Mapping the connectivity-conflict interface to inform conservation.

Balancing the competing, and often conflicting, needs of people and wildlife in shared landscapes is a major challenge for conservation science and policy worldwide. Connectivity is critical for wildlife persistence, but dispersing animals may come into conflict with people, leading to severe costs for humans and animals and impeding connectivity. Thus, conflict mitigation and connectivity present an apparent dilemma for conservation. We present a framework to address this dilemma and disentangle the effects of barriers to animal movement and conflict-induced mortality of dispersers on connectivity. We extend random-walk theory to map the connectivity-conflict interface, or areas where frequent animal movement may lead to conflict and conflict in turn impedes connectivity. We illustrate this framework with the endangered Asian elephant Elephas maximus, a species that frequently disperses out of protected areas and comes into conflict with humans. We mapped expected movement across a human-dominated landscape over the short- and long-term, accounting for conflict mortality. Natural and conflict-induced mortality together reduced expected movement and connectivity among populations. Based on model validation, our conflict predictions that explicitly captured animal movement better explained observed conflict than a model that considered distribution alone. Our work highlights the interaction between connectivity and conflict and enables identification of location-specific conflict mitigation strategies that minimize losses to people, while ensuring critical wildlife movement between habitats. By predicting where animal movement and humans collide, we provide a basis to plan for broad-scale conservation and the mutual well-being of wildlife and people in shared landscapes.

A Bayesian hierarchical approach to quantifying stakeholder attitudes toward conservation in the presence of reporting error.

Stakeholder support is vital for achieving conservation success, yet there are few reliable mechanisms to monitor stakeholder attitudes toward conservation. Approaches used to assess attitudes rarely account for bias arising from reporting error, which can lead to falsely reporting a positive attitude toward conservation (false-positive error) or not reporting a positive attitude when the respondent has a positive attitude toward conservation (false-negative error). Borrowing from developments in applied conservation science, we used a Bayesian hierarchical model to quantify stakeholder attitudes as the probability of having a positive attitude toward wildlife notionally (or in abstract terms) and at localized scales while accounting for reporting error. We compared estimates from our model, Likert scores, and naïve estimates (i.e., proportion of respondents reporting a positive attitude in at least 1 question that was only susceptible to false-negative error) with true stakeholder attitudes through simulations. We then applied the model in a survey of tea estate staff on their attitudes toward Asian elephants (Elephas maximus) in the Kaziranga-Karbi Anglong landscape of northeast India. In simulations, Bayesian model estimates of stakeholder attitudes toward wildlife were less biased than naïve estimates or Likert scores. After accounting for reporting errors, we estimated the probability of having a positive attitude toward elephants notionally as 0.85 in the Kaziranga landscape, whereas the proportion of respondents who had positive attitudes toward elephants at a localized scale was 0.50. In comparison, without accounting for reporting errors, naïve estimates of proportions of respondents with positive attitudes toward elephants were 0.69 and 0.23 notionally and at local scales, respectively. False (positive and negative) reporting probabilities were consistently not 0 (0.22-0.68). Regular and reliable assessment of stakeholder attitudes-combined with inference on drivers of positive attitudes-can help assess the success of initiatives aimed at facilitating human behavioral change and inform conservation decision making.

Una Estrategia de Jerarquía Bayesiana para Cuantificar las Actitudes de Grupos de Interés hacia la Conservación en Presencia de Errores de Información Resumen El apoyo de los grupos de interés es vital para alcanzar el éxito en la conservación, sin embargo, existen pocos mecanismos confiables para monitorear la actitud de los grupos de interés hacia la conservación. Las estrategias que se usan para valorar las actitudes de los grupos de interés pocas veces toman en cuenta el sesgo que surge de errores en la información, lo cual puede resultar en un falso reporte de actitudes positivas hacia la conservación (error falso positivo) o en que no se reporte una actitud positiva cuando el respondiente tiene una actitud positiva hacia la conservación (error falso negativo). Usamos un modelo de jerarquía bayesiana, construido a partir del desarrollo aplicado en la ciencia de la conservación, para cuantificar las actitudes de los grupos de interés como la probabilidad de tener, teóricamente (o en términos abstractos) y a escalas locales, una actitud positiva hacia la vida silvestre mientras se compensa el error de información. Comparamos mediante simulaciones las estimaciones de nuestro modelo, los puntajes de Likert y las estimaciones ingenuas (es decir, la proporción de los respondientes que reportaron una actitud positiva en al menos una pregunta que se encontraba solamente susceptible al error falso negativo) con las verdaderas actitudes de los grupos de interés. Después aplicamos el modelo al censo realizado al personal de una finca de té sobre sus actitudes hacia los elefantes asiáticos (Elephas maximus) en el paisaje de Kaziranga-Karbi Anglong al noreste de la India. En las simulaciones, las estimaciones de las actitudes de los grupos de interés hacia la vida silvestre generados por el modelo bayesiano estuvieron menos sesgados que las estimaciones ingenuas o los puntajes de Likert. Después de considerar los errores de información, estimamos una probabilidad de 0.85 de que los respondientes teóricamente tuvieran una actitud positiva ante los elefantes en el paisaje de Kaziranga, mientras que la proporción de respondientes con actitudes positivas hacia los elefantes a escalas locales fue de 0.50. Como contraste, sin considerar los errores de información, las estimaciones ingenuas de la proporción de los respondientes con actitud positiva hacia los elefantes fueron de 0.69 y 0.23 teóricamente y a escalas locales, respectivamente. El reporte de falsos (positivos y negativos) en las probabilidades constantemente no fue 0 (0.22 - 0.68). La valoración regular y confiable de las actitudes de los grupos de interés - combinada con la inferencia sobre los conductores de estas actitudes positivas - puede ayudar a evaluar el éxito de las iniciativas enfocadas en facilitar cambios en el comportamiento humano y en informar a las decisiones de conservación.

Mechanistic understanding of human-wildlife conflict through a novel application of dynamic occupancy models.

Crop and livestock depredation by wildlife is a primary driver of human-wildlife conflict, a problem that threatens the coexistence of people and wildlife globally. Understanding mechanisms that underlie depredation patterns holds the key to mitigating conflicts across time and space. However, most studies do not consider imperfect detection and reporting of conflicts, which may lead to incorrect inference regarding its spatiotemporal drivers. We applied dynamic occupancy models to elephant crop depredation data from India between 2005 and 2011 to estimate crop depredation occurrence and model its underlying dynamics as a function of spatiotemporal covariates while accounting for imperfect detection of conflicts. The probability of detecting conflicts was consistently <1.0 and was negatively influenced by distance to roads and elevation gradient, averaging 0.08-0.56 across primary periods (distinct agricultural seasons within each year). The probability of crop depredation occurrence ranged from 0.29 (SE 0.09) to 0.96 (SE 0.04). The probability that sites raided by elephants in primary period t would not be raided in primary period t + 1 varied with elevation gradient in different seasons and was influenced negatively by mean rainfall and village density and positively by distance to forests. Negative effects of rainfall variation and distance to forests best explained variation in the probability that sites not raided by elephants in primary period t would be raided in primary period t + 1. With our novel application of occupancy models, we teased apart the spatiotemporal drivers of conflicts from factors that influence how they are observed, thereby allowing more reliable inference on mechanisms underlying observed conflict patterns. We found that factors associated with increased crop accessibility and availability (e.g., distance to forests and rainfall patterns) were key drivers of elephant crop depredation dynamics. Such an understanding is essential for rigorous prediction of future conflicts, a critical requirement for effective conflict management in the context of increasing human-wildlife interactions.

Entendimiento Mecánico del Conflicto Humano - Animales Silvestre a través de la Novedosa Aplicación de los Modelos Dinámicos de Ocupación Resumen La depredación de cultivos y ganado por parte de animales silvestres es un conductor principal del conflicto humano - animales silvestres, un problema que amenaza la coexistencia de la gente y la vida silvestre a nivel global. Entender los mecanismos que son la base de los patrones de depredación es la clave para mitigar los conflictos a lo largo del tiempo y el espacio. Sin embargo, la mayoría de los estudios no consideran la detección imperfecta y el reporte de conflictos, lo que puede llevar a la interferencia incorrecta con respecto a los conductores espacio-temporales. Aplicamos modelos dinámicos de ocupación a datos de depredación de cultivos por elefantes en India desde 2005 y hasta 2011 para estimar la incidencia de depredación de cultivos y modelar sus dinámicas como una función de covarianzas espacio-temporales mientras representan la detección imperfecta de los conflictos. La probabilidad de detectar conflictos fue constantemente <1.0 y estuvo influenciada negativamente por la distancia a las carreteras y el gradiente de elevación, promediando 0.08 - 0.56 en los periodos primarios (temporadas agrícolas distintas dentro de cada año). La probabilidad de la incidencia de depredación de cultivos varió desde 0.29 (SE 0.09) hasta 0.96 (SE 0.04). La probabilidad de que los sitios saqueados por elefantes en un periodo primario t no fueran saqueados en un periodo primario t + 1 varió con el gradiente de elevación en diferentes temporadas y estuvo influenciado negativamente por la precipitación promedio y la densidad de la aldea y positivamente por la distancia al los bosques. Los efectos negativos de la variación en la precipitación y la distancia a los bosques explicaron de mejor manera la variación en la probabilidad de que los sitios no saqueados por elefantes en el periodo primario t serían saqueados en el periodo primario t + 1. Con nuestra novedosa aplicación de los modelos de ocupación, separamos a los conductores espacio-temporales de los factores que influyen en cómo son observados, permitiendo así la inferencia más fiable de los mecanismos que son la base de los patrones observados de los conflictos. Encontramos que los factores asociados con el incremento en la disponibilidad y accesibilidad de los cultivos (p. ej.: la distancia a los bosques y los patrones de precipitación) fueron conductores clave en las dinámicas de depredación de cultivos de los elefantes. Tal entendimiento es esencial para una predicción rigurosa de conflictos futuros, un requerimiento crítico para el manejo efectivo de conflictos en el contexto de las crecientes interacción humano - animales silvestres.

Wild animals enhance climate solutions across social-ecological systems.

Lamba et al. demonstrated the feasibility of explicitly incorporating wild animal conservation into nature-based climate solutions, the multifaceted value of which was recently promoted by Schmitz et al. I synthesize their ideas to highlight some issues critical for large-scale integration of these coupled priorities across social-ecological systems.

Synergistic influences of phase, density, and climatic variation on the dynamics of fluctuating populations.

Although ecologists have long recognized that certain mammalian species exhibit high-amplitude, often multiannual, fluctuations in abundance, their causes have remained poorly understood and the subject of intense debate. A key contention has been the relative role of density-dependent and density-independent processes in governing population dynamics. We applied capture-mark-recapture analysis to 25 years of monthly trapping data from a fluctuating prairie vole Microtus ochrogaster population in Illinois, USA, to estimate realized population growth rates and associated vital rates (survival and recruitment) and modeled them as a function of vole density and density-independent climatic variation. We also tested for phase dependence and seasonality in the effects of the above processes. Variation in the realized population growth rate was best explained by phase-specific changes in vole density lagged by one month and mean monthly temperatures with no time lags. The underlying vital rates, survival and recruitment, were influenced by the additive and interactive effects of phase, vole density, and mean monthly temperatures. Our results are consistent with the observation that large-scale population fluctuations are characterized by phase-specific changes in demographic and physiological characteristics. Our findings also support the growing realization that the interaction between climatic variables and density-dependent factors may be a widespread phenomenon, and they suggest that the direction and magnitude of such interactive effects may be phase specific. We conclude that density-dependent and density-independent climatic variables work in tandem during each phase of density fluctuations to drive the dynamics of fluctuating populations.

Coupled effects of climatic forcing and the human footprint on wildlife movement and space use in a dynamic floodplain landscape.

With climate change, terrestrial fauna in riparian floodplain ecosystems must adapt to a predicted increase in frequency and magnitude of fluvial perturbations. Seasonal migration to seek refuge from floodwaters represents a central adaptation strategy, but may entail risky navigation of anthropogenic spaces in heterogeneous landscapes. Here, we demonstrate the opportunities and constraints large-bodied mammalian herbivores face during an adaptive response of obligatory flood-driven refuge migration, across a human-dominated environment. Our study system, centred around a productive protected area--Kaziranga National Park in Assam, Northeast India--on the floodplains of the Brahmaputra River, is home to an abundance of large herbivores that undertake seasonal migrations in response to floods. We contrast species distribution data during a major flood event with those from the dry season to illustrate season-specific movement and space use decisions of large herbivores ranging in body mass from the 3000-kg Asian elephant Elephas maximus to the 20-kg muntjac Muntiacus muntjak. In the dry season, most large herbivores--a majority of which are endangered and threatened by anthropogenic pressures--avoided areas with a strong human footprint, while preferring spaces with high land-use diversity. During the floods, such species were pushed out of inundated habitats within the protected area, and they chose to move through woodlands and areas under bamboo cover on private lands, as they migrated to forested refugia on higher ground. Our results show how seasonal environmental constraints shaped by floods determine the internal motivation of animals to risk traversing a human-dominated space to seek refuge, which contextually defines how animals view and navigate the landscape. Such insights underscore the importance of dynamic and adaptive planning, and participatory conservation efforts, to facilitate connectivity in the changing environment and climate of the present Anthropocene.

Author Correction: Towards a reliable assessment of Asian elephant population parameters: the application of photographic spatial capture-recapture sampling in a priority floodplain ecosystem.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Towards a reliable assessment of Asian elephant population parameters: the application of photographic spatial capture-recapture sampling in a priority floodplain ecosystem.

The hitherto difficult task of reliably estimating populations of wide-ranging megafauna has been enabled by advances in capture-recapture methodology. Here we combine photographic sampling with a Bayesian spatially-explicit capture-recapture (SCR) model to estimate population parameters for the endangered Asian elephant Elephas maximus in the productive floodplain ecosystem of Kaziranga National Park, India. Posterior density estimates of herd-living adult females and sub-adult males and females (herd-adults) was 0.68 elephants/km2 (95% Credible Intervals, CrI = 0.56-0.81) while that of adult males was 0.24 elephants/km2 (95% CrI = 0.18-0.30), with posterior density estimates highlighting spatial heterogeneity in elephant distribution. Estimates of the space-usage parameter suggested that herd-adults ([Formula: see text] = 5.91 km, 95% CrI = 5.18-6.81) moved around considerably more than adult males ([Formula: see text] = 3.64 km, 95% CrI = 3.09-4.34). Based on elephant movement and age-sex composition, we derived the population that contributed individuals sampled in Kaziranga to be 908 herd-adults, 228 adult males and 610 young (density = 0.46 young/km2, SD = 0.06). Our study demonstrates how SCR is suited to estimating geographically open populations, characterising spatial heterogeneity in fine-scale density, and facilitating reliable monitoring to assess population status and dynamics for science and conservation.

"In a tree by the brook, there's a songbird who sings": Woodlands in an agricultural matrix maintain functionality of a wintering bird community.

The agricultural matrix has increasingly been recognized for its potential to supplement Protected Areas (PAs) in biodiversity conservation. This potential is highly contextual, depending on composition and spatial configuration of matrix elements and their mechanistic relationship with biological communities. We investigate the effects of local vegetation structure, and proximity to a PA on the site-use of different guilds in a wintering bird community within the PA, and in wooded land-use types in the surrounding matrix. We used occupancy models to estimate covariate-guild relationships and predict site-use. We also compared species richness (estimated through capture-recapture models) and species naïve site-use between the PA and the matrix to evaluate taxonomic changes. We found that tree cover did not limit the site-use of most guilds of the community, probably due to high canopy cover across all chosen sites. Exceptions to this were guilds comprising generalist species. Shrub cover and bamboo cover had important effects on some woodland-associated guilds, suggesting a change in limiting factors for site-use under adequate tree cover. Site-use across the matrix was high for all analyzed guilds. This was found to be due to three non-exclusive reasons: (i) presence of one or more ubiquitous species (found all across the landscape) within some guilds, (ii) redundancy of species within guilds that buffered against a decrease in site-use, and (iii) turnover in guild composition/abundances to more generalist species from PA to matrix. Estimated species richness was higher in the matrix (107± 11; mean ± SE) than in the PA (90± 7), which may have been in part due to the addition of generalist species in the matrix. Understanding factors that limit biological communities is crucial to better managing the ever-increasing matrix for biodiversity conservation. Our study provides insights into the effects of different components of vegetation structure on the bird community in wooded land-use types in the matrix. We highlight the value of woodlands surrounding PAs in maintaining multiple guilds, and hence, the functionality of a wintering bird community. However, we caution that the matrix may fall short in retaining some specialized species of the community.

Patterns and Determinants of Habitat Occupancy by the Asian Elephant in the Western Ghats of Karnataka, India.

Understanding species distribution patterns has direct ramifications for the conservation of endangered species, such as the Asian elephant Elephas maximus. However, reliable assessment of elephant distribution is handicapped by factors such as the large spatial scales of field studies, survey expertise required, the paucity of analytical approaches that explicitly account for confounding observation processes such as imperfect and variable detectability, unequal sampling probability and spatial dependence among animal detections. We addressed these problems by carrying out 'detection--non-detection' surveys of elephant signs across a c. 38,000-km(2) landscape in the Western Ghats of Karnataka, India. We analyzed the resulting sign encounter data using a recently developed modeling approach that explicitly addresses variable detectability across space and spatially dependent non-closure of occupancy, across sampling replicates. We estimated overall occupancy, a parameter useful to monitoring elephant populations, and examined key ecological and anthropogenic drivers of elephant presence. Our results showed elephants occupied 13,483 km(2) (SE = 847 km(2)) corresponding to 64% of the available 21,167 km(2) of elephant habitat in the study landscape, a useful baseline to monitor future changes. Replicate-level detection probability ranged between 0.56 and 0.88, and ignoring it would have underestimated elephant distribution by 2116 km(2) or 16%. We found that anthropogenic factors predominated over natural habitat attributes in determining elephant occupancy, underscoring the conservation need to regulate them. Human disturbances affected elephant habitat occupancy as well as site-level detectability. Rainfall is not an important limiting factor in this relatively humid bioclimate. Finally, we discuss cost-effective monitoring of Asian elephant populations and the specific spatial scales at which different population parameters can be estimated. We emphasize the need to model the observation and sampling processes that often obscure the ecological process of interest, in this case relationship between elephants to their habitat.

Survival, recruitment, and population growth rate of an important mesopredator: the northern raccoon.

Populations of mesopredators (mid-sized mammalian carnivores) are expanding in size and range amid declining apex predator populations and ever-growing human presence, leading to significant ecological impacts. Despite their obvious importance, population dynamics have scarcely been studied for most mesopredator species. Information on basic population parameters and processes under a range of conditions is necessary for managing these species. Here we investigate survival, recruitment, and population growth rate of a widely distributed and abundant mesopredator, the northern raccoon (Procyon lotor), using Pradel's temporal symmetry models and >6 years of monthly capture-mark-recapture data collected in a protected area. Monthly apparent survival probability was higher for females (0.949, 95% CI = 0.936-0.960) than for males (0.908, 95% CI = 0.893-0.920), while monthly recruitment rate was higher for males (0.091, 95% CI = 0.078-0.106) than for females (0.054, 95% CI = 0.042-0.067). Finally, monthly realized population growth rate was 1.000 (95% CI = 0.996-1.004), indicating that our study population has reached a stable equilibrium in this relatively undisturbed habitat. There was little evidence for substantial temporal variation in population growth rate or its components. Our study is one of the first to quantify survival, recruitment, and realized population growth rate of raccoons using long-term data and rigorous statistical models.