):e0241099. doi: 10.1371/journal.pone.0241099

In-stream habitat availability for river dolphins in response to flow: Use of ecological integrity to manage river flows

Shambhu Paudel ^1,^2,^*, John L Koprowski ^1,³, Usha Thakuri ², Ajay Karki ⁴

Editor: Susana Caballero⁵

PMCID: PMC8294540 PMID: 34288903

Abstract

Population decline and extinction risk of river dolphins are primarily associated with flow alteration. Previous studies predominantly highlighted maintenance of adequate flow for low water seasons when habitats contract and the risk of local extinction escalates. Although river dolphins are sensitive to reduction in river flow, no studies quantify the relationships between flow and ecology of river dolphins to mitigate the potential adverse impacts of flow alteration. We quantify the relationships between flow and the ecology of river cetaceans concerning Ganges River dolphins (GRD; Platanista gangetica gangetica) usable area availability (AWS) for the low water season at wider flows (50–575 m³/s) at finer spatial and temporal scales. This study reveals that distribution of area usable to GRD is highly regulated by the adequate flow and river attributes (velocity and depth) interactions that likely offer energetically efficient modes of locomotion to GRD, suggesting the hydro-physical environment as a major determinant of river dolphin distribution and abundance. Flow and AWS relationships indicate that the flow during the dry season negatively contributed to AWS, whereas that of pre-monsoon maximized the AWS, suggesting that modifying flow regimes does alter in-stream habitats at varying spatial scales and may influence life-history strategies. Substantial fragmentation in suitable pool availability and loss of longitudinal connectivity exhibited by dry season flow suggested a higher risk of adverse biological effects during the dry season, which may reduce population viability by reducing survivorship and reproduction failure. Owing to river dolphins’ dependence on the attribute of freshwater flow, they can be expected to be more affected by flow regulations as interactive effects. Considering the seasonal effects and changes in the availability of usable areas by flow alteration, adopting effective habitat retention plans by water-based development projects appears critical to avoid further ecological risks in aquatic species conservation. Identifying priority riverscapes for river cetaceans and prioritizing investment opportunities is an essential first step towards effective riverine cetacean conservation.

Introduction

As the human population size increases, freshwater species and ecosystems are increasingly threatened by many development activities, including habitat alteration, river diversions, fragmentation and flow regulation, expansion of agricultural and urban landscapes, and climate change [1]. All these anthropogenic consequences determine the quality and quantity of freshwater, which affects ecological processes and dynamics that determine freshwater ecosystem productivity and integrity. As withdrawals and diversions are the main threats to freshwater availability and quality [2–4], freshwater biodiversity is primarily threatened by habitat fragmentation and flow regulation [5]. Worldwide, agriculture accounts for about 70% of all freshwater usage, compared to 20% and 10% by industry and domestic use, respectively [6]. Accelerated water extraction or diversion combined with changes in climate, human population, and changing land use puts immense pressure on river basin biodiversity and ecosystem services through habitat loss and fragmentation [7].

Globally, a sharp decline in freshwater species, especially megafauna with large body size (adult body weight ≥30 kg) and complex habitat requirements, is commonly attributed to water diversion and extraction. From 1970 to 2012, populations of vertebrate freshwater declined by 88% due to habitat degradation induced by flow regulation [8, 9]. Several river basins in Southern Asia (Yangtze River, Ganges River, Indus River, Brahmaputra River) and Northern South America (Amazon, Orinoco, and Tocantins-Araguaia) have been impaired by large water extraction projects (i.e., hydropower and agriculture irrigation projects) with negative impacts on aquatic species conservation [1, 10, 11]. Such mega-projects threaten freshwater species with isolation, reduction in abundance and range, and extinction, especially in the case of apex predators and highly migratory river dolphins [10–13]. As river cetaceans are sensitive to river flow, reduced in-stream habitat quality due to the lack of adequate river flow further escalated endangerment and extinction risk by increasing entanglement and adverse biological effects through fisheries-freshwater cetaceans interactions [14]. Risks to river dolphins are more severe during the low water season when their habitats are fragmented and when dispersal ability is reduced [15]. Extinction of Yangtze River dolphins and a sharp decline in the populations of several river dolphins [Ganges River dolphin (Platanista gangetica gangetica), Indus River dolphin (Platanista gangetica minor), Irrawaddy dolphin (Orcaella brevirostris), Amazonian river dolphin (Inia geoffrensis), Bolivian river dolphin (Inia boliviensis), Tucuxi (Sotalia fluviatilis), Araguaian boto (Inia araguaiaensis)] are the example of consequences of inadequate flow in the Anthropocene [10, 11, 13, 16–18].

As habitat loss and fragmentation had significant adverse biological impacts on river cetaceans, previous studies recognized the sensitivity (presence/absence) of river dolphins to flow and their hydraulic properties (i.e., velocity, depth, and cross-sectional area) [19, 20]. Even though river flow directly regulates in-stream habitat structure that has a substantial impact on the organization and structure of biological communities [21], relationships between flow and ecological requirements of river cetaceans (particularly flows that determine the suitably usable area to river dolphins) have never been discussed and quantified. At the same time, appropriation of freshwater flows urged globally to sustain societal benefits and freshwater biodiversity by balancing the needs of humans, freshwater species, and ecosystems by setting limits for freshwater withdrawals and diversions [22]. Thus, there is an immediate need to understand the relationships between flow and river dolphins’ hydro-physical requirements at a finer scale to understand the effects of flow alternation on in-stream habitat availability while balancing river dolphins’ conservation and societal demands in the Anthropocene. Previous studies on aquatic ecosystem species conservation heavily consider ecological requirements of fish communities, thereby generalizing the flows over the entire ecosystem [23, 24]. Such an estimated flow for fish communities may not be ecologically adequate and relevant to the species that are at the top trophic level with large body size, i.e., freshwater cetaceans. Furthermore, studies on habitat selection by freshwater cetaceans conservatively link the presence and abundance data to coarse-scale (~1–3 km) satellite image drove hydro-physical variables and visually characterize habitat structure [South Asian river dolphins [19, 20, 25], Irrawaddy water dolphin [19, 26], Amazonian river dolphin [15, 27], Bolivian river dolphin [28], Yangtze finless porpoise [29], Tucuxi [15] with hydro-physical habitat preference, however, do not assess the quality and quantity of the hydro-physical parameters at discrete points occupied by river cetaceans. Even though species are sensitive to certain flow velocities and depths [30], previous studies on freshwater cetaceans did not account for these parameters when examining the cetaceans’ habitat preferences as these parameters play an important role in determining the availability of suitable in-stream habitat [20]. Lack of empirical relationships between river flow and river dolphins’ ecological responses may further elevate extinction risks by limiting our ability to establish thresholds on environmental flows that sustain remaining riverine endangered cetaceans.

We quantify the relationships between flow and river cetacean ecology to determine the availability of suitable in-stream physical habitat as a response to flow. We tested the effect of the individual hydro-physical parameters (flow, depth, velocity, cross-sectional area, width, and wetted perimeter) on the availability of the in-stream usable habitat of the Ganges River dolphins (GRD) at fine spatial and temporal scale. We assumed that GRD prefers a particular combination (velocity and depth at a specific flow) of the abiotic environment that determines the quality and availability of in-stream physical habitat. We, thus, developed the Habitat Suitability Curve (HSC) using a combination of the depth and velocity preferred by GRD, which allows us to quantify the availability of suitable in-stream habitat in the form of area-weighted suitability (AWS, m²/m). Our study quantifies the hydro-physical habitat selection of GRD at a wider level river flow, which could be essential to determine adequate river flows that are particularly significant for the conservation of in-stream habitats and critical to endangered freshwater cetaceans’ life activities during the low water season. Thus, the results of this study are essential to balance aquatic species’ conservation while minimizing the ecological risks induced through water extraction or diversion by development projects.

Materials and methods

Study area

This study was conducted in the Karnali River system of Nepal, where mega hydropower projects are under construction, and several are proposed and completed (Fig 1). Details about the current water-based projects and ecological significance are described in [10]. This river segment, particularly downstream, is highly significant to endanger aquatic species like GRD (Platanista gangetica gangetica), Gharial (Gavialis gangeticus), Smooth Indian otter (Lutra perspicillata), and diverse fish species. Current water extraction or diversion projects typically adopt a traditional biodiversity impact assessment (i.e., discussion and review based) but do not assess more detailed habitat relationships that include flow [31]. Additionally, water management plans adopted by such mega-projects are based on the proportion (or percentage) of total discharge at a particular season or time, undermining the aquatic species’ ecological requirements across space and time. Thus, balancing aquatic species conservation and development is the foremost priority of the concerned stakeholders.

Available habitat measurements

We conducted hydro-physical measurements across a 55 km continuous segment of the Karnali River of Nepal to the border with India during low water season when available habitat is reduced and river dolphin-anthropogenic activity interactions are intensified [32]. As the risk of changes in physical habitat may not truly represent the change in flow during the high flood season (or during daily fluctuation), we measured hydro-physical parameters two months from the termination of the monsoon (September). Field measurements of hydro-physical variables were conducted in December of 2017 and March and May of 2018 representing different flows (medium, low and high respectively) within the low water season. Therefore, our hydro-physical measurements represent a stable channel environment in response to flow. Flow was classified into different categories based on 39 years (1977–2015) of discharge data available for the study site from the Department of Hydrology, Government of Nepal. We stratified the study site into three segments (upper, middle, and lower, Fig 1) based on anthropogenic activities and hydro-physical characteristics of the river segment. The Mega hydropower project (Upper Karnali) is located upstream of the study site, whereas the Rani Jamara Kulariya Irrigation project water extraction point is in the upper segment of the study site. Within each segment, the study reach (the linear segment where cross-sections are established) was established in such a way that the length of each reach was at least higher than the mean width (so the number varies among segments) of the respective segment. Further, we also tried to maintain a relatively similar flow at the top and bottom of the reach to create hydro-physically homogenous reaches. Within each reach, random cross-sections were established to capture the hydraulic properties based on flow variation and length of the reach.

We used SonTek RiverSurveyor S5 (Acoustic Doppler Current Profiler-ADP) systems to measure open channel hydro-physical parameters (total discharge-m³/s; velocity-m/s; depth-m, wetted perimeter-m; total width-m, cross-sectional area (CSA)-m²) at each cross-section, which used multiple acoustic frequencies along with precise bandwidth control for the most robust and continuous shallow-to-deep discharge measurements. An intelligent algorithm with high ping rates of S5 looks at water depth, velocity, and turbulence. It then acoustically adapts to those conditions to ensure robust data collection by compensating for vessel motion due to surface conditions. All discharge computations are collected within the S5. Total discharge at each cross-section, along with its attributes (velocity and depth) were measured at a cell size between 0.02 to 0.5 m, with potential measurement errors of 0.25% and 1% in velocity and depth, respectively. The ADP S5 hydraulic data were imported into Excel databases (Microsoft v. 2010) to format for System for Environmental Flow Analysis (SEFA, version 1.5; Aquatic Habitat Analysts Inc.) software, where we estimated AWS for each cross-section and reach using HSC (described in a later section). The habitat type (HT), i.e., pool, run, and riffle, was classified based on the Froude number (Fr), where Froude is an index of hydraulic turbulence (the ratio of velocity by the acceleration of gravity) [33]. Because this index is a simple habitat classification criterion based on hydraulic characteristics of these three habitats, and correctly classified 66% of the observed habitats in a similar riverine ecosystem, we applied this index as a basis for habitat classification. Points with Froude numbers exceeding 0.41 were considered riffles, points with Froude numbers less than 0.18 were considered pools and intermediate values were classified as run habitats [33]. Although this approach to habitat classification is tested in a different environment, we adopted the generally acceptable and simple approach to standardize the fieldwork using state of the art technology (ADP) as previous research relied on visual based classification, which undermines the hydro-morphological characteristics. Thus, we recommend further testing and verification of this habitat classification approach to fit to the local environment context before future applications.

We used basic descriptive statistics (mean, range, standard deviation (SD)) to characterize the hydro-physical parameters. Variation of these parameters across the season and habitat type was examined using F-test at a 5% level of significance. All these analyses were done in R-Studio version 1.3.95.

GRD occupied habitat measurements

We measured the hydro-physical characteristics of the space used by GRD only in the main Karnali River, which is occupied by GRD most of the year. The tributary, Mohana segment, was excluded from the study as this tributary is only used by GRD during the monsoon season to avoid excessively high flow rates in the mainstream [32]. Also, across most of the year, this tributary exhibited seasonal characteristics (almost dry in the dry season). During each survey period, we used SonTek RiverSurveyor S5 for the measurement of hydro-physical parameters of GRD occupied. We used the widely applied Habitat Suitability Curve (HSC) approach to sustainable flow management while balancing aquatic conservation and societal demands to quantify area suitable to GRD [34]. We used the occupied habitat’s hydro-physical parameters of depth and velocity to develop the Habitat Suitability Curve (HSC) using the procedure described in [10]. We derived a suitability curve as a function of depth and velocity, which allows quantification of the in-stream river dolphin’s habitat availability in the form of area-weighted suitability (AWS, m²/m) at each cross section. Further, AWS of each cross-section is interpolated to get the value of AWS over the reach of the river [10]. This research was conducted under a research permit issued to the principal author of this paper by the Department of National Parks and Wildlife Conservation (DNPWC), Government of Nepal. All the observation procedures comply with regulations developed by the DNPWC.

Area weighted suitability model

Because of complex relationships between response (AWS) and explanatory variables, the risk of violation of statistical assumptions (risk of non-homogeneity of the variance of a response variable, skewness in the distribution of response) is very high. To address this, we used generalized additive models for location, scale, and shape (GAMLSS) to build relationships between response (AWS) and explanatory variables (flow, velocity, depth, season (S), habitat type (HT), width, wetted perimeter, cross-sectional area (CSA)) which permits us to address those statistical issues within the model [35]. First, we selected the distribution of the response variable that can adequately describe the nature of the response variable by building linear models of explanatory variables using available potential distribution type (gamma, Box-Cox Cole-Green orig., normal, inverse gamma, lognormal) within the GAMLSS package. The model with proper distribution type was selected using generalized Akaike information criterion (GAIC). We found gamma distribution to be the best distribution family that can describe our response variable adequately. We used the gamma distribution for all our subsequent analysis.

We select significant model terms–linear, smoothing, and interactive–separately to develop the initial model that consists of all potential linear, smoothing, and interactive terms. A significant linear term was selected by developing a full linear model of seven explanatory variables. Then we used the dropterm function to get the final significant linear terms, which adopts stepwise model selection steps based on GAIC. To obtain the significant smoothing term, the smoothing parameters (except categorical variables) were selected by developing the initial null model, and then each smoother was added, one at a time, to the null model to get significant smoothing terms. Further, we determine whether two-way interactions are needed in the model using stepGAIC function in between intercept (lower model) and the most complicated model with all two-way interactions (upper). After having a full initial model with significant terms (liner, interactive, and smoothers), we again used the dropterm function to get the final model with the lowest GAIC.

We use drop1 function available in the GAMLSS package to check for the approximate significance of the contribution of the smoothers (including the linear and interactive terms) at a 5% level of significance. To check the adequacy of the fitted GAMLSS model, we used a worm plot (wp function), which is a de-trended QQ-plot of the residuals [36]. For an adequate fitted model, we would expect the dots to be close to the middle horizontal line and 95% of them to lie between the upper and lower dotted curves, which act as 95% pointwise confidence intervals, with no systematic departure. All modeling procedures were completed using the gamlss package in R-Studio version 1.3.95.

Results

Available hydro-physical parameters

Available hydro-physical parameters differed over the season, except for depth (Table 1). All parameters were high in May and lowest in March. Across space or habitat type, hydro-physical parameters differ, except in flow (Table 2). The higher depth and cross-sectional area, along with the lowest velocity were recorded in deep pool habitat, followed by run and riffle habitats.

Table 1. Hydro-physical parameters across seasons.

	December (N = 70)	March (N = 60)	May(N = 47)	Total (N = 177)	P.value
Flow(m³/s)					F_2,174 = 22.05, P< 0.001
Mean (SD)	245.94 (81.52)	203.14(64.56)	326.33 (139.48)	252.78 (106.73)
Range	82.96–420.34	81.52–475.61	50.60–665.49	50.60–665.49
Depth(m)					F_2,174 = 1.91, P = 0.15
Mean (SD)	1.95 (0.79)	1.92 (0.74)	1.70 (0.47)	1.87 (0.71)
Range	0.93–4.71	0.88–5.02	1.05–3.12	0.88–5.02
Velocity(m/s)					F_2,174 = 4.89, P = 0.009
Mean (SD)	0.96 (0.33)	0.83 (0.29)	1.03 (0.35)	0.94 (0.33)
Range	0.454–2.120	0.335–2.111	0.374–1.822	0.335–2.120
Width(m)					F_2,174 = 10.23, P< 0.001
Mean (SD)	128.17 (46.54)	126.18 (56.18)	180 (102.37)	141.26 (72.06)
Range	47.50–271.62	56.56–390.50	55.01–490.15	47.50–490.15
CSA(m²)					F_2,174 = 3.78, P = 0.025
Mean (SD)	252.56 (136.35)	233.31 (102.97)	306.67 (181.26)	260.40 (142.40)
Range	68.45–760.94	74.79–593.67	80.72–774.76	68.45–774.76
WP(m)					F_2,174 = 10.14, < 0.001
Mean (SD)	129.29 (46.52)	127.23 (55.96)	180.87 (102.63)	142.29 (72.06)
Range	48.25–272.68	57.61–391.19	57.13–491.93	48.25–491.93

Open in a new tab

Variation on parameters across season tested using F-test and P value of significance reported.

Table 2. Hydro-physical parameters across habitat type.

	Pool(N = 65)	Riffle(N = 20)	Run(N = 92)	Total(N = 177)	P.value (F-test)
Flow(m³/s)					F_2,174 = 0.36, 0.695
Mean (SD)	261.78 (94.97)	245.99 (97.43)	247.90 (116.68)	252.78 (106.73)
Range	50.60–481.55	121.34–475.61	95.68–665.49	50.60–665.49
Depth(m)					F_2,174 = 58.16, P< 0.001
Mean (SD)	2.46 (0.80)	1.39 (0.24)	1.57 (0.35)	1.87 (0.71)
Range	1.17–5.02	0.93–1.92	0.88–2.87	0.88–5.02
Velocity(m/s)					F_2,174 = 203, P< 0.001
Mean (SD)	0.66 (0.14)	1.59 (0.28)	0.99 (0.18)	0.94 (0.33)
Range	0.33–1	1.12–2.12	0.53–1.41	0.33–2.12
Width(m)					F_2,174 = 3.59, P = 0.03
Mean (SD)	147.23 (64.87)	101.22 (34.05)	145.74 (80.27)	141.26 (72.06)
Range	55.01–441.05	47.50–171.49	56.56–490.15	47.50–490.15
CSA(m²)					F_2,174 = 28.55, P< 0.001
Mean (SD)	346.27 (139.31)	139.07 (45.61)	226.11(124.27)	260.40 (142.40)
Range	80.72–760.94	68.45–246.03	74.79–774.76	68.45–774.76
WP(m)					F_2,174 = 3.61, P = 0.029
Mean (SD)	148.73 (64.65)	102.16(34.29)	146.46 (80.35)	142.29 (72.06)
Range	57.13–442.75	48.25–172.08	57.61–491.93	48.25–491.93

Open in a new tab

Variation on parameters across season tested using F-test and P value of significance reported.

GAMLSS model of area-weighted suitability

The model with the lowest GAIC value consists of the linear (flow, velocity, habitat type, season), smoother (depth, cross-sectional area) and interactive terms (depth and velocity, velocity and season, habitat type, and season) [Model 1, Table 3]. As indicated by the summary statistics of the quantile residuals of the best-fitted model (the mean of the model is nearly zero, variance almost one, the coefficient of skewness is almost zero, and coefficient of kurtosis is almost 3), the residuals are approximately normally distributed, as for an adequate model [34]. Furthermore, the Filliben correlation coefficient (or the normal probability plot correlation coefficient) is almost 1. 95% of the points lie between the two elliptic curves of the Worm plot (Fig 2). All these statistical and visual graphs suggest that the fitted distribution (or the fitted terms) of the model is adequate to explain the response variable.

Table 3. GAMLSS models with df (degree of freedom) and GAIC (generalized Akaike Information Criteria) for the response variable area-weighted suitability (AWS, m²/m) and explanatory variables–flow (m³/s), velocity (m/s), depth(m), habitat type (HT- deep pool, riffle, run), cross-sectional area (m²) and season (December, March and May).

Model ID	Model	df	GAIC
1	AWS ~ Flow + Velocity + HT + Season + pb(Depth)+pb(CSA) + Depth:Velocity + Velocity:Season + HT:Season	27.73	1258.52
2	AWS ~ Flow + Depth + Velocity + CSA + HT + Season + pb(Depth) +pb(CSA) + Depth:Velocity + Flow:Season + Velocity:Season + HT:Season	29.66	1262.49
3	AWS ~ Flow + Depth + Velocity + CSA + HT + Season + pb(Depth) + Depth:Velocity + Flow:Season + Velocity:Season + HT:Season	27.06	1276.33
4	AWS ~ Flow + Depth + Velocity + CSA + HT + Season + Depth:Velocity +Velocity:Season + Depth:HT + Flow:CSA + HT:Season	25	1286.28
5	AWS ~ Flow + pb(Depth) + pb(Velocity) + CSA + HT + Season + Depth:Velocity + Flow:Season + Velocity:Season	22.97	1290.27
6	AWS ~ Flow + pb(Depth) + Velocity + CSA + HT + Season+Depth:Velocity + Flow:Season	20.7	1292.98
7	AWS ~ Flow + Depth + Velocity + CSA + HT + Season + Depth:Velocity + Velocity:Season + Depth:HT + Flow:CSA	21	1300
8	AWS ~ Flow + Depth + Velocity + CSA + HT + Season + Depth:Velocity +Flow:Season + Velocity:Season + Depth:HT + Flow:CSA	23	1303.54
9	AWS ~ Flow + Depth + Velocity + CSA + HT + Season + Depth:Velocity +Flow:Season + Velocity:Season + Depth:HT	22	1309.94
10	AWS ~ Flow + Depth + Velocity + CSA + HT + Season + Depth:Velocity + Flow:Season	18	1313.73
11	AWS~Flow + Depth + Velocity + CSA + HT + Season + Depth:Velocity +Flow:Season + Velocity:Season	20	1315.13
12	AWS ~ Flow + Depth + Velocity + CSA + HT + Season + Depth:Velocity	16	1324.36
13	AWS ~ Velocity + CSA + HT + Season	13	1339.85
14	AWS~Flow+Depth+Velocity+CSA+HT+Season	15	1343.82

Open in a new tab

The best fitted model is highlighted in bold, which consist of linear, smoother (as indicated by pb), and interactive terms of the explanatory variables.

Highly significant (the level of significance P < 0.001) linear predictors of the AWS were flow, velocity, season (March), depth, cross-sectional area, and of interactive terms were velocity and depth, and velocity and season (March). Flow and velocity exhibited linear negative relationships with AWS. In contrast, the depth and cross-sectional area revealed non-linear relationships, indicating both positive and negative contributions to AWS (Fig 3). Highest AWS was recorded in both December and March, and pools and riffle habitats exhibited higher AWS. The highest contribution to the variation of AWS was the interactions of the velocity and season (March) [β = 32.15, 95% CI range: 5.89–175.43], velocity and depth (β: 4.52, 95% CI: 2.26–9.03), followed by linear terms–cross-sectional area (β = 1.01, 95% CI: 1–1.01), flow (β = 0.992, 95% CI: 0.990–0.994), depth (β = 0.36, 95% CI: 0.21–0.60) and velocity (β = 0.03, 95% CI: 0.009–0.159) respectively. The cross-sectional area < 250 m² showed a negative contribution to the AWS, and above this point showed a positive linear contribution to the AWS (Fig 3). By season, peak dry season contributed negatively to the AWS. In contrast, both December and May had a positive contribution to the AWS in which the contribution of May was higher than December. Contribution of the deep pool and riffle habitats were higher to AWS than run (Fig 3). We model the contribution of wider flows (50–665 m³/s) to AWS, in which flows between 300 and 550 m³/s showed maximum positive contribution to AWS with the peak value of AWS at 450 m³/s (Fig 4). Relationships between flow and AWS reveal that a small and large value of flow has the same value of AWS. Velocity > 1m/s showed a negative contribution to the AWS in which 0.6 m/s had the highest positive contribution to AWS. Depth of 2–4 m maximized contribution to AWS, in which 2.5 m had the highest contribution to AWS (Fig 5).

Fig 3 — The contribution of the season to AWS was higher for both December and May, whereas March contributed negatively to AWS. Deep pool and riffle contributed positively, but run habitat holds a negative contribution to AWS.

Fig 4 — Vertical line represents an average of 90% exceedance flow of low (March), medium (December), and high (May) flow periods, suggesting highest AWS was available during May and AWS was substantially reduced during March and December due to reduced flow. It indicates that the flow of March (peak dry season) needs to be protected as it is under critical flow to protect river dolphins, which contributes negatively to AWS.

Fig 5 — 95 centile value of AWS >150 m²/m when depth and velocity were 2.7 m and 0.6 m/s, respectively.

Interactive effects of velocity and depth on area-weighted suitability

The velocity <0.25 m/s and depth with 2.5 m yielded the highest AWS (Fig 6). Depth between 2 and 3 m and higher cross-sectional area (>600 m²) predicted the highest AWS. Velocity between 0.5 and 1 m/s with a higher cross-sectional area (>600 m²) yielded the highest AWS.

Discussion

Lack of information on the fine-scale habitat selection of large and mobile aquatic predators–river cetaceans–limits our ability to understand the broad-scale impacts of human-caused changes to the dynamic riverine ecosystem. As river cetaceans exhibit a strong dependence on hydro-physical attributes, including geomorphic and seasonal flow variation effects, they are essential to informing the decision-making process of flow regulation management, including the identification and protection of river cetaceans’ priority habitats. Our results can be used to incorporate knowledge about in-stream habitat selection and the potential effects of declining freshwater flow on the ecology of the large top predator of the riverine ecosystem into the design of habitat retention plan and water development projects that may alter the natural flow regime at the cost of aquatic species conservation. Incorporation of the ecology of a key mobile aquatic predator may help to conserve other lower trophic or similar aquatic species that share the river’s physical habitat template and ecosystem [37].

Previous studies on river dolphins’ habitat selection or preference commonly reported the aggregation of river dolphins in certain hydro-physical habitats [32, 38], especially deep pools. The majority of the studies attributed such habitat selection to the higher biological productivity and prey abundance [39, 40]. However, the ecological significance of such habitats to river dolphins has never been described explicitly. Here, we characterize the hydro-physical parameters of the deep pools that may be significant to the ecology of river dolphins. We demonstrate that deep pools offer higher cross-sectional areas combined with the deepest depth and considerably reduced water velocity, and in turn, yield the highest usable area to the river dolphins. The ecological significance of deep pools that offer the highest usable area is linked to the diving physiology of dolphins as the selection of deeper usable areas appears to be a mechanism that enables diving river cetaceans with limited oxygen stores to extend the duration of a dive [41]. Further, reduced velocity of water in deep pools in comparison to other habitats (run, riffle) may support river dolphins to reduce their swimming speed as the elevated swimming speeds during dive or swimming decreases the duration of a dive due to rapid depletion of limited oxygen reserves [42]. As a result, frequent diving in deep pools by river dolphins is ecologically and physiologically important by reducing the metabolic cost of dives. Such energetically efficient modes of locomotion in deep pools provide an advantage during periods of diving (submerge) and will presumably increase foraging efficiency as the animals perform progressively longer dives.

Global population decline and isolation risks of river dolphins is frequently attributed to declining flows due to dams or barrages [11, 16, 18, 32, 43, 44]. As a result, the need for adequate flow to conserve the remaining endangered river dolphins is heightened globally [10, 19, 20, 44, 45]. However, to our knowledge, information on quantitative relationships between flow and river cetaceans is scant, particularly for the low water season when habitat availability reduces, and longitudinal connectivity worsens. The linear negative relationships between flow and AWS combined with physical effects of flow variability in the cross-sectional area of the channel exemplified that immediate effects of flow fluctuation (either increase or decrease) are the loss of suitably usable area (i.e. habitat loss). All flows are not contributing in the same fashion to AWS, offering the opportunity to balance water extraction and conservation. Availability of AWS as a function of river flow shows that the flow of May (average 90% exceedance flow = 439.4 m³/s) offers maximum AWS compared to the flows of December (average 90% exceedance flow = 335 m³/s) and March (average 90% exceedance flow = 221 m³/s) [Fig 4]. Flows in March represent critically low flow (negative contribution to AWS), which substantially reduces AWS. Flow from December to April seems more critical for river dolphin conservation. This flow variation across season suggests that flow is the major determinant of river cetaceans’ hydro-physical habitat, which substantially alters the habitat at varying spatial and temporal scales. Further, the variation in flow is likely to control the migration strategies of aquatic species [46]. This is demonstrated by GRD in our study site. As the monsoon starts with the average 90% exceedance flow of 672 m³/s in June, unusable habitats in the main stream with flow >600 m³/s (Fig 4) trigger GRD to migrate to a tributary (Mohana River; starts from the first week of June; personal observation), which offers seasonal refuge and suggests that a seasonal high flow has a major influence on shaping the life-history patterns of river dolphins. Similar high flow-regulated seasonal migration patterns are exhibited by river dolphins in an Amazonian floodplain [47]. As the river dolphins’ birthing peak is during low water season [48], such high flow with the potential of physical disturbance immediately after the birth may pose a risk of recruitment failure for young calves [49].

The requirement of adequate flow is commonly cited to protect river dolphins and avoid the risk of population isolations that may cause recruitment failure and intensify local extinction [10, 11, 19, 20]. Our results may assist to determine the adequate flow across seasons that might have potential ecological significance to maintain the longitudinal connectivity essential to sustain the viability of river dolphins and other aquatic taxa that share the ecosystem. As water extraction and dam construction limits aquatic species dispersal ability to move freely through the stream network, extinction risk and endangerment of river cetaceans whose existence relies on flow will particularly be high during low water season. Our results could help river managers to predict how far in-stream usable areas can be altered from their natural state before water extraction or withdrawal occurs. As the species’ abundance and distribution vary with stream depth and velocity [50], the microhabitat preferences of river cetaceans as a function of velocity and depth were poorly known. Our model shows that the distribution of suitable habitats (i.e. pools) of GRD is largely determined by the interactive effects of velocity and depth at a particular landform. The velocity (<0.5 m/s) combined with a depth between 2 and 3 m yielded a higher useable area to GRD in the study site (Fig 6). Further, a greater cross-sectional area (>600 m²) with similar velocity and depth ranges offer maximum suitable areas to GRD. Such complex habitat selection behavior (depth, velocity, and cross-sectional area) exhibited by Ganges River dolphins in a dynamic aquatic environment indicates GRD are habitat specialists with narrow habitat breadth and environmental plasticity. Given the often-cited patchy distribution pattern of GRD [51], such interactive effects may play a significant role in the distribution and abundance of river cetaceans. Understanding river dolphins’ specific in-stream habitat preference in relation to flow may offer an effective riverine conservation management plan for a heavily regulated river system [46].

Loss in habitat quality and the limited ability of species to migrate to new habitats is a major challenge for aquatic species conservation [52]. Our results indicate that the vulnerability of river cetaceans is increased by fragmentation and loss of longitudinal connectivity when the flow reduction is intensified either naturally or artificially. Higher risk of deep pool fragmentation and loss of longitudinal connectivity across suitable pools are commonly suggested conservation issues for river dolphins conservation, particularly in the dry season [10, 11, 17]. Effective flow regulation plans are critical to riverine cetacean conservation and management to avoid further acceleration of extinction risk [10, 11, 19, 20]. A 2D map of the segments (surface map of depth as a function of flow) for the low flow period (March) clearly indicates the substantial fragmentation in deep pools’ (>2) availability along with potential dolphin passage barriers (depth <0.5m) as a response to reduce flow (Fig 7). Barriers to passage may limit GRD dispersal ability to suitable habitats, which may exacerbate the rate of endangerment and local extinction of the remaining populations of endangered GRD [53]. We suggest that conservation agencies must be adopted effective assessment procedures to determine the true impact of flow extraction or diversion projects to intensify conservation of aquatic biota in these vanishing riverine ecosystems.

Fig 7 — A pseudo-2D view of the depth (m) surface showing in contours and shading for segments (a) upper, (b) medium, (c) lower using interpolation technique. Light yellow indices depth <0.5 m and dark blue indicate deep pools >2 m, respectively. Sparsely located dark blue and substantially present light yellow over the continuum of the segments indicate acute habitat fragmentation and loss of connectivity across suitable pools during low water (peak dry season-March) when flow reduced.

The biological consequences of habitat loss and fragmentation in declining river cetaceans are evident. Births and mating activities of river dolphins generally peak during low water season when all animals are concentrated along the main stream [48], likely reducing pairing success, which may hinder reproduction processes in isolated habitats and be a contributing factor to the low occupancy and decline of species, especially Platanista gangetica species. Further, spatial overlap during the low water season between river cetaceans and fisheries may intensify, leading to entanglement and reduction of survivorship [10, 14, 15]. Further diversion or withdrawal of flow from the mainstream contributes to habitat loss and undoubtedly leads to local extirpation. Combined effects of habitat loss with anthropogenic disturbances (fishing pressure and flow regulation by development projects) may lead to rapid population decline and local extinction of river cetaceans [53]. Rapid loss (~50%) of Platanista gangetica species is the clear evidence of such effects [10, 17]. Even though conserving the natural flow is unrealistic given societal demands [54], the seasonal effects and changes on the availability of usable areas to river cetaceans must be a central guiding element to conserve riverine biodiversity. Identifying priority riverscapes for river cetaceans, and prioritizing investment opportunities for development projects could be an essential first step towards effective conservation of riverine biodiversity.

Our research addresses a critical limitation in the ability to predict and quantify the river dolphins’ response to flow regulation. We demonstrated quantitative relationships between flow and cetaceans ecology in the form of usable area availability in response to flow. These findings should permit the development of a proactive riverine cetacean management plan that incorporates habitat manipulation and protection, including the creation of migration/movement corridors. Owing to the strong dependence on the attribute of freshwater flow, river dolphins are expected to be more affected by flow regulation as the interactive effects of flow and depth at particular landforms play a significant role to determine the usable area. Freshwater withdrawal and extraction by large-scale hydropower or irrigation projects will undoubtedly cause major ecological changes in the dynamic riverine ecosystem, which decreases the viability of river dolphins populations. River cetaceans are more sensitive to the attributes of freshwater flow, and the decline of freshwater flow may further put endangered cetaceans at risk of local extirpation, as exemplified by a sharp decline in abundance and range of GRD in a study site as flow regulation progress [32]. Knowledge of key hydro-physical habitat components may support development of a riverine habitat retention management plan in response to top predator or mega-species life history requirements [10].

Acknowledgments

We thank Rajesh Sigdel, RC Gautam and various local stakeholders for assisting data collection process. Two reviewers provided helpful comments to increase the accessibility of the manuscript and we appreciate their efforts. Thanks to Department of National Parks and Wildlife Conservation, Government of Nepal for granting research permit.

Data Availability

All relevant data are within the manuscript.

Funding Statement

The author (SP) received field research grants from: Rufford Foundation (UK), Commonwealth Scientific and Industrial Research Organization (CSIRO-Australia), and WWF-Nepal. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

1.Dudgeon D. Multiple threats imperil freshwater biodiversity in the Anthropocene. Current Biology. 2019. Oct 7;29(19):R960–7. doi: 10.1016/j.cub.2019.08.002 [DOI] [PubMed] [Google Scholar]
2.Destouni G, Jaramillo F, Prieto C. Hydroclimatic shifts driven by human water use for food and energy production. Nature Climate Change. 2013. Mar;3(3):213–7. [Google Scholar]
3.Jaramillo F, Destouni G. Local flow regulation and irrigation raise global human water consumption and footprint. Science. 2015. Dec 4;350(6265):1248–51. doi: 10.1126/science.aad1010 [DOI] [PubMed] [Google Scholar]
4.Destouni G, Jarsjö J. Zones of untreatable water pollution call for better appreciation of mitigation limits and opportunities. Wiley Interdisciplinary Reviews: Water. 2018. Nov;5(6):e1312. [Google Scholar]
5.Winemiller KO, McIntyre PB, Castello L, Fluet-Chouinard E, Giarrizzo T, Nam S, et al. Balancing hydropower and biodiversity in the Amazon, Congo, and Mekong. Science. 2016. Jan 8;351(6269):128–9. doi: 10.1126/science.aac7082 [DOI] [PubMed] [Google Scholar]
6.FAO. 2016. AQUASTAT database. http://www.fao.org/nr/water/aquastat/data/.
7.Elmhagen B, Destouni G, Angerbjörn A, Borgström S, Boyd E, Cousins SA, et al. Interacting effects of change in climate, human population, land use, and water use on biodiversity and ecosystem services. Ecology and Society. 2015. Mar 1;20(1). [Google Scholar]
8.Carrizo SF, Jähnig SC, Bremerich V, Freyhof J, Harrison I, He F, et al. Freshwater megafauna: Flagships for freshwater biodiversity under threat. Bioscience. 2017. Oct 1;67(10):919–27. doi: 10.1093/biosci/bix099 [DOI] [PMC free article] [PubMed] [Google Scholar]
9.He F, Zarfl C, Bremerich V, David JN, Hogan Z, Kalinkat G, et al. The global decline of freshwater megafauna. Global Change Biology. 2019. Nov;25(11):3883–92. doi: 10.1111/gcb.14753 [DOI] [PubMed] [Google Scholar]
10.Paudel S, Koprowski JL, Thakuri U, Sigdel R, Gautam RC. Ecological responses to flow variation inform river dolphin conservation. Scientific Reports. 2020. Dec 18;10(1):1–3. doi: 10.1038/s41598-019-56847-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
11.Paschoalini M, Almeida RM, Trujillo F, Melo-Santos G, Marmontel M, Pavanato HJ, et al. On the brink of isolation: Population estimates of the Araguaian river dolphin in a human-impacted region in Brazil. Plos one. 2020. Apr 22;15(4):e0231224. doi: 10.1371/journal.pone.0231224 [DOI] [PMC free article] [PubMed] [Google Scholar]
12.Braulik GT, Noureen U, Arshad M, Reeves RR. Review of status, threats, and conservation management options for the endangered Indus River blind dolphin. Biological Conservation. 2015. Dec 1;192:30–41. [Google Scholar]
13.Krützen M, Beasley I, Ackermann CY, Lieckfeldt D, Ludwig A, Ryan GE, et al. Demographic collapse and low genetic diversity of the Irrawaddy dolphin population inhabiting the Mekong River. Plos one. 2018. Jan 3;13(1):e0189200. doi: 10.1371/journal.pone.0189200 [DOI] [PMC free article] [PubMed] [Google Scholar]
14.Kelkar N, Krishnaswamy J, Choudhary S, Sutaria D. Coexistence of fisheries with river dolphin conservation. Conservation Biology. 2010. Aug;24(4):1130–40. doi: 10.1111/j.1523-1739.2010.01467.x [DOI] [PubMed] [Google Scholar]
15.Martin AR, da Silva VM, Salmon DL. Riverine habitat preferences of botos (Inia geoffrensis) and tucuxis (Sotalia fluviatilis) in the central Amazon. Marine Mammal Science. 2004. Apr;20(2):189–200. [Google Scholar]
16.Turvey ST, Pitman RL, Taylor BL, Barlow J, Akamatsu T, Barrett LA, et al. First human-caused extinction of a cetacean species?. Biology letters. 2007. Oct 22;3(5):537–40. doi: 10.1098/rsbl.2007.0292 [DOI] [PMC free article] [PubMed] [Google Scholar]
17.Braulik GT, Noureen U, Arshad M, Reeves RR. Review of status, threats, and conservation management options for the endangered Indus River blind dolphin. Biological Conservation. 2015. Dec 1;192:30–41. [Google Scholar]
18.Pavanato HJ, Melo-Santos G, Lima DS, Portocarrero-Aya M, Paschoalini M, Mosquera F, et al. Risks of dam construction for South American river dolphins: a case study of the Tapajós River. Endangered species research. 2016. Sep 21;31:47–60. [Google Scholar]
19.Smith BD, Braulik G, Strindberg S, Mansur R, Diyan MA, Ahmed B. Habitat selection of freshwater‐dependent cetaceans and the potential effects of declining freshwater flows and sea‐level rise in waterways of the Sundarbans mangrove forest, Bangladesh. Aquatic Conservation: Marine and Freshwater Ecosystems. 2009. Mar;19(2):209–25. [Google Scholar]
20.Braulik GT, Reichert AP, Ehsan T, Khan S, Northridge SP, Alexander JS, et al. Habitat use by a freshwater dolphin in the low‐water season. Aquatic Conservation: Marine and Freshwater Ecosystems. 2012. Jun;22(4):533–46. [Google Scholar]
21.Maddock I. The importance of physical habitat assessment for evaluating river health. Freshwater biology. 1999. Mar;41(2):373–91. [Google Scholar]
22.Aldaya MM, Martínez-Santos P, Llamas MR. Incorporating the water footprint and virtual water into policy: Reflections from the Mancha Occidental Region, Spain. Water Resources Management. 2010. Mar 1;24(5):941–58. [Google Scholar]
23.Rosenfeld JS. Developing flow–ecology relationships: Implications of nonlinear biological responses for water management. Freshwater Biology. 2017. Aug;62(8):1305–24. [Google Scholar]
24.Bruckerhoff LA, Leasure DR, Magoulick DD. Flow–ecology relationships are spatially structured and differ among flow regimes. Journal of applied ecology. 2019. Feb;56(2):398–412. [Google Scholar]
25.Choudhary S, Dey S, Dey S, Sagar V, Nair T, Kelkar N. River dolphin distribution in regulated river systems: implications for dry‐season flow regimes in the Gangetic basin. Aquatic Conservation: Marine and Freshwater Ecosystems. 2012. Jan;22(1):11–25. [Google Scholar]
26.Peter C, Poh AN, Ngeian J, Tuen AA, Minton G. Identifying habitat characteristics and critical areas for Irrawaddy dolphin, Orcaella brevirostris: Implications for conservation. InNaturalists, explorers and field scientists in South-East Asia and Australasia 2016. (pp. 225–238). Springer, Cham. [Google Scholar]
27.Araújo CC, da Silva VM. Spatial distribution of river dolphins, Inia geoffrensis (Iniidae), in the Araguaia River (central Brazil). Mammalia. 2014. Nov 1;78(4):481–6. [Google Scholar]
28.Guizada L, Aliaga-Rossel E. Abundance of the Bolivian River Dolphin (Inia boliviensis) in Mamore River, Upper Madeira Basin. Aquatic Mammals. 2016. Jul 1;42(3 [Google Scholar]
29.Chen M, Yu D, Lian Y, Liu Z. Population abundance and habitat preference of the Yangtze finless porpoise in the highest density section of the Yangtze River. Aquatic Conservation: Marine and Freshwater Ecosystems. 2020. Jun;30(6):1088–97. [Google Scholar]
30.Thomas JA, Bovee KD. Application and testing of a procedure to evaluate transferability of habitat suitability criteria. Regulated Rivers: Research & Management. 1993. Aug;8(3):285–94. [Google Scholar]
31.Rani Jamara Kulariya Irrigation Project, 2017. Environmental Assessment. Volume 2. Nepal: Department of Irrigation.
32.Paudel S, Pal P, Cove MV, Jnawali SR, Abel G, Koprowski JL, et al. The Endangered Ganges River dolphin Platanista gangetica gangetica in Nepal: abundance, habitat and conservation threats. Endangered Species Research. 2015. Nov 25;29(1):59–68. [Google Scholar]
33.Jowett IG. A method for objectively identifying pool, run, and riffle habitats from physical measurements. New Zealand journal of marine and freshwater research,1993; 27(2), pp.241–248. [Google Scholar]
34.Nestler JM, Milhous RT, Payne TR, Smith DL. History and review of the habitat suitability criteria curve in applied aquatic ecology. River Research and Applications. 2019. Oct; 35(8):1155–80. [Google Scholar]
35.Stasinopoulos MD, Rigby RA, Heller GZ, Voudouris V, De Bastiani F. Flexible regression and smoothing: using GAMLSS in R. CRC Press; 2017. Apr 21. [Google Scholar]
36.Buuren SV, Fredriks M. Worm plot: a simple diagnostic device for modelling growth reference curves. Statistics in medicine. 2001. Apr 30;20(8):1259–77. doi: 10.1002/sim.746 [DOI] [PubMed] [Google Scholar]
37.Turvey ST, Risley CL, Barrett LA, Yujiang H, Ding W. River dolphins can act as population trend indicators in degraded freshwater systems. PLoS One. 2012. May 29;7(5):e37902. doi: 10.1371/journal.pone.0037902 [DOI] [PMC free article] [PubMed] [Google Scholar]
38.Gomez‐Salazar C, Trujillo F, Portocarrero‐Aya M, Whitehead H. Population, density estimates, and conservation of river dolphins (Inia and Sotalia) in the Amazon and Orinoco river basins. Marine Mammal Science. 2012. Jan;28(1):124–53. [Google Scholar]
39.Smith BD, Haque AA, Hossain MS, Khan A. River dolphins in Bangladesh: conservation and the effects of water development. Environmental management. 1998. May 1;22(3):323–35. doi: 10.1007/s002679900108 [DOI] [PubMed] [Google Scholar]
40.Biswas SP, Boruah S. Ecology of the river dolphin (Platanista gangetica) in the upper Brahmaputra. Hydrobiologia. 2000. Jul 1;430(1–3):97–111. [Google Scholar]
41.Skrovan RC, Williams TM, Berry PS, Moore PW, Davis RW. The diving physiology of bottlenose dolphins (Tursiops truncatus). II. Biomechanics and changes in buoyancy at depth. Journal of Experimental Biology. 1999. Oct 15;202(20):2749–61. [DOI] [PubMed] [Google Scholar]
42.Williams TM, Haun JE, Friedl WA. The diving physiology of bottlenose dolphins (Tursiops truncatus). I. Balancing the demands of exercise for energy conservation at depth. Journal of Experimental Biology. 1999. Oct 15;202(20):2739–48. [DOI] [PubMed] [Google Scholar]
43.Choudhury NB, Mazumder MK, Chakravarty H, Choudhury AS, Boro F, Choudhury IB. The endangered Ganges river dolphin heads towards local extinction in the Barak river system of Assam, India: A plea for conservation. Mammalian Biology. 2019. Jan 1;95(1):102–11. [Google Scholar]
44.Trujillo-González F, Mosquera-Guerra F, Franco N. River dolphins: Species that indicate the state of health of the aquatic ecosystems of the Amazon and Orinoco regions. Revista de la Academia Colombiana de Ciencias Exactas, Físicas y Naturales. 2019. Jun;43(167):199–211. [Google Scholar]
45.Dey M., Krishnaswamy J., Morisaka T., & Kelkar N. (2019). Interacting effects of vessel noise and shallow river depth elevate metabolic stress in Ganges river dolphins. Scientific reports, 9(1), 1–13. doi: 10.1038/s41598-019-51664-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
46.Bunn SE, Arthington AH. Basic principles and ecological consequences of altered flow regimes for aquatic biodiversity. Environmental management. 2002. Oct 1;30(4):492–507. doi: 10.1007/s00267-002-2737-0 [DOI] [PubMed] [Google Scholar]
47.Mintzer VJ, Lorenzen K, Frazer TK, da Silva VM, Martin AR. Seasonal movements of river dolphins (Inia geoffrensis) in a protected Amazonian floodplain. Marine Mammal Science. 2016. Apr;32(2):664–81. [Google Scholar]
48.Martin AR, Da Silva VM. Reproductive parameters of the Amazon river dolphin or boto, Inia geoffrensis (Cetacea: Iniidae); an evolutionary outlier bucks no trends. Biological Journal of the Linnean Society. 2018. Mar 2;123(3):666–76. [Google Scholar]
49.Jowett IG, Richardson J, McDowall RM. Relative effects of in‐stream habitat and land use on fish distribution and abundance in tributaries of the Grey River, New Zealand. New Zealand journal of marine and freshwater research. 1996. Dec 1;30(4):463–75. [Google Scholar]
50.Smith BD. 1990 Status and conservation of the Ganges River dolphin Platanista gangetica in the Karnali River, Nepal. Biological Conservation. 1993. Jan 1;66(3):159–69. [Google Scholar]
51.Schwartz MW. Modelling effects of habitat fragmentation on the ability of trees to respond to climatic warming. Biodiversity & Conservation. 1993. Feb 1;2(1):51–61. [Google Scholar]
52.Battin J. When good animals love bad habitats: ecological traps and the conservation of animal populations. Conservation Biology. 2004. Dec;18(6):1482–91. [Google Scholar]
53.Walker KF, Thoms MC. Environmental effects of flow regulation on the lower River Murray, Australia. Regulated Rivers: Research & Management. 1993. May;8(1‐2):103–19. [Google Scholar]
54.Sowa SP, Annis G, Morey ME, Diamond DD. A gap analysis and comprehensive conservation strategy for riverine ecosystems of Missouri. Ecological monographs. 2007. Aug;77(3):301–34. [Google Scholar]

PLoS One. doi: 10.1371/journal.pone.0241099.r001

Decision Letter 0

Susana Caballero

24 Nov 2020

PONE-D-20-31590

In-stream habitat availability for river dolphins in response to flow: use of ecological integrity to manage river flows

PLOS ONE

Dear Dr. Paudel,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

I received two reviews for this manuscript. Both reviewers commend the authors on the work and they think this type of research is needed urgently to further understand ways in which river dolphins can be conserved and viable populations can be maintained. However, one of the reviewers, an expert in hydraulics, was critic considering the way in which the authors explain the concepts related to hydraulics. I cite him: "noted a few occasions when the authors did not appear to clearly understand what they were describing, and overall I felt that the presentation quality of the hydraulic results was low. If possible I would suggest collaborating with someone in that field as the data set looks promising and the problem clearly merits attention. I have made many other comments in the manuscript".

The second reviewer, and expert in river dolphin conservation was very positive about the manuscript and considered acceptance.

Considering these two reviews, I suggest the authors that they thoroughly revise their manuscript, especially the concepts and results related with hydraulics. Maybe communicate with a local expert in this field that can provide their expertise? I personally consider that we need all the good quality information that can be made available for river dolphin conservation, so I really hope the authors work on this recommendation to improve the quality of their paper.

Please submit your revised manuscript by 1st of February 2021. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

We look forward to receiving your revised manuscript.

Kind regards,

Susana Caballero, PhD

Academic Editor

PLOS ONE

Additional Editor Comments:

The second reviewer, and expert in river dolphin conservation was very positive about the manuscript and considered acceptance.

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. Thank you for stating the following in the Acknowledgments Section of your manuscript:

"Thanks to the numerous agencies -- Rufford Foundation (UK), WWF-EFN Program (USA),

Institute of Forestry (Tribhuvan University, Nepal), Commonwealth Scientific and Industrial

Research Organization (CSIRO-Australia), WWF-Nepal, University of Arizona – School of

Natural Resources and the Environment – for field funding support."

We note that you have provided funding information that is not currently declared in your Funding Statement. However, funding information should not appear in the Acknowledgments section or other areas of your manuscript. We will only publish funding information present in the Funding Statement section of the online submission form.

Please remove any funding-related text from the manuscript and let us know how you would like to update your Funding Statement. Currently, your Funding Statement reads as follows:

"The author (SP) received small field research grant from: Rufford Foundation (UK), Commonwealth Scientific and Industrial Research Organization (CSIRO-Australia), and WWF-Nepal. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript."

Please include your amended statements within your cover letter; we will change the online submission form on your behalf.

3. Please amend your authorship list in your manuscript file to include author Ajay Karki.

4. We note that Figure 1 in your submission contain map images which may be copyrighted. All PLOS content is published under the Creative Commons Attribution License (CC BY 4.0), which means that the manuscript, images, and Supporting Information files will be freely available online, and any third party is permitted to access, download, copy, distribute, and use these materials in any way, even commercially, with proper attribution. For these reasons, we cannot publish previously copyrighted maps or satellite images created using proprietary data, such as Google software (Google Maps, Street View, and Earth). For more information, see our copyright guidelines: http://journals.plos.org/plosone/s/licenses-and-copyright.

We require you to either (1) present written permission from the copyright holder to publish these figures specifically under the CC BY 4.0 license, or (2) remove the figures from your submission:

41. You may seek permission from the original copyright holder of Figure 1 to publish the content specifically under the CC BY 4.0 license.

We recommend that you contact the original copyright holder with the Content Permission Form (http://journals.plos.org/plosone/s/file?id=7c09/content-permission-form.pdf) and the following text:

“I request permission for the open-access journal PLOS ONE to publish XXX under the Creative Commons Attribution License (CCAL) CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). Please be aware that this license allows unrestricted use and distribution, even commercially, by third parties. Please reply and provide explicit written permission to publish XXX under a CC BY license and complete the attached form.”

Please upload the completed Content Permission Form or other proof of granted permissions as an "Other" file with your submission.

In the figure caption of the copyrighted figure, please include the following text: “Reprinted from [ref] under a CC BY license, with permission from [name of publisher], original copyright [original copyright year].”

4.2. If you are unable to obtain permission from the original copyright holder to publish these figures under the CC BY 4.0 license or if the copyright holder’s requirements are incompatible with the CC BY 4.0 license, please either i) remove the figure or ii) supply a replacement figure that complies with the CC BY 4.0 license. Please check copyright information on all replacement figures and update the figure caption with source information. If applicable, please specify in the figure caption text when a figure is similar but not identical to the original image and is therefore for illustrative purposes only.

The following resources for replacing copyrighted map figures may be helpful:

USGS National Map Viewer (public domain): http://viewer.nationalmap.gov/viewer/

The Gateway to Astronaut Photography of Earth (public domain): http://eol.jsc.nasa.gov/sseop/clickmap/

Maps at the CIA (public domain): https://www.cia.gov/library/publications/the-world-factbook/index.html and https://www.cia.gov/library/publications/cia-maps-publications/index.html

NASA Earth Observatory (public domain): http://earthobservatory.nasa.gov/

Landsat: http://landsat.visibleearth.nasa.gov/

USGS EROS (Earth Resources Observatory and Science (EROS) Center) (public domain): http://eros.usgs.gov/#

Natural Earth (public domain): http://www.naturalearthdata.com/

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: No

Reviewer #2: Yes

**********

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

Reviewer #1: I Don't Know

Reviewer #2: Yes

**********

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

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

Reviewer #2: Yes

**********

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

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: I read this study with interest as it did describe a novel approach to understanding the habitat of river dolphins, which is critical, as the authors say, for understanding what the impacts of flow regulation in the form of hydropower megaprojects will be on habitat loss and fragmentation. As a researcher on the hydraulic side, this seemed to me an important opportunity to delve into an important issue of our time and to link it with channel hydraulics. I am not an expert on the AWS modelling and the statistical tools used to asses the model and so will not comment extensively on them. I commend the researchers on their efforts to obtain a unique and important dataset in this environment. However, the study should not be considered adequate from a hydraulic perspective. I noted a few occasions when the authors did not appear to clearly understand what they were describing, and overall I felt that the presentation quality of the hydraulic results was low. If possible I would suggest collaborating with someone in that field as the data set looks promising and the problem clearly merits attention. I have made many other comments in the manuscript, but overall my recommendation is to reject.

Reviewer #2: The manuscript is well prepared and develops the objectives proposed in the investigation in a clear and robust way.

Please change the term "riverine cetaceans" in the document to "river dolphins", and in the abstract section in the lines 30 -31 change the words "with reference to" for concerning or regarding. Introduction in the line 59 delete the words "the", in the line 67 delete ",", line 94 include "," in the phrase "species, and", line 103 "the" in the phrase "the presence", and change the word "driven" for drove or has driven, line 107 include "," the word "however", line 108 include "the" in the phrase "the quality", line 129 change the phrase " in relation to" for "about, to, with or concerning", and change the phrase "properties of wider level" for "properties of a wider level". Materials and Methods in the line 141 change the words "endangered" for "endanger", line 177 change the words "cross section" for "cross-section", line 192 remove "," of the phrase "considered pools, and intermediate", line 201 change the word "main stream" or "mainstream", line 202 change the word "characteristic" for "characteristics", lines 231 and 238 change the word "dropterm" for "drop term", lines 241 and 247 include "the" in the phrase " in the GAMLSS package to", and "were completed using the gamlss package". Results in the line 252 include the word "the season" or "a season", line 254 include the word "The higher", and "the lowest", line 275 include "," in the phrase " , and", line 278 include "the coefficient", and line 295 change the word "were flowed or were flowing". Discussion in the line 363 include "-" in the phrase "broad-scale", line 364 include "a" in the phrase "a strong", line 382 include " the river", line 390 change the word "is" for "are", line 413 include " with an average", line 436 delete "a" in the phrase "with similar velocity", line 438 change the word "indicates" or "indicate", line 446 in include the word "that the vulnerability", line 447 change the word "is" for "are" and include the word "the flow", line 488 include the word "the development", line 449 include "the viability", and line 496 change the word "under" for "at".

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: Federico Mosquera-Guerra Phd.

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

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.

Attachment

Submitted filename: PONE-D-20-31590_reviewer.pdf

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

PLoS One. 2021 Jul 21;16(7):e0241099. doi: 10.1371/journal.pone.0241099.r002

Author response to Decision Letter 0

29 Dec 2020

Date: 12-29-2020

Susana Caballero, PhD

Academic editor

PLOS ONE

Dear Susana,

First of all, I would like to thank you for the opportunity to revise and resubmit our manuscript, entitled “In-stream habitat availability for river dolphins in response to flow: use of ecological integrity to manage river flows”. I found the reviewers’ comments to be helpful in revising the manuscript and have carefully considered and responded to each suggestion. We completely addressed issues raised by the reviewer two but in the case of reviewer one, the reviewer seems like deviated from the core aim and approach of the paper due to technical limitations that connect ecology-flow. Since this paper is extended findings of the research which was recently published in Nature Scientific Reports (Ecological responses to flow variation inform river dolphin conservation | Scientific Reports (nature.com)) that builds flow-ecology relationships, the approach mentioned in the submitted paper to PLOS ONE is scientifically and technically validated (the same approach we published in Nature Scientific Reports was used). The reviewer mentioned technically inadequate, and recommend to consult the hydrologist. However, we had a team of biologists, hydrologist, geologist and engineers, who made this approach collectively to develop the flow-ecology relationships and now scientifically accepted as indicated by the publication in Nature Scientific Reports. Even though we mentioned clear measurement approach (available and occupied hydro-physical habitats) and links between flow-ecology through AWS calculation, the reviewer one finds hard to connect the links between flow-ecology. We added lines (199-203) and references [10, 33; above published paper] to make the approach and goal clearer to the reader. This is clearly mentioned in lines 118- 126 and 169-206. Again, the approach mentioned in this paper is already published that indicates technically and scientifically validated.

I have included a response to reviewers (below) in which we address each comment the reviewers made. In our response to reviewers, our responses follow immediately below the comment in yellow highlight. Corresponding changes are highlighted in yellow in the manuscript text in the revised file.

Important notes:

1. Please include this funding statement in the system on behave of author: "The author (SP) received field research grants from: Rufford Foundation (UK), Commonwealth Scientific and Industrial Research Organization (CSIRO-Australia), and WWF-Nepal. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript."

2. Figure 1 is already published [ reference 10] written by same principal author (Shambhu Paudel). This figure is re-use under the CC BY License agreement.

Thank you again for your consideration of our revised manuscript.

Sincerely,

Shambhu Paudel, Ph.D. scholar

School of Natural Resource and the Environment

University of Arizona, Tucson, Arizona, USA

And

Institute of Forestry, Pokhara, Nepal

Email: spaudel@email.arizona.edu

Response to reviewers:

Editor Comments:

As this study combines river flow property and the ecology of the river dolphins to predict the in-stream habitat availability of river dolphins, the first reviewer finds it hard to understand its core approach and idea. Principally, we are not entirely working on modeling river hydraulics as does a hydrologist, but we quantify in-stream area availability to river dolphins as a function of river depth and flow at a particular flow level. To quantify habitat availability, we use ADP, which measures the complete cross-sectional dynamics using acoustics and provide us data on depth and velocity at cell size between 0.02-0.5 m, including cross-sectional area, width, discharge. Using hydro-physical properties of habitats with documented river dolphin use, we develop a habitat suitability curve, and then it was forwarded to estimate area-weighted suitability (AWS) measured in m2/m. AWS is the available suitable habitats at each cross-section. This details of the entire approach are described in lines 118-126 (introduction) and 169-206 (methods)

We also added a simple overview to the approach by adding lines 199-203 and a new reference in line 186.

The second reviewer, an expert in river dolphin conservation was very positive about the manuscript and considered acceptance.

The second reviewer who is river cetacean scientist did completely understand the approach that combines ecology and flow. We believe our additional details and a short overview should satisfy the breadth of readership that we suspect will find the paper useful. We appreciate the comments of Rev 1 and you to create a more accessible manuscript. Thank you!

Our paper that details some of the methods was just published and we now cite that reference here in this PLoS ONE paper and that should further help:

Ecological responses to flow variation inform river dolphin conservation | Scientific Reports (nature.com)

We had a team of geologists, hydrologists and biologist, who designed the research approach, estimated the AWS and were instrumental in the general approach detailed in the Nature Sci Reports paper and applied in our manuscript submitted manuscript to PLoS ONE. We believe that our added details and the reference to the recent publication will assist with the accessibility of this work and hope that you agree!

I personally consider that we need all the good quality information that can be made available for river dolphin conservation, so I really hope the authors work on this recommendation to improve the quality of their paper.

As we already published the first outcome of this project, this paper, with the same approach, we elaborated further details about the river dolphin’s habitat in relation to the flow. The approach adopted by this paper was the same that we used in the research paper published in Nature Scientific reports (Ecological responses to flow variation inform river dolphin conservation | Scientific Reports (nature.com)). I hope this helps with the decision and ensures that we used a technically sound approach to make this paper scientifically robust.

The aim of this paper is to estimate AWS as a function of velocity and depth at the finer spatial resolution at a particular flow level. We estimated the AWS as each cross-section in response to flow level. It is the primary or core goal of this paper to inform practice and policy. We have added more details and an overview of the technique to assist with this understanding.

I commend the researchers on their efforts to obtain a unique and important dataset in this environment. However, the study should not be considered adequate from a hydraulic perspective.

We have changed some of our wording as mentioned above and provided more details as we are not particularly dealing with hydraulic modeling. Here, we combine flow (velocity and depth at particular flow level) with reference to dolphin requirements to develop flow-ecology relationships in terms of in-stream habitat availability (AWS). This is the goal of this paper … an application of the hydrological characteristics to the ecology and conservation of river dolphins. To complete this task, we measured a continuum available hydro-physical habitat (line 147) and occupied habitats by river dolphins (line 191) to develop the suitable habitat curve. This curve is further used to estimate AWS at each cross-section. Here we define river dolphin habitat by the interaction of velocity and depth (lines 118-120), which were measured by ADP at 0.02 to 0.5m spatial resolution across the cross-section. We tweaked the details of this approach in the methods section. This approach is the standard way to estimate habitat suitability; we have published the methods in greater detail elsewhere and now reference them as noted above.

I noted a few occasions when the authors did not appear to clearly understand what they were describing, and overall I felt that the presentation quality of the hydraulic results was low.

We added further lines (199-203) and two references [10, 33] to make approach clearer to the reader.

If possible I would suggest collaborating with someone in that field as the data set looks promising and the problem clearly merits attention.

This is a project with a team member representing diverse areas, from ecologist, biologist, geologist, hydrologist to engineers. We have published the details elsewhere as noted above but we add more detail and citation to assist with the reader with the approach.

I have made many other comments in the manuscript,

We accepted all the comments made in the manuscript, which are highlighted by yellow color.

but overall my recommendation is to reject.

I think we have made the approach clearer, added information and references to improve the quality of the paper.

Reviewer #2: The manuscript is well prepared and develops the objectives proposed in the investigation in a clear and robust way.

Thank you! Yes, we appreciate that you found the details clear and the manuscript valuable.

We appreciate the suggestions and make all changes highlighted in yellow color in the manuscript and agree that the readability is improved.

Attachment

Submitted filename: Response _to reviewers.docx

Click here for additional data file.^{(21.7KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0241099.r003

Decision Letter 1

Susana Caballero

26 Apr 2021

PONE-D-20-31590R1

In-stream habitat availability for river dolphins in response to flow: use of ecological integrity to manage river flows

PLOS ONE

Dear Dr. Paudel,

both reviewers were positive regarding the contents and interest of your manuscript. However, one of the reviewers considers more work needs to be done to explain some of your methods and the statistical analyses you did. One of the reviewers noted that the authors may have had a defensive position when answering to the reviewer queries or suggestions. Remember that science is done by presenting our work to colleagues (pair review) and what this approach wants to achieve is to be able to look at our work under different eyes and being able to be accept criticism and suggestions to improve the clarity and quality of our work. I am sure you will be able to improve these aspect of your manuscript in the next version of it!!!

Please submit your revised manuscript by 1st of June 2021. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Susana Caballero, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (if provided):

[Note: HTML markup is below. Please do not edit.]

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 #1: (No Response)

Reviewer #2: All comments have been addressed

**********

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

Reviewer #1: No

Reviewer #2: Yes

**********

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

Reviewer #1: No

Reviewer #2: Yes

**********

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

Reviewer #1: Yes

Reviewer #2: Yes

**********

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

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Reviewer #1: A few comments on the revision:

1. At line 183, I’m still not sure where this definition of the Froude number comes from. You may be thinking of the Reynolds number, which is a better index of turbulence because it is the ratio of the inertial to the viscous force. Froude number is a ratio of the inertial to the gravitational force and is an index of wave behaviour. In rivers it is used to understand transitions between sub and supercritical flow. This poor definition of the Froude number was one of the main reasons I suggested working with someone with a better knowledge of open channel flow hydraulics.

2. At line 186 it is good to see that a reference is now provided to indicate the source for these Froude number thresholds. I note, however, that these numbers are from a single braided river in the Alps (Jowett, 1993). They are applied uncritically in this case to a much different river in terms of depth and velocity. I very much doubt that the morphologic description of riffles and pools from shallow braided river would apply to this much larger river where dolphins reside. The values used for the Froude number based classification system is thus still not well justified.

3. For the GAMLSS models and results presented in Table 3, the Habitat Type (HT) is based on Froude number, which is based on Velocity and Depth. What is the benefit or logic of including Velocity Depth and Habitat Type on the model? Can't you do it with Velocity and Depth alone? Based on Figure 3, is habitat type really useful? It still seems to me that you are double counting or mixing hydraulic variables. Riffles have high velocity, but low depth, which according to the other plots have opposite effects on AWS. Did you test any models without HT? In Table 3 they all have it.

4. Figure 7 is still poor quality. There no axes labels, labels on the color bars, or indications of what the contours mean and the contour labels are too small to read.

5. In the response to my comments the authors state that they are ‘not particularly dealing with hydraulic modeling’, but they are using hydraulic measurements and concepts and using those to describe the habitat of these river dolphins. In offering my opinion I am not deviating from the core aim of your paper as you state in the letter, but simply trying to ensure that sound science is being published. I am judging the work solely based on what is in the current paper and have not consulted the Nature paper, which, while a significant accomplishment, is not the subject of the current review. The manuscript in front of me has some serious flaws related to the core idea that you are describing the hydraulic habitat of these creatures and these have not been addressed by your revision.

Reviewer #2: he recommendations suggested in the first stage of revision have been incorporated into the manuscript. Besides, it is an important contribution to the knowledge of threats to river dolphins in the Asian continent.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: Federico Mosquera-Guerra PhD.

PLoS One. 2021 Jul 21;16(7):e0241099. doi: 10.1371/journal.pone.0241099.r004

Author response to Decision Letter 1

22 May 2021

Reviwer#1:

Thank you for your suggestion. We follow Jowett (1993-A method for objectively identifying pool, run, and riffle habitats from physical measurements) and System for Environmental Flow Analysis (SEFA; Jowett et al. 2019) software manual to classify the habitats into the pool, run and riffle habitats from physical measurements taking the Froude number as an index of hydraulic turbulence. The reference papers compare the hydraulic characteristics of these three habitats and derive a simple habitat classification criterion which we applied in our study. This is a simple classification rule which correctly classified 66% of the habitats (Jowett, 1993). We have added some of these statements (including reference) to the methods section (lines 184-187) and then the reviewer for requesting more clarity.

2. At line 186 it is good to see that a reference is now provided to indicate the source for these Froude number thresholds. I note, however, that these numbers are from a single braided river in the Alps (Jowett, 1993). They are applied uncritically in this case to a much different river in terms of depth and velocity. I very much doubt that the morphologic description of riffles and pools from shallow braided river would apply to this much larger river where dolphins reside. The values used for the Froude number-based classification system is thus still not well justified.

As this is the first study in the region that develops flow-ecology relationships taking behavioral ecology of a large predator, the adopted approaches can be revised or revisited in the future study as this approach correctly classified 66% of the habitats. Previous studies visually classified the habitat types; however, we consider hydraulic properties measured by ADP at a higher spatial scale to classify the habitat. At the initial phase of this project, we consulted our approach with a senior hydrologists and key stakeholders in Nepal who are responsible for aquatic species and flow management before conducting field sampling. Thus, we have adopted the generally acceptable and simple approach to standardize the fieldwork using state-of-the-art technology so that these can be applied by biologists in the field. We appreciate the reviewer’s concern and have added a statement about the need for further testing and refinement of habitat classification in the future (lines: 189-194).

First, we develop the full linear model using all the available variables to avoid bias on parameter selection. Then to get the final model with only significant terms, stepwise model selection step applied which helps to select the top model based on GAIC. This indicates parameters are included or excluded systematically based on significant contribution to the response variable (AWS).

After having these linear, interactive, and smoother terms which develop the full initial model, we again use a stepwise selection process based on GAIC. All models listed in the table are developed following the modeling procedure that considers only significant contributor and removes non-relevant elements by the stepwise process systematically.

We explicitly described all the statistical steps described above or that we followed in the lines 219-253.

4. Figure 7 is still poor quality. There no axes labels, labels on the color bars, or indications of what the contours mean and the contour labels are too small to read.

We included a high-quality image with label and color bar in the revised manuscript. We submitted journal standard quality, however, while creating a PDF for review, it loses it's quality. We uploaded high quality individual file of each maps separately in the system for the final publication.

This paper aims to quantify in-stream habitat availability using the predominantly applied Habitat Suitability Curve (HSC) approach (see application and relevance of HSC in aquatic ecology- Nestler et al. 2019). This approach is one of several approaches used in sustainable flow management while balancing societal demands and conservation. We built the HSC (based on velocity and depth) to estimate AWS (area-weighted suitability), the steps to develop HSC are explicitly described in Paudel et al. 2020 and cited in this paper as well to facilitate the learning process for the audience. Only the interactive function of velocity and depth was used to estimate AWS. We applied a widely consider approach to quantify the in-stream habitat availability in response to flow, but we did not include habitat type while estimating the AWS. As far as your concern is on the application of Froude number for habitat classification, habitat type was only included in the modeling process while identifying significant linear and interactive terms that define the AWS. Thus, we adopted an accepted approach while estimating AWS that includes only velocity and depth parameters. We believe that our modeling and quantification are explicitly defined and systematically conducted. Thus, we believe that our approach adopts simple mathematical steps that are justifiable and acceptable in the flow management process. Methodology with this clarification is now updated in lines (206-212).

Reviewer #2: The recommendations suggested in the first stage of revision have been incorporated into the manuscript. Besides, it is an important contribution to the knowledge of threats to river dolphins in the Asian continent.

Thank you!

Attachment

Submitted filename: Response to Reviwers.docx

Click here for additional data file.^{(19.3KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0241099.r005

Decision Letter 2

Susana Caballero

5 Jul 2021

In-stream habitat availability for river dolphins in response to flow: use of ecological integrity to manage river flows

PONE-D-20-31590R2

Dear Dr. Paudel,

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.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. 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.

Kind regards,

Susana Caballero, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Both reviewers suggested your manuscript to be accepted for publication. The only suggestion they made is to try to improve the quality of figure 7 (resolution) as well as the designation of the axis.

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #1: (No Response)

Reviewer #2: All comments have been addressed

**********

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

Reviewer #1: No

Reviewer #2: Yes

**********

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

Reviewer #1: Yes

Reviewer #2: Yes

**********

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

Reviewer #1: Yes

Reviewer #2: Yes

**********

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

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Reviewer #1: The authors have made some attempt to address my comments, although I would still disagree with their description of the Froude number and have not shown me a good quality version of their Figure 7, which I found difficult to read. Their responses overall are acceptable and the paper will likely be of interest to a wide audience.

Reviewer #2: The research is solid and robust, and the manuscript will surely be considered as a reference in the study of Asian river dolphins.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: Federico Mosquera Guerra

PLoS One. doi: 10.1371/journal.pone.0241099.r006

Acceptance letter

Susana Caballero

8 Jul 2021

PONE-D-20-31590R2

In-stream habitat availability for river dolphins in response to flow: use of ecological integrity to manage river flows

Dear Dr. Paudel:

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,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Susana Caballero

Academic Editor

PLOS ONE

Associated Data

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

Supplementary Materials

Attachment

Submitted filename: PONE-D-20-31590_reviewer.pdf

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

Attachment

Submitted filename: Response _to reviewers.docx

Click here for additional data file.^{(21.7KB, docx)}

Attachment

Submitted filename: Response to Reviwers.docx

Click here for additional data file.^{(19.3KB, docx)}

Data Availability Statement

All relevant data are within the manuscript.

[pone.0241099.ref001] 1.Dudgeon D. Multiple threats imperil freshwater biodiversity in the Anthropocene. Current Biology. 2019. Oct 7;29(19):R960–7. doi: 10.1016/j.cub.2019.08.002 [DOI] [PubMed] [Google Scholar]

[pone.0241099.ref002] 2.Destouni G, Jaramillo F, Prieto C. Hydroclimatic shifts driven by human water use for food and energy production. Nature Climate Change. 2013. Mar;3(3):213–7. [Google Scholar]

[pone.0241099.ref003] 3.Jaramillo F, Destouni G. Local flow regulation and irrigation raise global human water consumption and footprint. Science. 2015. Dec 4;350(6265):1248–51. doi: 10.1126/science.aad1010 [DOI] [PubMed] [Google Scholar]

[pone.0241099.ref004] 4.Destouni G, Jarsjö J. Zones of untreatable water pollution call for better appreciation of mitigation limits and opportunities. Wiley Interdisciplinary Reviews: Water. 2018. Nov;5(6):e1312. [Google Scholar]

[pone.0241099.ref005] 5.Winemiller KO, McIntyre PB, Castello L, Fluet-Chouinard E, Giarrizzo T, Nam S, et al. Balancing hydropower and biodiversity in the Amazon, Congo, and Mekong. Science. 2016. Jan 8;351(6269):128–9. doi: 10.1126/science.aac7082 [DOI] [PubMed] [Google Scholar]

[pone.0241099.ref006] 6.FAO. 2016. AQUASTAT database. http://www.fao.org/nr/water/aquastat/data/.

[pone.0241099.ref007] 7.Elmhagen B, Destouni G, Angerbjörn A, Borgström S, Boyd E, Cousins SA, et al. Interacting effects of change in climate, human population, land use, and water use on biodiversity and ecosystem services. Ecology and Society. 2015. Mar 1;20(1). [Google Scholar]

[pone.0241099.ref008] 8.Carrizo SF, Jähnig SC, Bremerich V, Freyhof J, Harrison I, He F, et al. Freshwater megafauna: Flagships for freshwater biodiversity under threat. Bioscience. 2017. Oct 1;67(10):919–27. doi: 10.1093/biosci/bix099 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0241099.ref009] 9.He F, Zarfl C, Bremerich V, David JN, Hogan Z, Kalinkat G, et al. The global decline of freshwater megafauna. Global Change Biology. 2019. Nov;25(11):3883–92. doi: 10.1111/gcb.14753 [DOI] [PubMed] [Google Scholar]

[pone.0241099.ref010] 10.Paudel S, Koprowski JL, Thakuri U, Sigdel R, Gautam RC. Ecological responses to flow variation inform river dolphin conservation. Scientific Reports. 2020. Dec 18;10(1):1–3. doi: 10.1038/s41598-019-56847-4 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0241099.ref011] 11.Paschoalini M, Almeida RM, Trujillo F, Melo-Santos G, Marmontel M, Pavanato HJ, et al. On the brink of isolation: Population estimates of the Araguaian river dolphin in a human-impacted region in Brazil. Plos one. 2020. Apr 22;15(4):e0231224. doi: 10.1371/journal.pone.0231224 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0241099.ref012] 12.Braulik GT, Noureen U, Arshad M, Reeves RR. Review of status, threats, and conservation management options for the endangered Indus River blind dolphin. Biological Conservation. 2015. Dec 1;192:30–41. [Google Scholar]

[pone.0241099.ref013] 13.Krützen M, Beasley I, Ackermann CY, Lieckfeldt D, Ludwig A, Ryan GE, et al. Demographic collapse and low genetic diversity of the Irrawaddy dolphin population inhabiting the Mekong River. Plos one. 2018. Jan 3;13(1):e0189200. doi: 10.1371/journal.pone.0189200 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0241099.ref014] 14.Kelkar N, Krishnaswamy J, Choudhary S, Sutaria D. Coexistence of fisheries with river dolphin conservation. Conservation Biology. 2010. Aug;24(4):1130–40. doi: 10.1111/j.1523-1739.2010.01467.x [DOI] [PubMed] [Google Scholar]

[pone.0241099.ref015] 15.Martin AR, da Silva VM, Salmon DL. Riverine habitat preferences of botos (Inia geoffrensis) and tucuxis (Sotalia fluviatilis) in the central Amazon. Marine Mammal Science. 2004. Apr;20(2):189–200. [Google Scholar]

[pone.0241099.ref016] 16.Turvey ST, Pitman RL, Taylor BL, Barlow J, Akamatsu T, Barrett LA, et al. First human-caused extinction of a cetacean species?. Biology letters. 2007. Oct 22;3(5):537–40. doi: 10.1098/rsbl.2007.0292 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0241099.ref017] 17.Braulik GT, Noureen U, Arshad M, Reeves RR. Review of status, threats, and conservation management options for the endangered Indus River blind dolphin. Biological Conservation. 2015. Dec 1;192:30–41. [Google Scholar]

[pone.0241099.ref018] 18.Pavanato HJ, Melo-Santos G, Lima DS, Portocarrero-Aya M, Paschoalini M, Mosquera F, et al. Risks of dam construction for South American river dolphins: a case study of the Tapajós River. Endangered species research. 2016. Sep 21;31:47–60. [Google Scholar]

[pone.0241099.ref019] 19.Smith BD, Braulik G, Strindberg S, Mansur R, Diyan MA, Ahmed B. Habitat selection of freshwater‐dependent cetaceans and the potential effects of declining freshwater flows and sea‐level rise in waterways of the Sundarbans mangrove forest, Bangladesh. Aquatic Conservation: Marine and Freshwater Ecosystems. 2009. Mar;19(2):209–25. [Google Scholar]

[pone.0241099.ref020] 20.Braulik GT, Reichert AP, Ehsan T, Khan S, Northridge SP, Alexander JS, et al. Habitat use by a freshwater dolphin in the low‐water season. Aquatic Conservation: Marine and Freshwater Ecosystems. 2012. Jun;22(4):533–46. [Google Scholar]

[pone.0241099.ref021] 21.Maddock I. The importance of physical habitat assessment for evaluating river health. Freshwater biology. 1999. Mar;41(2):373–91. [Google Scholar]

[pone.0241099.ref022] 22.Aldaya MM, Martínez-Santos P, Llamas MR. Incorporating the water footprint and virtual water into policy: Reflections from the Mancha Occidental Region, Spain. Water Resources Management. 2010. Mar 1;24(5):941–58. [Google Scholar]

[pone.0241099.ref023] 23.Rosenfeld JS. Developing flow–ecology relationships: Implications of nonlinear biological responses for water management. Freshwater Biology. 2017. Aug;62(8):1305–24. [Google Scholar]

[pone.0241099.ref024] 24.Bruckerhoff LA, Leasure DR, Magoulick DD. Flow–ecology relationships are spatially structured and differ among flow regimes. Journal of applied ecology. 2019. Feb;56(2):398–412. [Google Scholar]

[pone.0241099.ref025] 25.Choudhary S, Dey S, Dey S, Sagar V, Nair T, Kelkar N. River dolphin distribution in regulated river systems: implications for dry‐season flow regimes in the Gangetic basin. Aquatic Conservation: Marine and Freshwater Ecosystems. 2012. Jan;22(1):11–25. [Google Scholar]

[pone.0241099.ref026] 26.Peter C, Poh AN, Ngeian J, Tuen AA, Minton G. Identifying habitat characteristics and critical areas for Irrawaddy dolphin, Orcaella brevirostris: Implications for conservation. InNaturalists, explorers and field scientists in South-East Asia and Australasia 2016. (pp. 225–238). Springer, Cham. [Google Scholar]

[pone.0241099.ref027] 27.Araújo CC, da Silva VM. Spatial distribution of river dolphins, Inia geoffrensis (Iniidae), in the Araguaia River (central Brazil). Mammalia. 2014. Nov 1;78(4):481–6. [Google Scholar]

[pone.0241099.ref028] 28.Guizada L, Aliaga-Rossel E. Abundance of the Bolivian River Dolphin (Inia boliviensis) in Mamore River, Upper Madeira Basin. Aquatic Mammals. 2016. Jul 1;42(3 [Google Scholar]

[pone.0241099.ref029] 29.Chen M, Yu D, Lian Y, Liu Z. Population abundance and habitat preference of the Yangtze finless porpoise in the highest density section of the Yangtze River. Aquatic Conservation: Marine and Freshwater Ecosystems. 2020. Jun;30(6):1088–97. [Google Scholar]

[pone.0241099.ref030] 30.Thomas JA, Bovee KD. Application and testing of a procedure to evaluate transferability of habitat suitability criteria. Regulated Rivers: Research & Management. 1993. Aug;8(3):285–94. [Google Scholar]

[pone.0241099.ref031] 31.Rani Jamara Kulariya Irrigation Project, 2017. Environmental Assessment. Volume 2. Nepal: Department of Irrigation.

[pone.0241099.ref032] 32.Paudel S, Pal P, Cove MV, Jnawali SR, Abel G, Koprowski JL, et al. The Endangered Ganges River dolphin Platanista gangetica gangetica in Nepal: abundance, habitat and conservation threats. Endangered Species Research. 2015. Nov 25;29(1):59–68. [Google Scholar]

[pone.0241099.ref033] 33.Jowett IG. A method for objectively identifying pool, run, and riffle habitats from physical measurements. New Zealand journal of marine and freshwater research,1993; 27(2), pp.241–248. [Google Scholar]

[pone.0241099.ref034] 34.Nestler JM, Milhous RT, Payne TR, Smith DL. History and review of the habitat suitability criteria curve in applied aquatic ecology. River Research and Applications. 2019. Oct; 35(8):1155–80. [Google Scholar]

[pone.0241099.ref035] 35.Stasinopoulos MD, Rigby RA, Heller GZ, Voudouris V, De Bastiani F. Flexible regression and smoothing: using GAMLSS in R. CRC Press; 2017. Apr 21. [Google Scholar]

[pone.0241099.ref036] 36.Buuren SV, Fredriks M. Worm plot: a simple diagnostic device for modelling growth reference curves. Statistics in medicine. 2001. Apr 30;20(8):1259–77. doi: 10.1002/sim.746 [DOI] [PubMed] [Google Scholar]

[pone.0241099.ref037] 37.Turvey ST, Risley CL, Barrett LA, Yujiang H, Ding W. River dolphins can act as population trend indicators in degraded freshwater systems. PLoS One. 2012. May 29;7(5):e37902. doi: 10.1371/journal.pone.0037902 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0241099.ref038] 38.Gomez‐Salazar C, Trujillo F, Portocarrero‐Aya M, Whitehead H. Population, density estimates, and conservation of river dolphins (Inia and Sotalia) in the Amazon and Orinoco river basins. Marine Mammal Science. 2012. Jan;28(1):124–53. [Google Scholar]

[pone.0241099.ref039] 39.Smith BD, Haque AA, Hossain MS, Khan A. River dolphins in Bangladesh: conservation and the effects of water development. Environmental management. 1998. May 1;22(3):323–35. doi: 10.1007/s002679900108 [DOI] [PubMed] [Google Scholar]

[pone.0241099.ref040] 40.Biswas SP, Boruah S. Ecology of the river dolphin (Platanista gangetica) in the upper Brahmaputra. Hydrobiologia. 2000. Jul 1;430(1–3):97–111. [Google Scholar]

[pone.0241099.ref041] 41.Skrovan RC, Williams TM, Berry PS, Moore PW, Davis RW. The diving physiology of bottlenose dolphins (Tursiops truncatus). II. Biomechanics and changes in buoyancy at depth. Journal of Experimental Biology. 1999. Oct 15;202(20):2749–61. [DOI] [PubMed] [Google Scholar]

[pone.0241099.ref042] 42.Williams TM, Haun JE, Friedl WA. The diving physiology of bottlenose dolphins (Tursiops truncatus). I. Balancing the demands of exercise for energy conservation at depth. Journal of Experimental Biology. 1999. Oct 15;202(20):2739–48. [DOI] [PubMed] [Google Scholar]

[pone.0241099.ref043] 43.Choudhury NB, Mazumder MK, Chakravarty H, Choudhury AS, Boro F, Choudhury IB. The endangered Ganges river dolphin heads towards local extinction in the Barak river system of Assam, India: A plea for conservation. Mammalian Biology. 2019. Jan 1;95(1):102–11. [Google Scholar]

[pone.0241099.ref044] 44.Trujillo-González F, Mosquera-Guerra F, Franco N. River dolphins: Species that indicate the state of health of the aquatic ecosystems of the Amazon and Orinoco regions. Revista de la Academia Colombiana de Ciencias Exactas, Físicas y Naturales. 2019. Jun;43(167):199–211. [Google Scholar]

[pone.0241099.ref045] 45.Dey M., Krishnaswamy J., Morisaka T., & Kelkar N. (2019). Interacting effects of vessel noise and shallow river depth elevate metabolic stress in Ganges river dolphins. Scientific reports, 9(1), 1–13. doi: 10.1038/s41598-019-51664-1 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0241099.ref046] 46.Bunn SE, Arthington AH. Basic principles and ecological consequences of altered flow regimes for aquatic biodiversity. Environmental management. 2002. Oct 1;30(4):492–507. doi: 10.1007/s00267-002-2737-0 [DOI] [PubMed] [Google Scholar]

[pone.0241099.ref047] 47.Mintzer VJ, Lorenzen K, Frazer TK, da Silva VM, Martin AR. Seasonal movements of river dolphins (Inia geoffrensis) in a protected Amazonian floodplain. Marine Mammal Science. 2016. Apr;32(2):664–81. [Google Scholar]

[pone.0241099.ref048] 48.Martin AR, Da Silva VM. Reproductive parameters of the Amazon river dolphin or boto, Inia geoffrensis (Cetacea: Iniidae); an evolutionary outlier bucks no trends. Biological Journal of the Linnean Society. 2018. Mar 2;123(3):666–76. [Google Scholar]

[pone.0241099.ref049] 49.Jowett IG, Richardson J, McDowall RM. Relative effects of in‐stream habitat and land use on fish distribution and abundance in tributaries of the Grey River, New Zealand. New Zealand journal of marine and freshwater research. 1996. Dec 1;30(4):463–75. [Google Scholar]

[pone.0241099.ref050] 50.Smith BD. 1990 Status and conservation of the Ganges River dolphin Platanista gangetica in the Karnali River, Nepal. Biological Conservation. 1993. Jan 1;66(3):159–69. [Google Scholar]

[pone.0241099.ref051] 51.Schwartz MW. Modelling effects of habitat fragmentation on the ability of trees to respond to climatic warming. Biodiversity & Conservation. 1993. Feb 1;2(1):51–61. [Google Scholar]

[pone.0241099.ref052] 52.Battin J. When good animals love bad habitats: ecological traps and the conservation of animal populations. Conservation Biology. 2004. Dec;18(6):1482–91. [Google Scholar]

[pone.0241099.ref053] 53.Walker KF, Thoms MC. Environmental effects of flow regulation on the lower River Murray, Australia. Regulated Rivers: Research & Management. 1993. May;8(1‐2):103–19. [Google Scholar]

[pone.0241099.ref054] 54.Sowa SP, Annis G, Morey ME, Diamond DD. A gap analysis and comprehensive conservation strategy for riverine ecosystems of Missouri. Ecological monographs. 2007. Aug;77(3):301–34. [Google Scholar]

PERMALINK

In-stream habitat availability for river dolphins in response to flow: Use of ecological integrity to manage river flows

Shambhu Paudel

John L Koprowski

Usha Thakuri

Ajay Karki

Roles

Abstract

Introduction

Materials and methods

Study area

Fig 1. A study map showing the location of development structures and segments took for hydro-physical measurements.

Available habitat measurements

GRD occupied habitat measurements

Area weighted suitability model

Results

Available hydro-physical parameters

Table 1. Hydro-physical parameters across seasons.

Table 2. Hydro-physical parameters across habitat type.

GAMLSS model of area-weighted suitability

Fig 2. A worm plot depicts that points of the worm plot are inside the 95% pointwise confidence intervals (curves) and close to the middle horizontal line, indicating adequacy of the fitted model.

Fig 3. A plot of the final fitted model shows that the predictor (AWS) declines linearly as flow and velocity increase, and AWS exhibited nonlinear relationships with depth and cross-sectional area.

Fig 4. Centile curves for AWS (m2/m) against the flow (m3/s) for different percentiles (5–95%) shows that maximum AWS is obtained with the flow around 450 m3/s.

Fig 5. A plot of centile curves for AWS (m2/m) fitted against depth and velocity separately indicates AWS is maximized when depth is between 2 and 3.5 m and velocity 0.3–0.8 m/s.

Interactive effects of velocity and depth on area-weighted suitability

Fig 6. A surface plot of the AWS (m2/m) showing the interactive effects of (a) velocity and depth, (b) cross-sectional area and velocity, (c) cross-sectional area, and depth.

Discussion

Fig 7.

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Susana Caballero

Roles

Author response to Decision Letter 0

Decision Letter 1

Susana Caballero

Roles

Author response to Decision Letter 1

Decision Letter 2

Susana Caballero

Roles

Acceptance letter

Susana Caballero

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases

Fig 4. Centile curves for AWS (m²/m) against the flow (m³/s) for different percentiles (5–95%) shows that maximum AWS is obtained with the flow around 450 m³/s.

Fig 5. A plot of centile curves for AWS (m²/m) fitted against depth and velocity separately indicates AWS is maximized when depth is between 2 and 3.5 m and velocity 0.3–0.8 m/s.

Fig 6. A surface plot of the AWS (m²/m) showing the interactive effects of (a) velocity and depth, (b) cross-sectional area and velocity, (c) cross-sectional area, and depth.