Ecological and anthropogenic drivers of waterfowl productivity are synchronous across species, space, and time

Knowledge of interspecific and spatiotemporal variation in demography-environment relationships is key for understanding the population dynamics of sympatric species and developing multispecies conservation strategies. We used hierarchical random-effects models to examine interspecific and spatial variation in annual productivity in six migratory ducks (i.e., American wigeon [Mareca americana], blue-winged teal [Spatula discors], gadwall [Mareca strepera], green-winged teal [Anas crecca], mallard [Anas platyrhynchos] and northern pintail [Anas acuta]) across six distinct ecostrata in the Prairie Pothole Region of North America. We tested whether breeding habitat conditions (seasonal pond counts, agricultural intensification, and grassland acreage) or cross-seasonal effects (indexed by flooded rice acreage in primary wintering areas) better explained variation in the proportion of juveniles captured during late summer banding. The proportion of juveniles (i.e., productivity) was highly variable within species and ecostrata throughout 1961-2019 and generally declined through time in blue-winged teal, gadwall, mallard, pintail, and wigeon, but there was no support for a trend in green-winged teal. Productivity in Canadian ecostrata declined with increasing agricultural intensification and increased with increasing pond counts. We also found a strong cross-seasonal effect, whereby more flooded rice hectares during winter resulted in higher subsequent productivity. Our results suggest highly consistent environmental and anthropogenic effects on waterfowl productivity across species and space. Our study advances our understanding of current year and cross-seasonal effects on duck productivity across a suite of species and at finer spatial scales, which could help managers better target working-lands conservation programs on both breeding and wintering areas. We encourage other researchers to evaluate environmental drivers of population dynamics among species in a single modeling framework for a deeper understanding of whether conservation plans should be generalized or customized given limited financial resources.

Breeding populations of Marbled Godwits and Willets have high annual survival and strong site fidelity to managed wetlands

The Prairie Pothole Region of central Canada supports a diverse community of breeding waterbirds, but many species have declining populations and the demographic mechanisms driving the declines remain unknown. We conducted a 7-year field study during 1995-2001 to investigate the demographic performance of Marbled Godwits (Limosa fedoa) and Willets (Tringa semipalmata) breeding in managed wetlands near Brooks, Alberta. Mark-recapture analyses based on Cormack-Jolly-Seber models revealed that the annual rates of apparent survival for Marbled Godwits ( ϕ ^  = 0.953 ± 0.012SE) and Willets ( ϕ ^  = 0.861 ± 0.015SE) are among the highest rates of survivorship reported for any breeding or nonbreeding population of large-bodied shorebirds. Our estimates of life expectancy for males were comparable to longevity records in godwits (17.3 years ±5.8SE vs. 25-29+ years) and willets (7.7 ± 1.5SE vs. 10+ years). The two species both showed strong breeding site fidelity but differed in rates of mate fidelity. Pairs that reunited and males that switched mates usually nested <300 m from their previous nests, whereas females that switched mates usually moved longer distances >1.1-1.5 km. Returning pairs usually reunited in godwits (85%) but not in willets (28%), possibly because of species differences in adult survival or patterns of migration. Baseline estimates of annual survival for banded-only birds will be useful for evaluating the potential effects of new tracking tags or the environmental changes that have occurred during the past 20 years. Conservation strategies for large-bodied shorebirds should be focused on reduction of exposure to anthropogenic mortality because low rates of natural mortality suggest that losses to collisions at breeding sites or harvest at nonbreeding areas are likely to cause additive mortality.

Density-dependence produces spurious relationships among demographic parameters in a harvested species

Harvest of wild organisms is an important component of human culture, economy, and recreation, but can also put species at risk of extinction. Decisions that guide successful management actions therefore rely on the ability of researchers to link changes in demographic processes to the anthropogenic actions or environmental changes that underlie variation in demographic parameters. Ecologists often use population models or maximum sustained yield curves to estimate the impacts of harvest on wildlife and fish populations. Applications of these models usually focus exclusively on the impact of harvest and often fail to consider adequately other potential, often collinear, mechanistic drivers of the observed relationships between harvest and demographic rates. In this study, we used an integrated population model and long-term data (1973-2016) to examine the relationships among hunting and natural mortality, the number of hunters, habitat conditions, and population size of blue-winged teal Spatula discors, an abundant North American dabbling duck with a relatively fast-paced life history strategy. Over the last two and a half decades of the study, teal abundance tripled, hunting mortality probability increased slightly ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mo>&lt;</mml:mo> <mml:mn>0.02</mml:mn></mml:mrow> </mml:semantics> </mml:math> ), and natural mortality probability increased substantially ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mo>&gt;</mml:mo> <mml:mn>0.1</mml:mn></mml:mrow> </mml:semantics> </mml:math> ) at greater population densities. We demonstrate strong density-dependent effects on natural mortality and fecundity as population density increased, indicative of compensatory harvest mortality and compensatory natality. Critically, an analysis that only assessed the relationship between survival and hunting mortality would spuriously indicate depensatory mortality due to multicollinearity between abundance, natural mortality and hunting mortality. Our findings demonstrate that models that only consider the direct effect of hunting on survival or natural mortality can fail to accurately assess the mechanistic impact of hunting on population dynamics due to multicollinearity among demographic drivers. This multicollinearity limits inference and may have strong impacts on applied management actions globally.

Long-term trends and drought: Spatiotemporal variation in juvenile sex ratios of North American ducks

Sex ratios affect population dynamics and individual fitness, and changing sex ratios can be indicative of shifts in sex‐specific survival at different life stages. While climate and landscape changes alter sex ratios of wild bird populations, long‐term, landscape scale assessments of sex ratios are rare. Further, little work has been done to understand changes in sex ratios in avian communities. In this manuscript, we analyze long‐term (1961–2015) data on five species of ducks across five broad climatic regions of the United States to estimate the effects of drought and long‐term trends on the proportion of juvenile females captured at banding. As waterfowl have a 1:1 sex ratio at hatch, we interpret changes in sex ratios of captured juveniles as changes in sex‐specific survival rates during early life. Seven of 12 species‐region pairs exhibited evidence for long‐term trends in the proportion of juvenile females at banding. The proportion of juvenile females at banding increased for duck populations in the western United States and typically declined for duck populations in the eastern United States. We only observed evidence for an effect of drought in two of the 12 species‐region pairs, where the proportion of females declined during drought. As changes to North American landscapes and climate continue and intensify, we expect continued changes in sex‐specific juvenile survival rates. More broadly, we encourage further research examining the mechanisms underlying long‐term trends in juvenile sex ratios in avian communities.

A hierarchical model for jointly assessing ecological and anthropogenic impacts on animal demography

The management of sustainable harvest of animal populations is of great ecological and conservation importance. Development of formal quantitative tools to estimate and mitigate the impacts of harvest on animal populations has positively impacted conservation efforts. The vast majority of existing harvest models, however, do not simultaneously estimate ecological and harvest impacts on demographic parameters and population trends. Given that the impacts of ecological drivers are often equal to or greater than the effects of harvest, and can covary with harvest, this disconnect has the potential to lead to flawed inference. In this study, we used Bayesian hierarchical models and a 43-year capture-mark-recovery dataset from 404,241 female mallards Anas platyrhynchos released in the North American midcontinent to estimate mallard demographic parameters. Furthermore, we model the dynamics of waterfowl hunters and habitat, and the direct and indirect effects of anthropogenic and ecological processes on mallard demographic parameters. We demonstrate that density dependence, habitat conditions and harvest can simultaneously impact demographic parameters of female mallards, and discuss implications for existing and future harvest management models. Our results demonstrate the importance of controlling for multicollinearity among demographic drivers in harvest management models, and provide evidence for multiple mechanisms that lead to partial compensation of mallard harvest. We provide a novel model structure to assess these relationships that may allow for improved inference and prediction in future iterations of harvest management models across taxa.

A niche for null models in adaptive resource management

As global systems rapidly change, our collective ability to predict future ecological dynamics will become increasingly important for successful natural resource management. By merging stakeholder objectives with system uncertainty, and by adapting actions to changing systems and knowledge, adaptive resource management (ARM) provides a rigorous platform for making sound decisions in a changing world. Critically, however, applications of ARM could be improved by employing benchmarks (i.e., points of reference) for determining when learning is occurring through the cycle of monitoring, modeling, and decision-making steps in ARM. Many applications of ARM use multiple model-based hypotheses to identify and reduce systematic uncertainty over time, but generally lack benchmarks for gauging discovery of scientific evidence and learning. This creates the danger of thinking that directional changes in model weights or rankings are indicative of evidence for hypotheses, when possibly all competing models are inadequate. There is thus a somewhat obvious, but yet to be filled niche for including benchmarks for learning in ARM. We contend that carefully designed "ecological null models," which are structured to produce an expected ecological pattern in the absence of a hypothesized mechanism, can serve as suitable benchmarks. Using a classic case study of mallard harvest management that is often used to demonstrate the successes of ARM for learning about ecological mechanisms, we show that simple ecological null models, such as population persistence (Nt +1 = Nt ), provide more robust near-term forecasts of population abundance than the currently used mechanistic models. More broadly, ecological null models can be used as benchmarks for learning in ARM that trigger the need for discarding model parameterizations and developing new ones when prevailing models underperform the ecological null model. Identifying mechanistic models that surpass these benchmarks will improve learning through ARM and help decision-makers keep pace with a rapidly changing world.

Community science validates climate suitability projections from ecological niche modeling

Climate change poses an intensifying threat to many bird species and projections of future climate suitability provide insight into how species may shift their distributions in response. Climate suitability is characterized using ecological niche models (ENMs), which correlate species occurrence data with current environmental covariates and project future distributions using the modeled relationships together with climate predictions. Despite their widespread adoption, ENMs rely on several assumptions that are rarely validated in situ and can be highly sensitive to modeling decisions, precluding their reliability in conservation decision-making. Using data from a novel, large-scale community science program, we developed dynamic occupancy models to validate near-term climate suitability projections for bluebirds and nuthatches in summer and winter. We estimated occupancy, colonization, and extinction dynamics across species' ranges in the United States in relation to projected climate suitability in the 2020s, and used a Gibbs variable selection approach to quantify evidence of species-climate relationships. We also included a Bird Conservation Region strata-level random effect to examine among-strata variation in occupancy that may be attributable to land-use and ecoregional differences. Across species and seasons, we found strong evidence that initial occupancy and colonization were positively related to 2020 climate suitability, illustrating an independent validation of projections from ENMs across a large geographic area. Random strata effects revealed that occupancy probabilities were generally higher than average in core areas and lower than average in peripheral areas of species' ranges, and served as a first step in identifying spatial patterns of occupancy from these community science data. Our findings lend much-needed support to the use of ENM projections for addressing questions about potential climate-induced changes in species' occupancy dynamics. More broadly, our work highlights the value of community scientist observations for ground-truthing projections from statistical models and for refining our understanding of the processes shaping species' distributions under a changing climate.

Using value of information to prioritize research needs for migratory bird management under climate change: a case study using federal land acquisition in the United States

In response to global habitat loss, many governmental and non-governmental organizations have implemented land acquisition programs to protect critical habitats permanently for priority species. The ability of these protected areas to meet future management objectives may be compromised if the effects of climate change are not considered in acquisition decisions. Unfortunately, the effects of climate change on ecological systems are complex and plagued by uncertainty, making it difficult for organizations to prioritize research needs to improve decision-making. Herein, we demonstrate the use of qualitative value of information analysis to identify and prioritize which sources of uncertainty should be reduced to improve land acquisition decisions to protect migratory birds in the face of climate change. The qualitative value of information analysis process involves four steps: (i) articulating alternative hypotheses; (ii) determining the magnitude of uncertainty regarding each hypothesis; (iii) evaluating the relevance of each hypothesis to acquisition decision-making; and (iv) assessing the feasibility of reducing the uncertainty surrounding each hypothesis through research and monitoring. We demonstrate this approach using the objectives of 3 U.S. federal land acquisition programs that focus on migratory bird management. We used a comprehensive literature review, expert elicitation, and professional judgement to evaluate 11 hypotheses about the effect of climate change on migratory birds. Based on our results, we provide a list of priorities for future research and monitoring to reduce uncertainty and improve land acquisition decisions for the programs considered in our case study. Reducing uncertainty about how climate change will influence the spatial distribution of priority species and biotic homogenization were identified as the highest priorities for future research due to both the value of this information for improving land acquisition decisions and the feasibility of reducing uncertainty through research and monitoring. Research on how changes in precipitation patterns and winter severity will influence migratory bird abundance is also expected to benefit land acquisition decisions. By contrast, hypotheses about phenology and migration distance were identified as low priorities for research. By providing a rigorous and transparent approach to prioritizing research, we demonstrate that qualitative value of information is a valuable tool for prioritizing research and improving management decisions in other complex, high-uncertainty cases where traditional quantitative value of information analysis is not possible. Given the inherent complexity of ecological systems under climate change, and the difficulty of identifying management-relevant research priorities, we expect this approach to have wide applications within the field of natural resource management.