10Spatial capture-recapture (SCR) has emerged as the industry standard for 11 analyzing observational data to estimate population size by leveraging information from 12 spatial locations of repeat encounters of individuals. The resulting precision of density 13 estimates depends fundamentally on the number and spatial configuration of traps.14 Despite this knowledge, existing sampling design recommendations are heuristic and 15 their performance remains untested for most practical applications -i.e., 16spatially-structured and logistically challenging landscapes. To address this issue, we 17 propose a genetic algorithm that minimizes any sensible, criteria-based objective 18 function to produce near-optimal sampling designs. To motivate the idea of optimality, 19 we compare the performance of designs optimized using two model-based criteria 20 related to the probability of capture. We use simulation to show that these designs 21 out-perform those based on existing recommendations in terms of bias, precision, and 22 accuracy in the estimation of population size. Our approach allows conservation 23 practitioners and researchers to generate customized sampling designs that can improve 24 monitoring of wildlife populations. 25Keywords-SCR, spatial capture-recapture, spatially-explicit capture-recapture, 26 camera traps, density, optimal design, sampling design, spatial sampling, trap spacing 27 29 (Williams et al., 2002) which has driven the development of data collection and estimation 30 methods, especially those that can account for imperfect detection. Capture-recapture (CR), 31 and more recently, spatial capture-recapture (SCR: Royle et al., 2014) methods were 32 developed specifically for this purpose and are now routinely applied in ecological research. 33 Concurrently, SCR methods estimate detection, space use, and density by analyzing 34 2 individual encounter histories while explicitly incorporating auxiliary information from the 35 spatial organization of encounters (Efford, 2004; Royle et al., 2014). Despite widespread 36 adoption and rapid method development, recommendations about spatial sampling design 37 have received relatively little attention and are arguably heuristic. 38 The effects of sampling design have been investigated for both CR (Dillon and Kelly 39 2007; Bondrup-Nielsen 1983; Gardner et al. 2010) and SCR methods (discussed in the next 40 paragraph). While CR methods aim to balance the number of captures and the number of 41 recaptures, SCR requires a third consideration, the number of spatial recaptures, i.e., the 42 number of times individuals are observed at multiple locations. The ability to reliably 43 estimate these quantities is directly related to the quality of the data collected: the number of 44 captured individuals n is the sample size; the number of recaptures is directly related to the 45 baseline detection probability, g 0 ; and the number and spatial distribution of recaptures are 46 directly related to the spatial scale parameter, σ. Therefore, improving sampling design...

Spatial capture–recapture (SCR) has emerged as the industry standard for estimating population density by leveraging information from spatial locations of repeat encounters of individuals. The precision of density estimates depends fundamentally on the number and spatial configuration of traps. Despite this knowledge, existing sampling design recommendations are heuristic and their performance remains untested for most practical applications. To address this issue, we propose a genetic algorithm that minimizes any sensible, criteria‐based objective function to produce near‐optimal sampling designs. To motivate the idea of optimality, we compare the performance of designs optimized using three model‐based criteria related to the probability of capture. We use simulation to show that these designs outperform those based on existing recommendations in terms of bias, precision, and accuracy in the estimation of population size. Our approach, available as a function in the R package oSCR, allows conservation practitioners and researchers to generate customized and improved sampling designs for wildlife monitoring.

Understanding how broad-scale patterns in animal populations emerge from individual-level processes is an enduring challenge in ecology that requires investigation at multiple scales and perspectives. Complementary to this need for diverse approaches is the recent focus on integrated modeling in statistical ecology. Population-level processes represent the core of spatial capture-recapture (SCR), with many methodological extensions that have been motivated by standing ecological theory and data-integration opportunities. The extent to which these recent advances offer inferential improvements can be limited by the data requirements for quantifying individual-level processes. This is especially true for SCR models that use non-Euclidean distance to relax the restrictive assumption that individual space use is stationary and symmetrical to make inferences about landscape connectivity. To meet the challenges of scale and data quality, we propose integrating an explicit movement model with non-Euclidean SCR for joint estimation of a shared cost parameter between individual and population processes. Here, we define a movement kernel for step selection that uses "ecological distance" instead of Euclidean distance to quantify availability for each movement step in terms of landscape cost. We compare performance of our integrated model to that of existing SCR models using realistic animal movement simulations and data collected on black bears. We demonstrate that an integrated approach offers improvements both in terms of bias and precision in estimating the shared cost parameter over models fit to spatial encounters alone. Simulations suggest these gains were only realized when step lengths were small relative to home range size, and estimates of density were insensitive to whether or not an integrated approach was used. By combining the fine spatiotemporal scale of individual movement processes with the estimation of population density in SCR, integrated approaches such as the one we develop here have the potential to unify the fields of movement, population, and landscape ecology and improve our understanding of landscape connectivity.

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Ever since 1994, when the bacterial pathogen Mycoplasma gallisepticum jumped from poultry to wild birds, it has been assumed that the primary host species of this pathogen in wild North American birds was the house finch (Haemorhous mexicanus), in which disease prevalence was higher than in any other bird species. Here we tested two hypotheses to explain a recent increase in disease prevalence in purple finches (Haemorhous purpureus) around Ithaca, New York. Hypothesis 1 is that, as M. gallisepticum evolved and became more virulent, it has also become better adapted to other finches. If this is correct, early isolates of M. gallisepticum should cause less-severe eye lesions in purple finches than in house finches, while more-recent isolates should cause eye lesions of similar severity in the two species. Hypothesis 2 is that, as house finch abundance declined following the M. gallisepticum epidemic, purple finches around Ithaca increased in abundance relative to house finches and purple finches are thus more frequently exposed to M. gallisepticum-infected house finches. This would then lead to an increase in M. gallisepticum prevalence in purple finches. Following an experimental infection with an early and a more-recent M. gallisepticum isolate, eye lesions in purple finches were more severe than in house finches. This did not a support Hypothesis 1; similarly, an analysis of Project Feeder Watch data collected around Ithaca did not show differences in changes in purple and house finches' abundance since 2006, a result which does not support Hypothesis 2. We conclude that purple finch populations will, unlike those of house finches, not suffer a severe decline because of a M. gallisepticum epidemic.RESUMEN. ¿Son los pinzones purpúreos (Haemorhous purpureus) los próximos huéspedes de una epidemia de conjuntivitis por micoplasma?Desde el año 1994, cuando el patógeno bacteriano Mycoplasma gallisepticum saltó de las aves comerciales a las aves silvestres, se ha supuesto que la principal especie huésped de este patógeno en las aves silvestres de América del Norte era el pinzón mexicano (Haemorhous mexicanus), en el que la prevalencia de la enfermedad era mayor que en cualquier otra especie aviar. En este estudio se analizaron dos hipótesis para explicar un aumento reciente en la prevalencia de la enfermedad en los pinzones purpúreos (Haemorhous purpureus) alrededor de Ithaca, en Nueva York. La hipótesis 1 es que, a medida que M. gallisepticum evolucionó y se volvió ma ´s virulento, también se adaptó mejor a otros pinzones. Si esto es correcto, los aislamientos tempranos de M. gallisepticum deberían causar lesiones oculares menos graves en los pinzones purpúreos que en los pinzones mexicanos, mientras que los aislamientos ma ´s recientes deberían causar lesiones oculares de gravedad similar en las dos especies. La hipótesis 2 es que, a medida que la abundancia de pinzones mexicanos disminuyó después de la epidemia de M. gallisepticum, los pinzones purpúreos alrededor de Ithaca aumentaron en abundancia en relación con ...