TerrAdapt

ABSTRACT

Local extirpations influence species’ range contractions and are often precursors of range‐wide extinction. Understanding extinction dynamics is important for devising effective management strategies to protect threatened and endangered species. The greater sage‐grouse (
Centrocercus urophasianus
) is an example of a species undergoing range contraction, and has been extirpated from nearly half its historically occupied habitat. We used species distribution modeling to quantify environmental variables constraining a threatened sage‐grouse population inhabiting an agricultural landscape in Washington, USA. Fields planted to perennial vegetation as part of the Conservation Reserve Program (CRP) were important in providing year‐round habitat for sage‐grouse but only when intermixed with native sagebrush‐steppe vegetation. Without the CRP, we estimate 66% of sage‐grouse habitat in the study area would become unsuitable. Conversely, if CRP allotments were concentrated near occupied native sagebrush‐steppe, we estimate the area of sage‐grouse habitat could be increased by up to 63%. In addition to the area of native sagebrush‐steppe and CRP lands, we also found that climate variability, the patch configuration of sagebrush‐steppe, and proximity to major roads and transmission lines constrain the distribution of occupied habitat within the study area. Our study demonstrates how conservation programs such as CRP may be used as a management tool to reduce the risk of extirpation in agricultural areas, and to facilitate species range shifts in response to climatic changes in the sagebrush biome. © 2017 The Wildlife Society.

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Greater sage‐grouse habitat use in Washington, USA (1992–2014) is influenced by the local amount and configuration of native sagebrush‐steppe and Conservation Reserve Program (CRP) fields, proximity to transmission lines and roads, and climate variability. Our study suggests management targets based on these variables would support sage‐grouse occupancy and highlights a role for CRP lands in augmenting native sagebrush‐steppe to add additional habitat in agricultural landscapes.

Abstract
A major aim of landscape genetics is to understand how landscapes resist gene flow and thereby influence population genetic structure. An empirical understanding of this process provides a wealth of information that can be used to guide conservation and management of species in fragmented landscapes and also to predict how landscape change may affect population viability. Statistical approaches to infer the true model among competing alternatives are based on the strength of the relationship between pairwise genetic distances and landscape distances among sampled individuals in a population. A variety of methods have been devised to quantify individual genetic distances, but no study has yet compared their relative performance when used for model selection in landscape genetics. In this study, we used population genetic simulations to assess the accuracy of 16 individual‐based genetic distance metrics under varying sample sizes and degree of population genetic structure. We found most metrics performed well when sample size and genetic structure was high. However, it was much more challenging to infer the true model when sample size and genetic structure was low. Under these conditions, we found genetic distance metrics based on principal components analysis were the most accurate (although several other metrics performed similarly), but only when they were derived from multiple principal components axes (the optimal number varied depending on the degree of population genetic structure). Our results provide guidance for which genetic distance metrics maximize model selection accuracy and thereby better inform conservation and management decisions based upon landscape genetic analysis.

Abstract
Anthropogenic migration barriers fragment many populations and limit the ability of species to respond to climate‐induced biome shifts. Conservation actions designed to conserve habitat connectivity and mitigate barriers are needed to unite fragmented populations into larger, more viable metapopulations, and to allow species to track their climate envelope over time. Landscape genetic analysis provides an empirical means to infer landscape factors influencing gene flow and thereby inform such conservation actions. However, there are currently many methods available for model selection in landscape genetics, and considerable uncertainty as to which provide the greatest accuracy in identifying the true landscape model influencing gene flow among competing alternative hypotheses. In this study, we used population genetic simulations to evaluate the performance of seven regression‐based model selection methods on a broad array of landscapes that varied by the number and type of variables contributing to resistance, the magnitude and cohesion of resistance, as well as the functional relationship between variables and resistance. We also assessed the effect of transformations designed to linearize the relationship between genetic and landscape distances. We found that linear mixed effects models had the highest accuracy in every way we evaluated model performance; however, other methods also performed well in many circumstances, particularly when landscape resistance was high and the correlation among competing hypotheses was limited. Our results provide guidance for which regression‐based model selection methods provide the most accurate inferences in landscape genetic analysis and thereby best inform connectivity conservation actions.

Abstract
An assumption of correlative landscape genetic methods is that genetic differentiation at neutral markers arises solely from the degree to which the intervening landscape between individuals or populations resists gene flow. However, this assumption is violated when gene flow occurs into the sampled population from an unsampled, differentiated deme. This may happen when sampling within only a portion of a population's extent or when closely related species hybridize with the sampled population. In both cases, violation of the modelling assumptions has the potential to reduce landscape genetic model selection accuracy and result in poor inferences. We used individual‐based population genetic simulations in complex landscapes within a model selection framework to explore the potential confounding effect of gene flow from unsampled demes. We hypothesized that as gene flow from outside the sampling extent increased, model selection accuracy would decrease due to the formation of a hybrid zone where allele frequencies were perturbed in a way that was not correlated with effective distances between sampled individuals. Surprisingly, we found this expectation was unfounded, because the reduced accuracy due to admixture was counteracted by an increase in allelic diversity as alleles spread from the unsampled deme into the sampled population. These new alleles increased the power to detect landscape genetic relationships and even slightly improving model selection accuracy overall. This is a reassuring result, suggesting that sampling the full extent of a population or related species that may hybridize may be unnecessary, as long as other well‐established sampling requirements are met.

Abstract

Context

Understanding habitat dynamics is essential for effective conservation as landscapes rapidly change. In a companion paper in this issue, Shirk et al. (2023) introduced an automated habitat monitoring system using Google Earth Engine and applied this framework to develop a dynamic model of Mexican spotted owl (
Strix occidentalis lucida
) habitat across the southwestern US from 1986 to 2020.

Objectives
We explored the application of this dynamic model of Mexican spotted owl habitat in the context of the species’ ecology.

Methods
We evaluated environmental correlates of Mexican spotted owl habitat, assessed potential spatial non-stationarity in habitat selection, estimated long-term trends in habitat by quantifying changes in habitat amount and quality between 1986 and 2020, and evaluated the extent to which habitat changes over the past 35 years have been driven by wildfire.

Results
Topography and climate appeared to outweigh reflectance-based (vegetation) metrics in describing Mexican spotted owl habitat and habitat selection was non-stationary across modeling sub-regions. Total habitat area for Mexican spotted owls declined by ~ 21% since 1986 (0.6% annually), but trends varied spatially and some even reversed over the past decade. Wildfire was responsible for between 8 and 35% of total habitat loss, depending on the sub-region considered.

Conclusions
The automated habitat monitoring system allowed trend estimation and accurate assessment of current habitat status for Mexican spotted owls; maps were accurate, spatially detailed, and current. The ability to continually produce accurate maps for large land areas for threatened species such as the Mexican spotted owl facilitates science-based land management on public lands in the southwestern US.

Abstract
As the impacts of anthropogenic climate change increase, conservation of climate‐change refugia has become a key strategy for effective environmental stewardship. Over the last 5 years, the field of climate‐change refugia conservation has made exciting advances, shifting from concepts and theory to refugia mapping and implementation. However, few studies have advanced to action on the ground; while 84% of studies identified and mapped refugia, only 4% involved implementing management action. Moreover, taxonomic and geographic gaps remain, with most studies focused on terrestrial plants and vertebrates in Europe and North America. Here, we outline impediments to implementation following the steps of the Climate‐Change Refugia Conservation Cycle. Based on a systematic literature review, we elucidate advances and obstacles with examples from a diversity of systems and sectors from across the world and highlight emerging work bridging the gap between research and implementation.

Abstract
Climate change is reshaping landscapes in ways that challenge conventional approaches to conservation and resource planning. The concept of climate‐change refugia—areas with the potential to buffer species and ecosystems from the effects of climate change—offers a valuable lens for identifying strategic opportunities for long‐term stewardship. Building on this foundation, we present a flexible, climate‐informed approach to landscape planning that integrates climate‐change exposure and refugia information into a five‐step process: (1) define core ecological, cultural, and land resource values and identify those most at risk; (2) assess landscape capacity as a function of climate‐change exposure and conservation capacity (i.e., landscape condition); (3) develop place‐based strategies and identify relevant spatial data products; (4) incorporate macrorefugia, microrefugia, and corridors to align land‐use designations with strategies; and (5) implement, monitor, and adaptively refine refugia‐based planning over time. Recognizing variation in planning needs and contexts, our guidance supports the practical use of spatial refugia metrics to inform land‐use, conservation, and resource management decisions.

Abstract
In an era of environmental instability, climate‐informed land‐use planning allows preparation for a more resilient future. By identifying places with high climate‐change refugia potential and climate connectivity, management and stewardship plans can be adapted over time to achieve biodiversity goals. The objective of the Climate‐informed Conservation Planning project is to provide an efficient pathway for collaborative planning between Indigenous and provincial governments to develop a long‐term management approach to maintain environmental and cultural values while reducing the risks from climate change. Working directly with the shíshálh‐BC Modernized Land Use Planning table on the South Coast of British Columbia to support climate‐resilient planning, this process identified areas projected to have refugia potential, to maximize habitat connectivity, to monitor ecosystem resilience variables, and to realize planning objectives within dynamic adaptive planning cycles. Key activities include: (a) introducing the climate‐change refugia concept and other knowledge translation activities, (b) identifying and evaluating spatial priorities for conservation management with higher potential for climate‐change refugia and connectivity, (c) customizing priority scenarios with additional data and local knowledge to highlight where the best conservation investments might contribute to local and provincial biodiversity goals, and (d) suggestions for implementing the plan dynamically and proactively to mitigate current and emerging environmental risks with monitoring, reporting, and proactive adaptation planning cycles.

ABSTRACT

Populations of species located at southern range edges may be particularly vulnerable to the effects of climate change as warming temperatures and subsequent changes to ecosystems exceed species‐specific tolerances. One such species is Canada lynx (
Lynx canadensis
), a cold‐adapted mesocarnivore that maintains a large core population in Alaska, USA, and Canada but exists within several peripheral populations in the contiguous United States. Increases in temperature, declines in snow pack, and climate‐influenced increases in fire frequency and intensity, could negatively affect lynx populations, threatening their long‐term persistence in the continental United States. Despite these threats, our understanding of broad‐scale effects on lynx occupancy and the extent of current lynx distribution in many of these peripheral populations is minimal. We conducted an occupancy survey of lynx in Washington, USA, using a spatially extensive camera‐trapping array covering 7,000 km
2
of potential lynx habitat. We used the resulting database of detection data to develop single‐season occupancy models to examine the abiotic and biotic effects on current lynx occupancy and predict future lynx distribution based on climate change forecasts. Our results show lynx occupancy across the Washington landscape is restricted and dictated largely by abiotic factors, disturbance regimes, and distance from source populations in Canada. Predictions of future distribution suggest lynx will be increasingly challenged by climatic changes, particularly at the southern and lower elevation portions of their range in Washington. Our results paint an alarming picture for lynx persistence in Washington that is relevant to current deliberations regarding lynx delisting from the Endangered Species Act. Our simple camera design was a highly effective method for surveying lynx across broad spatial scales, and could be a key monitoring tool for lynx that is easy to implement by researchers and government agencies. © 2020 The Wildlife Society.

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Lynx occupancy across Washington state is highly restricted and dictated largely by abiotic factors, disturbance regimes, and distance from source populations in Canada with future predictions demonstrating a substantial potential northward retraction of lynx range in Washington by 2100. Understanding current occupancy patterns and factors influencing occupancy in Washington is particularly relevant in the broader context of ongoing discussions to remove lynx from listing in the Endangered Species Act.

Abstracts

Aim
The scales of space and time over which biotic interactions influence distribution patterns remain an area of debate. Biotic interactions may be particularly influential in the ecology of mammalian carnivores, which engage in strong predator–prey and competitive interactions. Regional, multi‐scale data on distribution patterns of interacting carnivore species are key to informing our understanding of this issue.

Location
Washington State, USA.

Methods
Using a spatially extensive camera‐trapping array, we examined the factors influencing distribution patterns of seven carnivore species at multiple spatial and temporal scales. We used single‐species occupancy models to assess the relative influence of abiotic and biotic covariates on distribution of individual carnivore species, and two‐species occupancy models to assess how dominant carnivores influence subordinate carnivore occupancy and detection.

Results
Carnivore occupancy patterns responded more strongly to abiotic than biotic covariates at both spatial grains and extents of analysis. The influence of biotic variables decreased as the grain of analysis increased, while constraining our study area extent substantially decreased the explanatory power of abiotic variables. Interspecific interactions among carnivores influenced occupancy and detection across spatial scales. However, there was little evidence that interactions were more pronounced at finer temporal scales.

Main Conclusions
Results demonstrate that at broad spatial extents, species distributions are largely dictated by abiotic factors, particularly climate. Although biotic factors related to habitat and prey were important factors for some species, they generally declined in importance as grain size of analysis increased, suggesting these interactions play out at finer resolutions. However, competitive and mutualistic interactions exerted an independent influence on distribution over broad extents and coarse grains of analysis, suggesting that failure to account for interactions may limit our ability to accurately model distributions of species and their responses to future large‐scale disturbances.

The “Global Safety Net” shows where nature could be conserved and connected to reverse biodiversity loss and stabilize climate.
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Global strategies to halt the dual crises of biodiversity loss and climate change are often formulated separately, even though they are interdependent and risk failure if pursued in isolation. The Global Safety Net maps how expanded nature conservation addresses both overarching threats. We identify 50% of the terrestrial realm that, if conserved, would reverse further biodiversity loss, prevent CO
2
emissions from land conversion, and enhance natural carbon removal. This framework shows that, beyond the 15.1% land area currently protected, 35.3% of land area is needed to conserve additional sites of particular importance for biodiversity and stabilize the climate. Fifty ecoregions and 20 countries contribute disproportionately to proposed targets. Indigenous lands overlap extensively with the Global Safety Net. Conserving the Global Safety Net could support public health by reducing the potential for zoonotic diseases like COVID-19 from emerging in the future.