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Sarah J. Converse

Publications and source records attributed to Sarah J. Converse.

At least 37 records · Page 2Linked to original sources
USGS2024

Merging integrated population models and individual-based models to project population dynamics of recolonizing species

Recolonizing species exhibit unique population dynamics, namely dispersal to and colonization of new areas, that have important implications for management. A resulting challenge is how to simultaneously model demographic and movement processes so that recolonizing species can be accurately projected over time and space. We introduce a framework for spatially explicit projection modeling that harnesses the rigorous parameter estimation made possible by an integrated population model (IPM) and the flexible movement modeling made possible by an individual-based model (IBM). Our framework has two components: [1] a Bayesian IPM-driven age- and state-structured population model that governs the population state process and estimation of demographic rates, and [2] an IBM-driven spatial model that allows for the projection of dispersal and habitat colonization. We applied this model framework to estimate current and project future dynamics of gray wolves ( Canis lupus ) in Washington State, USA. We used data from 74 telemetered wolves and yearly pup and pack counts to parameterize the model, and then projected statewide dynamics over 50 years. Mean population growth was 1.29 (95 % Bayesian Credible Interval = 1.26–1.33) during initial recolonization from 2009 to 2020 and decreased to 1.02 (95 % Prediction Interval = 0.98–1.04) in the projection period (2021–2070). Our results suggest that gray wolves have an ~100 % probability of colonizing the last of Washington State's three specified recovery regions by 2030, regardless of alternative assumptions about how dispersing wolves select new territories. Our spatially explicit projection model can be used to project the dynamics of any species for which spatial spread is an important driver of population dynamics.

Washington↗
USGS2024

Incorporating life history diversity in an integrated population model to inform viability analysis

Life history diversity can significantly affect population dynamics and effects of management actions. For instance, variation in individual responses to environmental variability can reduce extirpation risk to populations, as the portfolio effect dampens temporal variability in abundance. Moreover, differences in habitat use may cause individuals to respond differently to habitat management and climate variability. To explore the role of life history diversity in population trajectories, population models need to incorporate within-population variation. Integrated population modeling (IPM) is a population modeling approach that offers several advantages for sharing information and propagating uncertainty across datasets. In this study, we developed an IPM for an endangered population of Chinook salmon ( Oncorhynchus tshawytscha ) in the Wenatchee River, Washington, USA, that accounts for diversity in juvenile life histories, spawning location, and return age. Our analysis revealed that diversity in the age of juvenile emigration from natal streams had a portfolio effect, resulting in a 20% reduction in year-to-year variability in adult abundance in population projections. Our population viability analysis suggests that management interventions may be necessary to meet recovery goals, and our model should be useful for simulating the outcomes of proposed actions.

Washington↗
USGS2023

Identifying demographic and environmental drivers of population dynamics and viability in an endangered top predator using an integrated model

Knowledge about the demographic and environmental factors underlying population dynamics is fundamental to designing effective conservation measures to recover depleted wildlife populations. However, sparse monitoring data or persistent knowledge gaps about threats make it difficult to identify the drivers of population dynamics. In situations where small, declining, or depleted populations show continued evidence of decline for unknown reasons, integrated population models can make efficient use of available data to improve our understanding of demography, provide fundamental insights into factors that may be limiting recovery, and support conservation decisions. We used mark-resight and aerial survey data from 2004 to 2018 to build a Bayesian integrated population model for the Cook Inlet population of beluga whales ( Delphinapterus leucas ), which is listed as endangered under the U.S. Endangered Species Act. We examined the effects of prey availability and oceanographic conditions on beluga vital rates and conducted a population viability analysis to predict extinction risk across a range of hypothetical changes in beluga survival and reproduction. Our results indicated that while the survival of breeding females (0.97; 95% CI: 0.95–0.99) and young calves (0.92; 0.80–0.98) was relatively high, the survival of nonbreeders (0.94; 0.91–0.97) and fecundity (0.28; 0.22–0.36) may be depressed. Furthermore, our analysis indicates that the population will likely continue to decline, with a 17–32% probability of extinction in 150 years. Our model highlights the utility of integrated population modeling for maximizing the usefulness of available data and identifying factors contributing to the failure of protected populations to recover. This framework can be used to evaluate proposed conservation and recovery efforts for this and other endangered species.

Animal Conservation↗
USGS2023

Integrating community science and agency-collected monitoring data to expand monitoring capacity at large spatial scales

Monitoring species to better understand their status, ecology, and management needs is a major expense for agencies tasked with biodiversity conservation. Community science data have the potential to improve monitoring for minimal cost, given appropriate analytical frameworks. We describe a framework for integrating data from the eBird community science platform with agency-collected monitoring data using a multistate occupancy model. Our model accounts for the structural differences across datasets and allows for estimation of both occupancy and breeding probabilities. The framework was applied to Common Loons ( Gavia immer ) in Washington State. A total of 766 sites had observation effort, of which 713 sites had only eBird effort, 26 sites had only Washington Department of Fish and Wildlife (WDFW) effort, and 27 sites had both. We predicted that the probability of occupancy was only 0.07 (95% Bayesian credible interval, BCI = 0.02–0.51) at the 2324 sites in our sampling frame, though the probability that Common Loons were breeding at occupied sites was 0.95 (95% BCI = 0.71–1.00). We found that probability of occupancy was positively related to waterbody size (probability of a positive effect = 0.88) and negatively related to an index of human influence (probability of a negative effect = 0.94). We found that probability of breeding at occupied sites was positively related to tree canopy cover (0.86), negatively related to elevation (0.99), and negatively related to barren, scrub/shrub, and herbaceous land cover (0.98). We found that state agency biologists were 16 times more likely to detect breeding Common Loons at a site than were eBird users (0.94, 95% BCI = 0.78–0.99 for agency biologists vs. 0.08, 95% BCI = 0.06–0.10 for eBird users). However, the amount of effort expended by eBird users meant that they confirmed Common Loons at 94 sites while agency biologists confirmed them at just 24 sites, although evidence of reproduction was only contributed by agency biologists. Our results provide a better understanding of the distribution of Common Loons in Washington, while further demonstrating that community science data can be a valuable complement to agency-collected data, if appropriate frameworks are developed to integrate these data sources.

Ecosphere↗
USGS2023

Effects of population density and environmental conditions on life-history prevalence in a migratory fish

Individual variation in life-history traits can have important implications for the ability of populations to respond to environmental variability and change. In migratory animals, flexibility in the timing of life-history events, such as juvenile emigration from natal areas, can influence the effects of population density and environmental conditions on habitat use and population dynamics. We evaluated the functional relationships between population density and environmental covariates and the abundance of juveniles expressing different life-history pathways in a migratory fish, Chinook salmon ( Oncorhynchus tshawytscha ), in the Wenatchee River basin in Washington State, USA. We found that the abundance of younger emigrants from natal streams was best described by an accelerating or near-linear function of spawners, whereas the abundance of older emigrants was best described by a decelerating function of spawners. This supports the hypothesis that emigration timing varies in response to density in natal areas, with younger-emigrating life-history pathways comprising a larger proportion of emigrants when densities of conspecifics are high. We also observed positive relationships between winter stream discharge and abundance of younger emigrants, supporting the hypothesis that habitat conditions can also influence the prevalence of different life-history pathways. Our results suggest that early emigration, and a resultant increase in the use of downstream rearing habitats, may increase at higher population densities and with greater winter precipitation. Winter precipitation is projected to increase in this system due to climate warming. Characterizing relationships between life-history prevalence and environmental conditions may improve our understanding of species habitat requirements and is a first step in understanding the dynamics of species with diverse life-history strategies. As environmental conditions change—due to climate change, management, or other factors—resultant life-history changes are likely to have important demographic implications that will be challenging to predict when life-history diversity is not accounted for in population models.

Washington↗
USGS2023

Optimal management decisions are robust to unknown dynamics in an amphibian metapopulation plagued by disease

Identifying conservation actions to recover threatened species can be challenging due to many ecological uncertainties. For example, major threats to a species' conservation are commonly known or suspected, but the specific impacts on population or metapopulation dynamics can be uncertain. This is frequently the case with emerging infectious diseases, including chytridiomycosis, a global driver of amphibian population declines caused by the fungal pathogens Batrachochytrium dendrobatidis (Bd) and Batrachochytrium salamandrivorans . While these diseases are known to cause amphibian declines and extirpations, the mechanisms of their landscape-scale spread are still largely unknown. Such uncertainty can lead to inaction which may jeopardize timely recovery of a species. Decision analysis is a pragmatic approach to making transparent and defensible decisions while dealing with uncertainties. We investigated whether optimal actions aimed at recovering boreal toad ( Anaxyrus boreas boreas ) metapopulations in the southern Rocky Mountains are robust to the unknown dynamics of Bd spread using value of information and regret analyses. Value of information is a decision-analytic tool for calculating the value of new information in terms of performance on management objectives, while regret measures the cost of acting under incorrect information. We further conducted a stochastic sensitivity analysis to identify the relative effects of metapopulation parameters on system dynamics. We found optimal actions were robust to the unknown dynamics of Bd spread. While boreal toad breeding occurrence is highly sensitive to Bd distribution, the optimal decision is not. Resolving the unknown dynamics of Bd spread would lead to a minimal gain of less than one breeding toad subpopulation at the end of 50 years, given the currently available management actions. Applying a decision-analytic framework coupled with value of information and regret analyses can help frame how uncertainties affect decisions in a way that empowers decision makers.

Animal Conservation↗
USGS2023

Juvenile life history diversity is associated with lifetime individual heterogeneity in a migratory fish

Differences in the life history pathways (LHPs) of juvenile animals are often associated with differences in demographic rates in later life stages. For migratory animals, different LHPs often result in animals from the same population occupying distinct habitats subjected to different environmental drivers. Understanding how demographic rates differ among animals expressing different LHPs may reveal fitness trade-offs that drive the expression of alternative LHPs and enable better prediction of population dynamics in a changing environment. To understand how demographic outcomes and their relationships with environmental variables differ among animals with different LHPs, we analyzed a long-term (2006–2021) mark–recapture dataset for Chinook salmon ( Oncorhynchus tshawytscha ) from the Wenatchee River, Washington, USA. Distinct LHPs represented in this population include either remaining in the natal stream until emigrating to the ocean as a 1-year-old (natal-reach rearing) or emigrating from the natal stream and rearing in downstream habitats for several months before completing the emigration to the ocean as a 1-year-old (downstream rearing). We found that downstream-rearing fish emigrated to the ocean 19 days earlier on average and returned as adults from the ocean at higher rates. We detected a positive correlation between rate of return from the ocean by downstream-rearing fish and coastal upwelling in their spring of outmigration, whereas for natal-reach-rearing fish we detected a positive correlation with sea surface temperature during their first marine summer. Different responses to environmental variability should lead to asynchrony in adult abundance among juvenile LHPs. A higher proportion of downstream-rearing fish returned at younger ages compared with natal-reach-rearing fish, which contributed to variability in age at reproduction and greater mixing across generations. Our results demonstrate how diversity in juvenile LHPs is associated with heterogeneity in demographic rates during subsequent life stages, which can in turn affect variance in aggregate population abundance and response to environmental change. Our findings underscore the importance of considering life history diversity in demographic analyses and provide insights into the effects of life history diversity on population dynamics and trade-offs that contribute to the maintenance of life history diversity.

Washington↗
USGS2023

Differential shortstopping behaviour in Whooping Cranes: Habitat or social learning?

Many migratory bird species have begun shifting their wintering grounds closer to their breeding grounds, shortening their yearly migration distance through a behavior called shortstopping. While multiple studies have investigated possible drivers, it remains unclear why only some populations adopt this behavior. We studied the differential occurrence of shortstopping in two populations of Whooping Cranes (Grus americana): a remnant population where juveniles migrate with their parents, and a reintroduced population consisting largely of captive-reared birds trained to migrate by unrelated conspecifics or by humans. Shortstopping is widespread in the reintroduced population, while the remnant population has not shown any appreciable northward movement of its overwintering sites. We examined potential drivers for this lack of shortstopping, including a lack of suitable habitat north of their current wintering area or social differences between populations. Using characteristics of winter locations used by the reintroduced population, we found that 31.4% of the remnant migration corridor was predicted to be suitable for wintering, suggesting that insufficient habitat suitability is not limiting shortstopping behaviour. However, we found evidence for behavioural differences that might explain the absence of shortstopping in the remnant population: while all juveniles of the remnant population associate with their parents during overwintering, juveniles from the reintroduced population did not associate with older conspecifics in 12 out of 25 observed wintering events, suggesting that the social transmission of winter migration behaviours might be less effective in the reintroduced population. Although social learning is generally believed to increase flexibility in migratory strategies, a strong vertical transmission of behaviour might enforce adherence to established traditions and reduce the uptake of novel behaviours such as shortstopping. We suggest that, besides habitat availability, social factors may also play a role in explaining the absence of shortstopping behaviour in some migratory bird populations.

Global Ecology and Conservation↗
USGS2023

Using decision analysis to determine the feasibility of a conservation translocation

Conservation translocations, intentional movements of species to protect against extinction, have become widespread in recent decades and are projected to increase further as biodiversity loss continues worldwide. The literature abounds with analyses to inform translocations and assess whether they are successful, but the fundamental question of whether they should be initiated at all is rarely addressed formally. We used decision analysis to assess northern leopard frog reintroduction in northern Idaho, with success defined as a population that persists for at least 50 years. The Idaho Department of Fish and Game was the decision maker (i.e., the agency that will use this assessment to inform their decisions). Stakeholders from government, indigenous groups, academia, land management agencies, and conservation organizations also participated. We built an age-structured population model to predict how management alternatives would affect probability of success. In the model, we explicitly represented epistemic uncertainty around a success criterion (probability of persistence) characterized by aleatory uncertainty. For the leading alternative, the mean probability of persistence was 40%. The distribution of the modelling results was bimodal, with most parameter combinations resulting in either very low (<5%) or relatively high (>95%) probabilities of success. Along with other considerations, including cost, the Idaho Department of Fish and Game will use this assessment to inform a decision regarding reintroduction of northern leopard frogs. Conservation translocations may benefit greatly from more widespread use of decision analysis to counter the complexity and uncertainty inherent in these decisions.

Decision Analysis↗
USGS2023

Examining the effect of environmental variability on the viability of endangered Steller sea lions using an integrated population model

Understanding spatio-temporal variability in demography and the influence of environmental conditions offers insight into the factors underlying population dynamics. This is particularly true for species with divergent demographic patterns across large geographic areas. The contrasting abundance trends observed across the range of Steller sea lions (Eumetopias jubatus) have been studied extensively, with research suggesting that the primary drivers of localized population dynamics vary over time and space. We developed a Bayesian integrated population model for the endangered western distinct population segment of Steller sea lions that combines mark-recapture and count data from 2000-2021 to estimate demographic rates, abundance trends, and the effects of environmental variability on population growth. Our results highlight subregional demographic differences, including reduced pup survival in the central Aleutian Islands and reduced yearling survival west of Samalga Pass. Range-wide abundance increased by 1.7% yr-1 (95% credible interval: 0.14; 3.4%) over the study period, with a positive annual growth rate of 3.0% (1.1; 5.1%) yr-1 east of Samalga Pass, a negative growth rate of -2.1% (-4.6; 0.5%) yr-1 west of Samalga Pass, and an overall low probability of local extirpation (<2%) in 100 years even in subregions experiencing continued decline. The effect of environmental variability on population growth varied depending on subpopulation size and vital rates and was strongest in the area of greatest decline. Our model improves upon existing approaches for estimating abundance, accounts for environmental variability within the viability analysis, and can facilitate evaluating the efficacy of conservation actions and progress toward recovery goals.

Alaska↗
USGS2022

Environmental drivers of demography and potential factors limiting the recovery of an endangered marine top predator

Understanding what drives changes in wildlife demography is fundamental to the conservation and management of depleted or declining populations, though making inference about the intrinsic and extrinsic factors that influence survival and reproduction remains challenging. Here we use mark–resight data from 2000 to 2018 to examine the effects of environmental variability on age-specific survival and natality for the endangered western distinct population segment (wDPS) of Steller sea lions ( Eumetopias jubatus ) in Alaska, USA. Though this population has been studied extensively over the last four decades, the causes of divergent abundance trends that have been observed across the wDPS range remain unknown. We developed a Bayesian multievent mark–resight model that accounts for female reproductive state uncertainty. Annual survival probabilities for male pups (0.44; 0.36–0.53), female yearlings (0.63; 0.49–0.73), and male yearlings (0.62; 0.51–0.71) born in the western portion of the wDPS range, estimated here for the first time, were lower than those in the eastern portion of the wDPS range, estimated as: male pups (0.69; 0.65–0.74), female yearlings (0.76; 0.71–0.81), and male yearlings (0.71; 0.65–0.78). There was a higher proportion of young female breeders in the western portion of the range, but overall natality was lower (0.69; 0.47–0.96) than in the eastern portion of the range (0.80; 0.74–0.84). Additionally, pup mass had a positive effect on pup survival in the eastern portion of the range and a negative effect in the western portion of the range, potentially due to earlier weaning of heavier pups. Local- and basin-scale oceanographic features such as the Aleutian Low, the Arctic Oscillation Index, the North Pacific Gyre Oscillation, chlorophyll concentration, upwelling, and wind in certain seasons were correlated with vital rates. However, drawing strong inferences from these correlations is challenging given that relationships between ocean conditions and an adaptive top predator in a dynamic ecosystem are exceedingly complex. This study provides the first demographic rate estimates for the western portion of the range where abundance estimates continue to decline. These results will advance efforts to identify factors driving regionally divergent abundance trends, with implications for population-level responses to future climate variability.

Alaska↗
USGS2022

Estimating reproductive and juvenile survival rates when offspring ages are uncertain: A novel multievent mark-resight model with beluga whale case study

Understanding the survival and reproductive rates of a population is critical to determining its long-term dynamics and viability. Mark-resight models are often used to estimate these demographic rates, but estimation of survival and reproductive rates is challenging, especially for wide-ranging, patchily distributed, or cryptic species. In particular, existing mark-resight models cannot accommodate data from populations in which offspring remain with parents for multiple years, are not always detected, and cannot be aged with certainty. Here we describe a Bayesian multievent mark-resight modelling framework that uses all available adult and adult-offspring sightings (including sightings with older offspring of uncertain age) to estimate reproductive rates and survival rates of adults and juveniles. We extend existing multievent mark-resight models that typically only incorporate adult breeding state uncertainty by additionally accounting for age uncertainty in unmarked offspring and uncertainty in the duration of the mother-offspring association. We describe our model in general terms and with a simple illustrative example, then apply it in a more complex empirical setting using 13 years of photo-ID data from a critically endangered population of beluga whales Delphinapterus leucas . We evaluated model performance using simulated data under a range of sample sizes, and adult and offspring detection rates. Applying our model to the beluga data yielded precise estimates for all demographic rates of interest (despite substantial uncertainty in calf ages), including nonbreeder survival and reproductive rates lower than in other beluga populations. Simulations suggested our model yields asymptotically unbiased parameter estimates with good precision and low bias even with moderate sample sizes and detection rates. This work represents an important new development in multievent mark-resight modelling, allowing estimation of reproductive and juvenile survival rates for populations with extended adult—offspring associations and uncertain offspring ages (e.g. some marine mammals, elephants, bears, great apes, bats and birds). Our model facilitated estimation of robust demographic rates for an endangered beluga population that were previously inestimable (e.g. nonbreeder and juvenile survival, reproductive rate) and that will yield new insights into this population's continued decline.

Methods in Ecology and Evolution↗
USGS2022

Integrated animal movement and spatial capture–recapture models: Simulation, implementation, and inference

Over the last decade, spatial capture–recapture (SCR) models have become widespread for estimating demographic parameters in ecological studies. However, the underlying assumptions about animal movement and space use are often not realistic. This is a missed opportunity because interesting ecological questions related to animal space use, habitat selection, and behavior cannot be addressed with most SCR models, despite the fact that the data collected in SCR studies — individual animals observed at specific locations and times — can provide a rich source of information about these processes and how they relate to demographic rates. We developed SCR models that integrated more complex movement processes that are typically inferred from telemetry data, including a simple random walk, correlated random walk (i.e., short-term directional persistence), and habitat-driven Langevin diffusion. We demonstrated how to formulate, simulate from, and fit these models with standard SCR data using data-augmented Bayesian analysis methods. We evaluated their performance through a simulation study, in which we varied the detection, movement, and resource selection parameters. We also examined different numbers of sampling occasions and assessed performance gains when including auxiliary location data collected from telemetered individuals. Across all scenarios, the integrated SCR movement models performed well in terms of abundance, detection, and movement parameter estimation. We found little difference in bias for the simple random walk model when reducing the number of sampling occasions from T = 25 to T = 15. We found some bias in movement parameter estimates under several of the correlated random walk scenarios, but incorporating auxiliary location data improved parameter estimates and significantly improved mixing during model fitting. The Langevin movement model was able to recover resource selection parameters from standard SCR data, which is particularly appealing because it explicitly links the individual-level movement process with habitat selection and population density. We focused on closed population models, but the movement models developed here can be extended to open SCR models. The movement process models could also be easily extended to accommodate additional “building blocks” of random walks, such as central tendency (e.g., territoriality) or multiple movement behavior states, thereby providing a flexible and coherent framework for linking animal movement behavior to population dynamics, density, and distribution.

Ecology↗
USGS2022

Modeling spatiotemporal abundance and movement dynamics using an integrated spatial capture–recapture movement model

Animal movement is a fundamental ecological process affecting the survival and reproduction of individuals, the structure of populations, and the dynamics of communities. Methods to quantify animal movement and spatiotemporal abundances, however, are generally separate and therefore omit linkages between individual-level and population-level processes. We describe an integrated spatial capture–recapture (SCR) movement model to jointly estimate (1) the number and distribution of individuals in a defined spatial region and (2) movement of those individuals through time. We applied our model to a study of polar bears ( Ursus maritimus ) in a 28,125 km 2 survey area of the eastern Chukchi Sea, USA in 2015 that incorporated capture–recapture and telemetry data. In simulation studies, the model provided unbiased estimates of movement, abundance, and detection parameters using a bivariate normal random walk and correlated random walk movement process. Our case study provided detailed evidence of directional movement persistence for both male and female bears, where individuals regularly traversed areas larger than the survey area during the 36-day study period. Scaling from individual- to population-level inferences, we found that densities varied from <0.75 bears/625 km 2 grid cell/day in nearshore cells to 1.6–2.5 bears/grid cell/day for cells surrounded by sea ice. Daily abundance estimates ranged from 53 to 69 bears, with no trend across days. The cumulative number of unique bears that used the survey area increased through time due to movements into and out of the area, resulting in an estimated 171 individuals using the survey area during the study (95% credible interval 124–250). Abundance estimates were similar to a previous multiyear integrated population model using capture–recapture and telemetry data (2008–2016; Regehr et al., Scientific Reports 8:16780, 2018). Overall, the SCR–movement model successfully quantified both individual- and population-level space use, including the effects of landscape characteristics on movement, abundance, and detection, while linking the movement and abundance processes to directly estimate density within a prescribed spatial region and temporal period. Integrated SCR–movement models provide a generalizable approach to incorporate greater movement realism into population dynamics and link movement to emergent properties including spatiotemporal densities and abundances.

eastern Chukchi Sea↗
USGS2022

Cryptic population decrease due to invasive species predation in a long-lived seabird supports need for eradication

Invasive species are one of the greatest drivers of biodiversity loss worldwide, and the eradication of invasive species from islands is a highly efficient management strategy. Because eradication operations require large financial investments, uncertainty over the magnitude of impacts of both invasive species and their removal can impede the willingness of decision makers to invest in eradication. Such uncertainty is prevalent for long-lived species that display an inherent lag between life stages affected by invasive species and those used for population status assessments. Albatrosses are amongst the longest-living bird species and are threatened on land by invasive species and at sea by industrial fisheries. As in many seabird species, usually only a segment of the population (breeding adults) is used for status assessments, making it difficult to assess albatross population trends and the potential benefit of conservation action, such as the management of predatory invasive species. We used population monitoring and mark-recapture data to estimate the past population trajectory of the critically endangered Tristan albatross Diomedea dabbenena by accounting for unobservable birds at sea in an integrated population model. We then projected the future population trajectory of Tristan albatrosses for scenarios with or without predation by invasive house mice Mus musculus on their main breeding site, Gough Island. The adult breeding population remained stable between 2004 and 2021, but breeding success was low (31%) and our model indicated that the total population (including unobservable immature birds) decreased from a median estimate of 9,795 to 7,752 birds. Eradicating invasive mice leading to a two-fold increase in breeding success would result in a 1.8–7.6 times higher albatross population by 2050 (median estimate 10,352 individuals) than without this intervention. Low reproductive output for long-lived species may lead to a cryptic population decrease, which can be obscured from readily available counts of breeding pairs by changes in the population structure. Mouse eradication is necessary to halt the ongoing population decrease of the Tristan albatross, even if this decrease is not yet apparent in the breeding population size.

Gough Island↗
USGS2022

Using structured decision making to guide habitat restoration for butterflies: A case study of Oregon silverspots

When making decisions about how to restore habitat for at-risk species, land managers must balance multiple competing objectives in the face of uncertainty about the impacts of management actions on at-risk populations. The Oregon silverspot ( Speyeria = Argynnis zerene hippolyta ) is a federally threatened butterfly, and uncertainty exists about the effects of proposed management. We used structured decision making (SDM) to guide restoration for Oregon silverspots. Managers identified persistence as their primary objective and further identified effects of herbicides as a key uncertainty. We developed a model of population dynamics incorporating management actions and parameterized the model based on experiments with a surrogate subspecies, the Zerene silverspot ( S. z. zerene ). Herbicide application may directly harm Oregon silverspots by increasing larval mortality, while indirectly benefiting silverspots by reducing the competition faced by their host plant. In this system, potential herbicide treatments include grass-specific fluazifop-P-butyl or forb-specific clopyralid applied with Agri-Dex ® or Nu-Film ® -IR adjuvants. We found that Oregon silverspot population growth rate is greatest with clopyralid and fluazifop-P-butyl when combined with Nu-Film ® -IR than other alternatives (including no treatment) considering only direct effects or in combination with indirect effects. An adaptive management program would benefit Oregon silverspots by promoting exploration of management alternatives while allowing managers to act quickly to arrest steep declines. Uncertainty remains regarding how well our results will generalize in field conditions.

Journal of Insect Conservation↗
USGS2022

An introduction to decision science for conservation

Biodiversity conservation decisions are difficult, especially when they involve differing values, complex multidimensional objectives, scarce resources, urgency, and considerable uncertainty. Decision science embodies a theory about how to make difficult decisions and an extensive array of frameworks and tools that make that theory practical. We sought to improve conceptual clarity and practical application of decision science to help decision makers apply decision science to conservation problems. We addressed barriers to the uptake of decision science, including a lack of training and awareness of decision science; confusion over common terminology and which tools and frameworks to apply; and the mistaken impression that applying decision science must be time consuming, expensive, and complex. To aid in navigating the extensive and disparate decision science literature, we clarify meaning of common terms: decision science , decision theory , decision analysis , structured decision-making , and decision-support tools . Applying decision science does not have to be complex or time consuming; rather, it begins with knowing how to think through the components of a decision utilizing decision analysis (i.e., define the problem, elicit objectives, develop alternatives, estimate consequences, and perform trade-offs). This is best achieved by applying a rapid-prototyping approach. At each step, decision-support tools can provide additional insight and clarity, whereas decision-support frameworks (e.g., priority threat management and systematic conservation planning) can aid navigation of multiple steps of a decision analysis for particular contexts. We summarize key decision-support frameworks and tools and describe to which step of a decision analysis, and to which contexts, each is most useful to apply. Our introduction to decision science will aid in contextualizing current approaches and new developments, and help decision makers begin to apply decision science to conservation problems.

Conservation Biology↗