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Orin J. Robinson

Publications and source records attributed to Orin J. Robinson.

11 recordsLinked to original sources
USGS2026

Constructed value of information with iterative scoring and parametric uncertainty to identify management-relevant research priorities for a declining raptor species

Constructed value of information (CVoI) is an expert elicitation decision-analytic tool used to prioritize sources of uncertainty based on their potential to improve decision outcomes if resolved. Despite increased application of CVoI, the robustness of CVoI prioritization of sources of uncertainty relative to differences in expert elicitation and scoring methods has not been evaluated. We engaged a group of species experts in a decision-analytic process to elicit uncertainties, framed as alternative hypotheses, about current population declines of the American kestrel ( Falco sparverius ) in the United States. Participants scored 13 hypotheses across 3 CVoI criteria, which are defined as constructed scales. Rather than experts selecting a single score per criterion, we used a likelihood point method to incorporate parametric uncertainty in the scoring process, in which experts were given 100 points to distribute across possible score categories within the criterion-specific constructed scale. Experts provided scores over 2 scoring rounds, with an opportunity to review and discuss initial scores between rounds. We used a Shannon entropy calculation to quantify how evenly participants allotted their points. We used simulation to evaluate the robustness of our prioritization results relative to a scoring method in which participants selected a single score category for each criterion. Participants often spread their points across 2 adjacent scores, reflecting parametric uncertainty. For one third of the hypothesis-scoring round combinations, the prioritization results differed in approximately 50% of simulations. The highest scoring hypotheses related to how the use of artificial versus natural nest cavities affects fecundity or survival, whether winter roosting sites are a limiting factor for population growth, and whether gamebird habitat management may benefit kestrel populations. Our CVoI prioritization framework can be used to develop collaborative research that is directly relevant to a management decision and is an advance in eliciting more representative expert beliefs.

Conservation Biology↗
USGS2026

American kestrel population trends and vital rates at the continental scale

The American kestrel ( Falco sparverius , hereafter referred to as kestrel) has declined across much of its North American range since at least the mid-1960s. Kestrel population dynamics have been explored through a multitude of local studies and two broad reviews of available data. Across large geographic extents, however, the demographic cause(s) of kestrel population declines remain(s) largely unknown. As part of a collaborative effort to elucidate the drivers of kestrel population declines, we developed a continental-scale integrated population model using band-recovery data, productivity data, and Breeding Bird Survey indices from 1986 to 2019 to estimate indices of annual population sizes, survival, and productivity rates across the continental United States. We detected a decline in population size of ~1%–2% per year. Overall estimates of population growth from 1986 to 2019 suggest a 29% decline in population size (95% CI = −34% to −23%). There was little evidence of a trend in brood size. However, survival of juvenile birds (mean = −0.015, SD = 0.008 and mean = −0.024, SD = 0.010 for females and males, respectively) and adult males (mean = −0.016, SD = 0.010) in the summer declined, suggesting that these vital rates could be contributing to declines in populations over time. Winter adult survival rates (mean = −0.004, SD = 0.009 and mean = −0.009, SD = 0.010 for females and males, respectively) also declined but to a lesser extent than summer survival. For juvenile birds, winter survival increased (mean = 0.006, SD = 0.008 and mean = 0.002, SD = 0.009 for females and males, respectively); however, this was not enough to offset declines in summer survival and annual survival rates declined over the time series. Annual adult survival was also low relative to previous research on kestrel survival rates. Given the importance of survival to population trends, our findings provide support for several previously proposed broad classes of factors potentially contributing to observed population declines: declines in arthropod prey, second-generation rodenticides, neonicotinoid insecticides, and predation.

Ecosphere↗
USGS2025

Same view through a different lens: Comparing population trends for North American birds using eBird and the Breeding Bird Survey

Confidently estimating population trends is of vital importance for a wide range of ecological, conservation, and management applications. North America has 2 major data sources for estimating population trends of breeding birds—the North American Breeding Bird Survey (BBS) and the global participatory science project eBird. Because the surveys differ in protocols, coverage, and data analysis, their trend estimates are expected to vary in magnitude, direction, and/or precision for at least some species and regions. Here, we compare independently derived estimates of population change between 2012 and 2022 for every combination of species and bird conservation region (BCR) covered by both surveys ( n = 5,577 combinations) as well as aggregated across entire ranges or within the U.S. or Canada. Uncertainty was substantial for both surveys, though more prevalent for BBS (81% of credibility intervals for estimates included zero) than eBird (34% of confidence intervals overlapped zero). We found agreement of trend directions between the 2 surveys. Only 1.3% of estimated trends were significant in opposite directions between the 2 surveys for all species/BCR combinations, with the median difference in trend magnitude being –0.02% (BBS minus eBird trend). Correlations between the 2 were strongest for estimates that were graded as being high credibility compared to estimates judged to have medium or low credibility. Both surveys were subject to species, taxonomic, and regional effects that influenced agreement. Overall, we show where trend estimates derived from BBS and eBird agree, explore where they diverge, present several comparisons to assist in interpreting results from both surveys, and inform efforts to integrate information from each.

Ornithological Applications↗
USGS2023

Leveraging the strengths of citizen science and structured surveys to achieve scalable inference on population size

Population size is a key metric for management and policy decisions, yet wildlife monitoring programmes are often limited by the spatial and temporal scope of surveys. In these cases, citizen science data may provide complementary information at higher resolution and greater extent. We present a case study demonstrating how data from the eBird citizen science programme can be combined with regional monitoring efforts by the US Fish and Wildlife Service to produce high-resolution estimates of golden eagle abundance. We developed a model that uses aerial survey data from the western United States to calibrate high-resolution annual estimates of relative abundance from eBird. Using this model, we compared regional population size estimates based on the calibrated eBird information with those based on aerial survey data alone. Population size estimates based on the calibrated eBird information had strong correspondence to estimates from aerial survey data in two out of four regions, and population trajectories based on the two approaches showed high correlations. We demonstrate how the combination of citizen science data and targeted surveys can be used to (a) increase the spatial resolution of population size estimates, (b) extend the spatial extent of inference and (c) predict population size beyond the temporal period of surveys. Findings based on this case study can be used to refine policy metrics used by the US Fish and Wildlife Service and inform permitting regulations (e.g. mortality/harm associated with wind energy development). Policy implications : Our results demonstrate the ability of citizen science data to complement targeted monitoring programmes and improve the efficacy of decision frameworks that require information on population size or trajectory. After validating citizen science data against survey-based benchmarks, agencies can harness strengths of citizen science data to supplement information needs and increase the resolution and extent of population size predictions.

Journal of Applied Ecology↗
USGS2022

Leveraging community science data for population assessments during a pandemic

The COVID-19 pandemic has disrupted field research programs, making conservation and management decision-making more challenging. However, it may be possible to conduct population assessments using integrated models that combine community science data with existing data from structured surveys. We developed a space-time integrated model to characterize spatial and temporal variability in population distribution. We fit our integrated model to 10 years of eBird (2010-2020) and 9 years of aerial survey (2010-2019) mottled duck count data to forecast 2020 population size along the western Gulf Coast of Texas and Louisiana. Estimates of mottled duck abundance were similar in magnitude to estimates calculated using previous methods, but were more precise and showed evidence of a declining population. The spatial distribution for mottled ducks each year was characterized by several concentrations of relatively high abundance, although the location of these abundance ‘hotspots’ varied over time. Expected abundance was higher for areas with a higher proportion of area covered by marsh habitat. By leveraging large-scale community science data, we were able to conduct a population assessment despite the disruption in structured surveys caused by the pandemic. As participation in community science platforms continues to increase, we anticipate modeling frameworks, like the integrated model we developed here, will become increasingly useful for informing conservation and management decision-making.

Louisiana, Texas↗
USGS2018

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↗
USGS2016

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↗
USGS2016

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↗
USGS2016

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↗
USGS2016

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↗