Decision implementation and the double-loop process in adaptive management of horseshoe crab harvest in Delaware Bay
No abstract available.
Delaware Bay↗
Geology topics
Conor P. McGowan
Publications and source records attributed to Conor P. McGowan.
Foraging ecology mediates response to ecological mismatch during migratory stopover
Impacts of ecological mismatches should be most pronounced at points of the annual cycle when populations depend on a predictable, abundant, and aggregated food resource that changes in timing or distribution. The degree to which species specialize on a key prey item, therefore, should determine their sensitivity to mismatches. We evaluated the hypothesis that the effects of ecological mismatch during migratory stopover are mediated by a species’ foraging ecology by comparing two similar long‐distance migratory species that differ in their foraging strategies during stopover. We predicted that a specialist foraging strategy would make species more sensitive to effects of mismatch with a historically abundant prey, while an active, generalist foraging strategy should help buffer against changing local conditions. We estimated arrival times, start of mass gain, and rate of mass gain during spring stopover in Delaware Bay, USA. At this site, shorebirds feed on a temporally aggregated food resource (horseshoe crab Limulus polyphemus eggs), the timing of which is linked to water temperature; red knot ( Calidris canutus rufa ) specializes on these while the ruddy turnstone ( Arenaria interpres ) feeds more generally. We used a hierarchical nonlinear model to estimate the effect of mismatch between shorebird arrivals and timing of crab spawning on the timing and rate of mass gain over 22 yr. In years with cooler water temperature, crabs spawned later, which was associated with later and faster mass gain for the knots. Turnstones exhibited less inter‐annual variation in the timing and rate of mass gain than knots, and we found no relationship between mass gain dynamics and the availability of horseshoe crab eggs for this generalist species. Long‐distance migrants rely on predictable resources en route and even when these linkages are simple and predictable, populations can be vulnerable to change; these results suggest that generalist foraging strategies may buffer migratory species against phenological mismatch. We provide a framework to evaluate population responses to changes in prey phenology at sites vulnerable to climatic change.
Delaware↗
Modeling strategies and evaluating success during repatriations of elusive and endangered species
Wildlife repatriation is an important tool to decrease extinction risk for imperiled species, but successful repatriations require significant time, resources and planning. Because repatriations can be long and expensive processes, clear release strategies and monitoring programs are essential to efficiently use resources and evaluate success. However, monitoring can be challenging and surrounded by significant uncertainty, particularly for secretive species with extremely low detection probability. Here, we simulated how alternative repatriation strategies influence repatriation success for the eastern indigo snake Drymarchon couperi , a federally-Threatened species that is currently being repatriated in Alabama and Florida. Critically, we demonstrate how observed population growth can differ from true population growth when detection probabilities are low and mark-recapture analyses are not an option. Specifically, we built a stochastic stage-based population model to predict population growth and extinction risk under different release strategies and use information from ongoing repatriations to predict success and guide future releases. Because D. couperi is difficult to monitor, we modeled how detection probability influenced perceptions of abundance and population growth by monitoring programs. Simulated repatriation strategies releasing older, head-started snakes in greater abundance and frequency created wild populations with decreased extinction risk relative to scenarios releasing fewer and younger snakes less frequently. Ongoing repatriations currently have a 0.23 (Alabama) and 0.61 (Florida) probability of quasi-extinction, but extinction risk decreased to 0.07 and 0.10 at sites upon achieving the targeted number of releases. Abundances observed under realistic detection thresholds for D. couperi did not always predict true population growth; specifically, we demonstrate that monitoring programs during repatriations of secretive species may indicate that efforts have been unsuccessful when populations are actually growing. Overall, our modeling framework informs release strategies to maximize repatriation success while demonstrating the need to consider how detection processes influence assessment of success during conservation interventions.
Florida↗
Effects of individual misidentification on estimates of survival in long-term mark–resight studies
All ecological measurements are subject to error; the effects of missed detection (false negatives) are well known, but the effects of mistaken detection (false positives) are less understood. Long-term capture–recapture datasets provide valuable ecological insights and baselines for conservation and management, but where such studies rely on noninvasive re-encounters, such as field-readable color bands, there is the potential to accumulate detection errors as the length of the study and number of tags deployed increases. We investigated the prevalence and effects of misreads in a 10-yr dataset of Red Knots ( Calidris canutus rufa ) marked with field-readable leg flags in Delaware, USA. We quantified the effects of misreads on survival estimation via a simulation study and evaluated whether removal of individuals only reported once in a year (potential misreads) influenced survival estimation from both simulated datasets and our case study data. We found overall apparent error rates of 0.31% (minimum) to 6.6% (maximum). Observer-specific error rates and the variation among observers both decreased with the number of flags an observer recorded. Our simulation study showed that misreads lead to spurious negative trends in survival over time, particularly for long-term studies. Removing all records in which a flag was only recorded once in a sampling occasion reduced bias and eliminated spurious negative trends in survival but also reduced precision in survival estimates. Without data filtering, we found a slight decrease in Red Knot annual survival probability from 2008 to 2018 (β = −0.043 ± 0.03), but removing all single-observation records resulted in no apparent trend (β = −0.0074 ± 0.02). Spurious trends in demographic rates could influence inference about population trajectories and resultant conservation decision-making. Data filtering could eliminate errors, but researchers should carefully consider the tradeoff between precision obtained by larger sample sizes and potential bias due to misreads in their data.
Delaware↗
Managing the vanishing North American hunter: A novel framework to address declines in hunters and hunter-generated conservation funds
As long as the funding mechanism supporting state wildlife conservation relies heavily on hunter-generated funds, declines in hunter participation are a threat to the conservation of both game and non-game species. To address options to bolster wildlife agency profit from the sale of hunting licenses, we developed a stage-based, stochastic population model of a hunter population, and demonstrate its utility within a decision-making framework to inform state wildlife agency decisions. We evaluated hypothetical youth and adult recruitment-focused outreach programs over 10 years to increase license sale profit. Using our model as the core of a decision analysis, state agencies can set hunter population or license profit targets, and evaluate management actions designed to achieve those objectives. We anticipate that our approach will provide a valuable framework for anticipating the future of hunting and hunting-generated conservation funds, and can be extended to other user groups, including target shooters and anglers.
Human Dimensions of Wildlife: An International Jou↗
Extinction risk and conservation options for Maui Parrotbill, an endangered Hawaiian honeycreeper
Extinction rates for island birds around the world have been historically high. For forest passerines, the Hawaiian archipelago has suffered some of the highest extinction rates and reintroduction is a conservation tool that can be used to prevent the extinction of some of the remaining endangered species. Population viability analyses can be used to assess risks to vulnerable populations and evaluate the relative benefits of conservation strategies. Here we present a population viability analysis to assess the long-term viability for Maui parrotbill(s) (Kiwikiu) Pseudonestor xanthophrys, a federally endangered passerine on the Hawaiian island of Maui. Contrary to indications from population monitoring, our results indicate Maui parrotbills may be unlikely to persist beyond 25 years. Our modeling suggests female mortality as a primary factor driving this decline. To evaluate and compare management options involving captive rearing and translocation strategies we made a female-only stage-structured, meta-population simulation model. Due to the low reproductive potential of Maui parrotbills in captivity, the number of individuals (~ 20% of the global population) needed to source a reintroduction solely from captive reared birds is unrealistic. A reintroduction strategy that incorporates a minimal contribution from captivity and instead translocates mostly wild individuals was found to be the most feasible management option. Habitat is being restored on leeward east Maui, which may provide more favorable climate and habitat conditions and promote increased reproductive output. Our model provides managers with benchmarks for fecundity and survival needed to ensure reintroduction success, and highlights the importance of establishing a new population in potentially favorable habitat to ensure long-term persistence.
Journal of Fish and Wildlife Management↗
Development of a species status assessment process for decisions under the U.S. Endangered Species Act
Decisions under the U.S. Endangered Species Act (ESA) require scientific input on the risk that the species will become extinct. A series of critiques on the role of science in ESA decisions have called for improved consistency and transparency in species risk assessments and clear distinctions between science input and policy application. To address the critiques and document the emerging practice of the U.S. Fish and Wildlife Service (USFWS), we outline an assessment process based on principles and practices of risk and decision analyses that results in a scientific report on species status. The species status assessment (SSA) process has three successive stages: 1) document the life history and ecological relationships of the species in question to provide the foundation for the assessment, 2) describe and hypothesize causes for the current condition of the species, and 3) forecast the species' future condition. The future condition refers to the ability of a species to sustain populations in the wild under plausible future scenarios. The scenarios help explore the species' response to future environmental stressors and to assess the potential for conservation to intervene to improve its status. The SSA process incorporates modeling and scenario planning for prediction of extinction risk and applies the conservation biology principles of representation, resiliency, and redundancy to evaluate the current and future condition. The SSA results in a scientific report distinct from policy application, which contributes to streamlined, transparent, and consistent decision-making and allows for greater technical participation by experts outside of the USFWS, for example, by state natural resource agencies. We present two case studies based on assessments of the eastern massasauga rattlesnake Sistrurus catenatus and the Sonoran Desert tortoise Gopherus morafkai to illustrate the process. The SSA builds upon the past threat-focused assessment by including systematic and explicit analyses of a species' future response to stressors and conservation, and as a result, we believe it provides an improved scientific analysis for ESA decisions.
Journal of Fish and Wildlife Management↗
Efficacy of time-lapse photography and repeated counts abundance estimation for white-tailed deer populations
Automated cameras have become increasingly common for monitoring wildlife populations and estimating abundance. Most analytical methods, however, fail to account for incomplete and variable detection probabilities, which biases abundance estimates. Methods which do account for detection have not been thoroughly tested, and those that have been tested were compared to other methods of abundance estimation. The goal of this study was to evaluate the accuracy and effectiveness of the N-mixture method, which explicitly incorporates detection probability, to monitor white-tailed deer ( Odocoileus virginianus ) by using camera surveys and a known, marked population to collect data and estimate abundance. Motion-triggered camera surveys were conducted at Auburn University’s deer research facility in 2010. Abundance estimates were generated using N-mixture models and compared to the known number of marked deer in the population. We compared abundance estimates generated from a decreasing number of survey days used in analysis and by time periods (DAY, NIGHT, SUNRISE, SUNSET, CREPUSCULAR, ALL TIMES). Accurate abundance estimates were generated using 24 h of data and nighttime only data. Accuracy of abundance estimates increased with increasing number of survey days until day 5, and there was no improvement with additional data. This suggests that, for our system, 5-day camera surveys conducted at night were adequate for abundance estimation and population monitoring. Further, our study demonstrates that camera surveys and N-mixture models may be a highly effective method for estimation and monitoring of ungulate populations.
Mammal Research↗
AnimalFinder: A semi-automated system for animal detection in time-lapse camera trap images
Although the use of camera traps in wildlife management is well established, technologies to automate image processing have been much slower in development, despite their potential to drastically reduce personnel time and cost required to review photos. We developed AnimalFinder in MATLAB® to identify animal presence in time-lapse camera trap images by comparing individual photos to all images contained within the subset of images (i.e. photos from the same survey and site), with some manual processing required to remove false positives and collect other relevant data (species, sex, etc.). We tested AnimalFinder on a set of camera trap images and compared the presence/absence results with manual-only review with white-tailed deer ( Odocoileus virginianus ), wild pigs ( Sus scrofa ), and raccoons ( Procyon lotor ). We compared abundance estimates, model rankings, and coefficient estimates of detection and abundance for white-tailed deer using N-mixture models. AnimalFinder performance varied depending on a threshold value that affects program sensitivity to frequently occurring pixels in a series of images. Higher threshold values led to fewer false negatives (missed deer images) but increased manual processing time, but even at the highest threshold value, the program reduced the images requiring manual review by ~ 40% and correctly identified > 90% of deer, raccoon, and wild pig images. Estimates of white-tailed deer were similar between AnimalFinder and the manual-only method (~ 1–2 deer difference, depending on the model), as were model rankings and coefficient estimates. Our results show that the program significantly reduced data processing time and may increase efficiency of camera trapping surveys.
Ecological Informatics↗
Incorporating population viability models into species status assessment and listing decisions under the U.S. Endangered Species Act
Assessment of a species' status is a key part of management decision making for endangered and threatened species under the U.S. Endangered Species Act. Predicting the future state of the species is an essential part of species status assessment, and projection models can play an important role in developing predictions. We built a stochastic simulation model that incorporated parametric and environmental uncertainty to predict the probable future status of the Sonoran desert tortoise in the southwestern United States and North Central Mexico. Sonoran desert tortoise was a Candidate species for listing under the Endangered Species Act, and decision makers wanted to use model predictions in their decision making process. The model accounted for future habitat loss and possible effects of climate change induced droughts to predict future population growth rates, abundances, and quasi-extinction probabilities. Our model predicts that the population will likely decline over the next few decades, but there is very low probability of quasi-extinction less than 75 years into the future. Increases in drought frequency and intensity may increase extinction risk for the species. Our model helped decision makers predict and characterize uncertainty about the future status of the species in their listing decision. We incorporated complex ecological processes (e.g., climate change effects on tortoises) in transparent and explicit ways tailored to support decision making processes related to endangered species.
Sonoran Desert↗
Structured decision making as a conservation tool for recovery planning of two endangered salamanders
At least one-third of all amphibian species face the threat of extinction, and current amphibian extinction rates are four orders of magnitude greater than background rates. Preventing extirpation often requires both ex situ (i.e., conservation breeding programs) and in situ strategies (i.e., protecting natural habitats). Flatwoods salamanders ( Ambystoma bishopi and A. cingulatum ) are protected under the U.S. Endangered Species Act. The two species have decreased from 476 historical locations to 63 recently extant locations (86.8% loss). We suggest that recovery efforts are needed to increase populations and prevent extinction, but uncertainty regarding optimal actions in both ex situ and in situ realms hinders recovery planning. We used structured decision making (SDM) to address key uncertainties regarding both captive breeding and habitat restoration, and we developed short-, medium-, and long-term goals to achieve recovery objectives. By promoting a transparent, logical approach, SDM has proven vital to recovery plan development for flatwoods salamanders. The SDM approach has clear advantages over other previous approaches to recovery efforts, and we suggest that it should be considered for other complex decisions regarding endangered species.
Journal for Nature Conservation↗
Disentangling density-dependent dynamics using full annual cycle models and Bayesian model weight updating
Density dependence regulates populations of many species across all taxonomic groups. Understanding density dependence is vital for predicting the effects of climate, habitat loss and/or management actions on wild populations. Migratory species likely experience seasonal changes in the relative influence of density dependence on population processes such as survival and recruitment throughout the annual cycle. These effects must be accounted for when characterizing migratory populations via population models. To evaluate effects of density on seasonal survival and recruitment of a migratory species, we used an existing full annual cycle model framework for American black ducks Anas rubripes , and tested different density effects (including no effects) on survival and recruitment. We then used a Bayesian model weight updating routine to determine which population model best fit observed breeding population survey data between 1990 and 2014. The models that best fit the survey data suggested that survival and recruitment were affected by density dependence and that density effects were stronger on adult survival during the breeding season than during the non-breeding season. Analysis also suggests that regulation of survival and recruitment by density varied over time. Our results showed that different characterizations of density regulations changed every 8–12 years (three times in the 25-year period) for our population. Synthesis and applications . Using a full annual cycle, modelling framework and model weighting routine will be helpful in evaluating density dependence for migratory species in both the short and long term. We used this method to disentangle the seasonal effects of density on the continental American black duck population which will allow managers to better evaluate the effects of habitat loss and potential habitat management actions throughout the annual cycle. The method here may allow researchers to hone in on the proper form and/or strength of density dependence for use in models for conservation recommendations.
Journal of Applied Ecology↗
Decision analysis for habitat conservation of an endangered, range-limited salamander
Many species of conservation concern are habitat limited and often a major focus of management for these species is habitat acquisition and/or restoration. Deciding the location of habitat restoration or acquisition to best benefit a protected species can be a complicated subject with competing management objectives, ecological uncertainties and stochasticity. Structured decision making (SDM) could be a useful approach for explicitly incorporating those complexities while still working toward species conservation and/or recovery. We applied an SDM approach to Red Hills salamander Phaeognathus hubrichti habitat conservation decision making. Phaeognathus hubrichti is a severely range-limited endemic species in south central Alabama and has highly specific habitat requirements. Many known populations live on private lands and the primary mode of habitat protection is habitat conservation planning, but such plans are non-binding and not permanent. Working with stakeholders, we developed an objectives hierarchy linking land acquisition or protection actions to fundamental objectives. We built a model to assess and compare the quality of the habitat in the known range of P. hubrichti . Our model evaluated key habitat attributes of 5814 pixels of 1 km 2 each and ranked the pixels from best to worst with respect to P. hubrichti habitat requirements. Our results are a spatially explicit valuation of each pixel, with respect to its probable benefit to P. hubrichti populations. The results of this effort will be used to rank pixels from most to least beneficial, then identify land owners in the most useful areas for salamanders who are willing to sell or enter into a permanent easement agreement.
Alabama↗
Updating movement estimates for American black ducks (Anas rubripes)
Understanding migratory connectivity for species of concern is of great importance if we are to implement management aimed at conserving them. New methods are improving our understanding of migration; however, banding (ringing) data is by far the most widely available and accessible movement data for researchers. Here, we use band recovery data for American black ducks ( Anas rubripes ) from 1951–2011 and analyze their movement among seven management regions using a hierarchical Bayesian framework. We showed that black ducks generally exhibit flyway fidelity, and that many black ducks, regardless of breeding region, stopover or overwinter on the Atlantic coast of the United States. We also show that a non-trivial portion of the continental black duck population either does not move at all or moves to the north during the fall migration (they typically move to the south). The results of this analysis will be used in a projection modeling context to evaluate how habitat or harvest management actions in one region would propagate throughout the continental population of black ducks. This analysis may provide a guide for future research and help inform management efforts for black ducks as well as other migratory species.
PeerJ↗
A full annual cycle modeling framework for American black ducks
American black ducks ( Anas rubripes ) are a harvested, international migratory waterfowl species in eastern North America. Despite an extended period of restrictive harvest regulations, the black duck population is still below the population goal identified in the North American Waterfowl Management Plan (NAWMP). It has been hypothesized that density-dependent factors restrict population growth in the black duck population and that habitat management (increases, improvements, etc.) may be a key component of growing black duck populations and reaching the prescribed NAWMP population goal. Using banding data from 1951 to 2011 and breeding population survey data from 1990 to 2014, we developed a full annual cycle population model for the American black duck. This model uses the seven management units as set by the Black Duck Joint Venture, allows movement into and out of each unit during each season, and models survival and fecundity for each region separately. We compare model population trajectories with observed population data and abundance estimates from the breeding season counts to show the accuracy of this full annual cycle model. With this model, we then show how to simulate the effects of habitat management on the continental black duck population.
Natural Resource Modeling↗
Assessment and Mmanagement of North American horseshoe crab populations, with emphasis on a multispecies framework for Delaware Bay, U.S.A. populations: Chapter 24
The horseshoe crab fishery on the US Atlantic coast represents a compelling fishery management story for many reasons, including ecological complexity, health and human safety ramifications, and socio-economic conflicts. Knowledge of stock status and assessment and monitoring capabilities for the species have increased greatly in the last 15 years and permitted managers to make more informed harvest recommendations. Incorporating the bioenergetics needs of migratory shorebirds, which feed on horseshoe crab eggs, into the management framework for horseshoe crabs was identified as a goal, particularly in the Delaware Bay region where the birds and horseshoe crabs exhibit an important ecological interaction. In response, significant effort was invested in studying the population dynamics, migration ecology, and the ecologic relationship of a key migratory shorebird, the Red Knot, to horseshoe crabs. A suite of models was developed that linked Red Knot populations to horseshoe crab populations through a mass gain function where female spawning crab abundance determined what proportion of the migrating Red Knot population reached a critical body mass threshold. These models were incorporated in an adaptive management framework wherein optimal harvest decisions for horseshoe crab are recommended based on several resource-based and value-based variables and thresholds. The current adaptive framework represents a true multispecies management effort where additional data over time are employed to improve the predictive models and reduce parametric uncertainty. The possibility of increasing phenologic asynchrony between the two taxa in response to climate change presents a potential challenge to their ecologic interaction in Delaware Bay.
Book chapter↗
Comparing models of Red Knot population dynamics
Predictive population modeling contributes to our basic scientific understanding of population dynamics, but can also inform management decisions by evaluating alternative actions in virtual environments. Quantitative models mathematically reflect scientific hypotheses about how a system functions. In Delaware Bay, mid-Atlantic Coast, USA, to more effectively manage horseshoe crab ( Limulus polyphemus ) harvests and protect Red Knot ( Calidris canutus rufa ) populations, models are used to compare harvest actions and predict the impacts on crab and knot populations. Management has been chiefly driven by the core hypothesis that horseshoe crab egg abundance governs the survival and reproduction of migrating Red Knots that stopover in the Bay during spring migration. However, recently, hypotheses proposing that knot dynamics are governed by cyclical lemming dynamics garnered some support in data analyses. In this paper, I present alternative models of Red Knot population dynamics to reflect alternative hypotheses. Using 2 models with different lemming population cycle lengths and 2 models with different horseshoe crab effects, I project the knot population into the future under environmental stochasticity and parametric uncertainty with each model. I then compare each model's predictions to 10 yr of population monitoring from Delaware Bay. Using Bayes' theorem and model weight updating, models can accrue weight or support for one or another hypothesis of population dynamics. With 4 models of Red Knot population dynamics and only 10 yr of data, no hypothesis clearly predicted population count data better than another. The collapsed lemming cycle model performed best, accruing ~35% of the model weight, followed closely by the horseshoe crab egg abundance model, which accrued ~30% of the weight. The models that predicted no decline or stable populations (i.e. the 4-yr lemming cycle model and the weak horseshoe crab effect model) were the most weakly supported.
The Condor↗
Developing objectives with multiple stakeholders: adaptive management of horseshoe crabs and Red Knots in the Delaware Bay
Structured decision making (SDM) is an increasingly utilized approach and set of tools for addressing complex decisions in environmental management. SDM is a value-focused thinking approach that places paramount importance on first establishing clear management objectives that reflect core values of stakeholders. To be useful for management, objectives must be transparently stated in unambiguous and measurable terms. We used these concepts to develop consensus objectives for the multiple stakeholders of horseshoe crab harvest in Delaware Bay. Participating stakeholders first agreed on a qualitative statement of fundamental objectives, and then worked to convert those objectives to specific and measurable quantities, so that management decisions could be assessed. We used a constraint-based approach where the conservation objectives for Red Knots, a species of migratory shorebird that relies on horseshoe crab eggs as a food resource during migration, constrained the utility of crab harvest. Developing utility functions to effectively reflect the management objectives allowed us to incorporate stakeholder risk aversion even though different stakeholder groups were averse to different or competing risks. While measurable objectives and quantitative utility functions seem scientific, developing these objectives was fundamentally driven by the values of the participating stakeholders.
Environmental Management↗