Spatial variation in leopard (Panthera pardus) site use across a gradient of anthropogenic pressure in Tanzania's Ruaha landscape

Understanding large carnivore occurrence patterns in anthropogenic landscapes adjacent to protected areas is central to developing actions for species conservation in an increasingly human-dominated world. Among large carnivores, leopards (Panthera pardus) are the most widely distributed felid. Leopards occupying anthropogenic landscapes frequently come into conflict with humans, which often results in leopard mortality. Leopards’ use of anthropogenic landscapes, and their frequent involvement with conflict, make them an insightful species for understanding the determinants of carnivore occurrence across human-dominated habitats. We evaluated the spatial variation in leopard site use across a multiple-use landscape in Tanzania’s Ruaha landscape. Our study region encompassed i) Ruaha National Park, where human activities were restricted and sport hunting was prohibited; ii) the Pawaga-Idodi Wildlife Management Area, where wildlife sport hunting, wildlife poaching, and illegal pastoralism all occurred at relatively low levels; and iii) surrounding village lands where carnivores and other wildlife were frequently exposed to human-carnivore conflict related-killings and agricultural habitat conversion and development. We investigated leopard occurrence across the study region via an extensive camera trapping network. We estimated site use as a function of environmental (i.e. habitat and anthropogenic) variables using occupancy models within a Bayesian framework. We observed a steady decline in leopard site use with downgrading protected area status from the national park to the Wildlife Management Area and village lands. Our findings suggest that human-related activities such as increased livestock presence and proximity to human households exerted stronger influence than prey availability on leopard site use, and were the major limiting factors of leopard distribution across the gradient of human pressure, especially in the village lands outside Ruaha National Park. Overall, our study provides valuable information about the determinants of spatial distribution of leopards in human-dominated landscapes that can help inform conservation strategies in the borderlands adjacent to protected areas

Decision Trees for Data Publishing May Exacerbate Conservation Conflict

First paragraph: Tulloch et al. have rightly highlighted the need to increase the accessibility of species occurrence data to better support conservation efforts. They present a tree to aid decisions regarding making data publicly available. Their tree is essentially a visual aid to existing protocols. However, we feel that, owing to its failure to explicitly account for likely disagreements among stakeholders throughout the process, the proposed method may inadvertently fuel conservation conflicts.Output Type: Lette

Quantifying the checks and balances of collaborative governance systems for adaptive carnivore management

Recovering or threatened carnivore populations are often harvested to minimise their impact on human activities, such as livestock farming or game hunting. Increasingly, harvest quota decisions involve a set of scientific, administrative and political institutions operating at national and sub-national levels whose interactions and collective decision-making aim to increase the legitimacy of management and ensure population targets are met. In practice, however, assessments of how quota decisions change between these different actors and what consequences these changes have on population trends are rare. We combine a state-space population modelling approach with an analysis of quota decisions taken at both regional and national levels between 2007 and 2018 to build a set of decision-making models that together predict annual harvest quota values for Eurasian lynx (Lynx lynx) in Norway. We reveal a tendency for administrative decision-makers to compensate for consistent quota increases by political actors, particularly when the lynx population size estimate is above the regional target. Using population forecasts based on the ensemble of decision-making models, we show that such buffering of political biases ensures lynx population size remains close to regional and national targets in the long term. Our results go beyond the usual qualitative assessment of collaborative governance systems for carnivore management, revealing a system of checks and balances that, in the case of lynx in Norway, ensures both multi-stakeholder participation and sustainable harvest quotas. Nevertheless, we highlight important inter-regional differences in decision-making and population forecasts, the socio-ecological drivers of which need to be better understood to prevent future population declines. Synthesis and applications. Our work analyses the sequence of decisions leading to yearly quotas for lynx harvest in Norway, highlighting the collaborative and structural processes that together shape harvest sustainability. In doing so, we provide a predictive framework to evaluate participatory decision-making processes in wildlife management, paving the way for scientists and decision-makers to collaborate more widely in identifying where decision biases might lie and how institutional arrangements can be optimised to minimise them. We emphasise, however, that this is only possible if wildlife management decisions are documented and transparent

Integrating conflict, lobbying, and compliance to predict the sustainability of natural resource use

Acknowledgments: This study received funding from the European Research Council under the European Union’s H2020/ERC grant agreement no.679651 (ConFooBio) to N.B. A.B.D. is supported by a Leverhulme Trust Early Career Fellowship. We are grateful to Tim Coulson and E.J. Milner-Gulland for comments on previous versions of this manuscript. All authors conceived the study, developed the underlying theory and software, discussed the results, and wrote the manuscript. J.J.C. carried out the simulations and analyzed thedata.Peer reviewedPublisher PD

Development of a population model tool to predict shooting levels of Greenland barnacle geese on Islay

Background As part of the 10-year Islay Sustainable Goose Management Strategy (ISGMS), population management has been carried out on Islay based on a previous Population Viability Analysis (PVA) (Trinder 2005, 2014). However, Scottish Natural Heritage (SNH) now wishes to update its existing population model because intended Greenland barnacle geese (GBG) reductions during the first years of the ISGMS have proved difficult to achieve. Here, we present a new modelling approach combining data on population size, land-use, climate, and shooting effort that will enable shooting bags to be derived under quantified levels of uncertainty. Main findings - The Greenland barnacle goose (GBG) population on Islay has shown a logistic growth rate. After an initial rapid increase in population size, the population growth rate has declined. - The recent (e.g. 2003-2015) GBG Islay population fluctuates around 45,000 (± 4,082 standard deviation) individuals - The population model (PM) developed here accurately predicts the average winter population of GBG on Islay measured between November and March (inclusive) in the absence of culling on Islay. - Based on previous work, the PM assumes that both climate and the area of improved grassland (AIG) are strong predictors of the size of the GBG population on Islay. Similarly, the PM requires the inclusion of shooting bags implemented on Greenland and Iceland to estimate future population trends. Thus, all of the above (i.e. climate, AIG and shooting bags) need to be updated in the model to obtain future population predictions. - Integration of the PM into the Generalised Management Strategy Evaluation (GMSE) framework provides a tool for forecasting the dynamics of geese based on management targets and maximum allowed shooting bags. - The PM used here to inform shooting bags via the GMSE approach provides a good fit to available historic data and performs better than using the population count from the previous year alone, or using a simpler logistic growth model. - For the PM-GMSE modelling approach to work, it is expected that the user updates the value for each predictor (climate, AIG and shooting bags) in the model so that it can be re-run each year. If such data are not available, a simpler (e.g. logistic growth approximation) population model should be used. - The PM-GMSE approach produces an estimate of the future GBG mean winter count on Islay, as well as a range of shooting bags given a population target. - For an initial run of 1,000 simulated managed populations with a management target of 29,000 and a maximum per year shooting bag of 2,500, most simulations came close to the management target within 10 years. But uncertainty and stochasticity could lead to the target being achieved in a shorter or longer time period, as well as higher or lower population sizes. - Future access to individual-based datasets will allow the implementation of more sophisticated models (e.g. integral population model, IPM) able to account for demographic rates, including processes of immigration and emigration

Development of a population model tool to predict shooting levels of Greenland barnacle geese on Islay

Background As part of the 10-year Islay Sustainable Goose Management Strategy (ISGMS), population management has been carried out on Islay based on a previous Population Viability Analysis (PVA) (Trinder 2005, 2014). However, Scottish Natural Heritage (SNH) now wishes to update its existing population model because intended Greenland barnacle geese (GBG) reductions during the first years of the ISGMS have proved difficult to achieve. Here, we present a new modelling approach combining data on population size, land-use, climate, and shooting effort that will enable shooting bags to be derived under quantified levels of uncertainty. Main findings - The Greenland barnacle goose (GBG) population on Islay has shown a logistic growth rate. After an initial rapid increase in population size, the population growth rate has declined. - The recent (e.g. 2003-2015) GBG Islay population fluctuates around 45,000 (± 4,082 standard deviation) individuals - The population model (PM) developed here accurately predicts the average winter population of GBG on Islay measured between November and March (inclusive) in the absence of culling on Islay. - Based on previous work, the PM assumes that both climate and the area of improved grassland (AIG) are strong predictors of the size of the GBG population on Islay. Similarly, the PM requires the inclusion of shooting bags implemented on Greenland and Iceland to estimate future population trends. Thus, all of the above (i.e. climate, AIG and shooting bags) need to be updated in the model to obtain future population predictions. - Integration of the PM into the Generalised Management Strategy Evaluation (GMSE) framework provides a tool for forecasting the dynamics of geese based on management targets and maximum allowed shooting bags. - The PM used here to inform shooting bags via the GMSE approach provides a good fit to available historic data and performs better than using the population count from the previous year alone, or using a simpler logistic growth model. - For the PM-GMSE modelling approach to work, it is expected that the user updates the value for each predictor (climate, AIG and shooting bags) in the model so that it can be re-run each year. If such data are not available, a simpler (e.g. logistic growth approximation) population model should be used. - The PM-GMSE approach produces an estimate of the future GBG mean winter count on Islay, as well as a range of shooting bags given a population target. - For an initial run of 1,000 simulated managed populations with a management target of 29,000 and a maximum per year shooting bag of 2,500, most simulations came close to the management target within 10 years. But uncertainty and stochasticity could lead to the target being achieved in a shorter or longer time period, as well as higher or lower population sizes. - Future access to individual-based datasets will allow the implementation of more sophisticated models (e.g. integral population model, IPM) able to account for demographic rates, including processes of immigration and emigration

GMSE: an R package for generalised management strategy evaluation

1. Management strategy evaluation (MSE) is a powerful tool for simulating all key aspects of natural resource management under conditions of uncertainty. 2. We present the R package GMSE, which applies genetic algorithms to provide a generalised tool for simulating adaptive decision‐making management scenarios between stakeholders with competing objectives under complex social‐ecological interactions and uncertainty. 3. GMSE models can be agent‐based and spatially explicit, incorporating a high degree of realism through mechanistic modelling of links and feedbacks among stakeholders and with the ecosystem; additionally, user‐defined sub‐models can also be incorporated as functions into the broader GMSE framework. 4. We show how GMSE simulates a social‐ecological system using the example of an adaptively managed waterfowl population on an agricultural landscape; simulated waterfowl exploit agricultural land, causing conflict between conservation interests and the interest of food producers maximising their crop yield. 5. The R package GMSE is open source under GNU Public License; source code and documents are freely available on GitHub

A multispecies assessment of wildlife impacts on local community livelihoods

Conflicts between the interests of agriculture and wildlife conservation are a major threat to biodiversity and human wellbeing globally. Addressing such conflicts requires a thorough understanding of the impacts associated with living alongside protected wildlife. Despite this, most studies reporting on human‐wildlife impacts and the strategies used to mitigate them focus on a single species, thus over‐simplifying often complex systems of human‐wildlife interactions. In this study, we characterize the spatiotemporal patterns of impacts by multiple co‐occurring species on agricultural livelihoods in the eastern Okavango Delta Panhandle in northern Botswana. Using a database of 3,264 wildlife incidents recorded between 2009 and 2015 by the Department of Wildlife and National Parks, we show that a total of eight species – i.e. African elephant, hippopotamus, cheetah, crocodile, leopard, lion, spotted hyena and African wild dog – appear on incident reports, of which 56.5% are attributed to elephants. Most species were associated with only one type of damage (i.e. either damage to crops or livestock loss). Carnivores were primarily implicated in incident reports related to livestock loss, particularly towards the end of the dry season (May‐October). In contrast, herbivores were associated with crop loss incidents during the wet season (November‐April). Our study illustrates how local communities can face distinct livelihood challenges from different species at different times of the year. Such a multi‐species assessment has important implications for the design of conservation interventions aimed at addressing the costs of living with wildlife, and thereby mitigating the underlying conservation conflict. Our spatiotemporal, multi‐species approach is widely applicable to other regions where sustainable and long‐term solutions to conservation conflicts are needed for local communities and biodiversity

Quantifying the checks and balances of collaborative governance systems for adaptive carnivore management

1. Recovering or threatened carnivore populations are often harvested to minimise their impact on human activities, such as livestock farming or game hunting. Increasingly, harvest quota decisions involve a set of scientific, administrative and political institutions operating at national and sub-national levels whose interactions and collective decision-making aim to increase the legitimacy of management and ensure population targets are met. In practice, however, assessments of how quota decisions change between these different actors and what consequences these changes have on population trends are rare. 2. We combine a state-space population modelling approach with an analysis of quota decisions taken at both regional and national levels between 2007 and 2018 to build a set of decision-making models that together predict annual harvest quota values for Eurasian lynx (Lynx lynx) in Norway. 3. We reveal a tendency for administrative decision-makers to compensate for consistent quota increases by political actors, particularly when the lynx population size estimate is above the regional target. Using population forecasts based on the ensemble of decision-making models, we show that such buffering of political biases ensures lynx population size remains close to regional and national targets in the long term. 4. Our results go beyond the usual qualitative assessment of collaborative governance systems for carnivore management, revealing a system of checks and balances that, in the case of lynx in Norway, ensures both multi-stakeholder participation and sustainable harvest quotas. Nevertheless, we highlight important inter-regional differences in decision-making and population forecasts, the socio-ecological drivers of which need to be better understood to prevent future population declines. 5. Synthesis and applications. Our work analyses the sequence of decisions leading to yearly quotas for lynx harvest in Norway, highlighting the collaborative and structural processes that together shape harvest sustainability. In doing so, we provide a predictive framework to evaluate participatory decision-making processes in wildlife management, paving the way for scientists and decision-makers to collaborate more widely in identifying where decision biases might lie and how institutional arrangements can be optimised to minimise them. We emphasise, however, that this is only possible if wildlife management decisions are documented and transparent

Experimental evidence for conservation conflict interventions: the importance of financial payments, community trust and equity attitudes

Conflicts between the objectives of agricultural production and conservation are becoming increasingly complex. Of vital importance to the success of conflict interventions is a detailed understanding of how stakeholders react to management interventions as well as the influence of interacting social and political factors. Across Europe, goose populations have increased considerably, leading to widespread impacts on agriculture and significant conflicts between different stakeholder groups. We used a novel experimental game to understand farmer preferences regarding the design of goose conflict interventions in Scotland. We specifically examined how three alternative interventions (government financial support for scaring activities, subsidies and agglomeration payments that include bonus payments for adoption by neighbouring farms) affect farmer propensity to support goose conservation interests through reduced shooting and the provision of sacrificial crops. We also examined the links between within‐game behaviour and real‐life attributes and attitudes of farmers. We found that all three interventions were conducive to pro‐conservation behaviour in the games. The effects of all three interventions were stronger among farmers who had higher trust towards other community members. Agglomeration payments led to increased provision of sacrificial crops among farmers with negative attitudes towards the current allocation of goose finances in Scotland. Farmers with more positive attitudes towards wildlife tourism were more likely to provide more sacrificial crops, and less likely to shoot in the games. Farmers' real‐life traits had a statistically significant but marginal impact on the effectiveness of financial payments, such as the number of geese being shot on their own lands, remoteness and crop damage by geese. These game results provide evidence for the potential of innovative financial instruments in conflict management and their interactions with social factors such as community trust, equity attitude and real‐life shooting levels. Our study highlights the importance of socio‐political elements in fostering mutually beneficial outcomes in conservation conflicts in addition to addressing material losses to wildlife. We also show how games can help in addressing conservation conflicts in a wide range of settings