A Niche-Based Framework to Assess Current Monitoring of European Forest Birds and Guide Indicator Species' Selection

Concern that European forest biodiversity is depleted and declining has provoked widespread efforts to improve management practices. To gauge the success of these actions, appropriate monitoring of forest ecosystems is paramount. Multi-species indicators are frequently used to assess the state of biodiversity and its response to implemented management, but generally applicable and objective methodologies for species'' selection are lacking. Here we use a niche-based approach, underpinned by coarse quantification of species'' resource use, to objectively select species for inclusion in a pan-European forest bird indicator. We identify both the minimum number of species required to deliver full resource coverage and the most sensitive species'' combination, and explore the trade-off between two key characteristics, sensitivity and redundancy, associated with indicators comprising different numbers of species. We compare our indicator to an existing forest bird indicator selected on the basis of expert opinion and show it is more representative of the wider community. We also present alternative indicators for regional and forest type specific monitoring and show that species'' choice can have a significant impact on the indicator and consequent projections about the state of the biodiversity it represents. Furthermore, by comparing indicator sets drawn from currently monitored species and the full forest bird community, we identify gaps in the coverage of the current monitoring scheme. We believe that adopting this niche-based framework for species'' selection supports the objective development of multi-species indicators and that it has good potential to be extended to a range of habitats and taxa.     

Use of Terrestrial Invertebrates as Indicators of the Ecological Sustainability of Forest Management under the Montreal Process

Twelve nations involved in boreal or temperate forest management are committed to reporting on indicators under the Montreal Process as a mechanism for assessing progress towards sustainable forest management. For fauna, invertebrates are often considered too poorly known and diverse to include in sustainability indicator reporting. The alternative view, that no monitoring of sustainability can be considered adequate without inclusion of some invertebrate species, is espoused in this paper. The microhabitats of soil and litter, foliage and canopy, bark and branch, dead standing trees and coarse woody debris are highlighted as relevant in the context of determining the impacts of forest management on invertebrates and for selecting representative species. It is argued that a selection of those species from each of the key microhabitats that are restricted to later stages of succession should be monitored. This could be complemented by a selection of easily monitored species from a range of functional groups as a means of endeavouring to pick up adverse impacts not foreseen on the basis of present knowledge. In the longer term, habitat indices (developed from predictive models of fauna habitat) should be used to monitor the occurrence of indicator species across the broader landscape, rather than at specific sites where monitoring of species takes place. Most countries would be in a position to select indicator species and commence monitoring for some key microhabitats (e.g. soil and litter). However, further research is needed in many countries before indicator species can be selected for other key microhabitats (e.g. coarse woody debris).     

Dry season factors determining habitat use and distribution of mouse deer (Moschiola indica) in the Western Ghats

Ecology of Asia's smallest ungulate, the Indian chevrotain or mouse deer (Moschiola indica), has been poorly assessed. We used camera-trapping data to investigate habitat use of mouse deer in Mudumalai Tiger Reserve. Presence/absence data, collected under a systematic sampling framework, were used to test a priori hypotheses incorporating covariates believed to influence mouse deer occurrence and detection. The average occupancy rate of mouse deer in the study area was 0.56 (SE?=?0.22) with a low detection probability (0.29, SE?=?0.14). Model selection indicated that presence of moist bamboo brakes positively influenced while percent leaf litter negatively influenced mouse deer occupancy. Placement of camera-traps along narrow trails positively influenced detection probability of mouse deer. Future conservation efforts in India should focus on preservation of bamboo vegetation and dense forest cover which provide refuge for the mouse deer. Our results illustrate that occupancy can be suitable for monitoring elusive, forest dwelling, small ungulates; however, caution is needed when applying these models on small ranging species, as our study identifies the limitations in our survey design and its improvement for future monitoring which are applicable for similar-sized species across a range of habitats.     

Comparative detection,density, and reproductive performance of Kirtland's warbler in jack and red pine

The formerly endangered Kirtland's warbler (Setophaga kirtlandii) is among a growing number of conservation-reliant species that depend on active management to avoid reverting to endangered status. Because the Kirtland's warbler is a habitat specialist of young, even-aged jack pine (Pinus banksiana), managers of the recovery effort stressed creating new jack pine stands and monitoring numbers of singing males through an annual census using single visits to individual stands. Kirtland's warbler will occupy and breed in red pine (P. resinosa), but red pine has not been surveyed for Kirtland's warblers in the annual population census. Furthermore, the current monitoring approach cannot determine their species detection probability or individual detection probability, which is essential to evaluate both red pine use and the accuracy of the census. From 2016–2018 we estimated density and detection probabilities in jack pine and red pine stands through repeated visits to a limited number of stands rather than single visits to many stands. Estimates of species detection probability indicated that ≥1 male Kirtland's warbler would be detected on most sites when any were present, but individual detection probabilities were less and varied by stand type, indicating that single visits to sites would underestimate numbers and that accurate estimation of detection probability was important for estimation of density in different stand types. We offer quantitative estimates of detection probabilities for determination of Kirtland's warbler population size in jack pine versus red pine stands in the same areas and breeding seasons. Managers of Kirtland's warblers should incorporate detection probabilities into population surveys to achieve more accurate estimates of population size.     

Multi-species monitoring of rare wetland fishes should account for imperfect detection of sampling devices

Accuracy in estimating occupancy of a threatened species is important for conservation but false absences bias many monitoring programs. Imperfect detection is especially relevant to surveys of rare wetland fishes which are often small-bodied and cryptic. Many factors influence probability of detection, including fish size and abundance, habitat characteristics and sampling devices. Imperfect detection can be addressed by accounting for probability of detection when estimating occupancy by modelling detection/non-detection data collected in replicate surveys. Three ecological specialists were once common in habitats associated with Lake Alexandrina at the terminus of the Murray–Darling Basin, Australia. The threatened Murray Hardyhead (Craterocephalus fluviatilis), Southern Pygmy Perch (Nannoperca australis) and Yarra Pygmy Perch (N. obscura) are now rare in the region following population collapses during a prolonged drought, and ongoing monitoring aims to assess their statuses for management purposes. This study compares probability of detection of the rare wetland fishes and cohabiting species during 2 years of multi-species monitoring using contrasting sampling devices (fyke and seine). The findings suggest large variations in estimated probability of detection can occur between devices for Murray Hardyhead and Southern Pygmy Perch. Yarra Pygmy Perch was undetected during the study. Overall, the findings show multi-species monitoring programs using a single sampling device may wrongly estimate the occupancy of a target fish. By accounting for imperfect detection, multi-species monitoring programs will improve inferences regarding population status, recovery and habitat quality of fishes to more accurately inform wetland management.     

Optimal schedule for monitoring a plant incursion when detection and treatment success vary over time

Management of an invasive plant species can be viewed as two separate and successive processes. The first, survey, aims to find infested areas and remove individuals. The second, monitoring, consists of repeated visits to these areas in order to prevent possible re-emergence. As detection probability may vary over time, the timing and number of monitoring visits can dramatically impact monitoring efficacy. We explore the optimal timing and number of monitoring visits, by focusing on one infested site. Our decision-analysis framework defines an optimal monitoring schedule which accounts for a time-dependent probability of detection, based on the presence/absence of a flower. We use this framework to investigate the optimal monitoring schedule for Hieracium aurantiacum, an invasive species in the Australian Alps and many other countries. We also perform a sensitivity analysis to draw more general conclusions. For H. aurantiacum eight monitoring visits (compared to 12 visits in the current program) are sufficient to obtain a 99% monitoring efficacy. When four or fewer visits to a site are allowed, it is optimal to visit during the high season, when the weed is likely to initiate flowering. Any extra visits should be scheduled in the early season, before the plants flower. The sensitivity analysis shows that increasing the detection probability early in the season has a greater impact than increasing it late in the season. An effective treatment method increases the value of site visits late in the season, when the detection probability is higher. Our decision-analysis framework can assist invasive species managers to reduce or reallocate management resources by determining the minimum number of monitoring visits required to satisfy an acceptable risk of re-emergence.     

Selecting indicator species of infrastructure impacts using network analysis and biological traits: Bird electrocution and power lines

The use of indicator species may save a considerable amount of resources when the attributes of other species or of the ecological process of interest are difficult or costly to measure directly. However, identifying indicator species is not easy and there is a need for rigorous criteria and methods for their selection. In this study, we test a new approach to select indicator species of high mortality-risk of electrocution in power pylons comparing methods based on biological criteria and network analysis. For this purpose, we studied 335 mortality records of 19 bird species electrocuted between 1996 and 2013 in a Special Protected Area located in South-eastern Spain. Our results showed that both species-biology based methods and network analyses provided similar results, indicating that the eagle owl can be considered the best mortality indicator of the bird community on power pylons for the study area. The use of network analysis to select indicator species can be very useful to optimize the monitoring of infrastructure impacts, especially on complex or understudied communities because it does not require detailed information on the biology of the species.     

Evaluating uncertainty to improve a common monitoring method and guide management decisions for diamond-backed terrapins

Designing monitoring with adequate certainty to evaluate management actions can be challenging, especially for elusive species in relatively inaccessible habitats. The diamond-backed terrapin (Malaclemys terrapin) is considered a high priority species for management in all states within its range. Among key threats to terrapin populations is bycatch mortality in crab pots, prompting states throughout the species' range to consider crabbing regulations and creating a need for a monitoring approach able to evaluate the success of any new crabbing regulations to benefit terrapins. Because terrapins occupy extensive and often difficult to access estuarine habitat, it is hard to collect sufficient data to estimate population responses accurately and precisely for management. To assist state managers with decisions regarding monitoring bycatch reduction regulations, we modeled 12 years of terrapin capture-recapture data. We used estimates from those models to simulate capture-recapture data pre- and post-implementation of bycatch reduction that resulted in a 0.20 absolute increase in mean apparent survival probability. Results indicated weak reliability of a monitoring approach using only manual seining of tidal creeks to detect a real management effect, with a positive management effect detected at the 95% certainty level only 34% of the time. When we considered 85% and 75% certainty thresholds, we detected a positive effect on survival among 61% and 75% of simulations, respectively. Low within-year recapture probability and the effect of tide amplitude on terrapin availability indicate there is low feasibility of improving monitoring precision at a single site, requiring monitoring of more sites to improve confidence in the detection of the management effect. The number of sites monitored depends on the acceptable level of certainty. We recommend that researchers and management entities that use seining assess the level of certainty they require to evaluate management actions and increase the number of sites sampled to meet that level of certainty. Additionally, the use of multiple monitoring methods and integrated models should be explored to reduce uncertainty and to allow for easier monitoring of more populations over broader spatial scales.     

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.     

Seasonal variation in detectability of butterflies surveyed with Pollard walks

Monitoring protocols should be designed to maximize the probability of detecting target species with limited resources. Most species are imperfectly detected, hence, they will often be overlooked at sites where they actually occur, resulting in false-negative errors (i.e. false absences). Uncertain detection of target species has profound implications for conservation, but can be dealt with by using adequate survey designs and statistical models. Butterflies often are monitored with repeated, fixed-route transect counts (Pollard walks). Even though this survey method is widely used in temperate regions, its efficiency in terms of detection probability has never been rigorously assessed in part owing to a lack of suitable analysis methods. Here, I use site-occupancy models to explore the seasonal patterns in detection probability of four California butterflies using Pollard walks. In an effort to inventory the butterfly fauna in two natural areas in the eastern foothills of the Santa Cruz mountains (California), I surveyed twelve 250 m long transects weekly for 22 weeks. I estimated the detection probability (the probability of recording a species during a single transect walk, given it is present) of four species. The probability of detecting each species depended mostly on the monitoring week. Average detection probability across the season was 64% for Cercyonis pegala, 56% for Limenitis lorquini, 76% for Euphydryas chalcedona, and 50% for Lycaena arota. Based on the mean detection probability, I then inferred the number of visits necessary to be statistically confident that a given species was indeed absent from a transect where it was not observed (i.e. obtaining a false absence rate <5%). Knowledge of detection probabilities is fundamental to the optimal design of monitoring programs and the interpretation of their results. The methods applied in this study provide an efficient and evidence-based method to optimally allocate butterfly monitoring resources across space (number of transects) and time (number and timing of visits).     

Microhabitat selection when detection is imperfect: the case of an endemic Atlantic forest mammal

Studies on habitat selection based on the presence and absence of individuals still rarely include the uncertainty of absence. With it, one can model the probability of detection, which is a parameter of interest especially when dealing with species where non-detection is common. Here, we performed an analysis of microhabitat selection of a New World marsupial (Marmosa paraguayana, Tate 1931)??an arboreal species endemic to the Brazilian Atlantic forest??accounting for false absence. We found empirical evidence supporting one of our hypotheses: the angle of the terrain??s inclination at a site positively affects detection probability. This is probably due to the fact that, at an inclined site, the area available to the animals tends to be larger and the probability of detection of M. paraguayana would be higher, due either to greater local abundance or increased frequency of moving. The probability of resource use was heterogeneous, or rather, not constant in space, but constant in time. We found weak evidence for the correlation between the canopy volume and the probability of resource use. However, we observed a tendency in the estimates of site-specific probability of resource use: the highest values of the probability of resource use appeared in the upper part of the study grid, where the canopies were denser as well as more closed. Thus, this specie??s probability of resource use possibly diminishes in habitats such as early secondary forest with tiny canopies.     

Population size influences amphibian detection probability: implications for biodiversity monitoring programs

Monitoring is an integral part of species conservation. Monitoring programs must take imperfect detection of species into account in order to be reliable. Theory suggests that detection probability may be determined by population size but this relationship has not yet been assessed empirically. Population size is particularly important because it may induce heterogeneity in detection probability and thereby cause bias in estimates of biodiversity. We used a site occupancy model to analyse data from a volunteer-based amphibian monitoring program to assess how well different variables explain variation in detection probability. An index to population size best explained detection probabilities for four out of six species (to avoid circular reasoning, we used the count of individuals at a previous site visit as an index to current population size). The relationship between the population index and detection probability was positive. Commonly used weather variables best explained detection probabilities for two out of six species. Estimates of site occupancy probabilities differed depending on whether the population index was or was not used to model detection probability. The relationship between the population index and detectability has implications for the design of monitoring and species conservation. Most importantly, because many small populations are likely to be overlooked, monitoring programs should be designed in such a way that small populations are not overlooked. The results also imply that methods cannot be standardized in such a way that detection probabilities are constant. As we have shown here, one can easily account for variation in population size in the analysis of data from long-term monitoring programs by using counts of individuals from surveys at the same site in previous years. Accounting for variation in population size is important because it can affect the results of long-term monitoring programs and ultimately the conservation of imperiled species.     

Do population indicators work? Investigating correlated responses of bird populations in relation to predator management

Using population indicators to evaluate conservation achievements is widely practised, yet seldom empirically tested. If populations are consistently correlated in response to a shared ecological driver, the indicator species approach can be used as a cost-effective, ecologically-based shortcut to measuring the effects of conservation management. Long-term monitoring of forest bird populations associated with mammalian pest control programmes in New Zealand provides a useful framework for testing the population indicator species concept. We evaluated population trends in 21 bird species vulnerable to predation by introduced mammals (primarily mustelids and rodents) at managed and unmanaged beech (Nothofagus) forest sites. Correlated population trends between species pairs were detected at individual sites. However, neither positive nor negative correlations in species trends could be predicted by life history traits and predator management did not produce consistent, correlated population trends among sites. Our results do not support the use of a population indicator approach to management and reporting for forest birds in New Zealand. Relationships between purported indicator taxa and other species need to be understood for various management scenarios before population indicators can be confidently applied to measuring conservation achievement.     

The Debate About Bait: A Red Herring in Wildlife Research

The use of bait (or attractants) to lure animals to a sampling site is common in wildlife research and important for optimizing species detection rates. The effect of bait on animal movement and space-use, however, is contested, fueled by concerns bait may affect animal movement and increase residency time. If founded, bait may bias parameter estimates from density, species distribution, resource selection, or behavioral models, produce spurious ecological inferences, and skew resulting management recommendations. To test whether animal movement varies with proximity to bait, we used high-resolution global positioning system telemetry data of 10 fishers (Pekania pennanti), temporally paired with 64 baited wildlife camera traps, to quantify the effect of bait on individual and population movement metrics. Although bait appeared to have a significant correlative effect on 1-hour movement segments, landscape characteristics had an effect 1.7 times greater, where the proportion of mixed forest and cultivation explained the majority of variability in animal movements. We contend that maximizing probability of detection and controlling or modeling local-scale landscape variability that could affect the probability of detection is a more important consideration in wildlife research than the effect of bait, which is eclipsed by differences incurred by natural habitat heterogeneity. Failing to maximize the probability of detection may obscure the modest bias potentially presented by the use of bait, or attractants, on ecological inference. © 2019 The Wildlife Society     

Hierarchical multi-scale occupancy estimation for monitoring wildlife populations

Occupancy estimation is an effective analytic framework, but requires repeated surveys of a sample unit to estimate the probability of detection. Detection rates can be estimated from spatially replicated rather than temporally replicated surveys, but this may violate the closure assumption and result in biased estimates of occupancy. We present a new application of a multi-scale occupancy model that permits the simultaneous use of presence–absence data collected at 2 spatial scales and uses a removal design to estimate the probability of detection. Occupancy at the small scale corresponds to local territory occupancy, whereas occupancy at the large scale corresponds to regional occupancy of the sample units. Small-scale occupancy also corresponds to a spatial availability or coverage parameter where a species may be unavailable for sampling at a fraction of the survey stations. We applied the multi-scale occupancy model to a hierarchical sample design for 2 bird species in the Black Hills National Forest: brown creeper (Certhia americana) and lark sparrow (Chondestes grammacus). Our application of the multi-scale occupancy model is particularly well suited for hierarchical sample designs, such as spatially replicated survey stations within sample units that are typical of avian monitoring programs. The model appropriately accounts for the non-independence of the spatially replicated survey stations, addresses the closure assumption for the spatially replicated survey stations, and is useful for decomposing the observation process into detection and availability parameters. This analytic approach is likely to be useful for monitoring at local and regional scales, modeling multi-scale habitat relationships, and estimating population state variables for rare species of conservation concern. © 2011 The Wildlife Society.     

环境DNA在两栖动物监测中的应用研究进展

两栖动物是我国受威胁程度最高的动物类群,加强两栖动物资源调查和多样性监测,是开展两栖动物保护和濒危物种拯救行动的关键性基础工作。传统的两栖动物监测主要以形态学和声学为基础,耗时费力,且难以发现一些隐蔽性较强的稀有物种。基于环境DNA(environmental DNA, eDNA)的调查方法以其快速、灵敏、高效、无创等独特优势,为两栖动物多样性监测及保护提供了新的工具。综述了eDNA在两栖动物多样性监测、外来入侵和珍稀濒危物种调查、物种丰度或生物量估测等研究领域的应用进展,分析了两栖动物eDNA产生、扩散、迁移和降解的动态变化特征及其关键影响因子,探讨了eDNA应用于两栖动物监测研究的局限性并提出了优化建议,同时对未来的研究方向进行了展望,以充分挖掘eDNA在两栖动物监测中的应用潜力,为两栖动物多样性保护和管理提供新的思路。     

Designing occupancy surveys and interpreting non‐detection when observations are imperfect

Aim Conservation practitioners use biological surveys to ascertain whether or not a site is occupied by a particular species. Widely used statistical methods estimate the probability that a species will be detected in a survey of an occupied site. However, these estimates of detection probability are alone not sufficient to calculate the probability that a species is present given that it was not detected. The aim of this paper is to demonstrate methods for correctly calculating (1) the probability a species occupies a site given one or more non‐detections, and (2) the number of sequential non‐detections necessary to assert, with a pre‐specified confidence, that a species is absent from a site. Location Occupancy data for a tree frog in eastern Australia serve to illustrate methods that may be applied anywhere species’ occupancy data are used and detection probabilities are < 1. Methods Building on Bayesian expressions for the probability that a site is occupied by a species when it is not detected, and the number of non‐detections necessary to assert absence with a pre‐specified confidence, we estimate occupancy probabilities across tree frog survey locations, drawing on information about where and when the species was detected during surveys. Results We show that the number of sequential non‐detections necessary to assert that a species is absent increases nonlinearly with the prior probability of occupancy, the probability of detection if present, and the desired level of confidence about absence. Main conclusions If used more widely, the Bayesian analytical approaches illustrated here would improve collection and interpretation of biological survey data, providing a coherent way to incorporate detection probability estimates in the design of minimum survey requirements for monitoring, impact assessment and distribution modelling.     

Estimating the abundance of rare and elusive carnivores from photographic-sampling data when the population size is very small

Conservation and management agencies require accurate and precise estimates of abundance when considering the status of a species and the need for directed actions. Due to the proliferation of remote sampling cameras, there has been an increase in capture–recapture studies that estimate the abundance of rare and/or elusive species using closed capture–recapture estimators (C–R). However, data from these studies often do not meet necessary statistical assumptions. Common attributes of these data are (1) infrequent detections, (2) a small number of individuals detected, (3) long survey durations, and (4) variability in detection among individuals. We believe there is a need for guidance when analyzing this type of sparse data. We highlight statistical limitations of closed C–R estimators when data are sparse and suggest an alternative approach over the conventional use of the Jackknife estimator. Our approach aims to maximize the probability individuals are detected at least once over the entire sampling period, thus making the modeling of variability in the detection process irrelevant, estimating abundance accurately and precisely. We use simulations to demonstrate when using the unconditional-likelihood M ₀ (constant detection probability) closed C–R estimator with profile-likelihood confidence intervals provides reliable results even when detection varies by individual. If each individual in the population is detected on average of at least 2.5 times, abundance estimates are accurate and precise. When studies sample the same species at multiple areas or at the same area over time, we suggest sharing detection information across datasets to increase precision when estimating abundance. The approach suggested here should be useful for monitoring small populations of species that are difficult to detect.     

Monitoring program design for data‐limited marine biogenic habitats: A structured approach

Marine biogenic habitats—habitats created by living organisms—provide essential ecosystem functions and services, such as physical structuring, nutrient cycling, biodiversity support, and increases in primary, secondary, and tertiary production. With the growing trend toward ecosystem approaches to marine conservation and fisheries management, there is greater emphasis on rigorously designed habitat monitoring programs. However, such programs are challenging to design for data‐limited habitats for which underlying ecosystem processes are poorly understood. To provide guidance in this area, we reviewed approaches to benthic assessments across well‐studied marine biogenic habitats and identified common themes related to indicator selection, sampling methods, and survey design. Biogenic habitat monitoring efforts largely focus on the characteristics, distribution, and ecological function of foundation species, but may target other habitat‐forming organisms, especially when community shifts are observed or expected, as well as proxies of habitat status, such as indicator species. Broad‐scale methods cover large spatial areas and are typically used to examine the spatial configuration of habitats, whereas fine‐scale methods tend to be laborious and thus restricted to small survey areas, but provide high‐resolution data. Recent, emerging methods enhance the capabilities of surveying large areas at high spatial resolution and improve data processing efficiency, bridging the gap between broad‐ and fine‐scale methods. Although sampling design selection may be limited by habitat characteristics and available resources, it is critically important to ensure appropriate matching of ecological, observational, and analytical scales. Drawing on these common themes, we propose a structured, iterative approach to designing monitoring programs for marine biogenic habitats that allows for rigorous data collection to inform management strategies, even when data and resource limitations are present. A practical application of this approach is illustrated using glass sponge reefs—a recently discovered and data‐limited habitat type—as a case study.     

Spatial patch occupancy patterns of the Lower Keys marsh rabbit

Reliable estimates of presence or absence of a species can provide substantial information on management questions related to distribution and habitat use but should incorporate the probability of detection to reduce bias. We surveyed for the endangered Lower Keys marsh rabbit (Sylvilagus palustris hefneri) in habitat patches on 5 Florida Key islands, USA, to estimate occupancy and detection probabilities. We derived detection probabilities using spatial replication of plots and evaluated hypotheses that patch location (coastal or interior) and patch size influence occupancy and detection. Results demonstrate that detection probability, given rabbits were present, was <0.5 and suggest that naïve estimates (i.e., estimates without consideration of imperfect detection) of patch occupancy are negatively biased. We found that patch size and location influenced probability of occupancy but not detection. Our findings will be used by Refuge managers to evaluate population trends of Lower Keys marsh rabbits from historical data and to guide management decisions for species recovery. The sampling and analytical methods we used may be useful for researchers and managers of other endangered lagomorphs and cryptic or fossorial animals occupying diverse habitats. © 2011 The Wildlife Society.