Protected areas slow declines unevenly across the tetrapod tree of life.

Protected areas (PAs) are the primary strategy for slowing terrestrial biodiversity loss. Although expansion of PA coverage is prioritized under the Convention on Biological Diversity, it remains unknown whether PAs mitigate declines across the tetrapod tree of life and to what extent land cover and climate change modify PA effectiveness1,2. Here we analysed rates of change in abundance of 2,239 terrestrial vertebrate populations across the globe. On average, vertebrate populations declined five times more slowly within PAs (-0.4% per year) than at similar sites lacking protection (-1.8% per year). The mitigating effects of PAs varied both within and across vertebrate classes, with amphibians and birds experiencing the greatest benefits. The benefits of PAs were lower for amphibians in areas with converted land cover and lower for reptiles in areas with rapid climate warming. By contrast, the mitigating impacts of PAs were consistently augmented by effective national governance. This study provides evidence for the effectiveness of PAs as a strategy for slowing tetrapod declines. However, optimizing the growing PA network requires targeted protection of sensitive clades and mitigation of threats beyond PA boundaries. Provided the conditions of targeted protection, adequate governance and well-managed landscapes are met, PAs can serve a critical role in safeguarding tetrapod biodiversity.

Predicting vulnerability of forest patches to invasion by non-native plants for landscape scale management.

As a leading cause of forest health degradation, non-native invasive plant species are a key focus for many forest management and conservation efforts. These efforts come at a high price for resource-limited agencies and organizations making cost-effectiveness an important objective of invasion response plans. In this paper, we present an approach to guide the prioritization of locations for invasion management using species distribution models that account for the non-equilibrium of invasive species distributions and use readily available land use data as the primary explanatory variables. This approach takes advantage of the relatively high spatial resolution, as well as the broad, continuous geographic coverage, of land use data to provide results at a landscape scale relevant to practitioners responsible for invasive species management. In our example from northern Virginia, we simultaneously modeled a suite of invasive plant species to identify common indicators of invasion. We found that the proportions of surrounding non-forested land use types (grasses, crops, and development) were the most common and strongest indicators of invasion risk. These outcomes can guide managers of large protected areas to focus on major divides between forest and non-forest land over linear disturbances. We also found useful species-specific traits that can inform specific management actions. Additionally, we demonstrate through a case study how organizations that manage multiple smaller properties can take advantage of the projected distribution maps when considering acquiring or administering properties.

Is the future female for turtles? Climate change and wetland configuration predict sex ratios of a freshwater species.

Climate change and land-use change are leading drivers of biodiversity decline, affecting demographic parameters that are important for population persistence. For example, scientists have speculated for decades that climate change may skew adult sex ratios in taxa that express temperature-dependent sex determination (TSD), but limited evidence exists that this phenomenon is occurring in natural settings. For species that are vulnerable to anthropogenic land-use practices, differential mortality among sexes may also skew sex ratios. We sampled the spotted turtle (Clemmys guttata), a freshwater species with TSD, across a large portion of its geographic range (Florida to Maine), to assess the environmental factors influencing adult sex ratios. We present evidence that suggests recent climate change has potentially skewed the adult sex ratio of spotted turtles, with samples following a pattern of increased proportions of females concomitant with warming trends, but only within the warmer areas sampled. At intermediate temperatures, there was no relationship with climate, while in the cooler areas we found the opposite pattern, with samples becoming more male biased with increasing temperatures. These patterns might be explained in part by variation in relative adaptive capacity via phenotypic plasticity in nest site selection. Our findings also suggest that spotted turtles have a context-dependent and multi-scale relationship with land use. We observed a negative relationship between male proportion and the amount of crop cover (within 300 m) when wetlands were less spatially aggregated. However, when wetlands were aggregated, sex ratios remained consistent. This pattern may reflect sex-specific patterns in movement that render males more vulnerable to mortality from agricultural machinery and other threats. Our findings highlight the complexity of species' responses to both climate change and land use, and emphasize the role that landscape structure can play in shaping wildlife population demographics.

Evaluating the effect of expert elicitation techniques on population status assessment in the face of large uncertainty.

Population projection models are important tools for conservation and management. They are often used for population status assessments, for threat analyses, and to predict the consequences of conservation actions. Although conservation decisions should be informed by science, critical decisions are often made with very little information to support decision-making. Conversely, postponing decisions until better information is available may reduce the benefit of a conservation decision. When empirical data are limited or lacking, expert elicitation can be used to supplement existing data and inform model parameter estimates. The use of rigorous techniques for expert elicitation that account for uncertainty can improve the quality of the expert elicited values and therefore the accuracy of the projection models. One recurring challenge for summarizing expert elicited values is how to aggregate them. Here, we illustrate a process for population status assessment using a combination of expert elicitation and data from the ecological literature. We discuss the importance of considering various aggregation techniques, and illustrate this process using matrix population models for the wood turtle (Glyptemys insculpta) to assist U.S. Fish and Wildlife Service decision-makers with their Species Status Assessment. We compare estimates of population growth using data from the ecological literature and four alternative aggregation techniques for the expert-elicited values. The estimate of population growth rate based on estimates from the literature (λmean = 0.952, 95% CI: 0.87-1.01) could not be used to unequivocally reject the hypotheses of a rapidly declining population nor the hypothesis of a stable, or even slightly growing population, whereas our results for the expert-elicited estimates supported the hypothesis that the wood turtle population will decline over time. Our results showed that the aggregation techniques used had an impact on model estimates, suggesting that the choice of techniques should be carefully considered. We discuss the benefits and limitations associated with each method and their relevance to the population status assessment. We note a difference in the temporal scope or inference between the literature-based estimates that provided insights about historical changes, whereas the expert-based estimates were forward looking. Therefore, conducting an expert-elicitation in addition to using parameter estimates from the literature improved our understanding of our species of interest.

Scale-insensitive estimation of speed and distance traveled from animal tracking data.

BACKGROUND: Speed and distance traveled provide quantifiable links between behavior and energetics, and are among the metrics most routinely estimated from animal tracking data. Researchers typically sum over the straight-line displacements (SLDs) between sampled locations to quantify distance traveled, while speed is estimated by dividing these displacements by time. Problematically, this approach is highly sensitive to the measurement scale, with biases subject to the sampling frequency, the tortuosity of the animal's movement, and the amount of measurement error. Compounding the issue of scale-sensitivity, SLD estimates do not come equipped with confidence intervals to quantify their uncertainty. METHODS: To overcome the limitations of SLD estimation, we outline a continuous-time speed and distance (CTSD) estimation method. An inherent property of working in continuous-time is the ability to separate the underlying continuous-time movement process from the discrete-time sampling process, making these models less sensitive to the sampling schedule when estimating parameters. The first step of CTSD is to estimate the device's error parameters to calibrate the measurement error. Once the errors have been calibrated, model selection techniques are employed to identify the best fit continuous-time movement model for the data. A simulation-based approach is then employed to sample from the distribution of trajectories conditional on the data, from which the mean speed estimate and its confidence intervals can be extracted. RESULTS: Using simulated data, we demonstrate how CTSD provides accurate, scale-insensitive estimates with reliable confidence intervals. When applied to empirical GPS data, we found that SLD estimates varied substantially with sampling frequency, whereas CTSD provided relatively consistent estimates, with often dramatic improvements over SLD. CONCLUSIONS: The methods described in this study allow for the computationally efficient, scale-insensitive estimation of speed and distance traveled, without biases due to the sampling frequency, the tortuosity of the animal's movement, or the amount of measurement error. In addition to being robust to the sampling schedule, the point estimates come equipped with confidence intervals, permitting formal statistical inference. All the methods developed in this study are now freely available in the ctmmR package or the ctmmweb point-and-click web based graphical user interface.

Concurrent visual encounter sampling validates eDNA selectivity and sensitivity for the endangered wood turtle (Glyptemys insculpta).

Environmental DNA (eDNA) has been used to record the presence of many different organisms in several different aquatic and terrestrial environments. Although eDNA has been demonstrated as a useful tool for the detection of invasive and/or cryptic and declining species, this approach is subject to the same considerations that limit the interpretation of results from traditional survey techniques (e.g. imperfect detection). The wood turtle is a cryptic semi-aquatic species that is declining across its range and, like so many chelonian species, is in-need of a rapid and effective method for monitoring distribution and abundance. To meet this need, we used an eDNA approach to sample for wood turtle presence in northern Virginia streams. At the same time, we used repeat visual encounter surveys in an occupancy-modelling framework to validate our eDNA results and reveal the relationship of detection and occupancy for both methods. We sampled 37 stream reaches of varying size within and beyond the known distribution of the wood turtle across northern Virginia. Wood turtle occupancy probability was 0.54 (0.31, 0.76) and while detection probability for wood turtle occupancy was high (0.88; 0.58, 0.98), our detection of turtle abundance was markedly lower (0.28; 0.21, 0.37). We detected eDNA at 76% of sites confirmed occupied by VES and at an additional three sites where turtles were not detected but were known to occur. Environmental DNA occupancy probability was 0.55 (0.29, 0.78); directly comparable to the VES occupancy estimate. Higher probabilities of detecting wood turtle eDNA were associated with higher turtle densities, an increasing number of days since the last rainfall, lower water temperatures, and lower relative discharges. Our results suggest that eDNA technology holds promise for sampling aquatic chelonians in some systems, even when discharge is high and biomass is relatively low, when the approach is validated and sampling error is quantified.