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Conservation practitioners have long recognized ecological connectivity as a global priority for preserving biodiversity and ecosystem function. In the early years of conservation science, ecologists extended principles of island biogeography to assess connectivity based on source patch proximity and other metrics derived from binary maps of habitat. From 2006 to 2008, the late Brad McRae introduced circuit theory as an alternative approach to model gene flow and the dispersal or movement routes of organisms. He posited concepts and metrics from electrical circuit theory as a robust way to quantify movement across multiple possible paths in a landscape, not just a single least-cost path or corridor. Circuit theory offers many theoretical, conceptual, and practical linkages to conservation science. We reviewed 459 recent studies citing circuit theory or the open-source software Circuitscape. We focused on applications of circuit theory to the science and practice of connectivity conservation, including topics in landscape and population genetics, movement and dispersal paths of organisms, anthropogenic barriers to connectivity, fire behavior, water flow, and ecosystem services. Circuit theory is likely to have an effect on conservation science and practitioners through improved insights into landscape dynamics, animal movement, and habitat-use studies and through the development of new software tools for data analysis and visualization. The influence of circuit theory on conservation comes from the theoretical basis and elegance of the approach and the powerful collaborations and active user community that have emerged. Circuit theory provides a springboard for ecological understanding and will remain an important conservation tool for researchers and practitioners around the globe. Quienes practican la conservación han reconocido durante mucho tiempo que la conectividad ecológica es una prioridad mundial para la preservación de la biodiversidad y el funcionamiento del ecosistema. Durante los primeros años de la ciencia de la conservación los ecólogos difundieron los principios de la biografía de islas para evaluar la conectividad con base en la proximidad entre el origen y el fragmento, así como otras medidas derivadas de los mapas binarios de los hábitats. Entre 2006 y 2008 el fallecido Brad McRae introdujo la teoría de circuitos como una estrategia alternativa para modelar el flujo génico y la dispersión o las rutas de movimiento de los organismos. McRae propuso conceptos y medidas de la teoría de circuitos eléctricos como una manera robusta para cuantificar el movimiento a lo largo demúltiplescaminos posibles en un paisaje, no solamente a lo largo de un camino o corredor de menor costo. La teoría de circuitos ofrece muchos enlaces teóricos, conceptuales y prácticos con la ciencia de la conservación. Revisamos 459 estudios recientes que citan la teoría de circuitos o el software de fuente abierta Circuitscape. Nos enfocamos en las aplicaciones de la teoría de circuitos a la ciencia y a la práctica de la conservación de la conectividad, incluyendo temas como la genética poblacional y del paisaje, movimiento y caminos de dispersión de los organismos, barreras antropogénicas de la conectividad, comportamiento ante incendios, flujo del agua, y servicios ambientales. La teoría de circuitos probablemente tenga un efecto sobre la ciencia de la conservación y quienes la practican por medio de una percepción mejorada de las dinámicas del paisaje, el movimiento animal, y los estudios de uso de hábitat, y por medio del desarrollo de nuevas herramientas de software para el análisis de datos y su visualización. La influencia de la teoría de circuitos sobre la conservación viene de la base teórica y la elegancia de la estrategia y de las colaboraciones fuertes y la comunidad activa de usuarios que han surgido recientemente. La teoría de circuitos proporciona un trampolín para el entendimiento ecológico y seguirá siendo una importante herramienta de conservación para los investigadores y practicantes en todo el mundo. 保护实践者长期以来一直将生态连接度视为保护生物多祥性和生态系统功能的当务之急。在保护科学发 展早期，生态学家将岛屿生物地理学的原理进行扩展，基于源斑块邻近度和其它来_ ニ元生境图的指标来评估连 接度。2006 年到 2008 年，已故的 Brad McRae 引入了电路理论，作为模拟基因流和生物体扩散或移动路径的新 方法。他用电路理论中的概念和指标开发了一种稳健的方法来量化景观中多种可能的移动路径，而这不只是ー 条最低成本的路径或廊道。电路理论为保护科学提供了许多理论、概念和实践方面的联系。我们综述了近期引 用电路理论或是开源软件Circidtscape的459项研究，重点关注电路理论在连接度保护科学与实践中的应用，包 括景观和种群遗传学、生物体运动和扩散路径、连接度的人为障碍、火灾、水流和生态系统服务等间题。电路 理论通过帮助理解景观动力学、动物移动和生境利用研究，以及开发新的数据分析和可视化软件工具，影响着 保护科学和实践者。电路理论对保护的影响来自于该方法的理论基础和优雅性，以及现已出现的強大的合作队 伍和活跃的用户群体。电路理论为生态学理解提供了跳板，并将继续作为全球研究人员和实践者的重要保护エ 具。

The propensity for a grizzly bear to develop conflict behaviours might be a result of social learning between mothers and cubs, genetic inheritance, or both learning and inheritance. Using non-invasive genetic sampling, we collected grizzly bear hair samples during 2011-2014 across southwestern Alberta, Canada. We targeted private agricultural lands for hair samples at grizzly bear incident sites, defining an incident as an occurrence in which the grizzly bear caused property damage, obtained anthropogenic food, or killed or attempted to kill livestock or pets. We genotyped 213 unique grizzly bears (118 M, 95 F) at 24 microsatellite loci, plus the amelogenin marker for sex. We used the program COLONY to assign parentage. We evaluated 76 mother-offspring relationships and 119 father-offspring relationships. We compared the frequency of problem and non-problem offspring from problem and non-problem parents, excluding dependent offspring from our analysis. Our results support the social learning hypothesis, but not the genetic inheritance hypothesis. Offspring of problem mothers are more likely to be involved in conflict behaviours, while offspring from non-problem mothers are not likely to be involved in incidents or human-bear conflicts themselves (Barnard's test, p = 0.05, 62.5% of offspring from problem mothers were problem bears). There was no evidence that offspring are more likely to be involved in conflict behaviour if their fathers had been problem bears (Barnard's test, p = 0.92, 29.6% of offspring from problem fathers were problem bears). For the mother-offspring relationships evaluated, 30.3% of offspring were identified as problem bears independent of their mother's conflict status. Similarly, 28.6% of offspring were identified as problem bears independent of their father's conflict status. Proactive mitigation to prevent female bears from becoming problem individuals likely will help prevent the perpetuation of conflicts through social learning.

Understanding social aggregation patterns in ungulate herds is essential for gaining behavioral insights, optimizing resource use, reducing human-wildlife conflict, and managing disease risk. As chronic wasting disease is the preeminent disease-related threat to cervid populations in North America, knowledge of contact between individuals and spatiotemporal patterns of aggregation provides opportunity to understand and potentially reduce disease risk while supporting sustainable population sizes. Herd density metrics, derived from global positioning system (GPS) data, can be used to inform management decisions. To effectively compare aggregation behavior within and between herds, aggregation metrics must be accurate. However, the consistency of metrics across different GPS collar sample sizes remains unclear and robust studies of big game require understanding how these factors may vary in different contexts. We examined the minimum sample size necessary for reliable calculations of three aggregation metrics: pairwise inter-animal distances, daily proximity rates, and kernel density estimate (KDE) areas. We used GPS collar data from the Jackson and West Green River elk herds (Cervus canadensis) in western Wyoming, USA, that differ in herd size and group structure (single versus multiple sub-groups), representing common practical contexts. Elk locations were acquired for the Jackson herd between 2016 and 2019 and from 2005 to 2010 for the West Green River herd. Herd-specific characteristics substantially influence the sample size necessary for accurate density measurements. As predicted, larger herds with many groups require more GPS collars than small herds with fewer groups. The sample size needed to accurately estimate aggregation varies by metric, with KDE areas, useful for indexing environmentally transmitted disease risk, generally requiring fewer samples, especially in high-density contexts. The required sample size also varies with seasonal changes in density. During periods of highest density, similar sample sizes are required to estimate inter-animal distances and proximity rates regardless of herd characteristics. Our results have implications for costs associated with studying big game herds, indicating fewer collars may be sufficient in some cases. These insights can aid researchers and managers in determining the appropriate number of GPS collars required for effective herd monitoring and informing relevant aggregation metrics for their management goals.

Several species of bears are known to rub deliberately against trees and other objects, but little is known about why bears rub. Patterns in rubbing behavior of male and female brown bears ( Ursus arctos ) suggest that scent marking via rubbing functions to communicate among potential mates or competitors. Using DNA from bear hairs collected from rub objects in southwestern Alberta from 2011–2014 and existing DNA datasets from Montana and southeastern British Columbia, we determined sex and individual identity of each bear detected. Using these data, we completed a parentage analysis. From the parentage analysis and detection data, we determined the number of offspring, mates, unique rub objects where an individual was detected, and sampling occasions during which an individual was detected for each brown bear identified through our sampling methods. Using a Poisson regression, we found a positive relationship between bear rubbing behavior and reproductive success; both male and female bears with a greater number of mates and a greater number of offspring were detected at more rub objects and during more occasions. Our results suggest a fitness component to bear rubbing, indicate that rubbing is adaptive, and provide insight into a poorly understood behaviour.

Occupancy models have become increasingly popular for species monitoring and assessment, in part, because detection/non‐detection data are readily obtained using a variety of methods. Multispecies occupancy models (MSOMs) can yield more accurate parameter estimates than single‐species models (SSOMs) with less data through their hierarchical structure, making MSOMs an attractive option when species are hard to detect or when data collection is constrained, leading to sparse datasets. Such constraints may arise from limited sampling resources, but also occur in rare species monitoring or where preliminary results are desired to inform adaptive management. Further, experimental habitat treatments often impose spatial constraints on sampling based on the scale of their implementation. Whether a MSOM outperforms SSOMs depends on the volume of data, characteristics of the ecological community, research goals of a study and how these factors align with modeling assumptions. We performed a simulation study of hypothetical pollinator communities under varying sampling intensities for scenarios in which experimental habitat treatments produced different community‐level effects. We fit occupancy models to simulated datasets and assessed model performance. At lower sampling intensities (< 20 spatial replicates and < 4 temporal replicates), MSOM community‐level treatment effect estimates were biased. Even at twice this sampling intensity, SSOMs yielded more accurate species‐specific effect estimates in treatment effect scenarios with high variance. In some cases, MSOMs can pull species in the tails of distributions too far toward the community mean effect, which risks incorrect conclusions concerning whether treatments help or harm individual species. When quantifying species‐specific effects is the main objective, particularly for rarely observed species, SSOMs are more robust to outliers across a range of community response scenarios. Researchers can use this information to inform study design, guide simulation studies and decide whether the higher precision of MSOMs outweighs risks of improperly estimated effects for some species.

Conservation biologists recognize that a system of isolated protected areas will be necessary but insufficient to meet biodiversity objectives. Current approaches to connecting core conservation areas through corridors consider optimal corridor placement based on a single optimization goal: commonly, maximizing the movement for a target species across a network of protected areas. We show that designing corridors for single species based on purely ecological criteria leads to extremely expensive linkages that are suboptimal for multispecies connectivity objectives. Similarly, acquiring the least-expensive linkages leads to ecologically poor solutions. We developed algorithms for optimizing corridors for multispecies use given a specific budget. We applied our approach in western Montana to demonstrate how the solutions may be used to evaluate trade-offs in connectivity for 2 species with different habitat requirements, different core areas, and different conservation values under different budgets. We evaluated corridors that were optimal for each species individually and for both species jointly. Incorporating a budget constraint and jointly optimizing for both species resulted in corridors that were close to the individual species movement-potential optima but with substantial cost savings. Our approach produced corridors that were within 14% and 11% of the best possible corridor connectivity for grizzly bears (Ursus arctos) and wolverines (Gulo gulo), respectively, and saved 75% of the cost. Similarly, joint optimization under a combined budget resulted in improved connectivity for both species relative to splitting the budget in 2 to optimize for each species individually. Our results demonstrate economies of scale and complementarities conservation planners can achieve by optimizing corridor designs for financial costs and for multiple species connectivity jointly. We believe that our approach will facilitate corridor conservation by reducing acquisition costs and by allowing derived corridors to more closely reflect conservation priorities. Los biólogos de la conservación reconocen que un sistema de áreas protegidas aisladas será necesario pero insuficiente para alcanzar los objetivos de la biodiversidad. Las estrategias actuales para conectar las áreas núcleos de conservación por medio de corredores consideran la ubicación óptima de estos con base en un solo objetivo de optimización: maximizar, comúnmente, el movimiento de una especie blanco a lo largo de una red de áreas protegidas. Mostramos que diseñar los corredores para una especie única con base solamente en un criterio ecológico lleva a enlazamientos extremadamente caros que son sub-óptimos para los objetivos de conectividad de especies múltiples. De manera similar, adquirir los enlazamientos menos caros lleva a soluciones ecológicamente pobres. Desarrollamos algoritmos para optimizarlos corredores para el uso de especies múltiples dado un presupuesto específico. Aplicamos nuestra estrategia en el oeste de Montana para demostrar cómo las soluciones pueden utilizarse para evaluar las compensaciones en la conectividad de dos especies con requerimientos de habitat diferentes, áreas nucleares diferentes y valores de conservación diferentes bajo presupuestos diferentes. Evaluamos los corredores que fueron óptimos para cada especie individualmente y para ambas especies en conjunto. Incorporar una restricción de presupuesto y optimizar en conjunto para ambas especies resultó en corredores que estuvieron próximos al potencial óptimo de movimiento de las especies individuales pero con ahorros sustanciales de gastos. Nuestra estrategia produjo corredores que estuvieron dentro del 14 % y el 11 % de la mejor conectividad posible entre corredores para los osos pardos (Ursus arctos) y los glotones (Gulo gulo), respectivamente, y ahorro el 75 % del costo. De igual manera, la optimización conjunta bajo un presupuesto combinado resultó en una conectividad mejorada para ambas especies en relación a la división del presupuesto en dos para optimizar para cada especie individualmente. Nuestros resultados demuestran la economía de escala y las complementariedades que los planeadores de la conservación pueden obtener al optimizar los diseños del corredor para financiar los costos y para los objetivos de conectividad de especies múltiples en conjunto. Creemos que nuestra estrategia puede facilitar la conservación de corredores al reducir los costos de adquisición y al permitir que los corredores derivados reflejen más cercanamente las prioridades de conservación.

Population size and landscape connectivity are key determinants of population viability, yet no methods exist for simultaneously estimating density and connectivity parameters. Recently developed spatial capture–recapture (SCR) models provide a framework for estimating density of animal populations but thus far have not been used to study connectivity. Rather, all applications of SCR models have used encounter probability models based on the Euclidean distance between traps and animal activity centers, which implies that home ranges are stationary, symmetric, and unaffected by landscape structure. In this paper we devise encounter probability models based on “ecological distance,” i.e., the least‐cost path between traps and activity centers, which is a function of both Euclidean distance and animal movement behavior in resistant landscapes. We integrate least‐cost path models into a likelihood‐based estimation scheme for spatial capture–recapture models in order to estimate population density and parameters of the least‐cost encounter probability model. Therefore, it is possible to make explicit inferences about animal density, distribution, and landscape connectivity as it relates to animal movement from standard capture–recapture data. Furthermore, a simulation study demonstrated that ignoring landscape connectivity can result in negatively biased density estimators under the naive SCR model.

A shifting climate poses threats to alpine‐adapted species including mountain goats. We used long‐term (12 years) citizen science monitoring data and Bayesian N‐mixture modeling to estimate population trends and drivers of population metrics among mountain goats in Glacier National Park (GNP). Median goats per site (n = 37 sites) declined by 45% (95% credible interval [CRI] = 32%, 57%) from 77.8 (95% CRI = 64.4, 95.1) in 2008 to 42.3 (95% CRI = 34.3, 52.2) in 2019, with consistent declines from 2008 until 2015, when the number of estimated goats stabilized. The decline exceeds IUCN criteria for classifying a population as vulnerable, >30% declines over only two generations. Across years, relatively few goats occupied northwestern GNP. Goat numbers declined the most at northeastern sites, trended toward decline in most southern sites, and increased at only two west‐central sites. The proportion of permanent snow and glaciers, the presence of natural mineral licks, and habituation strongly increased the initial abundance of goats in the area. Weather variables had the greatest influence on population growth rates, particularly precipitation between May 15 and June 15 of the previous summer, the neonatal period. Lower growth occurred with less snow water equivalent and lower mean winter temperature, early summer temperature, and early summer precipitation. Projected reductions of permanent snow, increasing spring and summer temperatures, and insufficient and variable spring precipitation raise concerns for the future of native goats in this region. Our analyses reveal ways to improve detection rates of goats during surveys, which is important for optimizing the precision of estimates and the power to detect future trends. Detection increased with goat habituation, retention of observers with experience, use of binoculars, and conducting surveys at lower temperatures and earlier dates. Improving detection will be particularly important given the lower number of goats currently observed in the park. Research to estimate park‐wide population size, evaluate genetic structure and diversity, assess changing habitat, human recreation levels and forage, and forward‐project climate effects on persistence will be crucial to understanding the context of these results and conserving this iconic, metapopulation at the southern edge of the distribution of native mountain goats.

Although shale drilling operations for oil and natural gas have increased greatly in the past decade, few studies directly quantify the impacts of shale development on plants and wildlife. We evaluate knowledge gaps related to shale development and prioritize research needs using a quantitative framework that includes spatial and temporal extent, mitigation difficulty, and current level of understanding. Identified threats to biota from shale development include: surface and groundwater contamination; diminished stream flow; stream siltation; habitat loss and fragmentation; localized air, noise, and light pollution; climate change; and cumulative impacts. We find the highest research priorities to be probabilistic threats (underground chemical migration; contaminant release during storage, during disposal, or from accidents; and cumulative impacts), the study of which will require major scientific coordination among researchers, industry, and government decision makers. Taken together, our research prioritization outlines a way forward to better understand how energy development affects the natural world.

Sociality directly influences mating success, survival rates, and disease, but ultimately likely evolved for its fitness benefits in a challenging environment. The tradeoffs between the costs and benefits of sociality can operate at multiple scales, resulting in different interpretations of animal behavior. We investigated the influence of intrinsic ( e.g. , relatedness, age) and extrinsic factors ( e.g. , land cover type, season) on direct contact (simultaneous GPS locations ≤ 25 m) rates of bighorn sheep ( Ovis canadensis ) at multiple scales near the Waterton-Glacier International Peace Park. During 2002–2012, male and female bighorn were equipped with GPS collars. Indirect contact (GPS locations ≤ 25 m regardless of time) networks identified two major breaks whereas direct contact networks identified an additional barrier in the population, all of which corresponded with prior disease exposure metrics. More direct contacts occurred between same-sex dyads than female-male dyads and between bighorn groups with overlapping summer home ranges. Direct contacts occurred most often during the winter-spring season when bighorn traveled at low speeds and when an adequate number of bighorn were collared in the area. Direct contact probabilities for all dyad types were inversely related to habitat quality, and differences in contact probability were driven by variables related to survival such as terrain ruggedness, distance to escape terrain, and canopy cover. We provide evidence that probabilities of association are higher when there is greater predation risk and that contact analysis provides valuable information for understanding fitness tradeoffs of sociality and disease transmission potential.