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Single‐visit surveys of plots are often used for estimating the abundance of species of conservation concern. Less‐than‐perfect availability and detection of individuals can bias estimates if not properly accounted for. We developed field methods and a Bayesian model that accounts for availability and detection bias during single‐visit visual plot surveys. We used simulated data to test the accuracy of the method under a realistic range of generating parameters and applied the method to Florida's east coast diamondback terrapin in the Indian River Lagoon system, where they were formerly common but have declined in recent decades. Simulations demonstrated that the method produces unbiased abundance estimates under a wide range of conditions that can be expected to occur in such surveys. Using terrapins as an example we show how to include covariates and random effects to improve estimates and learn about species‐habitat relationships. Our method requires only counting individuals during short replicate surveys rather than keeping track of individual identity and is simple to implement in a variety of point count settings when individuals may be temporarily unavailable for observation. We provide examples in R and JAGS for implementing the model and to simulate and evaluate data to validate the application of the method under other study conditions. [ABSTRACT FROM AUTHOR]

Fecundity, the number of young produced by a breeding pair during a breeding season, is a primary component in evolutionary and ecological theory and applications. Fecundity can be influenced by many environmental factors and requires long‐term study due to the range of variation in ecosystem dynamics. Fecundity data often include a large proportion of zeros when many pairs fail to produce any young during a breeding season due to nest failure or when all young die independently after fledging. We conducted color banding and monthly censuses of Florida scrub‐jays (Aphelocoma coerulescens) across 31 years, 15 populations, and 761 territories along central Florida's Atlantic coast. We quantified how fecundity (juveniles/pair‐year) was influenced by habitat quality, presence/absence of nonbreeders, population density, breeder experience, and rainfall, with a zero‐inflated Bayesian hierarchical model including both a Bernoulli (e.g., brood success) and a Poisson (counts of young) submodel, and random effects for year, population, and territory. The results identified the importance of increasing "strong" quality habitat, which was a mid‐successional state related to fire frequency and extent, because strong territories, and the proportion of strong territories in the overall population, influenced fecundity of breeding pairs. Populations subject to supplementary feeding also had greater fecundity. Territory size, population density, breeder experience, and rainfall surprisingly had no or small effects. Different mechanisms appeared to cause annual variation in fecundity, as estimates of random effects were not correlated between the success and count submodels. The increased fecundity for pairs with nonbreeders, compared to pairs without, identified empirical research needed to understand how the proportion of low‐quality habitats influences population recovery and sustainability, because dispersal into low‐quality habitats can drain nonbreeders from strong territories and decrease overall fecundity. We also describe how long‐term study resulted in reversals in our understanding because of complications involving habitat quality, sociobiology, and population density. [ABSTRACT FROM AUTHOR]

Adult nonbreeders are important for the stability and conservation of many species despite that their functional roles are often undervalued. Nonbreeders can buffer breeding population sizes and help their kin raise new generations of offspring, but in high numbers can compete and have negative effects. Long‐term studies are useful for elucidating relationships among nonbreeder population parameters, such as density, survival, and transitions to breeding status. Florida scrub‐jays are cooperative breeders where young delay breeding often for many years and are at risk of extinction across most of their range. Our objectives were to estimate how population covariates (pair density and mean family size) influenced Florida scrub‐jay adult nonbreeder survival and breeding transitions using long‐term data of uniquely marked birds and multistate capture–recapture models. The evolution and maintenance of Florida scrub‐jay delayed breeding has been attributed to living in crowded and sharply delineated habitat at Archbold Biological Station, the site of longest long‐term study. Contrastingly, most habitat we studied had a dynamic mixture of habitat quality with mean family sizes and pair densities much lower than the stable, optimal habitat at Archbold Biological Station. Despite having densities below carrying capacity, Florida scrub‐jays still delayed breeding. We found that greater mean family size was associated with greater breeder survival, possibly because nonbreeders contributed to predator detection and territory defense. Nonbreeder‐to‐breeder transitions increased with increased annual breeder mortality rates but were influenced little by population densities. Most Florida scrub‐jays became breeders by replacing dead breeders within occupied territories, and many male and female nonbreeders inherited their territories upon the death of their parents. Nonbreeders buffered changes in the breeding population supporting greater recognition of nonbreeder population roles within field and modeling studies. [ABSTRACT FROM AUTHOR]

Quantifying the contribution of habitat dynamics relative to intrinsic population processes in regulating species persistence remains an ongoing challenge in ecological and applied conservation. Understanding these drivers and their relationship is essential for managing habitat‐dependent species, especially those that specialize in transitional habitats. Limitations in the ability of natural disturbance to mediate transitional habitat dynamics have resulted in a decline in early‐ and mid‐successional vegetation structure and prompted the need for aggressive habitat management to replace natural perturbations and increase habitat structural complexity. We describe a collaborative effort with a group of independent land managers to design an adaptive management program for restoring an imperiled ecosystem and recovering declining populations of an endemic habitat specialist. We developed a set of integrated, hierarchical models to estimate management‐mediated transition rates among vegetation classes in two dominant scrub communities and the species response (local colonization and extinction probabilities) as a function of habitat state. Models were fit using a long‐term data set of habitat and occupancy observations from 361 Florida scrub‐jay territories across two Florida counties. Occupancy model results correspond closely to previous approaches of estimating differential survival and reproductive success associated with habitat conditions, with highest colonization and lowest extinction rates estimated for those habitat states found to have the highest rates of survival and reproduction. In addition to offering an innovative approach for jointly modeling habitat and species population dynamics, the program we describe will also be of interest from a management perspective by providing guidance for developing collaborative, adaptive management frameworks from the ground up. We engaged land managers via workshops to specify objectives and desired state‐variable conditions, identify management alternatives, and elicit consensus opinions on model parameters. Treating expert opinions as pseudo‐observations to define Dirichlet priors allowed us to make use of existing management knowledge. Formal learning was then accumulated by updating transition probability estimates as management activities were implemented over the study period. We believe this adaptive management framework provides a useful approach for increasing our understanding of complex ecological relationships and hope that it will be adopted by others who have interest in informing management and conservation efforts. [ABSTRACT FROM AUTHOR]

The Florida east coast terrapin (Malaclemys terrapin tequesta) is a rare and potentially endangered species that is difficult to survey because of poor detection probability and a patchy distribution. Like many rare species sampling programs, we apply a density and multistate occupancy sampling approach that considered the impacts of imperfect detection. We separated the detection process into availability of the animal within the sampling area (e.g., coming to surface) and perceptibility (actually seeing it). Our study employed a density estimation approach originally developed for birds, which combined time to detection and distance sampling within a Bayesian N-mixture model. Our study also estimated two abundance occupancy states (few and many terrapins). We were able to estimate large differences in terrapin densities between sites through functions of site-specific environmental covariates (water depth, distance to mangrove, and distance to land). The detection probability was poor (0.28) for the few terrapin occupancy state, but was much greater for many (0.75). The time to detection and distance-sampling approach for this aquatic animal should be useful for other aquatic organisms that regularly surface. Terrapins were generally available to be sighted within four minutes but detection declined rapidly to a low probability of terrapin detection >30 m. The approach of estimating density as a function of habitat covariates to identify habitat associations can provide an effective method that combined with adaptive sampling should be useful to investigate the distribution of terrapins in open water. [ABSTRACT FROM AUTHOR]

The combined effects of fire history, climate, and landscape features (e.g., edges) on habitat specialists need greater focus in fire ecology studies, which usually only emphasize characteristics of the most recent fire. Florida scrub-jays are an imperiled, territorial species that prefer medium (1.2–1.7 m) shrub heights, which are dynamic because of frequent fires. We measured short, medium, and tall habitat quality states annually within 10-ha grid cells (that represented potential territories) because fires and vegetative recovery cause annual variation in habitat quality. We used multistate models and model selection to test competing hypotheses about how transition probabilities vary between states as functions of environmental covariates. Covariates included vegetative type, edges (e.g., roads and forests), precipitation, openings (gaps between shrubs), mechanical cutting, and fire characteristics. Fire characteristics not only included an annual presence/absence of fire covariate, but also fire history covariates: time since the previous fire, the longest fire-free interval, and the number of repeated fires. Statistical models with support included many covariates for each transition probability, often including fire history, interactions, and nonlinear relationships. Tall territories resulted from 28 yr of fire suppression and habitat fragmentation that reduced the spread of fires across landscapes. Despite 35 yr of habitat restoration and prescribed fires, half the territories remained tall, suggesting a regime shift to a less desirable habitat condition. Edges reduced the effectiveness of fires in setting degraded scrub and flatwoods into earlier successional states, making mechanical cutting an important tool to compliment frequent prescribed fires. [ABSTRACT FROM AUTHOR]

Seagrasses are the foundation of many coastal ecosystems and are in global decline because of anthropogenic impacts. For the Indian River Lagoon (Florida, U.S.A.), we developed competing multistate statistical models to quantify how environmental factors (surrounding land use, water depth, and time [year]) influenced the variability of seagrass state dynamics from 2003 to 2014 while accounting for time-specific detection probabilities that quantified our ability to determine seagrass state at particular locations and times. We classified seagrass states (presence or absence) at 764 points with geographic information system maps for years when seagrass maps were available and with aerial photographs when seagrass maps were not available. We used 4 categories (all conservation, mostly conservation, mostly urban, urban) to describe surrounding land use within sections of lagoonal waters, usually demarcated by land features that constricted these waters. The best models predicted that surrounding land use, depth, and year would affect transition and detection probabilities. Sections of the lagoon bordered by urban areas had the least stable seagrass beds and lowest detection probabilities, especially after a catastrophic seagrass die-off linked to an algal bloom. Sections of the lagoon bordered by conservation lands had the most stable seagrass beds, which supports watershed conservation efforts. Our results show that a multistate approach can empirically estimate state-transition probabilities as functions of environmental factors while accounting for state-dependent differences in seagrass detection probabilities as part of the overall statistical inference procedure. [ABSTRACT FROM AUTHOR]

Many ecosystems are influenced by disturbances that create specific successional states and habitat structures that species need to persist. Estimating transition probabilities between habitat states and modeling the factors that influence such transitions have many applications for investigating and managing disturbance-prone ecosystems. We identify the correspondence between multistate capture-recapture models and Markov models of habitat dynamics. We exploit this correspondence by fitting and comparing competing models of different ecological covariates affecting habitat transition probabilities in Florida scrub and flatwoods, a habitat important to many unique plants and animals. We subdivided a large scrub and flatwoods ecosystem along central Florida's Atlantic coast into 10-ha grid cells, which approximated average territory size of the threatened Florida Scrub-Jay (Aphelocoma coerulescens), a management indicator species. We used l.0-m resolution aerial imagery for 1994, 1999, and 2004 to classify grid cells into four habitat quality states that were directly related to Florida Scrub-Jay source-sink dynamics and management decision making. Results showed that static site features related to fire propagation (vegetation type, edges) and temporally varying disturbances (fires, mechanical cutting) best explained transition probabilities. Results indicated that much of the scrub and flatwoods ecosystem was resistant to moving from a degraded state to a desired state without mechanical cutting, an expensive restoration tool. We used habitat models parameterized with the estimated transition probabilities to investigate the consequences of alternative management scenarios on future habitat dynamics. We recommend this multistate modeling approach as being broadly applicable for studying ecosystem, land cover, or habitat dynamics. The approach provides maximum-likelihood estimates of transition parameters, including precision measures, .and can be used to assess evidence among competing ecological models that describe system dynamics. [ABSTRACT FROM AUTHOR]

Quantifying habitat-specific survival and changes in habitat quality within disturbance-prone habitats is critical for understanding population dynamics and variation in fitness, and for managing degraded ecosystems. We used 18 years of color-banding data and multistate capture-recapture models to test whether habitat quality within territories influences survival and detection probability of breeding Florida Scrub-Jays (Apheloconia coerulescens) and to estimate bird transition probabilities from one territory quality state to another. Our study sites were along central Florida's Atlantic coast and included two of the four largest metapopulations within the species range. We developed Markov models for habitat transitions and compared these to bird transition probabilities. Florida Scrub-Jay detection probabilities ranged from 0.88 in the tall territory state to 0.99 in the optimal state; detection probabilities were intermediate in the short state. Transition probabilities were similar for birds and habitat in grid cells mapped independently of birds. Thus, bird transitions resulted primarily from habitat transitions between states over time and not from bird movement. Survival ranged from 0.71 in the short state to 0.82 in the optimal state, with tall states being intermediate. We conclude that average Florida Scrub-Jay survival will remain at levels that lead to continued population declines because most current habitat quality is only marginally suitable across most of the species range. Improvements in habitat are likely to be slow and difficult because tall states are resistant to change and the optimal state represents an intermediate transitional stage. The multistate modeling approach to quantifying survival and habitat transition probabilities is useful for quantifying habitat transition probabilities and comparing them to bird transition probabilities to test for habitat selection in dynamic environments. [ABSTRACT FROM AUTHOR]

The article presents the study that investigates the implications of fires, population density and habitat potential on the dispersal and demography of Florida Scrub-Jay, Aphelocoma coerulescens. The topics discussed include the factors that influenced the characteristics of scrub ridge, the effects of fires and population density on the temporal variation of demographic success, and the reasons why Palmetto-oak territories are considered true sinks.

The article discusses a study which examines the source-sink dynamics and territory quality transitions of the bird specie Florida Scrub-Jays. It investigates the reproductive success, survival, immigration, pair bond fidelity and the duration of delayed breeding by young Florida Scrub-Jay to enhance habitat restoration. It suggests to improve habitat quality at the territorial scale to attain successful habitat restoration.

The article discusses the distribution of quantitative and qualitative uncertainties in habitat suitability indices (HSI) that are solved using the mechanics of fuzzy numbers which is applied to a habitat model for Florida Scrub-Jay. The product of patch size and the estimate of habitat suitability is noted to be insufficient for optimal ecological decision making. The reliability of the indices are also found to influence the ecological assessment decisions and priorities.

Focuses on a study which developed a population risk model to examine the influence of population size, catastrophes, and habitat management scenarios on Florida scrub-jay or Aphelocoma coerulescens populations. Information on the model; Methodology; Results of the study.

Presents information on a study which tested whether the presence of ruderal grass resulted in small territories and whether the assignment of optimal habitat suitability (HSI) values led to an overestimate of demographic success. Florida scrub-jay biology and habitat suitability; Methods and study site; Results and discussion including the patterns in habitat use and territory size.

Habitat occupancy models, designed to deal with non‐detection of a target species in occupied sites, have been expanded to allow for false‐positive detections when species are mistakenly detected in unoccupied sites. When a subset of the data are unambiguous detections, such occupancy models can produce reliable results. However, if not properly accounted for, heterogeneity in the rate of false‐positive detection between sites may bias estimates of habitat occupancy. We studied habitat occupancy of the southeastern beach mouse (Peromyscus polionotus niveiventris), a species along Florida's Atlantic coast that is threatened due to the reduction of its core range by over 79% since 1950. Southeastern beach mice were detected based on their footprints in track tubes, but because of co‐occurrence of the cotton mouse (Peromyscus gossypinus) with overlapping footprint size, we had to allow for possible false‐positive detections. Differences in the relative abundance of these two species between habitats may have resulted in heterogeneity in the false‐positive rate. By combining uncertain (track tube) and certain (live capture) detection methods, we were able to use covariates to account for heterogeneity in false‐positive detection rates between habitats. Southeastern beach mouse habitat occupancy was higher in coastal dune and strand habitat than in coastal scrub or interior scrub habitats. The rate of false‐positive detections was much higher in coastal scrub habitat than in coastal dune and strand habitat or interior scrub habitat, reinforcing the need for methods that accommodate heterogeneity in the rate of false positives to reduce bias in estimates of habitat occupancy. Using simulations, we show that heterogeneity in the false‐positive detection rate leads to bias in habitat occupancy estimates unless properly accounted for. We also discuss how differences in relative abundance between the target species and a confusing species can directly impact the heterogeneity of false‐positive detections. [ABSTRACT FROM AUTHOR]