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. 2020 Aug 21;15(8):e0227163. doi: 10.1371/journal.pone.0227163

Global extent and drivers of mammal population declines in protected areas under illegal hunting pressure

Alfan A Rija 1,*, Rob Critchlow 2, Chris D Thomas 2, Colin M Beale 2
Editor: Stefano Grignolio3
PMCID: PMC7446782  PMID: 32822346

Abstract

Illegal hunting is a persistent problem in many protected areas, but an overview of the extent of this problem and its impact on wildlife is lacking. We reviewed 40 years (1980–2020) of global research to examine the spatial distribution of research and socio-ecological factors influencing population decline within protected areas under illegal hunting pressure. From 81 papers reporting 988 species/site combinations, 294 mammal species were reported to have been illegally hunted from 155 protected areas across 48 countries. Research in illegal hunting has increased substantially during the review period and showed biases towards strictly protected areas and the African continent. Population declines were most frequent in countries with a low human development index, particularly in strict protected areas and for species with a body mass over 100 kg. Our results provide evidence that illegal hunting is most likely to cause declines of large-bodied species in protected areas of resource-poor countries regardless of protected area conservation status. Given the growing pressures of illegal hunting, increased investments in people’s development and additional conservation efforts such as improving anti-poaching strategies and conservation resources in terms of improving funding and personnel directed at this problem are a growing priority.

Introduction

Protected areas (PAs) are the cornerstone of biodiversity conservation and have increased in number globally (covering at least 15% of global terrestrial land and 7% of ocean [1, 2]; to reach estimated conservation targets of protecting at least 17% of the global land area by 2020 [3, 4]. The effectiveness of PAs is challenged by increasing pressures from management efficiency such as governance and resource deficiency [57], and anthropogenic pressures such as habitat loss and illegal hunting [810]. Consequently, many PAs continue to experience wildlife declines [2, 9], suggesting that enlarging the PA network alone does not necessarily lead to conservation success when other efforts such as improved law enforcement, funding and regulation of land use change pressure outside are not considered [2]. Despite these challenges to protecting biodiversity, broad scale patterns on illegal hunting in PAs and the consequences for species conservation remain poorly assessed, yet could help improve the effectiveness of PAs and improve biodiversity conservation [8].

Anthropogenic threats to wildlife within and outside PAs have been studied extensively including logging [11, 12], hunting [9, 13] and encroachment through cropland conversion and livestock grazing [8, 11]. These threats can have serious conservation and ecological implications. For example, recent assessments of wildlife abundance across tropical forests reported at least 40% decline in mammal distribution range due to hunting [14]. Mammal population declines by 80% and 30% have been reported across tropical forests caused by hunting and land use change respectively [9, 15], consequently leading to potential loss of species interaction networks [13, 16]. Further, bushmeat hunting (i.e. hunting for wild meat) is a growing conservation problem across the savanna biomes [17], threatening several hundred thousand vertebrate species across the globe [13, 18]. Very few of those studies that investigate hunting impact account for protection status of an area and separate legal and illegal hunting, which may occur together [8, 9]. This potentially confounds efforts needed to target illegal hunting pressures particularly in PAs managed through law enforcement. At the individual PA level, the drivers of illegal hunting are often known. This includes subsistence hunting to ensure food security and offtake for commercial gains [17, 19]. Species traits such as taste [13, 20] and body size also influence hunting preference [9, 13, 20], but have rarely been assessed on a large scale [15]. Increasing access to PAs due to anthropogenic encroachment and land use change has also resulted in wildlife population declines, threatening PA effectiveness [2, 9]. Thus, research targeting the effectiveness of species conservation in relation to illegal hunting pressure is needed as PAs remain the major stronghold of biodiversity, and as important key refuge areas [8, 21].

Mammals contribute the highest proportion to total biomass across forest and savanna landscapes making them highly sought after by illegal hunters [19, 22, 23]. Loss of mammals due to illegal hunting pressure has been related to substantial loss of important functional characteristics such as seed dispersal and regeneration and ecological interactions, thus endangering many ecological services that they support [2, 24, 25] and threatening humanity [26]. Therefore, due to their functional importance and growing threats, mammals are an excellent taxon to document hunting pressures and identify improved conservation strategies in PAs. Fortunately, the distribution changes of mammals brought about by hunting are broadly known [14, 27]–but current research rarely focuses on PAs [8].

Few studies have quantified the relative contribution of individual threats to the overall pattern of population change and decline in PAs [10]. Such an assessment is required to identify strategies to improve PA effectiveness, such as where to target additional resources and which actions are most effective at enforcing existing regulations [28]. Here, we investigated spatial patterns and impact of illegal hunting on wild mammal populations within PAs using a comprehensive database collated from 40 years of published literature. We built models that integrate both the outcome of illegal hunting pressure on species and the socio-ecological parameters to derive patterns of impacts on broader regional and global scales. Specifically, we aimed to:

  1. Assess the extent and scale of research on illegal hunting of mammal populations in PAs.

  2. Examine what factors are associated with mammal declines and their variations across species and PAs and between geographic regions.

  3. Identify current limitations in existing literature and propose recommendations for improving PAs effectiveness in relation to illegal hunting of mammals.

Material and methods

Data collection

Literature searches were carried out in Web of Science, Google Scholar and Scopus between March 2014 and 2015 and in March 2020. Restricting the search period to 1980–2020, the search terms included: ‘illegal activity’ OR ‘illegal activities’ OR ‘illegal hunting’ OR poach* AND ‘protected area’ OR reserve OR ‘biodiversity outcome’. Full details of search terms can be found in the PART II in S1 File. Results were screened based on criteria (i-iv below) to ensure each paper were related to both PAs and illegal mammal hunting:

  1. Whether the research was done in a PA and addressed issues of illegal hunting of mammals.

  2. If the research showed impact on species population within the PA

  3. Only used primary data papers not meta-analyses or reviews.

  4. For results that returned more than one study covering the same PA and year of data collection these were examined for relevance and only one that satisfied all criteria (i-iii) was included in the analysis.

From each paper, we extracted information on PA location, threat types, study species, reason for illegal hunting, purpose of research and data collection method (Table 1 and S1 Raw data). We recorded population trend (i.e. decline, no decline or unstated) for each PA/species combination and the reasons mentioned for such outcomes if not directly related to illegal hunting. Each species / site combination and associated variables became one row in the dataset, including the impact scores (1 = species decline or 0 = no decline or NA = no reported impact for that species) and any covariate information (see S1 Raw data for detailed database). The method arriving at the reported population trend status was recorded but not analyzed because most studies did not show the data used to arrive at a species outcome (e.g. decline), thus was difficult to tease apart whether the species decline was causal or correlative, a common problem in many meta-analysis studies [29].

Table 1. Description of the terms under methods extracted from the reviewed papers reported in Fig 2.

Method Description
Animal counts Population size and trend of animals in a protected area under illegal hunting pressure documented from animal count methods such as aerial sample counts, systematic strip transect survey and Distance sampling.
Interviews/counts Illegal hunting and impact on mammal population trends from interviews of field rangers or local communities and direct animal counts in the field.
Interviews Assessment of illegal hunting and trend of illegally hunted populations from local communities directly involved in illegal hunting or consumption of bushmeat. E.g. use of questionnaires and interviews surveys.
Market Surveys Records of live animals or carcasses from markets, or surveys of markets to record these data
Other surveys Surveys of illegally killed mammal carcasses in the field, surveys of snares used in illegal hunting, animal bone surveys, poacher arrest records, combined carcass survey and local expert opinion of the population trends of illegal hunted animals.
Patrol data Information about illegal hunting of wildlife and impact on population trends inferred from law enforcement data conducted by rangers in a protected area.

Species body size is likely to influence mammal hunting risk [13]. We extracted body mass from the mammal database PanTHERIA (www.pantheria.org) and EltonTraits [30]. The body mass for two species (Eulemur rufifrons and Gazella dorcas massaesyla) were extracted from published literature (PART I in S1 File). The WCMC IUCN Protected Planet database was used to identify the geographic location (latitude/longitude) of a PA. To assess whether legal status influences the outcome of species populations, we extracted the IUCN category of each PA [31].To explore the effect of legal status on species decline we grouped the PAs into two levels of protection: strict PAs (IUCN category I & II) and less strict PAs (categories III-IV). PAs in IUCN categories V-VI were excluded from analysis because they are not specifically designated for biodiversity conservation [32].

To assess whether population change reported was related to broad scale economic or social change, we used country-level human development index (HDI) and agricultural land use change (ALC) index extracted from the UNDP and World Bank databases [33, 34]. Agricultural land use change index is a measure of the amount of land converted to agriculture and other human activities such as settlement. The ALC index is associated with habitat loss within PAs due to encroaching on PAs [2, 11, 35], and is also related to illegal hunting because farmers encroaching on PAs often engage in illegal hunting of animals [36]. We calculated the ALC over a decade period encompassing the times when research for the reviewed papers were conducted as most papers did not report the exact dates of data collection. We used HDI as a measure of socio-economic change and governmental effectiveness because HDI is a direct indicator of development [37].

Data analysis

We used each unique combination of species within an individual PA (i.e. species × PA) reported in a paper as a study and as an individual data point, with therefore potentially several studies per paper (see data extraction in methods and S1 Raw data). Using PA location and publication year, we assessed spatial and temporal patterns of illegal hunting in PAs. Prior to conducting formal analyses, species body mass (BM) was logged and scaled and ALC scaled. HDI was used than other variables such as country corruption level and, government effectiveness because HDI has mostly been used in similar assessments and is a direct measure of poverty [38, 39]. To examine the effect of species traits and socio-economic variables on illegal mammal hunting in PAs, we used generalized linear mixed models (GLMMs) with a binomial error term and logit link function implemented in the R-package ‘lme4’ [40] in the statistical software R (version 3.6.3). For all models, we excluded records where the population outcome was unknown, and the response variable was whether a species had declined in that PA (1) or not (0). We built an initial global model incorporating six fixed factors: HDI, ALC, log species body mass, illegal hunting type (commercial, subsistence, or combined), PA protection status (i.e. IUCN categories classified as strict and less strict) and continent (Africa/Asia/Central and South America). Records from Europe were excluded from all analyses due to a low number of records (n = 3). Because different species could relate to the same PA and country as studies from other papers at different times, we accounted for this by including country, paper and PA as random effects in all models. We used a backwards stepwise removal of non-significant terms (with Chi-test) to evaluate the relative effect of each factor on the population decline. We obtained model confidence intervals around variables showing statistical significance in the minimum adequate model using the Wald-method [40]. Models of all analysis subsets were assessed using Akaike information criterion (AIC) to select the most parsimonious model after the stepwise removal of terms. We calculated a measure of variance explained by the models using the squared correlation between the response variable and the predicted values. These pseudo R2 values should be interpreted with caution as it only shows the variance explained by the fixed effects in the final model. Conditional R2 values were calculated using the MuMIn R package [41].

The majority of illegal mammal hunting records were from Africa and Asia. We therefore built two additional models using the same structure as the global model, but restricted data to Africa and Asia respectively. Finally, because the savanna elephant (Loxodonta africana), had a large percentage of records (19%) in the Africa dataset, reflecting the increasing concerns for illegal hunting of elephant and illegal ivory trade [42], we built two further models for Africa using the same random effects structure as the global model: one excluding savanna elephants (where the fixed effects were HDI, ALC, log body mass and PA protection status) and another only including savanna elephants (where the fixed effects were HDI, ALC and PA protection status.

Results

Extent and scale of research on illegal hunting of mammals in PAs

Our searches found 2245 papers in total, 81 of which qualified our selection criteria for inclusion in the review (PART III in S1 File). The reviewed papers were from 48 countries and four continents, Africa, South America, Asia and Europe and covered 155 PAs (Fig 1). Further, the reviewed papers reported 294 mammal species to have been illegally extracted from the PAs across the four continents (PART IV in S1 File).

Fig 1. Spatial distribution of research on illegal hunting of mammals in 155 PAs from 48 countries over four decades as collated in the literature.

Fig 1

Black dots correspond to the centroid of a PA where research for the reviewed papers was conducted. [The map used in this figure was sourced from Natural Earth, which is an open access map source].

There was an increasing trend in research on illegal hunting in PAs with the number of publications increasing two-fold each decade since 1980. Types of study methods have also increased, particularly studies that have included use of ranger patrol data and interview techniques (Fig 2).

Fig 2. Number of studies per data collection method over 10-year periods.

Fig 2

Numbers at top of bars indicate the cumulative number of publications. The majority (81%) of PAs studied were in the strictest IUCN categories (I-II).

Most papers focused on single PA (i.e. local scale, n = 44), compared to PAs existing as one contiguous ecosystem (n = 24) or landscape (n = 19). All protected area types were investigated but the IUCN category II level of protection was researched the most (55.2%, n = 90). The research had varying purposes: investigating impacts on species (n = 64); conservation rationale (e.g. providing new methods for investigating illegal activities; n = 17) and management of illegal activities (n = 4). The publication trend has increased substantially during the last 40 years with a greater number of published papers since 2005; most of this increase was in Africa.

Socio-economic and species traits influencing population decline in PAs

We found differing impacts of socio-economic variables and species traits on the population trends of mammals in PAs as reported in final models that only included significant terms. In the global model (n = 523), species body mass and PA strictness had a significant effect on the probability of species decline in PA. The probability of a population to decline in a PA increased with body mass and populations in stricter PAs (IUCN categories I-II) had a lower probability of decline compared to less strict PAs (IUCN categories III-IV) (Fig 3 and Table 2; model1). When limiting analysis to Africa (n = 374), populations were more likely to decline in countries with a lower HDI and for species with greater body mass (Fig 4 and Table 2; model 2). Accounting for the influence of studies on illegal elephant hunting, results limited to Africa and excluding elephants (n = 302) showed that mammals with larger body mass were at greater risk of population decline in PAs (Table 2; model 3). Restricting analysis to African elephants (n = 72), showed that probability of population decline decreased with an increase in HDI (Table 2; model 4).

Fig 3. Effect of species body mass and PA strictness on the probability of decline of mammal species from global records.

Fig 3

Shaded area shows 95% confidence intervals. Circles represent raw data points.

Table 2. Summary of GLMMs fixed effects of socio-economic factors and species traits on the probability of mammal decline in PAs.
Models 1 2 3 4 5
Global Africa only Africa- ex.elephant Africa- elephant only Asia only
HDI -8.97* -15.80**
(-16.59, -1.35) (-26.33, -5.28)
Body mass 0.21** 0.34*** 0.37***
(0.07, 0.34) (0.16, 0.53) (0.17, 0.58)
PA strictness -1.11* 1.77**
(-1.95, -0.27) (0.66, 2.88)
Intercept 1.00 3.53 -0.08 8.28*** -0.35
(-0.22, 2.21) (-0.11, 7.17) (-1.32, 1.16) (3.36, 13.14) (-1.09, 0.39)
Observations 523 374 302 72 65
Pseudo R2 0.37 0.47 0.43 0.68 0.16
Conditional R2 0.64 0.77 0.61 0.83 0.19

Significance *p<0.05;

**p<0.01;

***p<0.001.

Values in brackets represent 95% confidence intervals.

Fig 4. The probability of decline of mammals in Africa’s PAs threatened by illegal hunting pressure showing population decline was strong in PAs located in countries with low human development index and in species with larger body mass.

Fig 4

Results focusing on illegal mammals hunting in Asia (n = 65) showed that mammal populations in strictest PAs designated to protect biodiversity had a significantly greater probability of decline compared to mammal populations in less strict PAs (Fig 5 and Table 2; model 5).

Fig 5. Probability of population decline for Asia’s only PAs indicating strong influence of PA types.

Fig 5

Higher decline of mammals was more likely in stricter than less-strict PAs.

Discussion

We analyzed data published since 1980 to understand impacts of illegal hunting on species population decline in PAs. There was strong geographic bias in research on illegal hunting within PAs dominated by records in Africa and Asia. Globally, we found that illegally hunted mammals in strict PAs (IUCN categories I-II) had a lower probability of population decline compared to less strict PAs (IUCN categories III-IV). In contrast, we found illegally hunted Asian mammals in strict PAs had a greater probability of population decline than less strict PAs. Human development index had a strong influence on likelihood of mammal declines in Africa, while larger bodied mammals were more likely to show population decline globally and in Africa.

The identification of correlations between human development indices and illegal hunting in this study supports a widely held view, e.g. [4345] but one that is often based on limited data [46]: that biodiversity decline is higher in relatively poor regions. Low HDI scores could impact illegal hunting in two ways: firstly, poor people may tend to exploit species illegally from PAs because they have limited alternatives [47]. Secondly, poor countries have fewer resources to invest in PA conservation, therefore underfunding may result in increased illegal hunting, as well as other illegal activities such as agricultural encroachment in PAs due to insufficient law enforcement [48]. Hilborn, and others [49] demonstrated that increased funding budgets for anti-poaching activities in the Serengeti National Park greatly reduced illegal hunting pressures and led to the recovery of the buffalo population. However, increasing conservation funding may not necessarily result in improved conservation particularly when social and political constraints exist. For example, social and political unrest may increase rates of illegal hunting and encroachment in PAs, reduce wildlife populations and thwart conservation efforts altogether [50, 51]. Our results provide evidence that poverty, in as much as it is measured by the HDI, may have significant negative impacts on species due to accelerated illegal hunting, whether that be because of increased external pressures on PAs or decreased policing and protection within strict PAs.

Our model that included only African elephants also highlights the importance of low HDI in relation to illegal ivory trade. Poor people in countries with low HDI may directly engage in the ivory trade chain mainly as illegal hunters, supplying ivory to the demand illegal markets [52]. Such a trade chain may be maintained by ivory traders or consumers through providing means and or financing illegal hunters to target the protected areas [53, 54]. Additionally, people faced with poverty in low HDI countries may be forced to alternatives such as illegal hunting and habitat destructive activities [55]. Although we did not find an association of habitat loss and mammal declines, destructive activities such as charcoal burning and logging for timber and fuelwood is common in poor countries with low HDI [56, 57],thereby reducing habitat suitability for elephants and other mammals, leading to population declines [39, 58]. Our study highlights the need to consider human development issues more seriously to ensure effective conservation of biodiversity within existing PAs.

Large bodied species are likely highly susceptible to decline because they have slow growth rates and so overharvesting is likely to cause population decline [15, 59]. This is because low population growth rates in combination with illegal hunting are known to cause significant reduction in population persistence [60, 61]. An alternative explanation to the large mammal decline observed in our data could be that large mammals, due to their relatively bulk meat content compared to smaller mammals they are mostly being targeted by illegal hunters for bushmeat sale. For example, illegal hunters in the Serengeti prefer to hunt larger animals for their potential higher income returns [20] and such hunting pressure caused the buffalo population to collapse in the 1980s [49]. By contrast, smaller mammals (with higher reproductive and growth rates) showed fewer declines and appeared to sustain harvest, though relatively few small species are the specific targets of illegal hunting in PAs due to their relatively low income returns from bushmeat sale [20]. The pattern of species declines across the network of PAs is worrying and suggests that PA policing (including access to appropriate conservation information) and resources need to be improved. PA-specific information is important for understanding how illegal hunting varies spatially and across time and there is a need to be able to predict future trends and thereby possible future management strategies [62]. Although at a global scale, mammals were less likely to decline by hunting in strict PAs, the opposite was true for Asian PAs. This could be attributable to three reasons; first, it could be that due to high illegal trade of wildlife body parts for traditional medicines in most parts of Asia [63], illegal hunters are forced to enter into protected areas where most sought after species such as snow leopard, tiger, pangolin, orangutans and sub bears still remain in order to satisfy demand for the traditional Asian medicine [6365]. Second, wild mammals targeted for body parts may have been hunted to completion in wider unconserved landscapes across Asia where human-induced land pressures have increased [57, 66]. Thus, illegal hunters may resort to hunting in protected areas as they remain the only sources of these animals. Third, habitat loss and illegal hunting could be occurring together inside these PAs, hence hastening extinction risks for these animals [67, 68]. These results are consistent with previous studies that have reported biodiversity decline and loss within PAs in these regions e.g. Geldmann and others [10], Harrison [69], Laurance and others [70] and Gallego-Zamorano and others [14]. Our findings suggest that the effectiveness of Asian PAs requires urgent attention to improve biodiversity conservation across in continental Asia.

The geographical bias in the spatial distribution of research observed in these data is likely a consequence of interests among the researchers rather than being driven solely by the levels of illegal hunting in particular PAs or countries. However, the temporal and spatial patterns of research observed in this study provide insight into the extent of the problem of illegal hunting in PAs and therefore suggest that PAs are currently in need of new strategies to minimize impacts of illegal hunting pressure and to improve their conservation effectiveness [71]. To date, research effort has concentrated on quantifying the extent and impact of illegal hunting on focal species; in other words, documenting the problem. Far less information is available on which conservation management strategies (including human development and preventing illegal international trade, as well as within-PA activities) are most effective at reducing illegal hunting pressures. New research should focus on developing and testing new methods for reducing levels and impacts of illegal hunting on wild mammal species in PAs.

Conclusion

Tackling illegal hunting within PAs remains a high conservation priority. Our results suggested that a combination of strategies may be required to reduce the extent of illegal hunting activities. We found that illegal hunting in poor countries often leads to population declines within PAs, suggesting that poverty alleviation may be an appropriate conservation strategy to reduce illegal hunting pressures [44]. The implication of this for local and national policies is that more effort needs to be invested to improve the social and economic status of the human populations. This needs to work in tandem with increasing the effectiveness of traditional conservation activities to prevent illegal hunting; which may itself reduce the inclination of people to attempt future illegal hunting activities. Curbing external pressures to the PAs also needs improved efforts to prevent encroachment and other illegal activities such as crop farming within and squeezing of the PA borders. This will be urgent especially for Asia where stricter PAs are at greatest risk of losing their mammal populations.

Supporting information

S1 File

(DOCX)

S1 Raw data

(CSV)

Acknowledgments

We are grateful to the anonymous reviewers for the comments on earlier drafts of this manuscript.

Data Availability

Data are available as Supporting Information files.

Funding Statement

AAR was a commonwealth scholar funded by the U.K. government. The sponsor-Commonwealth Scholarship Commission had no role in the design, data collection and analysis, decision to publish or preparation of the manuscript.

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Decision Letter 0

Stefano Grignolio

7 Feb 2020

PONE-D-19-34271

Spatial distribution and research trend of illegal activities and the factors associated with wild mammal population declines in protected areas

PLOS ONE

Dear DR Rija,

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.

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Stefano Grignolio, Ph.D

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PLOS ONE

Additional Editor Comments (if provided):

Both the reviewers have appreciated your idea and found it intriguing and worth publishing the potential results of this research. There are several aspects, however, that must be carefully addressed before I can consider your paper for publication.

In general, the current draft of the manuscript is confusing, and it is not presented in an attractive way so. The manuscript has to be fully reviewed by a native English speaker. The vocabulary needs a revision (see reviewer #2) to be consistent with the literature and through the text. Both reviewers point out the need to complete the review of literature, including the scientific papers published in the last years (from 2016 to date).

I agree with the concerns of the reviewer #2 on the statistical analysis. Please, pay attention to provide a full reply to the comments about this issue. Moreover, I did not understand your description of the results about figures 6 and 7: I think that these trends are not significant, because the CIs are very large and they include the variations described by the regression lines.

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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: Yes

Reviewer #2: Partly

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

Reviewer #1: Yes

Reviewer #2: Yes

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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: Yes

Reviewer #2: No

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

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Reviewer #1: No

Reviewer #2: No

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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: Abstract

Line 34 - It should be 1980-2014?

Introduction

Line 75 - change "hunting" to "hunting/poaching"

Line 76 - Insert "threat" in the "each threat can reduce..."

Line 95 - conjugate verbs in the past tense. E.g. change "review" to "reviewed".

Line 96 - 1980-2014?

Line 96 - Why only until 2014? A literature review paper should be updated. It has been 6 years and certainly many studies have been published across the globe and should be included in the analysis before the MS is considered for publication.

Line 98 - change "evaluate" to "evaluated".

Line 99 - We assessed

Line 106 - "Material and methods"

Line 107 - Data collection?

Overall, I recommend that MS be reviewed by an English native prior to publication.

Line 109 - What is the reason for being from 1950? Authors must define why this temporal cut. Also, in the abstract and introduction is written from 1980-2014?

Lines 112-113 - Again, a review study of the scientific literature must be current. Therefore, it is important that the authors include data by 2019 at least.

Lines 147-150 - The MS title is said to be a study of mammalian populations. It may be better to modify for vertebrates since the authors have used other taxonomic groups.

Lines 165-167 - Again, if other taxonomic groups were analyzed, it is important to modify the title of the study.

Line 173 - "referred"

Lines 227-228 - Importantly, the period included in the search was 1950-2014 and not 1980-2014. The fact that no studies were found until 1979 is a result.

Lines 288-289 - ???

Line 293 - ???

Line 333 - ???

Line 339 - ???

Line 360- ???

Line 364 - ???

Line 430 - ???

The MS presents important information to understand how impacts on protected areas are distributed across the globe. And no doubt it is of great relevance to conservation. However, it is necessary to update the data before publication! A literature review study should be as current as possible at the time of publication. That is, authors must at least include data from papers by 2019.

Reviewer #2: The researchers of this paper made a review of the illegal activities affecting populations of different species inside protected areas (PAs). This is a very relevant topic because it is increasingly shown that protected areas are not enough to stop the biodiversity crisis we observe worldwide. Especially, in the last years, it has been shown that overexploitation and land-use change are the main drivers of biodiversity loss. However, the paper does not include any reference to recent studies (the most recent reference is from 2016) and therefore I think they missed some relevant and new insights on the topic. I believe that the manuscript and their database has potential for publication, yet, the manuscript was confusing in many parts, difficult to follow, and not presented in an attractive way so, in my opinion, it requires a profound revision from the authors to clarify several aspects and improve the scientific basis of it.

In general, I think that more attention needs to be paid to the vocabulary and the overall aim of the paper. In the introduction (and title) they talk about illegal activities, however, in the methods they explain that they only included illegal extraction and no other illegal activity as such for the analysis (criteria ii). I would frame the paper differently because otherwise, the reader expects a different outcome from it. Moreover, the methods were really short and some decisions that they made were difficult to understand, e.g., why put all non-mammals together? The dataset although relatively large is too patchily distributed and it should be refined (filtered) before being analysed. I suggest to restrict the analysis to Africa as most of the data (~80%) is from there. In contrast to the methods, the results were quite extensive with some non-informative figures that could be merged or eliminated, tables that could be clearer, and paragraphs that also need clarification (see comments). Overall, the discussion was easier to follow than other parts of the paper, however, as I had difficulties following the general setup and I think that some of the results cannot be fully trusted due to low data points, most of my specific comments regard the methods.

Title

The main title is misleading as it talks about illegal activities, while the paper is about poaching only. Therefore, the short title is much better as it focusses on the poaching impact. Please, consider changing the title

Introduction

Lines 66-71: Please revise recent literature on large-scale patterns on the efficiency of PAs (e.g. Geldmann et al. 2015, 2019) and wilderness areas (Di Marco et al. 2019) to protect biodiversity. Also check the effect of hunting and land use on biodiversity worldwide (Brodie et al. 2015; Ripple et al. 2016; Benítez-López et al. 2017, 2019; Gallego‐Zamorano et al. 2020) because in your citations, you only focus on local assessments but there has been an effort on the last years to assess overall impacts of these pressures. This also applies to other parts of the text e.g. Lines 91-93 and discussion.

Line 96: Both here and in the abstract the years (I supposed) are wrong, please correct.

Methods

Lines 115: Until now, you talked only about illegal activities in general and mentioned illegal extraction (poaching) as one of them. Here, you restricted your search to only studies that included illegal extraction (criteria i and ii), which is fine but mislead the overall aim of the paper.

Line 127-129: What if several studies satisfied all the criteria, how did you select the paper?

Line 134: But logging was not included in the analysis right?

Line 139-140: I would like to know all the information that you put in the database and see the full database that you used for the analysis. Please, remove the “etc” and name all the variables, do not be short in words.

Lines 140-143: Do you use meta-analytical tools for the analysis or not? If yes, which type of weighting method did you use for each study (sample size, variance)? How can I believe that your analyses are robust? Reference 18 is not suitable for this statement.

Line 149: The fish data is missing in SM1, is all the body mass coming from primary sources?

Line 155-162: As you focus on population changes of species inside PAs, could you use spatial analysis to calculate for example the agricultural land-use change inside each of the PAs? I propose this because PAs, in general, are not big and species suffer more from local-scale changes (e.g. deforestation or hunting in the area) than from country-level changes. Some areas of a country can be heavily degraded while others are intact, therefore a more detailed and spatially-explicit analysis will benefit the paper in my opinion.

Lines 164-165: If the purpose of your study is to assess the effectiveness of PAs against illegal activities, specifically illegal extraction, please consider to re-do the levels of PAs and stick to PAs that are designated at conserving biodiversity. Categories I‐IV, are designated for that, with I-II being stricter. Categories V‐VI allow sustainable use (see Santini et al. 2016; Oldekop et al. 2016).

Lines 167-170: This can mislead the results because reptiles, birds, fishes and mollusc have very different ecological requirements and their extraction is very different. If the data was poor, then I would simply not use it. Same applies to the spatial data, I would not include the European study nor (maybe) the American ones.

Lines 171-209: In this paragraph, I would specify more explicitly that the response variable of your models is species decline (1) or not (0). This is mentioned in the previous section but as an example, so here I was a bit confused about which response variable you used.

Line 183: Please be consistent with the vocabulary. Here, you use poaching type, but in line 194 you use hunting level (same applies to the whole paper). Poaching refers to illegal hunting, but the level of hunting is something different, e.g., intense vs not intense hunting. I would not use poaching and hunting interchangeably as hunting can be legal.

Line 188: Which datasets? Do you have more than one?

Lines 195-197: How did you do this? Please, expand the explanation.

Line 202-204: How about using cross-validation instead of a subset data specifically for elephants? What is sufficient data in this case?

Line 204-206: So if I understood correctly you have three sets of data, in all sets, you started from a global model and did backwards removal to assess the generality of the effects, is this correct? Did you use any model selection criteria (AIC or BIC) to assess if the model with all the significant variables was the best or not? Moreover, as I said, I would stick only to the continents with enough data (Africa and Asia) the rest are quite scarce (maybe even only Africa as it accounts for 80% of your data). Figure 1 shows how this is a problem with very few points in Europe and America.

Results

In my opinion, there are too many figures (8 in total) and some of them are not very informative, please, consider to remove some of them or combine them. For instance, Figure 2 could be replaced with text.

Lines 246-252: These two paragraphs could be merged in one, Figure 3 already shows the increase in studies so no need for Figure S1. Moreover, is there a reason for the different colors in Figure 3?

Line 263-264: These numbers also show a strong biased towards mammals with very low numbers for the rest of the groups, therefore, I would suggest to completely remove them from the analysis and not include them as “non-mammals”.

Line 286-292: This paragraph and Table 1 are really confusing. You mix all different models and is really difficult to follow. Why Figure 6b is the model without African elephants? And did you only removed African elephants or all elephants as mentioned in line 200? Again, please be consistent with terminology. Moreover, I don’t understand Model 1, how is it possible that none of the poaching types (not levels) is significant when including the elephants? Aren’t elephants very influenced by poaching (line 202)?

Line 302: I thought Figure 6a is for Model 1 (line 288-289) but in the caption, you put that is for the model without elephants, can you clarify it?

Line 315: I think you confuse the terminology here is not best explained but significantly affected by agricultural change. Could you provide the explained variance by each of the models, i.e. marginal and condition R2?

Line 356: Did you actually removed Europe? How about Central America? Why did you combine Latin America+Asia?

Line 360: So the stricter the more decline?

Discussion

Please, do not talk about illegal activities in general through all the discussion as you only included illegal extraction (poaching) in the analysis, focus on that.

Lines 376-377: Could you maybe create different body size groups to test this?

Line 378: You did not calculate habitat loss as such, even less at the PA scale. Is there any animal in your list that have affinity for agricultural areas? If yes, then the increase in agriculture for them is not habitat loss.

Suggested references

Benítez-López A, Alkemade R, Schipper AM, Ingram DJ, Verweij PA, Eikelboom JAJ, Huijbregts MAJ. 2017. The impact of hunting on tropical mammal and bird populations. Science 356:180–183. Available from: http://science.sciencemag.org/content/sci/356/6334/180.full.pdf.

Benítez-López A, Santini L, Schipper AM, Busana M, Huijbregts MAJ. 2019. Intact but empty forests? Patterns of hunting-induced mammal defaunation in the tropics. PLOS Biology 17:e3000247. Available from: https://doi.org/10.1371/journal.pbio.3000247.

Brodie JF, Giordano AJ, Zipkin EF, Bernard H, Mohd-Azlan J, Ambu L. 2015. Correlation and persistence of hunting and logging impacts on tropical rainforest mammals. Conservation Biology 29:110–121. John Wiley & Sons, Ltd. Available from: https://doi.org/10.1111/cobi.12389.

Di Marco M, Ferrier S, Harwood TD, Hoskins AJ, Watson JEM. 2019. Wilderness areas halve the extinction risk of terrestrial biodiversity. Nature 573:582–585. Available from: https://doi.org/10.1038/s41586-019-1567-7.

Gallego‐Zamorano J, Benítez‐López A, Santini L, Hilbers JP, Huijbregts MAJ, Schipper AM. 2020. Combined effects of land use and hunting on distributions of tropical mammals. Conservation Biology:cobi.13459. Available from: https://onlinelibrary.wiley.com/doi/abs/10.1111/cobi.13459.

Geldmann J et al. 2015. Changes in protected area management effectiveness over time: A global analysis. Biological Conservation 191:692–699. Available from: http://www.sciencedirect.com/science/article/pii/S0006320715300793.

Geldmann J, Manica A, Burgess ND, Coad L, Balmford A. 2019. A global-level assessment of the effectiveness of protected areas at resisting anthropogenic pressures. Proceedings of the National Academy of Sciences:201908221. Available from: http://www.pnas.org/content/early/2019/10/22/1908221116.abstract.

Oldekop JA, Holmes G, Harris WE, Evans KL. 2016. A global assessment of the social and conservation outcomes of protected areas. Conservation Biology 30:133–141. John Wiley & Sons, Ltd. Available from: https://doi.org/10.1111/cobi.12568.

Ripple WJ et al. 2016. Bushmeat hunting and extinction risk to the world’s mammals. Royal Society open science 3:160498. The Royal Society. Available from: https://www.ncbi.nlm.nih.gov/pubmed/27853564.

Santini L, Saura S, Rondinini C. 2016. Connectivity of the global network of protected areas. Diversity and Distributions 22:199–211. Available from: http://doi.wiley.com/10.1111/ddi.12390.

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PLoS One. 2020 Aug 21;15(8):e0227163. doi: 10.1371/journal.pone.0227163.r002

Author response to Decision Letter 0


16 Apr 2020

Details of our responses to each reviewer and the Journal Editor is found in the Response to Reviewers document included in the attachments

Attachment

Submitted filename: Response to reviewers - Wild mammal declines in PAs.docx

Decision Letter 1

Stefano Grignolio

26 May 2020

PONE-D-19-34271R1

Global extent and drivers of mammal population declines in protected areas under illegal hunting pressure

PLOS ONE

Dear Dr. Rija,

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.

Please submit your revised manuscript by Jul 10 2020 11:59PM. 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.

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

We look forward to receiving your revised manuscript.

Kind regards,

Stefano Grignolio, Ph.D

Academic Editor

PLOS ONE

Additional Editor Comments (if provided):

I appreciated the impressive job of responding to comments and increasing the quality of the manuscript. Both reviewers agree to point out this result, even if the reviewer #1 suggests to add some articles in your review.

Although I noted the big efforts to improve the writing of the manuscript, I agree with reviewer #1 to request you a further revision in the use of specific terms and acronyms.

I feel that the method section needs a more detailed description of the statistical analysis, particularly of the methods used to estimate the explanatory variables. Finally, I would like to see a broader description of the results in order to better highlight the findings of the manuscript and to make them easier to understand for readers.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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

Reviewer #1: (No Response)

Reviewer #2: All comments have been addressed

**********

2. 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: Partly

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?

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: Yes

Reviewer #2: Yes

**********

5. 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: No

Reviewer #2: Yes

**********

6. 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: The second version of the MS submitted by the authors presented a text that was difficult to understand, which complicated decision making. The study is important, however, it needs a careful editing of the text to improve reading. There is a lack of standardization in writing and abbreviations, terms, etc. Furthermore, I believe that the review conducted by the authors is incomplete and biased, because several studies conducted in Brazil that showed the impact of illegal hunting on mammals have not been mentioned.

My biggest concern is the writing of the MS and the absence of some important references.

See my comments in the PDF file.

Reviewer #2: (No Response)

**********

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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: No

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Attachment

Submitted filename: PONE-D-19-34271_R1_reviewer2020.pdf

Attachment

Submitted filename: Review_PONE-D-19-34271_R1.docx

PLoS One. 2020 Aug 21;15(8):e0227163. doi: 10.1371/journal.pone.0227163.r004

Author response to Decision Letter 1


17 Jul 2020

Many thanks to the reviewers for their constructive comments on the manuscript. We have responded to each comment from the reviewers and Editor. The details can be found in the response to reviewers document attached

Attachment

Submitted filename: Response to reviewers.docx

Decision Letter 2

Stefano Grignolio

30 Jul 2020

Global extent and drivers of mammal population declines in protected areas under illegal hunting pressure

PONE-D-19-34271R2

Dear Dr. Rija,

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,

Stefano Grignolio, Ph.D

Academic Editor

PLOS ONE

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: All comments have been addressed

**********

2. 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: Yes

**********

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

Reviewer #1: Yes

**********

4. 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: Yes

**********

5. 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

**********

6. 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: After careful review of the second version of the MS entitled PONE-D-19-34271R2 "Global extent and drivers of mammal population declines in protected areas under illegal hunting pressure", I decided to recommend for publication.

**********

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

Acceptance letter

Stefano Grignolio

11 Aug 2020

PONE-D-19-34271R2

Global extent and drivers of mammal population declines in protected areas under illegal hunting pressure

Dear Dr. Rija:

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. Stefano Grignolio

Academic Editor

PLOS ONE

Associated Data

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

    Supplementary Materials

    S1 File

    (DOCX)

    S1 Raw data

    (CSV)

    Attachment

    Submitted filename: Response to reviewers - Wild mammal declines in PAs.docx

    Attachment

    Submitted filename: PONE-D-19-34271_R1_reviewer2020.pdf

    Attachment

    Submitted filename: Review_PONE-D-19-34271_R1.docx

    Attachment

    Submitted filename: Response to reviewers.docx

    Data Availability Statement

    Data are available as Supporting Information files.


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