Patch Occupancy Model Research Articles

Multi-generational dispersal and dynamic patch occupancy reveals spatial and temporal stability of seascapes

The success of non-native species (NNS) invasions depends on patterns of dispersal and connectivity, which underpin genetic diversity, population establishment and growth. In the marine environment, both global environmental change and increasing anthropogenic activity can alter hydrodynamic patterns, leading to significant inter-annual variability in dispersal pathways. Despite this, multi-generational dispersal is rarely explicitly considered in attempts to understand NNS spread or in the design of management interventions. Here, we present a novel approach to quantifying species spread that considers range expansion and network formation across time using the non-native Pacific oyster, Magallana gigas (Thunberg 1793), as a model. We combined biophysical modelling, dynamic patch occupancy models, consideration of environmental factors, and graph network theory to model multi-generational dispersal in northwest Europe over 13 generations. Results revealed that M. gigas has a capacity for rapid range expansion through the creation of an ecological network of dispersal pathways that remains stable through time. Maximum network size was achieved in four generations, after which connectivity patterns remained temporally stable. Multi-generational connectivity could therefore be divided into two periods: network growth (2000−2003) and network stability (2004–2012). Our study is the first to examine how dispersal trajectories affect the temporal stability of ecological networks across biogeographic scales, and provides an approach for the assignment of site-based prioritisation of non-native species management at different stages of the invasion timeline. More broadly, the framework we present can be applied to other fields (e.g. Marine Protected Area design, management of threatened species and species range expansion due to climate change) as a means of characterising and defining ecological network structure, functioning and stability.

Broadening applications of stochastic patch occupancy models over three decades

AbstractAimStochastic patch occupancy models (SPOMs) are a type of spatial population simulation. They are arguably well‐suited to guide conservation in human‐altered landscapes, but their appropriateness for a wide range of species and landscape types has often been questioned. Here, we provide an overview of how SPOM research has expanded over the last three decades and discuss the untapped potential for these models to inform current conservation strategies.LocationWorldwide.MethodsWe carried out a systematic review of studies that have fitted SPOMs to real species and landscapes. We assessed temporal trends in SPOMs' use in conservation and management studies, their taxonomic and geographic coverage, and the attributes of studied landscapes. We quantitatively and qualitatively evaluated whether the authors' modelling choices reflected the perceived advantages and disadvantages of SPOMs.ResultsThe proportion of SPOMs used to answer conservation questions has increased over time. Questions of where, when and how to conserve have all been addressed, sometimes considering additional aspects such as cost‐effectiveness and climate change. Taxonomic diversity coverage has increased over time, and SPOMs have been used in landscapes with a higher proportion of suitable habitat. They have, however, been predominantly applied in temperate biomes. Few studies have explored parameter extrapolation in taxonomically and ecologically related species with mixed results.Main ConclusionsOver the past three decades, authors have exploited the simplicity and flexibility of SPOMs to answer a broad range of questions with practical implications. The use of SPOMs in less fragmented landscapes, and for an increasing range of taxa, suggests that the strictest definitions of their applicability can be challenged. Stochastic patch occupancy models have untapped potential for informing conservation under climate change. Given the urgent need to plan for large numbers of species with limited data for fitting, SPOMs could better fulfil their potential to guide conservation if parameters could be extrapolated to data‐deficient landscapes and species.

Temporally robust occupancy frequency distributions in riverine metacommunities explained by local biodiversity regulation

AbstractAimThe mechanisms determining the distribution of the number of sites species occupy, the occupancy frequency distribution (OFD), remain incompletely understood despite decades of research. To explore the dominant mechanisms responsible for the shape and temporal dynamics of empirical OFD, we develop a simple patch occupancy framework with intrinsically regulated local richness and fit the model to a highly replicated dataset describing macroinvertebrate, macrophyte and diatom occupancy.LocationEngland.Time periodUp to years between 1990 and 2020.Major taxa studiedMacroinvertebrates, macrophytes and diatoms.MethodsWe study the OFD in a highly replicated dataset of freshwater metacommunities in England across time. We consider temporal change in species richness, composition, and in the shape of the OFD. Goodness‐of‐fit of the steady state of a simple patch occupancy model—which predicts a log‐series OFD—to the empirical observations is assessed. Additionally, we test the capacity of the model to predict metacommunity‐scale processes.ResultsOur model provides a consistently good fit to empirical OFDs. It can additionally be used to predict metacommunity‐scale species turnover.Main conclusionsOur results support the view that metacommunity structure reflects a dynamic steady state controlled by local limits to coexistence.

Reactive persistence, spatial management, and conservation of metapopulations: An application to seagrass restoration.

Assessing the conditions for persistence of spatially structured populations, especially those that are exploited by humans or threatened by global change, is of critical importance to inform management and conservation efforts. Observations for entire metapopulations are usually incomplete and rarely, if ever, sufficiently long to deduce population persistence from spatial patterns of abundance. Instead, insights based on metapopulation theory are often used for interpreting the demographic trajectories of real populations and for informing management decisions. The classical theoretical tool used to assess conditions for metapopulation persistence is the "invasibility criterion," which characterizes the asymptotic, or long-term, stability of a small colonizing population. Essentially, when the linear operator governing the metapopulation dynamics of an invasion event has a positive eigenvalue, recovery and resistance to extinction (resilience) are implied. The converse, however, is not necessarily the case-an invasion may grow over multiple generations, even when the eigenvalues indicate that extinction will eventually occur, a situation referred to here as "reactive persistence." For the management, restoration, and conservation of real metapopulations subject to continual disturbance, this transient behavior is often more relevant than the asymptotic behavior over long time scales. We develop the theoretical tools for assessing reactive persistence, demonstrating how the conditions for asymptotic and reactive persistence differ in both the patch-occupancy models suited to many terrestrial populations and those where local patch extinctions can be disregarded in the dynamics, often suited to marine species. After presenting the mathematical basis for generalizing the invasibility criterion to include reactive persistence, we illustrate how these concepts and tools can be applied in practice, using as a case study the population ecology and restoration of the seagrass Zostera muelleri (Irmisch ex Ascherson, 1867) in the Port of Gladstone in the Great Barrier Reef World Heritage Area Australia. It is shown how the analysis of the transient dynamics of the Z. muelleri metapopulation can be used to guide restoration efforts. Moreover, it is demonstrated that these reactive persistence concepts provide a more appropriate basis for site prioritization for restoration interventions than traditional stability analysis.

The effect of population model choice and network topologies on extinction time patterns in dendritic ecological networks

Models of populations in habitat networks are vital for understanding and linking processes and patterns across individuals, environments, ecological interactions, and population structures. River ecosystem models combine the physical structure of the networks with the biological processes of the organisms using structural and functional models, respectively. Previous studies on dendritic river networks have employed different functional (population) models and either directly claimed or implied that the results illustrate general properties of actual river systems. However, these studies have used different approaches and assumptions when modeling population characteristics and behavior, and it is possible that inferences regarding a system may vary based on the combination of functional model and the spatial structure of a network. This study aims to understand if different functional models in river systems produce substantially different model results and, therefore, whether conclusions are model-dependent. We compare variation in extinction time and occupancy proportion of river networks with linear, trellis, dendritic and ring-lattice topologies, using three population models (uniform, age-class and individual based) and one metapopulation-based (patch-occupancy) model. Dendritic, linear, and trellis structures did not show notable differences among extinction times for any of the four models. The difference between topologies was higher for the patch-occupancy model compared to the three population models. There were significant differences in the variations of patch-occupancy between the metapopulation and the population models, but the three population models of differing complexity produced broadly similar results. Therefore, if the occupancy data is obtained based on local subpopulations, spatial arrangement and connectivity does not appear to be the sole predictor of single-species metapopulation responses. We conclude that the outputs from functional models are robust to assumptions and varying levels of detail as long as they contain at least some detail at the level of individuals within habitat nodes. Also, if we are modeling network-scale populations, models that include at least some detailed information on individuals are a far better choice than considering populations implicitly.

Habitat diversity and peat moss cover drive the occurrence probability of the threatened ground beetle Carabus menetriesi (Coleoptera: Carabidae) in a Bavarian mire

Within the Natura 2000 network, there is a legal imperative to protect endangered species. A lack of knowledge about habitat requirements for these species undermines the ability to make informed decisions about appropriate conservation measures, especially for isolated populations that may have developed habitat preferences specific to their region. Carabus menetriesi is an endangered ground beetle found in Europe and warrants protection under EU law. We collected occupancy data of C. menetriesi using live pitfall traps over two seasons in 2016 and 2018 at a protected nature reserve in southern Bavaria, Germany. Here, we present the results of a patch-occupancy modeling approach to determine habitat preferences for C. menetriesi at this site. Our model shows that increasing Sphagnum cover and habitat diversity led to higher occupancy levels for C. menetriesi at this site, while tree cover was negatively correlated with occupancy, but increased the detectability of the species.Implications for insect conservationMeasures for protecting the C. menetriesi population at the study site were taken in accordance with our results. Areas with high tree cover were thinned at several sites, although the success of this measure has yet to be determined. Our findings about habitat diversity suggest that expansion of low intensity grazing in the area, a measure that was suggested as a result of our survey and is currently in process of implementation, might benefit the species. Whether our results can be transferred to C. menetriesi populations in different habitats remains to be investigated, however, our methodological approach with regard to both the data collection and analysis can be used to assess other populations and provide important information about relevant habitat parameters for that population. This will allow conservation managers to make well-informed decisions about conserving C. menetriesi, or indeed other similar carabid species with isolated populations.

Abundance and Migration Success of Overshoot Steelhead in the Upper Columbia River

AbstractSummer steelhead Oncorhynchus mykiss may enter freshwater almost a year before spawning and potentially make long migrations (>1,000 km) to interior headwater habitats. However, in response to suboptimal freshwater habitat conditions (e.g., warmer water temperatures), adult summer steelhead may exhibit complex behaviors during upstream migration in the Columbia River basin. Steelhead may migrate upstream of their natal tributary (hereafter, referred to as “overshoot”) and spend days to several months before subsequently migrating downstream (hereafter, referred to as “fallback”) to their natal tributary to spawn. An expansion of an existing Bayesian patch occupancy model, derived from observations of adult steelhead that were PIT‐tagged to estimate population‐specific abundance upstream of the tagging location, incorporated downstream detection locations to estimate the abundance of overshoot fallbacks. Overshoot steelhead abundance at the tagging location was estimated based on the relationship between the number of known overshoot fallbacks (i.e., the number of steelhead that overshot and successfully migrated downstream to their natal tributary) and their model‐estimated abundance. During the study period (2010–2017), the annual mean proportion of overshoot steelhead that successfully migrated downstream of the tagging location (Priest Rapids Dam) was 0.59 (SD = 0.14). The number of dams encountered by overshoot steelhead during their downstream migration was negatively correlated with their downstream migration success probability. Improved downstream passage survival for adult steelhead will increase the abundance of affected populations while reducing potential genetic introgression of upstream populations (i.e., strays). This is the first study to estimate the abundance of overshoot and fallback steelhead, providing the data necessary for scientists to estimate potential conservation benefits of improved downstream survival. For example, surface flow passage routes (e.g., sluiceways and temporary spillway weirs) are very effective in guiding and passing adult steelhead downstream of Columbia River hydroelectric projects and data from this assessment show that changes in dam operations throughout the downstream migration period may maximize conservation benefits.

Extinction threshold and large population limit of a plant metapopulation model with recurrent extinction events and a seed bank component

We introduce a new model for plant metapopulations with a seed bank component, living in a fragmented environment in which local extinction events are frequent. This model is an intermediate between population dynamics models with a seed bank component, based on the classical Wright–Fisher model, and Stochastic Patch Occupancy Models (SPOMs) used in metapopulation ecology. Its main feature is the use of “ghost” individuals, which can reproduce but with a very strong selective disadvantage against “real” individuals, to artificially ensure a constant population size. We show the existence of an extinction threshold above which persistence of the subpopulation of “real” individuals is not possible, and investigate how the seed bank characteristics affect this extinction threshold. We also show the convergence of the model to a SPOM under an appropriate scaling, bridging the gap between individual-based models and occupancy models.

The Temporal Dimension of Plant-Soil Microbe Interactions: Mechanisms Promoting Feedback between Generations.

AbstractSoil microbes can influence plant competitive outcomes by stabilizing plant community dynamics or mediating plant competitive hierarchies. Which effect dominates depends on whether microbial effects can extend beyond the focal conditioning individual. While it is well known that microbial effects can extend to other individuals through space, we lack an explicit theoretical understanding of the factors that regulate their spread to other individuals in subsequent generations. Here, we examine how the commonly assumed stabilizing effects of host-specific pathogens in fact depend on two factors that allow microbial effects to be cross-generational-which plant demographic vital rate is influenced by microbes and the conditioning and decay rates of soil microbial communities. With a novel patch occupancy model that incorporates the transition of soil states following plant colonization and mortality, we show that host-specific pathogens enable plant coexistence when they suppress conspecific plant colonization of empty patches but contribute to competitive hierarchies when they modify only the mortality and fecundity of the conditioning plant individual. In a series of model extensions, we further demonstrate that these latter microbial effects can still promote coexistence, but only when microbial communities decay slowly following plant death, thereby allowing microbial effects to be cross-generational. Our study calls for further empirical work quantifying the demographic rates most affected by soil microbes as well as the timescales of conditioning and decay.

Dynamic spatio-temporal patterns of metapopulation occupancy in patchy habitats.

Spatio-temporal dynamics in habitat suitability and connectivity among mosaics of heterogeneous wetlands are critical for biological diversity and species persistence in aquatic patchy landscapes. Despite the recognized importance of stochastic hydroclimatic forcing in driving wetlandscape hydrological dynamics, linking such effects to emergent dynamics of metapopulation poses significant challenges. To fill this gap, we propose here a dynamic stochastic patch occupancy model (SPOM), which links parsimonious hydrological and ecological models to simulate spatio-temporal patterns in species occupancy in wetlandscapes. Our work aims to place ecological studies of patchy habitats into a proper hydrologic and climatic framework to improve the knowledge about metapopulation shifts in response to climate-driven changes in wetlandscapes. We applied the dynamic version of the SPOM (D-SPOM) framework in two wetlandscapes in the US with contrasting landscape and climate properties. Our results illustrate that explicit consideration of the temporal dimension proposed in the D-SPOM is important to interpret local- and landscape-scale patterns of habitat suitability and metapopulation occupancy. Our analyses show that spatio-temporal dynamics of patch suitability and accessibility, driven by the stochasticity in hydroclimatic forcing, influence metapopulation occupancy and the topological metrics of the emergent wetlandscape dispersal network. D-SPOM simulations also reveal that the extinction risk in dynamic wetlandscapes is exacerbated by extended dry periods when suitable habitat decreases, hence limiting successful patch colonization and exacerbating metapopulation extinction risks. The proposed framework is not restricted only to wetland studies but could also be applied to examine metapopulation dynamics in other types of patchy habitats subjected to stochastic external disturbances.

Porównawcza ocena programów analizy żywotności populacji (PVA) w rankingu scenariuszy przekształceń krajobrazu = A comparative assessment of PVA software packages applied to rank the landscape management scenarios

Because of the scale and speed of species extinctions conservationists require methods that facilitate decision making. Therefore, a wide range of habitat and population viability analysis (PVA) software has been developed. Given the diversity of available programs it is currently challenging to decide which program is the most appropriate for a particular problem and what has to be considered when interpreting and comparing results from different approaches. Previous comparisons of PVA software addressed more generic questions such as data requirements, assumptions and predictive accuracy. In contract, we focus on a more applied problem that is still unresolved: how do simple habitat models and PVA software packages affect the ranking of alternative management scenarios? We addressed this problem by comparing different packages (LARCH, META-X, VORTEX and RAMAS GIS). As a test case, we studied the impact of alternative landscape development scenarios (river regulation, grassland restoration, reforestation and renaturalisation) for the Vistula valley, Poland, on the natterjack toad (Bufo calamita). In this context we also aimed to assess whether the use of at least two different PVA packages can enable users to better understand the differences in model predictions, which would imply a greater awareness and critical use of the packages. Our model selection represents different approaches to population viability analysis, including habitat, local population and stochastic patch occupancy models. The models can be evaluated in regard to the complexity of parameters and to the way the landscape is handled. We used RAMAS GIS to create a habitat model (RAMASh) and a detailed spatially explicit stochastic metapopulation model (RAMASp) which combined served as a complete “virtual” dataset for parameterisation of other programs. As an example of a stochastic patch occupancy model, we selected the META-X software. For a more independent comparison we added VORTEX – another package that includes explicit population dynamics, similar to RAMAS. Additionally, we included the habitat model LARCH because this type of model is often used by policy makers. We compared the metapopulation structure produced by RAMASh and LARCH. Scenario ranking according to the predicted carrying capacity in both programs was exactly the same, because the quantitative results for each scenario were almost identical in both programs. However, the metapopulation structure showed big differences between the programs, especially in the number of small populations. The analyses of results of different PVA programs (RAMASp, VORTEX and META-X) showed that absolute values of viability measures partly differed among these programs. Slight differences in population growth rate in RAMASp and VORTEX were amplified by stochasticity and resulted in visibly lower values of final abundance in VORTEX than in RAMASp. Also the absolute values of intrinsic mean time to extinction showed some discrepancies in VORTEX and META-X. These results are in agreement with findings of previous PVA comparisons, which emphasizes that absolute values of viability measures produced by any single model should be treated with caution. Nevertheless, despite these differences the rankings of the scenarios were the same in all three programs. However the order of the scenarios was different than in habitat models. In addition, these rankings were robust to the choice of viability measure. Taken together, these results emphasize that scenario ranking delivered by PVA software is robust and thus very useful for conservation management. Furthermore, we recommend using at least two PVA software packages in parallel, as this forces user to scrutinize the simplifying assumptions of the underlying models and of the viability metrics used.

A Bayesian nested patch occupancy model to estimate steelhead movement and abundance.

Anthropogenic impacts on riverine systems have, in part, led to management concerns regarding the population status of species using these systems. In an effort to assess the efficacy of restoration actions, and in order to improve monitoring of species of concern, managers have turned to PIT (passive integrated transponder) tag studies with in-stream detectors to monitor movements of tagged individuals throughout river networks. However, quantifying movements in a river network using PIT tag data with incomplete coverage and imperfect detections presents a challenge. We propose a flexible Bayesian analytic framework that models the imperfectly detected movements of tagged individuals in a nested PIT tag array river network. This model structure provides probabilistic estimates of up-stream migration routes for each tagged individual based on a set of underlying nested state variables. These movement estimates can be converted into abundance estimates when an estimate of abundance is available for a location within the river network. We apply the model framework to data from steelhead (Oncorhynchus mykiss) in the Upper Columbia River basin and evaluate model performance (precision/variance of simulated population sizes) as a function of population tagging rates and PIT tag array detection probability densities within the river system using a simulation framework. This simulation framework provides both model validation (precision) and the ability to evaluate expected performance improvements (variance) due to changes in tagging rates or PIT receiver array configuration. We also investigate the impact of different network configurations on model estimates. Results from such investigations can help inform decisions regarding future monitoring and management.

Normal approximations for discrete-time occupancy processes

We study normal approximations for a class of discrete-time occupancy processes, namely, Markov chains with transition kernels of product Bernoulli form. This class encompasses numerous models which appear in the complex networks literature, including stochastic patch occupancy models in ecology, network models in epidemiology, and a variety of dynamic random graph models. Bounds on the rate of convergence for a central limit theorem are obtained using Stein’s method and moment inequalities on the deviation from an analogous deterministic model. As a consequence, our work also implies a uniform law of large numbers for a subclass of these processes.

Uniform persistence and almost periodic solutions of a nonautonomous patch occupancy model

In this paper, a nonlinear nonautonomous model in a rocky intertidal community is studied. The model is composed of two species in a rocky intertidal community and describes a patch occupancy with global dispersal of propagules and occupy each other by individual organisms. Firstly, we study the uniform persistence of the model via differential inequality techniques. Furthermore, a sharp threshold of global asymptotic stability and the existence of a unique almost periodic solution are derived. To prove the main results, we construct an appropriate Lyapunov function whose conditions are easily verified. The assumptions of the model are reasonable, and the results complement previously known ones. An example with specific values of parameters is included for demonstration of theoretical outcomes.

Integrating social and ecological data to model metapopulation dynamics in coupled human and natural systems.

Understanding how metapopulations persist in dynamic working landscapes requires assessing the behaviors of key actors that change patches as well as intrinsic factors driving turnover. Coupled human and natural systems (CHANS) research uses a multidisciplinary approach to identify the key actors, processes, and feedbacks that drive metapopulation and landscape dynamics. We describe a framework for modeling metapopulations in CHANS that integrates ecological and social data by coupling stochastic patch occupancy models of metapopulation dynamics with agent-based models of land-use change. We then apply this framework to metapopulations of the threatened black rail (Laterallus jamaicensis) and widespread Virginia rail (Rallus limicola) that inhabit patchy, irrigation-fed wetlands in the rangelands of the California Sierra Nevada foothills. We collected data from five diverse sources (rail occupancy surveys, land-use change mapping, a survey of landowner decision making, climate and reservoir databases, and mosquito trapping and West Nile virus testing) and integrated them into an agent-based stochastic patch occupancy model. We used the model to (1) quantify the drivers of metapopulation dynamics, and the potential interactions and feedbacks among them; (2) test predictions of the behavior of metapopulations in dynamic working landscapes; and (3) evaluate the impact of three policy options on metapopulation persistence (irrigation district water cutbacks during drought, incentives for landowners to create wetlands, and incentives for landowners to protect wetlands). Complex metapopulation dynamics emerged when landscapes functioned as CHANS, highlighting the importance of integrating human activities and other ecological processes into metapopulation models. Rail metapopulations were strongly top-down regulated by precipitation, and the black rail's decade-long decline was caused by the combination of West Nile virus and drought. Theoretical predictions of the two metapopulations' responses to dynamic landscapes and incentive programs were complicated by heterogeneity in patch quality and CHANS couplings, respectively. Irrigation cutbacks during drought posed a serious extinction risk that neither incentive policy effectively ameliorated.

Use of stochastic patch occupancy models in the California red-legged frog for Bayesian inference regarding past events and future persistence.

Assessing causes of population decline is critically important to management of threatened species. Stochastic patch occupancy models (SPOMs) are popular tools for examining spatial and temporal dynamics of populations when presence–absence data in multiple habitat patches are available. We developed a Bayesian Markov chain method that extends existing SPOMs by focusing on past environmental changes that may have altered occupancy patterns prior to the beginning of data collection. Using occupancy data from 3 creeks, we applied the method to assess 2 hypothesized causes of population decline—in situ die‐off and residual impact of past source population loss—in the California red‐legged frog. Despite having no data for the 20–30 years between the hypothetical event leading to population decline and the first data collected, we were able to discriminate among hypotheses, finding evidence that in situ die‐off increased in 2 of the creeks. Although the creeks had comparable numbers of occupied segments, owing to different extinction–colonization dynamics, our model predicted an 8‐fold difference in persistence probabilities of their populations to 2030. Adding a source population led to a greater predicted persistence probability than did decreasing the in situ die‐off, emphasizing that reversing the deleterious impacts of a disturbance may not be the most efficient management strategy. We expect our method will be useful for studying dynamics and evaluating management strategies of many species.

Empirical selection between least-cost and current-flow designs for establishing wildlife corridors in Gabon.

Corridors are intended to increase species survival by abating landscape fragmentation resulting from the conversion of natural habitats into human-dominated matrices. Conservation scientists often rely on 1 type of corridor model, typically the least-cost model or current-flow model, to construct a linkage design, and their choice is not usually based on theory or empirical evidence. We developed a method to empirically confirm whether corridors produced by these 2 models are used by target species under current landscape conditions. We applied this method in the Gamba landscape between 2 national parks in southwestern Gabon. We collected signs of presence of African forest elephant (Loxodonta cyclotis), forest buffalo (Syncerus caffer nanus), and 2 apes, western lowland gorilla (Gorilla gorilla gorilla) and central chimpanzee (Pan troglodytes troglodytes), on transects. We used patch-occupancy models to identify least-cost and current-flow corridors for these 4 species. On average, 28.7% of current-flow corridors overlapped with least-cost corridors, confirming that the choice of corridor model can affect the location of the resulting linkage design. We validated these corridors by monitoring signs and examining camera detections on new transects within and outside modeled corridors. Current-flow corridors performed better than least-cost corridors for elephants, whereas the opposite was found for buffalo and apes. Locations of the highest priority corridors for the 3 taxa did not overlap, and only 18.3% of their combined surface was common among 2 species. We used centrality metrics to calculate the average contribution of corridor pixels to landscape connectivity and derived an index that can be used to prioritize corridors. As a result, we recommend protecting at least 17.4% of the land surface area around Gamba town to preserve the preferred travel routes of the target species.

Abundance-based detectability in a spatially-explicit metapopulation: a case study on a vulnerable beetle species in hollow trees

In many fragmented habitats, the detectability of a population in a habitat patch closely depends on the local abundance of individuals. However, metapopulation studies rarely connect abundance and detectability. We propose a framework for using abundance-based estimates of detectability in the analysis of a spatially-explicit stochastic patch occupancy model (SPOM). We illustrate our approach with the example of Tenebrio opacus, a beetle inhabiting hollows in old trees, and have based it on a 6-year monitoring programme of adult beetles in an area harbouring a high density of old oaks. We validated our abundance-based methodology by showing that the estimates of detectability were positively and significantly correlated with those obtained from presence/absence data (Pearson r = 0.54, p < 2E−16) in our study system. We further showed that the height of the hollow on the tree and the area of its entrance hole, the living status and girth of the host tree, and the time of survey significantly affected the detectability of beetle populations. Median detectability was 51% for one survey. The SPOM analysis revealed a high but heterogeneous extinction risk among trees, suggesting a metapopulation dynamics between the “classic” and “mainland–island” paradigms. However, it also indicated unexplained beetle colonization of trees in our study, despite the fact that we included limited detectability in our estimation procedure. This may have been due to the cryptic larval stage of T. opacus and may thus invalidate the use of a classic SPOM in our study system.

Using metapopulation models to assess species conservation–ecosystem restoration trade-offs

Ecological restoration is needed to counter global-scale ecosystem degradation, but can conflict with endangered species conservation when restoration impacts habitat quality. In such cases, prioritizing long-vacant patches for restoration is an intuitively appealing strategy for minimizing the effects on endangered species. Metapopulation models grounded in empirical data potentially provide a rigorous framework for developing theoretical “patch vacancy thresholds” (i.e., duration of vacancy required before implementing restoration) and assessing the implications of such criteria for restoration objectives. We develop such a model for spotted owls (Strix occidentalis), which embody the species–ecosystem dilemma given their preference for closed-canopy forests that are also susceptible to severe fire and drought and hence the center of debates about forest restoration intended to reduce fire and drought risk. We leveraged a >20-year territory occupancy dataset to parameterize a Stochastic Patch Occupancy Model (SPOM) to assess relative risk to a metapopulation of owls in California under alternative conservation guidelines, including a range of vacancy thresholds. Territories with greater amounts of owl habitat were more likely to be recolonized and less likely to go extinct. Importantly, the probability of a vacant owl territory becoming recolonized declined as length of vacancy increased; territories vacant for 1 and 10 years had annual recolonization probabilities of 0.34 and 0.06, respectively. Based on our SPOM, projected territory occupancy rates declined as the vacancy threshold decreased and as habitat within territories was impacted by restoration. However, more liberal territory vacancy thresholds were projected to increase the proportion of territories (and thus landscape) that could be restored and that restored conditions could be maintained with repeated treatments. Reintroducing natural disturbance regimes, which eliminated the need for repeated treatments, was projected to reduce risk to owls, particularly with relaxed vacancy thresholds. We provide a simple, yet novel, metapopulation framework for quantifying how alternative conservation guidelines might impact owl occupancy and influence forest restoration guidelines. Similar analyses could facilitate restoration efforts in other systems by more explicitly quantifying tradeoffs between species–ecosystem objectives.

Predicting spatial spread of rabies in skunk populations using surveillance data reported by the public

BackgroundPrevention and control of wildlife disease invasions relies on the ability to predict spatio-temporal dynamics and understand the role of factors driving spread rates, such as seasonality and transmission distance. Passive disease surveillance (i.e., case reports by public) is a common method of monitoring emergence of wildlife diseases, but can be challenging to interpret due to spatial biases and limitations in data quantity and quality.Methodology/Principal findingsWe obtained passive rabies surveillance data from dead striped skunks (Mephitis mephitis) in an epizootic in northern Colorado, USA. We developed a dynamic patch-occupancy model which predicts spatio-temporal spreading while accounting for heterogeneous sampling. We estimated the distance travelled per transmission event, direction of invasion, rate of spatial spread, and effects of infection density and season. We also estimated mean transmission distance and rates of spatial spread using a phylogeographic approach on a subsample of viral sequences from the same epizootic. Both the occupancy and phylogeographic approaches predicted similar rates of spatio-temporal spread. Estimated mean transmission distances were 2.3 km (95% Highest Posterior Density (HPD95): 0.02, 11.9; phylogeographic) and 3.9 km (95% credible intervals (CI95): 1.4, 11.3; occupancy). Estimated rates of spatial spread in km/year were: 29.8 (HPD95: 20.8, 39.8; phylogeographic, branch velocity, homogenous model), 22.6 (HPD95: 15.3, 29.7; phylogeographic, diffusion rate, homogenous model) and 21.1 (CI95: 16.7, 25.5; occupancy). Initial colonization probability was twice as high in spring relative to fall.Conclusions/SignificanceSkunk-to-skunk transmission was primarily local (< 4 km) suggesting that if interventions were needed, they could be applied at the wave front. Slower viral invasions of skunk rabies in western USA compared to a similar epizootic in raccoons in the eastern USA implies host species or landscape factors underlie the dynamics of rabies invasions. Our framework provides a straightforward method for estimating rates of spatial spread of wildlife diseases.