Summary1. Movement is influenced by landscape structure, configuration and geometry, but measuring distance as perceived by animals poses technical and logistical challenges. Instead, movement is typically measured using Euclidean distance, irrespective of location or landscape structure, or is based on arbitrary cost surfaces. A recently proposed extension of spatial capture-recapture (SCR) models resolves this issue using spatial encounter histories of individuals to calculate least-cost paths (ecological distance: Ecology, 94, 2013, 287) thereby relaxing the Euclidean assumption. We evaluate the consequences of not accounting for movement heterogeneity when estimating abundance in highly structured landscapes, and demonstrate the value of this approach for estimating biologically realistic space-use patterns and landscape connectivity. 2. We simulated SCR data in a riparian habitat network, using the ecological distance model under a range of scenarios where space-use in and around the landscape was increasingly associated with water (i.e. increasingly less Euclidean). To assess the influence of miscalculating distance on estimates of population size, we compared the results from the ecological and Euclidean distance based models. We then demonstrate that the ecological distance model can be used to estimate home range geometry when space use is not symmetrical. Finally, we provide a method for calculating landscape connectivity based on modelled species-landscape interactions generated from capture-recapture data. 3. Using ecological distance always produced unbiased estimates of abundance. Explicitly modelling the strength of the species-landscape interaction provided a direct measure of landscape connectivity and better characterised true home range geometry. Abundance under the Euclidean distance model was increasingly (negatively) biased as space use was more strongly associated with water and, because home ranges are assumed to be symmetrical, produced poor characterisations of home range geometry and no information about landscape connectivity. 4. The ecological distance SCR model uses spatially indexed capture-recapture data to estimate how activity patterns are influenced by landscape structure. As well as reducing bias in estimates of abundance, this approach provides biologically realistic representations of home range geometry, and direct information about specieslandscape interactions. The incorporation of both structural (landscape) and functional (movement) components of connectivity provides a direct measure of species-specific landscape connectivity.

Spatial heterogeneity in the environment induces variation in population demographic rates and dispersal patterns, which result in spatio-temporal variation in density and gene flow. Unfortunately, applying theory to learn about the role of spatial structure on populations has been hindered by the lack of mechanistic spatial models and inability to make precise observations of population state and structure. Spatial capture-recapture (SCR) represents an individual-based analytic framework for overcoming this fundamental obstacle that has limited the utility of ecological theory. SCR methods make explicit use of spatial encounter information on individuals in order to model density and other spatial aspects of animal population structure, and they have been widely adopted in the last decade. We review the historical context and emerging developments in SCR models that enable the integration of explicit ecological hypotheses about landscape connectivity, movement, resource selection, and spatial variation in density, directly with individual encounter history data obtained by new technologies (e.g. camera trapping, non-invasive DNA sampling). We describe ways in which SCR methods stand to advance the study of animal population ecology.

Environmental DNA (eDNA) metabarcoding has revolutionized biomonitoring in both marine and freshwater ecosystems. However, for semi‐aquatic and terrestrial animals, the application of this technique remains relatively untested. We first assess the efficiency of eDNA metabarcoding in detecting semi‐aquatic and terrestrial mammals in natural lotic ecosystems in the UK by comparing sequence data recovered from water and sediment samples to the mammalian communities expected from historical data. Secondly, using occupancy modelling we compared the detection efficiency of eDNA metabarcoding to multiple conventional non‐invasive survey methods (latrine surveys and camera trapping). eDNA metabarcoding detected a large proportion of the expected mammalian community within each area. Common species in the areas were detected at the majority of sites. Several key species of conservation concern in the UK were detected by eDNA sampling in areas where authenticated records do not currently exist, but potential false positives were also identified. Water‐based eDNA metabarcoding provided comparable results to conventional survey methods in per unit of survey effort for three species (water vole, field vole and red deer) using occupancy models. The comparison between survey ‘effort’ to reach a detection probability of ≥.95 revealed that 3–6 water replicates would be equivalent to 3–5 latrine surveys and 5–30 weeks of single camera deployment, depending on the species. Synthesis and applications. eDNA metabarcoding can be used to generate an initial ‘distribution map’ of mammalian diversity at the landscape level. If conducted during times of peak abundance, carefully chosen sampling points along multiple river courses provide a reliable snapshot of the species that are present in a catchment area. In order to fully capture solitary, rare and invasive species, we would currently recommend the use of eDNA metabarcoding alongside other non‐invasive surveying methods (i.e. camera traps) to maximize monitoring efforts.

Abstract. Patch occupancy models are extremely important and popular tools for understanding the dynamics, and predicting the persistence, of spatially structured populations. Typically this endeavor is facilitated either by models from classic metapopulation theory focused on spatially explicit, dispersal-driven colonization-extinction dynamics and generally assuming perfect detection, or by more recent hierarchical site occupancy models that account for imperfect detection but rarely include spatial effects, such as dispersal, explicitly. Neither approach explicitly considers local demographics in a way that can be used for future projections. However, despite being arguably of equal importance, dispersal and connectivity, local demography, and imperfect detection are rarely modeled explicitly and simultaneously. Understanding the spatiotemporal occurrence patterns of spatially structured populations and making biologically realistic long-term predictions of persistence would benefit from the simultaneous treatment of space, demography, and detectability. We integrated these key ideas in a tractable and intuitive way to develop a demographic and spatially realistic patch occupancy model that incorporates components of dispersal, local demographic stage-structure, and detectability. By explicitly relating stage-specific abundances to measurable patch properties, biologically realistic projections of long-term metapopulation dynamics could be made. We applied our model to data from a naturally fragmented population of water voles Arvicola amphibius to describe observed patch occupancy dynamics and to investigate long-term persistence under scenarios of elevated stage-specific local extinction. Accounting for biases induced by imperfect detection, we were able to estimate: stable, and higher than observed metapopulation occupancy; high rates of patch turnover and stage-specific colonization and extinction rates ( juvenile and adult, respectively); and juvenile dispersal distances (average 2.10 km). We found that metapopulation persistence in the presence of elevated extinction risk differed depending on which life stage was exposed, and was more sensitive to elevated juvenile rather than adult extinction risk. Predictions of persistence when dynamics are stage-specific suggest that metapopulations may be more resilient to changes in the environment than predicted when relationships are based on patch size approximations rather than population sizes. Our approach allows explicit consideration of local dynamics and dispersal in spatially structured and stage-structured populations, provides a more detailed mechanistic understanding of metapopulation functioning, and can be used to investigate future extinction risk under biologically meaningful scenarios.