Geology topics

Eric V. Lonsdorf

Publications and source records attributed to Eric V. Lonsdorf.

8 recordsLinked to original sources

USGS2023

Marginal value analysis reveals shifting importance of migration habitat for waterfowl under a changing climate

Migratory waterfowl are an important resource for consumptive and non-consumptive users alike and provide tremendous economic value in North America. These birds rely on a complex matrix of public and private land for forage and roosting during migration and wintering periods, and substantial conservation effort focuses on increasing the amount and quality of target habitat. Yet, the value of habitat is a function not only of a site's resources but also of its geographic position and weather. To quantify this value, we used a continental-scale energetics-based model of daily dabbling duck movement to assess the marginal value of lands across the contiguous United States during the non-breeding period (September to May). We examined effects of eliminating each habitat node (32 × 32 km) in both a particularly cold and a particularly warm winter, asking which nodes had the largest effect on survival. The marginal value of habitat nodes for migrating dabbling ducks was a function of forage and roosting habitat but, more importantly, of geography (especially latitude and region). Irrespective of weather, nodes in the Southeast, central East Coast, and California made the largest positive contributions to survival. Conversely, nodes in the Midwest, Northeast, Florida, and the Pacific Northwest had consistent negative effects. Effects (positive and negative) of more northerly nodes occurred in late fall or early spring when climate was often severe and was most variable. Importance and effects of many nodes varied considerably between a cold and a warm winter. Much of the Midwest and central Great Plains benefited duck survival in a warm winter, and projected future warming may improve the value of lands in these regions, including many National Wildlife Refuges, for migrating dabbling ducks. Our results highlight the geographic variability in habitat value, as well as shifts that may occur in these values due to climate change.

Ecology and Evolution↗

USGS2022

Effects of weather variation on waterfowl migration: Lessons from a continental-scale generalizable avian movement and energetics model

We developed a continental energetics-based model of daily mallard ( Anas platyrhynchos ) movement during the non-breeding period (September to May) to predict year-specific migration and overwinter occurrence. The model approximates movements and stopovers as functions of metabolism and weather, in terms of temperature and frozen precipitation (i.e., snow). The model is a Markov process operating at the population level and is parameterized through a review of literature. We applied the model to 62 years of daily weather data for the non-breeding period. The average proportion of available habitat decreased as weather severity increased, with mortality decreasing as the proportion of available habitat increased. The most commonly used locations during the course of the non-breeding period were generally consistent across years, with the most inter-annual variation present in the overwintering area. Our model revealed that the distribution of mallards on the landscape changed more dramatically when the variation in daily available habitat was greater. The main routes for avian migration in North America were predicted by our simulations: the Atlantic, Mississippi, Central, and Pacific flyways. Our model predicted an average of 77.4% survivorship for the non-breeding period across all years (range = 76.4%–78.4%), with lowest survivorship during autumn (90.5 ± 1.4%), intermediate survivorship in winter (91.8 ± 0.7%), and greatest survivorship in spring (93.6 ± 1.1%). We provide the parameters necessary for exploration within and among other taxa to leverage the generalizability of this migration model to a broader expanse of bird species, and across a range of climate change and land use/land cover change scenarios.

Ecology and Evolution↗

USGS2020

Cooperatively improving tallgrass prairie with adaptive management

Adaptive management (AM) is widely recommended as an approach for learning to improve resource management, but successful AM projects remain relatively uncommon, with few documented examples applied by natural resource management agencies. We used AM to make recommendations for the management of native tallgrass prairie plant communities in western Minnesota and eastern North and South Dakota, USA. After nine years of data collection and learning, we report on whether the condition of the prairie improved with management and which actions and frequency of action allowed improvement. Our approach to AM employed Bayesian updating to generate annual management recommendations at a site and state-dependent scale. We also used a logistic regression approach to complement the output from the AM model and evaluate the more general conditions which led to attaining management goals. Overall, the cover of native plants increased for low-quality sites, and among the management practices considered, we found that burning most effectively enhanced the native prairie plant community and increased the dominance of native indicator species. Contrary to expectations, the results also suggest that grazing on sites that started in a poor condition were less likely to show improvements in the native plant community. Complementing AM with more traditional statistical analyses can help inform the iterative doubleloop learning phase of the AM framework. AM has many challenges, but we demonstrate that multi-agency AM can be successful. Keys to success include starting the project with an in-person, in-depth workshop; standardized protocols and a centralized database; a core project team with multi-disciplinary backgrounds; stability in project leadership; and regular communication to meet annual deadlines.

Minnesota, North Dakota, South Dakota↗

USGS2019

Pesticides and pollinators: A socioecological synthesis

The relationship between pesticides and pollinators , while attracting no shortage of attention from scientists, regulators, and the public, has proven resistant to scientific synthesis and fractious in matters of policy and public opinion. This is in part because the issue has been approached in a compartmentalized and intradisciplinary way, such that evaluations of organismal pesticide effects remain largely disjoint from their upstream drivers and downstream consequences. Here, we present a socioecological framework designed to synthesize the pesticide-pollinator system and inform future scholarship and action. Our framework consists of three interlocking domains-pesticide use, pesticide exposure, and pesticide effects–each consisting of causally linked patterns, processes, and states. We elaborate each of these domains and their linkages, reviewing relevant literature and providing empirical case studies. We then propose guidelines for future pesticide-pollinator scholarship and action agenda aimed at strengthening knowledge in neglected domains and integrating knowledge across domains to provide decision support for stakeholders and policymakers. Specifically, we emphasize (1) stakeholder engagement, (2) mechanistic study of pesticide exposure, (3) understanding the propagation of pesticide effects across levels of organization, and (4) full-cost accounting of the externalities of pesticide use and regulation. Addressing these items will require transdisciplinary collaborations within and beyond the scientific community, including the expertise of farmers, agrochemical developers, and policymakers in an extended peer community.

Science of the Total Environment↗

USGS2018

Modeling golden eagle‐vehicle collisions to design mitigation strategies

The incidental take of golden eagles ( Aquila chrysaetos ) as a result of wind energy development requires some form of compensatory mitigation. Although several options have been proposed, only one has been formerly accepted and implemented, and the lack of options can limit the permit process for wind facilities. We developed a model to estimate numbers of golden eagles that die when struck by vehicles when eagles scavenge road kill to evaluate removal of road‐killed carcasses as an additional mitigation option. Our model estimates vehicle collision rates as a function of eagle densities, road traffic volume, and animal carcass abundance at the scale of a Wyoming, USA, county during fall‐winter, and quantifies the effects of different mitigation strategies, including estimates of uncertainty. We evaluated the plausibility of our model estimates by predicting mortality rates for each county in Wyoming and comparing overall state mortality to current estimates of mortality using derived estimates from expert judgment. We also developed a context‐dependent analysis of potential mitigation credits controlling for carcass number, traffic volume, and background carcass removals. We found that mitigation credit should be highest in areas with greatest number of carcasses. Collision mitigation is a potentially useful addition to the mitigation toolbox for wind energy development or other activities that need to offset predicted golden eagle mortality and satisfy incidental take permit requirements.

Wyoming↗

USGS2016

A generalizable energetics-based model of avian migration to facilitate continental-scale waterbird conservation

Conserving migratory birds is made especially difficult because of movement among spatially disparate locations across the annual cycle. In light of challenges presented by the scale and ecology of migratory birds, successful conservation requires integrating objectives, management, and monitoring across scales, from local management units to ecoregional and flyway administrative boundaries. We present an integrated approach using a spatially explicit energetic-based mechanistic bird migration model useful to conservation decision-making across disparate scales and locations. This model moves a mallard-like bird (Anas platyrhynchos), through spring and fall migration as a function of caloric gains and losses across a continental scale energy landscape. We predicted with this model that fall migration, where birds moved from breeding to wintering habitat, took a mean of 27.5 days of flight with a mean seasonal survivorship of 90.5% (95% CI = 89.2%, 91.9%) whereas spring migration took a mean of 23.5 days of flight with mean seasonal survivorship of 93.6% (95% CI = 92.5%, 94.7%). Sensitivity analyses suggested that survival during migration was sensitive to flight speed, flight cost, the amount of energy the animal could carry and the spatial pattern of energy availability, but generally insensitive to total energy availability per se. Nevertheless, continental patterns in the bird-use days occurred principally in relation to wetland cover and agricultural habitat in the fall. Bird-use days were highest in both spring and fall in the Mississippi Alluvial Valley and along the coast and near-shore environments of South Carolina. Spatial sensitivity analyses suggested that locations nearer to migratory endpoints were less important to survivorship; for instance, removing energy from a 1,036 km2 stopover site at a time from the Atlantic Flyway suggested coastal areas between New Jersey and North Carolina, including Chesapeake Bay and the North Carolina piedmont, are essential locations for efficient migration and increasing survivorship during spring migration but not locations in Ontario and Massachusetts. This sort of spatially explicit information may allow decision-makers to prioritize their conservation actions toward locations most influential to migratory success. Thus, this mechanistic model of avian migration provides a decision-analytic medium integrating the potential consequences of local actions to flyway-scale phenomena.

Ecological Applications↗

USGS2016

A decision support tool for adaptive management of native prairie ecosystems

The Native Prairie Adaptive Management initiative is a decision support framework that provides cooperators with management-action recommendations to help them conserve native species and suppress invasive species on prairie lands. We developed a Web-based decision support tool (DST) for the U.S. Fish and Wildlife Service and the U.S. Geological Survey initiative. The DST facilitates cross-organizational data sharing, performs analyses to improve conservation delivery, and requires no technical expertise to operate. Each year since 2012, the DST has used monitoring data to update ecological knowledge that it translates into situation-specific management-action recommendations (e.g., controlled burn or prescribed graze). The DST provides annual recommendations for more than 10,000 acres on 20 refuge complexes in four U.S. states. We describe how the DST promotes the long-term implementation of the program for which it was designed and may facilitate decision support and improve ecological outcomes of other conservation efforts.

Interfaces↗

USGS2015

Strategic Grassland Bird Conservation throughout the annual cycle: Linking policy alternatives, landowner decisions, and biological population outcomes

Grassland bird habitat has declined substantially in the United States. Remaining grasslands are increasingly fragmented, mostly privately owned, and vary greatly in terms of habitat quality and protection status. A coordinated strategic response for grassland bird conservation is difficult, largely due to the scope and complexity of the problem, further compounded by biological, sociological, and economic uncertainties. We describe the results from a collaborative Structured Decision Making (SDM) workshop focused on linking social and economic drivers of landscape change to grassland bird population outcomes. We identified and evaluated alternative strategies for grassland bird conservation using a series of rapid prototype models. We modeled change in grassland and agriculture cover in hypothetical landscapes resulting from different landowner decisions in response to alternative socio-economic conservation policy decisions. Resulting changes in land cover at all three stages of the annual cycle (breeding, wintering, and migration) were used to estimate changes in grassland bird populations. Our results suggest that successful grassland bird conservation may depend upon linkages with ecosystem services on working agricultural lands and grassland-based marketing campaigns to engage the public. With further development, spatial models that link landowner decisions with biological outcomes can be essential tools for making conservation policy decisions. A coordinated non-traditional partnership will likely be necessary to clearly understand and systematically respond to the many conservation challenges facing grassland birds.

PLoS ONE↗