Estimating indices of range shifts in birds using dynamic models when detection is imperfect

There is intense interest in basic and applied ecology about the effect of global change on current and future species distributions. Projections based on widely used static modeling methods implicitly assume that species are in equilibrium with the environment and that detection during surveys is perfect. We used multiseason correlated detection occupancy models, which avoid these assumptions, to relate climate data to distributional shifts of Louisiana Waterthrush in the North American Breeding Bird Survey (BBS) data. We summarized these shifts with indices of range size and position and compared them to the same indices obtained using more basic modeling approaches. Detection rates during point counts in BBS surveys were low, and models that ignored imperfect detection severely underestimated the proportion of area occupied and slightly overestimated mean latitude. Static models indicated Louisiana Waterthrush distribution was most closely associated with moderate temperatures, while dynamic occupancy models indicated that initial occupancy was associated with diurnal temperature ranges and colonization of sites was associated with moderate precipitation. Overall, the proportion of area occupied and mean latitude changed little during the 1997–2013 study period. Near‐term forecasts of species distribution generated by dynamic models were more similar to subsequently observed distributions than forecasts from static models. Occupancy models incorporating a finite mixture model on detection – a new extension to correlated detection occupancy models – were better supported and may reduce bias associated with detection heterogeneity. We argue that replacing phenomenological static models with more mechanistic dynamic models can improve projections of future species distributions. In turn, better projections can improve biodiversity forecasts, management decisions, and understanding of global change biology.     

Site Occupancy Dynamics of Northern Spotted Owls in the Eastern Cascades,Washington, USA, 1990–2003

Abstract: Northern spotted owls (Strix occidentalis caurina) have received intense research and management interest since their listing as a threatened species by the United States Fish and Wildlife Service in 1990. Several spotted owl (Strix occidentalis) response variables have been examined in various investigations, but recent advances in statistical modeling permit evaluations of temporal and spatial variability in site occupancy, local-extinction, and colonization probabilities while incorporating imperfect detection probabilities. Following recent work by other researchers on site occupancy dynamics of spotted owls in Oregon, USA, we evaluated temporal variability of detection, occupancy, local-extinction, and colonization probabilities for spotted owls, as well as potential influences of barred owl (Strix varia) presence on these parameters. We used spotted owl survey data collected from 1990 to 2003 on a study area in the eastern Cascades Mountains, Washington, USA, to compare competing occupancy models from Program PRESENCE using Akaike's Information Criterion. Detection probabilities for individual spotted owls ranged from 0.54 to 0.80 if barred owls were not detected during the survey season and from 0.19 to 0.71 if barred owls were detected during the survey season. Pair detection probabilities ranged from 0.27 to 0.67 if barred owls were not detected during an individual survey and from 0.09 to 0.36 if barred owls were detected during an individual survey. During the study, site occupancy probabilities for spotted owl pairs declined by approximately 50%. For all spotted owls, both singles and pairs, site occupancy probabilities declined moderately during the study. Barred owl presence was negatively associated with spotted owl detection probabilities, and it had a positive association with local-extinction probabilities for all spotted owls, both singles and pairs. Given that our study area has supported higher densities of barred owls for longer periods than other study areas, our results may provide insight into how barred owls have influenced spotted owl site occupancy dynamics in adjacent British Columbia, Canada, or will influence spotted owl site occupancy dynamics in Oregon and California, USA, in the future.     

Effects of rangeland management on the site occupancy dynamics of prairie-chickens in a protected prairie preserve

We investigated the site occupancy dynamics of greater prairie-chickens at Konza Prairie Biological Station, a protected site in northeastern Kansas that is managed for ecological research. We surveyed the site during mid-Mar to mid-May, 1981–2008, and recorded detections of birds in a grid of 6.3 ha survey plots (n = 187 plots). We used multiseason occupancy models to estimate the probabilities of occupancy (ψ) and detection (p), and tested whether land cover in woody vegetation, and land use with prescribed fire or grazing management influenced the dynamic processes of site colonization and local extinction. Probability of detection per site was consistently <1 and varied among years (p = 0.12–0.82). Site occupancy of prairie-chickens declined 40% over the study period from a high of ψ = 0.19 ± 0.02 SE in 1981 to a low of 0.11 ± 0.03 in 2008, despite protection from disturbance at leks and losses to harvest. We found that different sets of environmental factors impacted the probabilities of colonization and local extinction. Probability of colonization for an unoccupied site was negatively associated with the proportion of site occupied by woodland cover (β = −1.25), and was lower for grazed sites (β = −0.62). In contrast, probability of local extinction was affected by a weak interaction between grazing and average frequency of prescribed fire (β = −1.01), but model-averaged slope coefficients were not statistically different than 0. To conserve prairie-chickens, we recommend prairies be managed with combinations of prescribed fire and grazing that maintain a heterogeneous mosaic of prairie habitats, while preventing woody encroachment. To assess biotic responses to land management practices, field sampling should be based on occupancy models or similar techniques that account for imperfect detection. © 2011 The Wildlife Society.     

Land use drivers of species re‐expansion: inferring colonization dynamics in Eurasian otters

Aim Land use intensity has been recognized as one of the major determinants of native species declines. The re‐expansion of species previously constrained by habitat degradation has been rarely investigated. Here, we use site occupancy models incorporating imperfect detection to identify the land use drivers of the re‐expansion of the Eurasian otter (Lutra lutra). Location Czech Republic. Methods We applied multi‐season occupancy models to otter presence–non‐detection data collected in three national surveys (1992, 2000, 2006) at 552 sites (11.2 × 12 km grid cells). Model parameters included site occupancy, colonization and extinction probabilities, and detection probability at a sub‐site level. We modelled changes in occupancy over time as a function of agricultural, urban and industrial land use and change in the extent of agricultural land use. Results Under the best fitting model, occupancy was estimated to be 34.6% in 1992, 51.3% in 2000 and 83.7% in 2006. Detection probability was neither perfect nor constant. Occupancy probability in 1992 was negatively related to land use gradients. Colonization was more likely to occur where a reduction in agricultural land was larger. Variation in extinction and colonization rates along land use gradients resulted in increased occupancy in industrial and especially urban landscapes. Conversely, occupancy remained almost unchanged along agricultural gradients. Main conclusions Dynamics of otter expansion were strongly associated with the two main patterns of the rapid environmental transition that has taken place in the Czech Republic since the early 1990s. Results show that a reduction in intensive agricultural land use led to an increase in otter distribution, providing evidence of the impact of agricultural land use on stream ecosystems. Moreover, otters recolonized urban and industrial landscapes, probably as a result of extensive reduction in water pollution from point sources. Our results suggest that active conservation of otter populations should focus on restoration of freshwater habitat at large scales, especially in agricultural landscapes.     

Dealing with detection error in site occupancy surveys: what can we do with a single survey?

Aim Site occupancy probabilities of target species are commonly used in various ecological studies, e.g. to monitor current status and trends in biodiversity. Detection error introduces bias in the estimators of site occupancy. Existing methods for estimating occupancy probability in the presence of detection error use replicate surveys. These methods assume population closure, i.e. the site occupancy status remains constant across surveys, and independence between surveys. We present an approach for estimating site occupancy probability in the presence of detection error that requires only a single survey and does not require assumption of population closure or independence. In place of the closure assumption, this method requires covariates that affect detection and occupancy.Methods Penalized maximum-likelihood method was used to estimate the parameters. Estimability of the parameters was checked using data cloning. Parametric boostrapping method was used for computing confidence intervals.Important findings The single-survey approach facilitates analysis of historical datasets where replicate surveys are unavailable, situations where replicate surveys are expensive to conduct and when the assumptions of closure or independence are not met. This method saves significant amounts of time, energy and money in ecological surveys without sacrificing statistical validity. Further, we show that occupancy and habitat suitability are not synonymous and suggest a method to estimate habitat suitability using single-survey data.     

Use of classical bird census transects as spatial replicates for hierarchical modeling of an avian community

New monitoring programs are often designed with some form of temporal replication to deal with imperfect detection by means of occupancy models. However, classical bird census data from earlier times often lack temporal replication, precluding detection‐corrected inferences about occupancy. Historical data have a key role in many ecological studies intended to document range shifts, and so need to be made comparable with present‐day data by accounting for detection probability. We analyze a classical bird census conducted in the region of Murcia (SE Spain) in 1991 and 1992 and propose a solution to estimating detection probability for such historical data when used in a community occupancy model: the spatial replication of subplots nested within larger plots allows estimation of detection probability. In our study, the basic sample units were 1‐km transects, which were considered spatial replicates in two aggregation schemes. We fit two Bayesian multispecies occupancy models, one for each aggregation scheme, and evaluated the linear and quadratic effect of forest cover and temperature, and a linear effect of precipitation on species occupancy probabilities. Using spatial rather than temporal replicates allowed us to obtain individual species occupancy probabilities and species richness accounting for imperfect detection. Species‐specific occupancy and community size decreased with increasing annual mean temperature. Both aggregation schemes yielded estimates of occupancy and detectability that were highly correlated for each species, so in the design of future surveys ecological reasons and cost‐effective sampling designs should be considered to select the most suitable aggregation scheme. In conclusion, the use of spatial replication may often allow historical survey data to be applied formally hierarchical occupancy models and be compared with modern‐day data of the species community to analyze global change process.     

Modelling occupancy of an imperilled stream fish at multiple scales while accounting for imperfect detection: implications for conservation

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Assessing the impacts of imperfect detection on estimates of diversity and community structure through multispecies occupancy modeling

Detecting all species in a given survey is challenging, regardless of sampling effort. This issue, more commonly known as imperfect detection, can have negative impacts on data quality and interpretation, most notably leading to false absences for rare or difficult‐to‐detect species. It is important that this issue be addressed, as estimates of species richness are critical to many areas of ecological research and management. In this study, we set out to determine the impacts of imperfect detection, and decisions about thresholds for inclusion in occupancy, on estimates of species richness and community structure. We collected data from a stream fish assemblage in Algonquin Provincial Park to be used as a representation of ecological communities. We then used multispecies occupancy modeling to estimate species‐specific occurrence probabilities while accounting for imperfect detection, thus creating a more informed dataset. This dataset was then compared to the original to see where differences occurred. In our analyses, we demonstrated that imperfect detection can lead to large changes in estimates of species richness at the site level and summarized differences in the community structure and sampling locations, represented through correspondence analyses.     

Detection Probabilities for Ground-Based Breeding Waterfowl Surveys

ABSTRACT Current methods for conducting ground-based surveys of breeding waterfowl pairs make the unlikely assumption that detection probabilities are constant and approach 100%. To test this assumption, we conducted independent double-observer pair surveys in North Dakota, USA, to evaluate sources of variation in detection probabilities for 8 common species of prairie-nesting ducks. An experienced observer had 0.911 detection probability averaged over all 8 species (range = 0.866-0.944) versus 0.790 (range = 0.537-0.890) for a novice observer. Detection probabilities also varied substantially among species, but patterns were not consistent between observers. Detection probabilities declined as number of ducks per wetland increased, presumably due to difficulty in identifying large numbers of flushing ducks. Other covariates affecting detection probabilities included size of social groups, precipitation, survey methodology (roadside vs. walk-up), cloud cover, time of day, and amount of wetland vegetation, but these covariates only affected detection probabilities by 2–5%. Our results demonstrated that the assumption of 100% detection probabilities for ground-based waterfowl counts was clearly false and surveys based on this erroneous assumption underestimated population size by 10–29%. We recommend that future investigators measure detection probabilities explicitly by using double-observer methodologies.     

Predicting species distributions from checklist data using site‐occupancy models

Aim (1) To increase awareness of the challenges induced by imperfect detection, which is a fundamental issue in species distribution modelling; (2) to emphasize the value of replicate observations for species distribution modelling; and (3) to show how ‘cheap’ checklist data in faunal/floral databases may be used for the rigorous modelling of distributions by site‐occupancy models. Location Switzerland. Methods We used checklist data collected by volunteers during 1999 and 2000 to analyse the distribution of the blue hawker, Aeshna cyanea (Odonata, Aeshnidae), a common dragonfly in Switzerland. We used data from repeated visits to 1‐ha pixels to derive ‘detection histories’ and apply site‐occupancy models to estimate the ‘true’ species distribution, i.e. corrected for imperfect detection. We modelled blue hawker distribution as a function of elevation and year and its detection probability of elevation, year and season. Results The best model contained cubic polynomial elevation effects for distribution and quadratic effects of elevation and season for detectability. We compared the site‐occupancy model with a conventional distribution model based on a generalized linear model, which assumes perfect detectability (p = 1). The conventional distribution map looked very different from the distribution map obtained using site‐occupancy models that accounted for the imperfect detection. The conventional model underestimated the species distribution by 60%, and the slope parameters of the occurrence–elevation relationship were also underestimated when assuming p = 1. Elevation was not only an important predictor of blue hawker occurrence, but also of the detection probability, with a bell‐shaped relationship. Furthermore, detectability increased over the season. The average detection probability was estimated at only 0.19 per survey. Main conclusions Conventional species distribution models do not model species distributions per se but rather the apparent distribution, i.e. an unknown proportion of species distributions. That unknown proportion is equivalent to detectability. Imperfect detection in conventional species distribution models yields underestimates of the extent of distributions and covariate effects that are biased towards zero. In addition, patterns in detectability will erroneously be ascribed to species distributions. In contrast, site‐occupancy models applied to replicated detection/non‐detection data offer a powerful framework for making inferences about species distributions corrected for imperfect detection. The use of ‘cheap’ checklist data greatly enhances the scope of applications of this useful class of models.     

Red-Shouldered Hawk Occupancy Surveys in Central Minnesota,USA

ABSTRACT Forest-dwelling raptors are often difficult to detect because many species occur at low density or are secretive. Broadcasting conspecific vocalizations can increase the probability of detecting forest-dwelling raptors and has been shown to be an effective method for locating raptors and assessing their relative abundance. Recent advances in statistical techniques based on presence—absence data use probabilistic arguments to derive probability of detection when it is < 1 and to provide a model and likelihood-based method for estimating proportion of sites occupied. We used these maximum-likelihood models with data from red-shouldered hawk (Buteo lineatus) call-broadcast surveys conducted in central Minnesota, USA, in 1994–1995 and 2004–2005. Our objectives were to obtain estimates of occupancy and detection probability 1) over multiple sampling seasons (yr), 2) incorporating within-season time-specific detection probabilities, 3) with call type and breeding stage included as covariates in models of probability of detection, and 4) with different sampling strategies. We visited individual survey locations 2–9 times per year, and estimates of both probability of detection (range = 0.28-0.54) and site occupancy (range = 0.81-0.97) varied among years. Detection probability was affected by inclusion of a within-season time-specific covariate, call type, and breeding stage. In 2004 and 2005 we used survey results to assess the effect that number of sample locations, double sampling, and discontinued sampling had on parameter estimates. We found that estimates of probability of detection and proportion of sites occupied were similar across different sampling strategies, and we suggest ways to reduce sampling effort in a monitoring program.     

Is metapopulation patch occupancy in nature well predicted by the Levins model?

Although the Levins model has made important theoretical contributions to ecology, its empirical support has not been conclusively established yet. We used published colonization and extinction data from 55 metapopulations to calculate their Levins equilibrium patch occupancy. Over all species, there were not significant differences between the observed patch occupancies and the Levins model's estimates. However, invertebrates and vertebrate species with some degree of threat had patch occupancies larger than the model's expectancies. A temporal sampling effect was found for invertebrate species, with departure from the Levins model decreasing as the length of the study period increased. There was a negative relationship between patch occupancy and extinction probability, as expected under the “rescue effect”. The high rates at which invertebrates produce propagules could lead the Levins model to underestimate patch occupancy, whereas the observed patch occupancy of threatened species may be a transient phenomenon that results from extinction probabilities that increase over time. Therefore, the Levins model captures the metapopulation dynamics of a wide range of species in a simple formula whereas its equilibrium point can be used as evidence of metapopulation stability. Although mechanistic models provide more precise and accurate metapopulation predictions, they also can sacrifice the generality and simplicity of the Levins model.     

Occupancy modeling of ruffed grouse in the Black Hills National Forest

Ruffed grouse (Bonasa umbellus) are a popular game bird and the management indicator species for quaking aspen (Populus tremuloides) in the Black Hills National Forest (BHNF), which requires development of a robust monitoring protocol to evaluate trends in ruffed grouse populations. We used roadside drumming surveys in spring 2007 and 2008 to estimate ruffed grouse occupancy and detection probabilities in the BHNF while simultaneously assessing the influence of sampling and site covariates on these processes. Ruffed grouse occupancy estimates were constant between spring 2007 and 2008 (Ψ = 0.12, SE = 0.03) and were positively influenced by the amount of aspen surrounding the site. Detection probability estimates were constant between spring 2007 and 2008 (p = 0.27, SE = 0.06) and were influenced by survey date in a quadratic form and negatively influenced by wind speed and time of the survey. Collectively, our results demonstrated that ruffed grouse occupancy and detection probabilities in the BHNF were low. Occupancy could be increased by increasing the extent of aspen. To improve monitoring efficiency and maximize probability of detecting ruffed grouse, ruffed grouse monitoring should be conducted during the peak of drumming (mid-May), during favorable weather conditions such as low wind speeds and little precipitation, and during early morning, near sunrise. © 2010 The Wildlife Society.     

Site occupancy models with heterogeneous detection probabilities

Models for estimating the probability of occurrence of a species in the presence of imperfect detection are important in many ecological disciplines. In these "site occupancy" models, the possibility of heterogeneity in detection probabilities among sites must be considered because variation in abundance (and other factors) among sampled sites induces variation in detection probability (p). In this article, I develop occurrence probability models that allow for heterogeneous detection probabilities by considering several common classes of mixture distributions for p. For any mixing distribution, the likelihood has the general form of a zero-inflated binomial mixture for which inference based upon integrated likelihood is straightforward. A recent paper by Link demonstrates that in closed population models used for estimating population size, different classes of mixture distributions are indistinguishable from data, yet can produce very different inferences about population size. I demonstrate that this problem can also arise in models for estimating site occupancy in the presence of heterogeneous detection probabilities. The implications of this are discussed in the context of an application to avian survey data and the development of animal monitoring programs.     

Monitoring site occupancy for American mink in its native range

American mink (Neovison vison) are secretive, semi-aquatic carnivores that often require noninvasive methods based on field signs such as tracks and scat for determining their spatial distribution. Most previous assessments of survey methods for American mink have been conducted in the United Kingdom where mink are an invasive species. We evaluated survey techniques for American mink in riparian habitat in its native range in the midwestern United States. We used occupancy modeling to compare detection rates between walking surveys and mink raft surveys, and we evaluated the potential for environmental covariates and observer bias to influence detectability from walking surveys. Per-survey detection probabilities were greater for walking surveys (0.72) than for mink rafts (0.39). Walking surveys also were cheaper and easier to conduct in small streams prone to flooding when compared to mink raft surveys. However, detection probabilities from walking surveys were affected by observer bias, recent rainfall, substrate, and date. We recommend walking surveys for determining the distribution of American mink in riparian habitat in the Midwest if occupancy modeling is applied to adjust for environmental and observer effects on detectability. We used such an approach to demonstrate occupancy dynamics of mink were related to variable water depths, which has implications for how this carnivore might be influenced by climate change. Mink rafts standardize the substrate for recording mink tracks and reduce the likelihood of observer effects. For studies using many volunteers, we recommend mink rafts for determining site occupancy by American mink. © 2011 The Wildlife Society.     

Effects of point‐count duration on estimated detection probabilities and occupancy of breeding birds

Increasingly, point‐count data are used to estimate occupancy, the probability that a species is present at a given location; occupancy accounts for imperfect detection, the probability that a species is detected given that it is present. To our knowledge, effects of sampling duration on inferences from models of bird occupancy have not been evaluated. Our objective was to determine whether changing count duration from 5 to 8 min affected inferences about the occupancy of birds sampled in the Chesapeake Bay Lowlands (eastern United States) and the central and western Great Basin (western United States) in 2012 and 2013. We examined the proportion of species (two doves, one cuckoo, two swifts, five hummingbirds, 11 woodpeckers, and 122 passerines) for which estimates of detection probability were ≥ 0.3. For species with single‐season detection probabilities ≥ 0.3, we compared occupancy estimates derived from 5‐ and 8‐min counts. We also compared estimates for three species sampled annually for 5 yr in the central Great Basin. Detection probabilities based on both the 5‐ and 8‐min counts were ≥ 0.3 for 40% ± 3% of the species in an ecosystem. Extending the count duration from 5 to 8 min increased the detection probability to ≥ 0.3 for 5% ± 0.5% of the species. We found no difference in occupancy estimates that were based on 5‐ versus 8‐min counts for species sampled over two or five consecutive years. However, for 97% of species sampled over 2 yr, precision of occupancy estimates that were based on 8‐min counts averaged 12% ± 2% higher than those based on 5‐min counts. We suggest that it may be worthwhile to conduct a pilot season to determine the number of locations and surveys needed to achieve detection probabilities that are sufficiently high to estimate occupancy for species of interest.     

Spatial dynamics of an invasive bird species assessed using robust design occupancy analysis: the case of the Eurasian collared dove (Streptopelia decaocto) in France

Aim The study of the spatial dynamics of invasive species is a key issue in invasion ecology. While mathematical models are useful for predicting the extent of population expansions, they are not suitable for measuring and characterizing spatial patterns of invasion unless the probability of detection is homogeneous across the distribution range. Here, we apply recently developed statistical approaches incorporating detection uncertainty to characterize the spatial dynamics of an invasive bird species, the Eurasian collared dove (Streptopelia decaocto). Location France. Methods Data on presence/absence of doves were recorded from 1996 to 2004 over 1045 grid cells (28 × 20 km) covering the entire country. Each grid cell included five point counts spaced along a route, which was visited twice a year, allowing for an estimation of detection probability. Each route was assigned to one of six geographical regions. We used robust design occupancy analysis to assess spatial and temporal variation in parameters related to the spatial dynamics of the species. These parameters included occupancy rate, colonization and local extinction probabilities. Our inference approach was based on the selection of the most parsimonious model among competitive models parametrized with conditional probabilities. Results The probability of detecting the presence of doves on a given route was high. However, we found evidence to incorporate detection uncertainty in inference processes about spatial dynamics, since detection probability was neither perfect (i.e. it was < 1), nor constant over space and time. Results showed a clear positive trend in occupancy rate over the study period, increasing from 55% in 1996 to 76% in 2004. In addition, occupancy rate differed among regions (range: 37–79%) and further analysis showed that colonization probability by region was positively related to occupancy rate. Finally, local extinction probability was lower than colonization probability and showed a tendency to decrease over the study period. Main conclusions Our results emphasize the importance of estimating detection probabilities in order to draw proper inferences about the spatial and temporal dynamics of the invasion pattern of the collared dove. In contrast to the perceived spatial dynamics from national atlas surveys, we provide evidence that the range of this species is currently increasing in France. Other results, such as regional specificity in colonization probabilities and time variation in local extinction are consistent with expectations from invasion and metapopulation theory.     

Inferring wildlife poaching in southeast Asia with multispecies dynamic occupancy models

Determining the ‘space race’ between co-occurring species is crucial to understand the effects of interspecific interactions on the extinction risk of species threatened by poachers and predators. Dynamic two-species occupancy models provide a flexible framework to decompose complex species interaction patterns, while accounting for imperfect detection. These models can describe poachers–wildlife interactions, as they allow estimating occupancy, extinction and colonisation probabilities of wildlife conditional on the occurrence of poachers and vice versa. We applied our model to a case study on wildlife poaching in the eastern plains of Cambodia. We used co-occurrence data extracted from the database of the SMART partnership to study the distribution dynamics between poachers and six ungulate species pooled together into the tiger prey guild. We used four years of survey data reporting the locations of snares and of presence signs of the ungulates recorded by rangers during their monthly multi-patrolling sessions. Our results showed that a substantial proportion of the sites occupied by ungulate species went extinct over the years of the study while the proportion of sites colonised by poachers increased. We also showed, for the first time, that spatio-temporal heterogeneity in the patrolling effort explains a great deal of the variation in the detection of poachers and ungulates. Our approach provides practitioners with a flexible and robust tool to assess conservation status of species and extinction risk of wildlife populations. It can assist managers in better evaluating, learning and adapting the patrolling strategies of rangers.     

Assessing the effectiveness of long-term monitoring of the Broad-toothed Rat in the Barrington Tops National Park,Australia

Biodiversity monitoring is crucial for effective conservation efforts. Effective monitoring allows managers to determine the status and trends of biodiversity, as well as the success of conservation actions. The population of the Broad-toothed Rats (Mastacomys fuscus) in the Barrington Tops National Park New South Wales, Australia has been monitored since 1999 via scat and live-trapping surveys. We reviewed the methods used and analysed the data produced with the aim of describing patterns of population change over time using a range of outcome variables and identifying different climate correlates. A secondary aim was to explore the use of population statistics that account for imperfect detection by comparing naïve occupancy, with an index of relative abundance based on trap effort, the latency to find scats during scat surveys and an occupancy model based on trapping surveys. Neither of these three methods accounts for detectability variation. Naïve occupancy decreased slightly over time, while the relative abundance based on trap effort revealed no evidence of change. Additionally, naïve occupancy decreased with increasing temperature while temperature had no clear impact on relative abundance. Finally, precipitation had no impact on either naïve occupancy or relative abundance. We found no evidence of a relationship between the latency to find scats and the index of relative abundance, suggesting that one or neither is related to actual abundance. Finally, a multi-season occupancy model found occupancy probability to be 0.78 ± 0.23 (standard error); detection probability as 0.51 ± 0.06; seasonal colonisation rate as 0.36 ± 0.13 and seasonal extinction rate at 0.44 ± 0.13. We conclude that despite significant investment in monitoring, this historical data set does not allow managers to ascertain whether population change has occurred and to identify potential drivers of change. Careful consideration of future methods, in particular, whether there is imperfect detection in scat surveys, will help to inform future monitoring.     

Testing metapopulation concepts: effects of patch characteristics and neighborhood occupancy on the dynamics of an endangered lagomorph

Metapopulation ecology is a field that is richer in theory than in empirical results. Many existing empirical studies use an incidence function approach based on spatial patterns and key assumptions about extinction and colonization rates. Here we recast these assumptions as hypotheses to be tested using 18 years of historic detection survey data combined with four years of data from a new monitoring program for the Lower Keys marsh rabbit. We developed a new model to estimate probabilities of local extinction and colonization in the presence of nondetection, while accounting for estimated occupancy levels of neighboring patches. We used model selection to identify important drivers of population turnover and estimate the effective neighborhood size for this system. Several key relationships related to patch size and isolation that are often assumed in metapopulation models were supported: patch size was negatively related to the probability of extinction and positively related to colonization, and estimated occupancy of neighboring patches was positively related to colonization and negatively related to extinction probabilities. This latter relationship suggested the existence of rescue effects. In our study system, we inferred that coastal patches experienced higher probabilities of extinction and colonization than interior patches. Interior patches exhibited higher occupancy probabilities and may serve as refugia, permitting colonization of coastal patches following disturbances such as hurricanes and storm surges. Our modeling approach should be useful for incorporating neighbor occupancy into future metapopulation analyses and in dealing with other historic occupancy surveys that may not include the recommended levels of sampling replication.