Geology topics

Anna Maureen Tucker

Publications and source records attributed to Anna Maureen Tucker.

7 recordsLinked to original sources

USGS2026

Floral resource availability and surrounding land cover influence bumble bee community composition in an agricultural landscape

Agricultural intensification and the loss of floral resources are suspected factors in bumble bee declines in North America. Understanding the effects of land use on bumble bee communities at the local and landscape scale is important to support conservation efforts. We surveyed 55 prairie and grassland sites in a highly agricultural landscape in 2023 and 2024. We used a multispecies occupancy model to estimate effects of site characteristics on both community-level and species-level occupancy probability. We also evaluated the relationship between species richness and the land cover within 1.6 km of sites. We detected 13 species of bumble bees, including four that are threatened or endangered. Bumble bee community occupancy probability was positively associated with local plant diversity ( β = 0.545, 95% CRI: 0.0293, 1.22) and was generally higher in more forested landscapes ( β = 0.530, 95% CRI: −0.0727, 1.24), but this varied greatly among species. Species richness was significantly lower at sites with high corn/soybean land cover (Spearman's rank correlation coefficient ρ = −0.318, 95% CRI: −0.570, −0.0705) and significantly greater at sites with high forest cover within 1.6 km ( ρ = 0.491, 95% CRI: 0.273, 0.687). Maintaining sites with a continuous availability of flowering plants during bumble bee foraging periods within proximity to forests may be an effective means of sustaining diverse bumble bee communities in highly agricultural landscapes.

Iowa↗

USGS2025

Stable occupancy of conservation-priority birds amid community shifts across 16 years on Iowa wetland easements

Intensive agriculture in the Prairie Pothole Region of Iowa, USA has resulted in significant wetland drainage and wildlife population declines. However, easement programs are increasingly used to protect and restore wetlands and revitalize biodiversity. Short-term responses (i.e., 1–5 years) of birds to wetland restorations are well-documented, but long-term trends are less understood. We surveyed wetland easements in Iowa during 2007–2009 and 2022–2023 to assess changes in breeding bird communities and occupancy for conservation-priority species. We conducted bird point counts and vegetation surveys at 55 wetland easements. We used species accumulation curves to estimate overall breeding bird richness by guild, and site-occupancy models to estimate occupancy for 20 conservation-priority species. Species richness remained stable between time periods, but community composition shifted, with fewer grassland and more forest bird species despite no change in woody vegetation cover estimates (2007–2009: 3.2%, standard deviation [SD] = 5.9; 2022–2023: 3.1%, SD = 3.8). Occupancy for most species at wetland easements remained stable over time; however, 4 species declined (e.g., Cistothorus stellaris [Sedge Wren]). Six grassland bird species (e.g., Sturnella magna [Eastern Meadowlark]) exhibited positive or stable occupancy trends. Forest-dependent species generally maintained or increased in occupancy (e.g., Icterus galbula [Baltimore Oriole]). Increased forest bird richness despite stable woody vegetation cover may indicate changing structural characteristics as existing forests mature, whereas management to control woody encroachment at wetland easements may explain our observations of stable forest bird occupancy. Wetland easements may be strongholds for some grassland bird species, which are in precipitous decline across North America. Our study highlights the importance of wetland easements in an agricultural landscape to breeding bird communities and emphasizes the value of continued monitoring to track changes over time.

Iowa↗

USGS2025

Effects of northern bobwhite habitat management on avian species of conservation concern

The umbrella species concept is often used as a tool to guide management decisions and focus efforts towards one focal species whose habitat needs overlap that of other species. We assessed this concept in the context of an agriculturally dominant landscape using one of the most well-studied avian species in North America as a target for conservation efforts: Northern Bobwhite ( Colinus virginianus ). This species is often viewed as an umbrella species for grassland and shrubland bird conservation throughout its native range due to its complex, year-round habitat requirements. We assessed the influence of Northern Bobwhite habitat management on six songbird species of conservation concern in Iowa by evaluating similarities and differences in habitat associations between each species. Our objectives were to (1) assess which vegetation characteristics were most strongly associated with Northern Bobwhite occupancy and (2) evaluate whether those characteristics were also associated with abundance of the focal songbird species. We used occupancy and N-mixture models to assess relationships between vegetation characteristics and Northern Bobwhite occupancy and songbird abundance, respectively. We found that the vegetation characteristics most strongly associated with Northern Bobwhite occupancy probability were the amounts of closed canopy forest, early successional woody vegetation, non-vegetated areas, and percent cover of bare ground. We found that for some of these covariates, including the amounts of forest and non-vegetated area, the effect on focal songbird species abundance aligned with Northern Bobwhite occupancy. For others, including the amount of early successional woody vegetation, the effects differed. This assessment of overlap and variability in habitat associations suggests that Northern Bobwhite-targeted management can provide benefits to other grassland and shrubland birds, but may also come with some trade-offs. This work adds to existing literature, further highlighting the nuances of the umbrella species concept in that land management benefits from the assessment of trade-offs and inclusion of local community dynamics.

Iowa↗

USGS2024

Best practices for incorporating climate change science into Department of the Interior analyses, consultations, and decision making

The purpose of this document is to provide technical guidance, practical application examples, and resource lists for those who conduct, manage, and/or interpret technical workflows within the Department of the Interior. This document is intended to support implementation of Department of the Interior policy 526 DM 1 and establish best practices for using climate change science to inform analysis, consultation, and decision making. The Earth’s climate is an interconnected system that distributes energy, heat, and water around the planet. Due to human-driven increases in long-lived greenhouse gases, the Earth’s climate is now changing. For Departmental decision-making purposes, assuming a static, unchanging baseline climate is no longer consistent with current knowledge about the climate system. There are uncertainties about future climate and how resources or assets (RoAs) will respond to new conditions. To depict the possibilities, the global climate science community develops scenarios and models to explore how future climate may respond to socioeconomic and technological development in the world. Principles for informing policy development, planning and decisions, and regulatory processes using climate change science must: 1) consider the effects of future climate change, 2) characterize the risks, and 3) characterize the uncertainties. Best practices include: Use multiple scenarios to assess risks from a range of plausible societal pathways. When constraints prevent the use of multiple scenarios or if decision makers are risk averse, ensure that the chosen scenario considers higher risk outcomes. This is particularly important for large investments or irreversible decisions and reduces the chances of overconfident decision making. Use multiple climate models within each scenario to account for the range of outcomes due to model uncertainty. Do not rely solely on a single model or an ensemble average. Use relevant climate data . Use a time-period for model projections of the future climate change consistent with the relevant timeframe of the policy, action, or decision being considered. Historical observations are useful for understanding past conditions and climate trends for the next several years, but not beyond the next decade. Consult with climate data and modeling experts to assess which data and model resources are most appropriate for any given application. Clearly describe key analysis uncertainties (including with any climate observations, models, and scenarios used), and how they were addressed in the analysis and/or decision process. This ensures transparency and learning among analysts and decision makers.

Report↗

USGS2023

Estimating recruitment rate and population dynamics at a migratory stopover site using an integrated population model

Consideration of the full annual cycle population dynamics can provide useful insight for conservation efforts, but collecting data needed to estimate demographic parameters is often logistically difficult. For species that breed in remote areas, monitoring is often conducted during migratory stopover or at nonbreeding sites, and the recruitment rate of new breeding adults can be difficult to estimate directly. Here, we present an integrated population model that uses mark-resight and count data to estimate survival probability, population growth rate, and recruitment rate for an Arctic-breeding shorebird of conservation concern, the red knot ( Calidris canutus rufa ), from data collected during spring stopover in Delaware Bay, USA, from 2005 to 2018. At this site, red knots feed primarily on the eggs of spawning horseshoe crabs ( Limulus polyphemus ), a legally harvested species. We used this model to estimate the relationship between horseshoe crab abundance and red knot demographics, which informed a recent revision to the framework used to establish horseshoe crab harvest regulations. Our analysis indicates that the red knot population was most likely stable from 2005 to 2018 (average λ = 1.03, 95% credible interval [CRI]: 0.961, 1.15) despite low recruitment rates (average ρ = 0.088, 95% CRI: 0.012, 0.18). Adult survival probability was positively associated with horseshoe crab abundance in the same year (β = 0.35, 95% CRI: 0.09, 0.63), but we found no effect of horseshoe crab abundance two years previously on recruitment of new adults (β = −0.08, 95% CRI: −0.41, 0.38). Our approach demonstrates the utility of integrated population models for understanding population dynamics, even when data are only available from migratory stopover monitoring.

Delaware, New Jersey↗

USGS2021

Decision context as an essential component of population viability analysis

Population viability analysis (PVA) is a widely used tool that applies demographic data in simulation frameworks to assess extinction risk for species or populations. It is used in diverse conservation applications, including evaluating management effectiveness, relative risk of threats, and potential changes to protective status (Beissinger & McCullough, 2002 ), and can be a critical tool for making decisions with imperfect knowledge of the system state, often on limited timelines (Meine et al., 2006 ). Chaudhary and Oli ( 2020 ) recently developed a framework to appraise the quality of PVAs based on the presence of essential background, model, and analysis components. They evaluated 160 published PVAs and reported a decline in the quality of PVAs over time (1990−2017). We agree PVA studies should report unambiguous descriptions of their essential components (Table 1 in Chaudhary and Oli) and explicitly state the model's biological and statistical assumptions. The need for increased transparency in PVAs is evident. Morrison et al. ( 2016 ) reported that only 50% of PVAs published in peer-reviewed and gray literature were both reproducible and repeatable. Further, in an examination of 67 studies that used matrix population models (widely used in PVAs), Kendall et al. ( 2019 ) reported that models frequently contained misspecification errors. Given the rapid advancement of simulation techniques, updated guidance for PVA construction is warranted. However, we believe the essential PVA components identified by Chaudhary and Oli contain a critical omission: the decision context in which the PVA was created and its usefulness in that context. Quality and utility are not mutually exclusive; however, some models that do not meet idealized quality standards might still be valuable because they are useful and represent the best available science for a given decision context (hereafter, decision-support models). The definition of quality for decision-support models should be different than models developed for the purpose of learning (hereafter, heuristic models) and should incorporate how useful the model was, despite information gaps. We further argue that assessment questions should be used prospectively to guide modeling projects, rather than for retrospective comparison of model quality.

Conservation Biology↗

USGS2021

Optimal strategies for managing wildlife harvest under climate change

Wildlife populations are experiencing shifting dynamics due to climate and landscape change. Management policies that fail to account for non‐stationary dynamics may fail to achieve management objectives. We establish a framework for understanding optimal strategies for managing a theoretical harvested population under non‐stationarity. Building from harvest theory, we develop scenarios representing changes in population growth rate ( ) or carrying capacity ( ) and derive time‐dependent optimal harvest policies using stochastic dynamic programming. We then evaluate the cost of falsely assuming stationarity by comparing the outcomes of forward projections in which either the optimal policy or a stationary policy is applied. When declines over time, the stationary policy leads to an underharvest of the population, resulting in less harvest over the short term but leaving the population in a higher‐value state. When declines over time, the stationary policy leads to overharvest, resulting in greater harvest returns in the short term but leaving the population in a lower and potentially more vulnerable state. This work demonstrates the basic properties of time‐dependent harvest management and provides a framework for evaluating the many outstanding questions about optimal management strategies under climate change. Published 2021. This article is a U.S. Government work and is in the public domain in the USA.

Journal of Wildlife Management↗