Metapopulation ecology and landscape ecology aim to understand how spatial structure influences ecological processes, yet these disciplines address the problem using fundamentally different modeling approaches. Metapopulation models describe how the spatial distribution of patches affects colonization and extinction, but often do not account for the heterogeneity in the landscape between patches. Models in landscape ecology use detailed descriptions of landscape structure, but often without considering colonization and extinction dynamics. We present a novel spatially explicit modeling framework for narrowing the divide between these disciplines to advance understanding of the effects of landscape structure on metapopulation dynamics. Unlike previous efforts, this framework allows for statistical inference on landscape resistance to colonization using empirical data. We demonstrate the approach using 11 yr of data on a threatened amphibian in a desert ecosystem. Occupancy data for Lithobates chiricahuensis (Chiricahua leopard frog) were collected on the Buenos Aires National Wildlife Refuge (BANWR), Arizona, USA from 2007 to 2017 following a reintroduction in 2003. Results indicated that colonization dynamics were influenced by both patch characteristics and landscape structure. Landscape resistance increased with increasing elevation and distance to the nearest streambed. Colonization rate was also influenced by patch quality, with semi-permanent and permanent ponds contributing substantially more to the colonization of neighboring ponds relative to intermittent ponds. Ponds that only hold water intermittently also had the highest extinction rate. Our modeling framework can be widely applied to understand metapopulation dynamics in complex landscapes, particularly in systems in which the environment between habitat patches influences the colonization process.

Summary Plants interact simultaneously with both mutualists and antagonists. While webs of plant–animal interactions in natural systems can be highly complex, most interactions can be simplified into those that are either direct (mediated through pairwise interactions) or indirect (mediated through third‐party species). Mechanistic studies of the direct and indirect pathways by which foliar herbivores affect plants have been well explored; however, mechanistic explorations of how floral herbivores, such as nectar robbers, affect total plant fitness via direct vs. indirect pathways have received less attention. The goal of this study was to assess the importance of direct vs. pollinator‐mediated indirect effects of a floral antagonist on female and male components of plant fitness. We focused on the hummingbird‐pollinated plant scarlet gilia, Ipomopsis aggregata, which is nectar‐robbed by the bumblebee Bombus occidentalis. Prior studies have found evidence for pollinator‐mediated indirect effects of robbing on female and male components of I. aggregata fitness, but the mechanisms by which these indirect effects occur, and experimental evidence supporting or refuting direct effects of robbing, have been lacking. We found no evidence for direct effects of robbing on plant fitness. Robbers did not act as pollinators of I. aggregata nor did they directly affect seed production by making nectar‐robber holes or removing nectar in hand‐pollinated flowers. Moreover, robbing had no direct effect on pollen production per flower or the ability of pollen from robbed flowers to sire seeds in hand pollinations. However, nectar robbing had indirect effects on plant reproduction mediated through per‐visit pollinator effectiveness at depositing pollen in robbed vs. unrobbed flowers. A simple model of a plant‐robber‐pollinator system suggested that robbing effects in general may occur through more indirect mechanisms when nectar removal by robbers is high relative to nectar replenishment, and that compensation for robbing is then more profitable through the production of additional flowers. Synthesis. Our results highlight the importance of indirect effects in mediating the fitness consequences of species interactions.

Reliable methods for monitoring wildlife populations are paramount to effective conservation and management. There are a variety of available techniques that vary in cost and feasibility. We field‐tested a commercially available acoustic recording device (ARD) in July and August of 2018 with the goal of standardizing the process of surveying northern bobwhite (Colinus virginianus) populations using acoustic data. We projected bobwhite covey calls from programmable speakers, and analyzed recordings manually and with automatic recognition software. We manually detected 48% of projected covey calls with the furthest detection at 241 m. We developed an automatic classifier using Kaleidoscope Pro (Wildlife Acoustics Inc.), which detected 31% of the manually detected covey calls. The automatic classifier was ineffective, so we used manual analysis to acquire measurements for call strength and background noise at each visible covey call spectrogram signature. Detection probability declined as distance from the ARD increased and background noise increased. However, in our study system, there was no effect of vegetation structure on detection probability. Our results provide a blueprint for evaluating ARDs for application to wildlife monitoring. We believe ARDs can be used to evaluate northern bobwhite occupancy at fine scales and may potentially be useful in estimating autumn densities for setting harvest regulations. We encourage the evaluation of other software recognition programs and the relationship between covey call detection and landscape structure. © 2020 The Wildlife Society.

Context Throughout the world, declines in large mammalian carnivores have led to the release of smaller meso-mammalian predators. Coyotes (Canis latrans) have increased in abundance, distribution and ecological influence following the extirpation of apex predators in North America. Coyotes have had substantial influence on many ecosystems in recently colonised portions of their range, but those influences can vary across land cover types. Thus, understanding the relationship between coyote abundance and land cover may enhance our ability to predict spatial variation in the ecological effects of coyotes. Aims Our objective was to examine the influence of landscape attributes on eastern coyote abundance to ultimately facilitate predictions of spatial variation in the effects of coyotes on prey populations, ecological communities and human interests. Methods We collected count data from repeated visits to 24 sites by eliciting howl responses from coyotes. We fit abundance models to howl-response data to examine the effects of landscape composition and configuration on coyote abundance in a mixed forest/agricultural ecosystem in south-western Georgia, USA. Key results Our investigation revealed that coyote abundance was positively associated with grasslands that were predominantly used for livestock production, and negatively associated with patch diversity. Conclusions Our results supported the prediction that coyotes would be positively associated with open habitats and that they are well adapted for areas structurally similar to the plains of central North America, where the species originated. In addition, these results suggest that aspects of fragmentation, such as patch diversity, can negatively affect coyote abundance. Our results highlight the importance of patch type and landscape juxtaposition on the abundance of coyotes in complex heterogeneous landscapes. Implications Our results further our understanding of the spatial variation in coyote abundances across a recently colonised portion of the species range. Combining howl-response surveys with abundance modelling is a promising approach for studying the associations between population dynamics of vocal canids and landscape structure over large spatial scales.

Continual population declines in northern bobwhites (Colinus virginianus) have prompted the use of population restoration techniques in conjunction with habitat management to restore their populations. We tested the site familiarity hypothesis to determine if translocation to new environments affected offspring survival and growth rates of bobwhites. We used bobwhites from north Florida and translocated them to a study site in Brunswick County, North Carolina, USA, and monitored birds during April−October 2016 and April−October 2017. We used the corral capture method and modified‐suture technique to capture and radio‐tag chicks to evaluate offspring growth and survival rates of resident and translocated bobwhites. Offspring survival varied by year and age. We did not find any difference in offspring survival rates of resident and translocated individuals, lending no support to the site familiarity hypothesis with regards to survival. Offspring of resident bobwhites did not grow at a faster rate than offspring of translocated bobwhites, indicating a lack of support for the site familiarity hypothesis in terms of physiological development. Survival, however, is a more important metric for determining post‐translocation population dynamics, and our results indicated that translocated bobwhites can reproduce and raise offspring similar to resident counterparts, but both had low survival. © 2019 The Wildlife Society.

Population size estimates are given both on the "Summary" tab and the "Data table and detailed info" tab of the factsheet for each species at http://datazone.birdlife.org/species/search. They are also available through the IUCN Red List API at https://apiv3. iucnredlist.org/ and the IUCN Red List Advanced Search at https://www.iucnredlist.org/search.

Passive acoustic monitoring using Autonomous Recording Units (ARUs) is becoming a significant research tool for collecting large amounts of ecological data. Northern bobwhite Colinus virginianus is an economically important game bird whose declining populations are of conservation concern, so efforts to monitor bobwhite abundance using ARUs are being intensified. Yet, manual processing of ARU data is time consuming and often expensive, so developing automatic call detection methods is a key step in acoustic monitoring. We present here the first single species convolutional neural network (CNN) developed purely for automatic bobwhite covey call identification and classification. We demonstrate the value of meaningful data augmentation by including nontarget calls and background noise into our training dataset, as well as evaluating alternative CNN score thresholds and model extrapolation performance. We trained our CNN on 6,682 manually labeled covey calls across three groups of sites within the southeastern USA. Precision and AUC from both CNN classification and individual call detection was high (0.80-0.99), and our model showed strong extrapolation ability across site groups. However, extrapolation performance significantly decreased for sites that were more dissimilar to the training data set if our meaningful data augmentation process was omitted. Our CNN detected significantly more covey calls than manual labeling using Raven Pro software, and processing time was greatly reduced: a single one hour wav file can be now analyzed by the CNN in roughly eight seconds. We also demonstrate using a simple case study that extremely high variability in estimates of bobwhite site occupancy and detection are obtained depending on the method of acoustic data processing (manual versus CNN). Our results suggest that our CNN provides robust and time-saving analysis of bobwhite covey call acoustic data and can be applied to future research and monitoring projects with high confidence in the performance of the model.

Conservation of at‐risk species is aided by reliable forecasts of the consequences of environmental change and management actions on population viability. Forecasts from conventional population viability analysis (PVA) are made using a two‐step procedure in which parameters are estimated, or elicited from expert opinion, and then plugged into a stochastic population model without accounting for parameter uncertainty. Recently developed statistical PVAs differ because forecasts are made conditional on models fitted to empirical data. The statistical forecasting approach allows for uncertainty about parameters, but it has rarely been applied in metapopulation contexts where spatially explicit inference is needed about colonization and extinction dynamics and other forms of stochasticity that influence metapopulation viability. We conducted a statistical metapopulation viability analysis (MPVA) using 11 yr of data on the federally threatened Chiricahua leopard frog (Lithobates chiricahuensis) to forecast responses to landscape heterogeneity, drought, environmental stochasticity, and management. We evaluated several future environmental scenarios and pond restoration options designed to reduce extinction risk. Forecasts over a 50‐yr time horizon indicated that metapopulation extinction risk was <4% for all scenarios, but uncertainty was high. Without pond restoration, extinction risk is forecasted to be 3.9% (95% CI 0–37%) by year 2066. Restoring six ponds by increasing their hydroperiod reduced extinction risk to <1% and greatly reduced uncertainty (95% CI 0–2%). Our results suggest that managers can mitigate the impacts of drought and environmental stochasticity on metapopulation viability by maintaining ponds that hold water throughout the year and keeping them free of invasive predators. Our study illustrates the utility of the spatially explicit statistical forecasting approach to MPVA in conservation planning efforts.