USGS ScienceSearch

Geology topics

Laura D’Acunto

Publications and source records attributed to Laura D’Acunto.

14 recordsLinked to original sources

Predicting niche spaces of expanding Evening Bat (Nycticeius humeralis) populations following white-nose syndrome establishment

Observations of the Evening Bat ( Nycticeius humeralis ), a species historically distributed abundantly throughout the southeastern United States, are speculated to have increased in the Midwest. One hypothesis for this expansion in geographic distribution is that local extirpations of other bat species resulted in the expanded realized niche spaces for evening bats. In Indiana, such niche spaces may have been created by declines in populations of the Northern Long-eared Bat ( Myotis septentrionalis ), Indiana Bat ( M. sodalis ), Little Brown Bat ( M. lucifugus ), Big Brown Bat ( Eptesicus fuscus ), and the Tri-colored Bat ( Perimyotis subflavus ) due to white-nose syndrome (WNS). Our goal was to estimate the occupancy of Evening Bat in Indiana post-WNS establishment relative to the occupancy of other bat species before significant population declines caused by WNS. We expected that indices of occupancy of nearly extirpated species pre-WNS establishment would best predict current Evening Bat observations, and this would elucidate the niche space evening bats are now filling. We hypothesized that Evening Bat populations may be expanding their geographic range due to compensatory community dynamics, and that their realized niche space may be expanding in part due to losses of other bat species from WNS. We constructed multi-season Bayesian occupancy models using informative priors and integrative prior knowledge to test our predictions. We found that evening bats are occupying the niche space they were already occupying pre-WNS establishment. Furthermore, our results indicate that evening bats may be filling the niche space left behind by Myotis spp. ( M. sodalis and M. lucifigus ). These results can help us understand the dynamics of bat communities in a post-WNS establishment landscape and may also help to inform conservation of imperiled Myotis species.

Journal of Mammalogy

Restoring the Florida Everglades: Insights on integrating sea level rise into decision-support tools

Although coastal ecosystems are impacted by climate change and sea-level rise, many ecological and hydrological models do not yet incorporate sea-level rise projections in their modeling outputs. Therefore, this research examined the various challenges that may prevent sea-level rise from being effectively incorporated in modeling and decision-support tools. We conducted semi-structured interviews with twenty-six professionals involved in Florida’s Everglades restoration. We applied the Diffusions of Innovations Theory to better understand factors that can impact practitioners’ adoption of newly designed decision-support tools that examine sea-level rise in the freshwater Everglades. The Diffusions of Innovations Theory provided insights into practitioners’ perceptions of these tools. We found that these practitioners have a strong interest in using dynamic decision-support tools to plan for sea-level rise impacts on Everglades restoration, particularly when they receive information at appropriate geographic and temporal scales and are given hands-on tools and training. However, challenges that prevent developing these tools include outdated data, limited organizational capacity and funding, limited use of long-term indicators, uncertainty about climate change impacts on local ecosystems, and lack of integration between hydrological and ecological models. Our research also highlights that greater availability of different types of tools can help to meet the needs of the scientific and non-scientific audiences involved in Everglades restoration.

Florida

Linking environmental variability to long-term demographic change of an endangered species using integrated population models

Understanding how species populations change with environmental conditions is important for implementing effective habitat management and conservation strategies. Challenges to evaluating population-level responses to environmental conditions arise when data are sparse or not spatiotemporally aligned, especially for at-risk species with small, declining numbers. We synthesized 30 years (1992–2021) of three partially aligned data sets to build a Bayesian integrated population model (IPM) and evaluate demographic and environmental drivers of growth rates for six separately managed ‘subpopulations’ (A–F) of the federally endangered Cape Sable seaside sparrow endemic to the Florida Everglades. We found that juvenile survival peaked at inundation periods (hydroperiods) around 100–220 days and dropped sharply outside those values, while adult survival increased with longer periods of water depth <20 cm, but not with longer periods of water depth >20 cm. Fecundity increased when water depths were more stable, more area was dry, intervals between fires were longer and less area was burned. Changes in population growth rates tended to occur in years that juvenile and adult survival were associated with hydroperiod, especially in the two largest subpopulations B and E. Population growth rates were also associated with hydrologic conditions during the breeding season and fire dynamics through changes in fecundity, most notably in the smaller subpopulations A, C/F and D. Synthesis and applications . Our IPM represents the first long-term population analysis of the Cape Sable seaside sparrow connecting demographic processes to environmental factors. Our results suggest that sustaining periods of shallow water year-round may enhance Cape Sable seaside sparrow survival and population growth. Also, limiting water depth variability and maintaining dry conditions during the breeding season and inhibiting fires in consecutive years may increase fecundity and population growth. Identifying the mechanistic links between environmental and population dynamics could inform how species are expected to respond to management decisions and anticipated ecosystem changes.

Florida

Integrating sea level rise scenarios into Everglades restoration planning

One of the largest and most expensive restoration efforts in the world is occurring in the Everglades, a sub-tropical freshwater wetland system located in southern Florida. This unique ecosystem supports several endangered species, provides flood control for Florida’s large urban population, and provides water for both agriculture and drinking supply within the state. The Comprehensive Everglades Restoration Plan (CERP), authorized by Congress in 2000, guides federal, state, and local efforts to build the infrastructure necessary to bring more water into the Everglades and restore its ecological integrity, while balancing other water-related needs such as water supply and flood protection in the human environment. The Everglades encompasses the southern coast of Florida and restoration efforts are likely to be impacted by climate-induced sea level rise. However, currently, many project planning studies do not formally incorporate the potential impacts of sea level rise when evaluating restoration plan outcomes. Resource managers and project planners require methods and tools to confidently incorporate scenarios of sea level rise into their evaluations. The U.S. Geological Survey (USGS) and partners from the University of Florida worked with project planners from multiple agencies to identify restoration questions for consideration when addressing sea level rise. In addition, our project team sought to understand the types of sea level rise decision-support tools that would be of interest, and then worked with Everglades restoration managers and project planners to develop those tools. The tools developed by this project can be used by project planners to inform their decision-making abilities when considering multiple restoration plans across the Everglades landscape. Specifically, the novel ways to visualize output information from ecological models that came of this project can help project planners compare alternative restoration plans that include potential sea level rise impacts. This effort demonstrates how incorporating sea level rise scenarios into Everglades restoration project planning can help managers decide whether projects will maintain or improve ecological integrity and evaluate water availability for wildlife and humans.

Final Report

Temporal habitat use of mule deer in the Pueblo of Santa Ana, New Mexico

Mule deer ( Odocoileus hemionus ) are important economically, culturally, and recreationally to the Pueblo of Santa Ana in central New Mexico, USA. Studies of habitat selection improve our understanding of mule deer ecology in central New Mexico and provide the Tribe with valuable information for management of mule deer. We used global positioning system telemetry-collar data collected on mule deer around the Pueblo of Santa Ana to create resource selection functions from proximity-based habitat predictors using a generalized linear mixed model. We created separate resource selection functions for females and males during summer and winter at different times of the day. Season generally had a greater effect on mule deer habitat use than the time of day. Female and male mule deer selected for similar habitats but were sexually segregated in their summer distributions. These findings are consistent with results from other locations where mule deer partitioned habitat similarly between seasons and sexes. Supported models reaffirm accepted patterns of habitat selection for mule deer to the Pueblo of Santa Ana where local results were lacking. Our results can help managers identify locations in and around the Pueblo of Santa Ana where future development such as highway expansion are likely to conflict with mule deer activity and locations where habitat enhancement projects such as adding water sources can have the greatest effect for the deer population.

New Mexico

Bobcat occupancy, tree islands, and invasive Burmese pythons in an Everglades conservation area

Bobcats ( Lynx rufus ) are terrestrial mammals that also inhabit tree islands (i.e., topographically elevated patches of forested land) embedded in the subtropical Everglades wetlands, which serve as a dry refuge habitat during the wet season in this region of Florida, USA. The Comprehensive Everglades Restoration Plan seeks to restore Everglades water flow to pre-drainage conditions, but little is known about how water levels or other landscape-level factors may influence mammalian occurrence, such as bobcats, on the tree islands in this ecosystem. We used game camera records and occupancy modeling to test for effects of static habitat variables and dynamic hydrologic variables. We hypothesized that deep water levels would limit the accessibility of tree islands to bobcats; therefore, we predicted that bobcat occupancy would decline with higher water levels. We also tested for the effect of an expanding invasive snake (i.e., Burmese python [ Python molarus bivittatus ]) using output from a model constructed to predict density and spread of Burmese pythons across southern Florida. We hypothesized that increases in Burmese pythons on the landscape would influence the food resources of bobcats, resulting in reduced bobcat occupancy at higher predicted densities of pythons. We built detection histories using 1,855 bobcat images from game cameras set on 87 tree islands in an Everglades conservation area from 2005–2019. Bobcat occupancy was significantly diminished when predicted Burmese python densities exceeded approximately 3 Burmese pythons/km 2 . Bobcat occupancy probability also increased with tree-island density around the focal tree island. Although water depth and hydroperiod surrounding tree islands appeared in our top 3 candidate models, the hydrologic variables had weak effects on bobcat occupancy. Our results suggest that while hydrologic dynamics may play a role, the invasive Burmese python has stronger influences on bobcat occupancy of tree islands in this Everglades conservation area.

Florida

The Everglades vulnerability analysis: Linking ecological models to support ecosystem restoration

Understanding of the Everglades’ ecological vulnerabilities and restoration needs has advanced over the past decade but has not been applied in an integrated manner. To address this need, we developed the Everglades Vulnerability Analysis (EVA), a decision support tool that uses modular Bayesian networks to predict the ecological outcomes of a subset of the ecosystem’s health indicators. This tool takes advantage of the extensive modeling work already done in the Everglades and synthesizes information across indicators of ecosystem health to forecast long-term, landscape-scale changes. In addition, the tool can predict indicator vulnerability through comparison to user-defined ideal system states that can vary in the level of certainty of outcomes. An integrated understanding of the Everglades system is essential for evaluation of trade-offs at local, regional, and system-wide scales. Through EVA, Everglades restoration decision makers can provide effective guidance during restoration planning and implementation processes to mitigate unintended consequences that could result in further damage to the Everglades system.

Florida

Nest-site selection model for endangered Everglade snail kites to inform ecosystem restoration

dictors of nesting for snail kites in south Florida. The results of our modeling indicate that hydrology, percent canopy cover, and proximity to recently burned areas were the most important factors associated with nest-site selection for snail kites. Water depths between 75 and 100 cm, water recession rates between 0 and 1.25 cm/day, percent canopy covers <20%, and areas <10 km from recently burned habitat were associated with the greatest likelihood of nest-site selection. KiteNest is applicable to natural resource management decisions in the Everglades and may be useful independently or in conjunction with other ecological models for restoration decision support.

Florida

Long-term demographic analysis of the Cape Sable seaside sparrow (1992–2021)

The Cape Sable seaside sparrow (Ammospiza maritima mirabilis) is an endangered species that has experienced a population decline of more than 60% since 1981. Despite its critical population status, a statistically robust analysis of the species’ demographic rates utilizing all data has yet to be completed (Benscoter et al. 2021). Furthermore, long-term population processes in response to hydrologic and environmental conditions have not been evaluated for this species. To address these substantial gaps in knowledge, 30 years of demographic data were synthesized to assess population dynamics of this imperiled species using an integrated population model (IPM). Three demographic data types (range-wide counts, capture-mark-recapture, nest monitoring) were incorporated into a unified IPM to evaluate demographic processes and predict population trajectories. The following were calculated: (1) annual estimates of annual population size, survival, and fecundity; (2) coefficient estimates of hydrologic and environmental variables on survival and fecundity; (3) estimates of annual population growth and their correlation with demographic rates; and (4) a Bayesian population viability analysis (BPVA) that includes predicted population size, demographic rates, and extinction risks ten years into the future.

Report

Joint species distribution models of Everglades wading birds to inform restoration planning

Restoration of the Florida Everglades, a substantial wetland ecosystem within the United States, is one of the largest ongoing restoration projects in the world. Decision-makers and managers within the Everglades ecosystem rely on ecological models forecasting indicator wildlife response to changes in the management of water flows within the system. One such indicator of ecosystem health, the presence of wading bird communities on the landscape, is currently assessed using three species distribution models that assume perfect detection and report output on different scales that are challenging to compare against one another. We sought to use current advancements in species distribution modeling to improve models of Everglades wading bird distribution. Using a joint species distribution model that accounted for imperfect detection, we modeled the presence of nine species of wading bird simultaneously in response to annual hydrologic conditions and landscape characteristics within the Everglades system. Our resulting model improved upon the previous model in three key ways: 1) the model predicts probability of occupancy for the nine species on a scale of 0–1, making the output more intuitive and easily comparable for managers and decision-makers that must consider the responses of several species simultaneously; 2) through joint species modeling, we were able to consider rarer species within the modeling that otherwise are detected in too few numbers to fit as individual models; and 3) the model explicitly allows detection probability of species to be less than 1 which can reduce bias in the site occupancy estimates. These improvements are essential as Everglades restoration continues and managers require models that consider the impacts of water management on key indicator wildlife such as the wading bird community.

Florida

Landscape-scale drivers of endangered Cape Sable Seaside Sparrow (Ammospiza maritima mirabilis) presence using an ensemble modeling approach

The Florida Everglades is a vast and iconic wetland ecosystem in the southern United States that has undergone dramatic changes from habitat degradation, development encroachment, and water impoundment. Starting in the past few decades, large restoration projects have been undertaken to restore the landscape, including improving conditions for threatened and imperiled taxa. One focus of restoration has been the marl prairie ecosystem, where the federally endangered Cape Sable Seaside Sparrow ( Ammospiza maritima mirabilis ; CSSS) resides. The CSSS is endemic to the Everglades where populations have been steadily declining, signaling the importance of decision support tools for natural resource managers for evaluating water management and restoration scenarios. Here we developed an ensemble logistic regression, combining a frequentist and Bayesian approach, to model CSSS presence and measure how environmental factors such as hydrometrics, fire occurrence, and vegetation structure impact CSSS habitat suitability. This is the first analysis to quantitatively assess the interdependent relationships between a broad range of environmental factors and CSSS presence across the landscape. Our results show that the probability of CSSS presence was highest in areas with dry conditions, hydroperiods between 80 and 120 days, percentages of canopy cover and woody vegetation less than 10%, and more than six years post-fire where 75% or more of the area was burned. Because the frequentist and Bayesian models had nearly identical spatial outputs with the Bayesian model having slightly higher validation metrics, we used the Bayesian approach as our final model (EverSparrow). The results from our analysis can provide a valuable decision support tool as natural resource managers work to restore the Everglades landscape.

Florida

Habitat suitability index model improvement recommendations

As part of the model improvement effort for the 2023 Coastal Master Plan, the Habitat Suitability Index (HSI) models used during previous master plans were reevaluated to assess how the model relationships could be improved, and to determine what species should be included in the master plan analyses. This process considered the technical reviews, comments, and suggested improvements provided by model developers, advisory groups, and other experts during previous master plans. Reviews were then conducted to determine the availability of data and information that could be used to make model improvements. As a result of this effort, a recommended list of relevant species to model is provided, and HSI model improvements are recommended that are categorized by whether the suitability index (SI) relationship to be improved is statistical-based or literature-based. The species recommended to be included in the 2023 Coastal Master Plan analyses are: eastern oyster, brown shrimp, white shrimp, blue crab, crayfish, gulf menhaden, spotted seatrout, largemouth bass, American alligator, gadwall, mottled duck, brown pelican, seaside sparrow, and bald eagle. These species were selected because they represent a range of taxonomies, life histories, trophic levels, and habitats, and most are commercially- or recreationally-important in coastal Louisiana. Most of these species were also included in the 2017 Coastal Master Plan analyses, and the models used during that effort should be further improved. Seaside sparrow and bald eagle are new for the master plan, and new models should be developed for the analyses. The 2017 fish, shrimp, and blue crab HSI models included a water quality SI that was based on statistical analyses of species catch and environmental data collected by the Louisiana Department of Wildlife and Fisheries. As suggested during the 2017 Coastal Master Plan, the modeling approach used to develop the water quality SI was revisited and alternate modeling approaches were explored. Using literature and an evaluation of the general steps of model development, three components for HSI model improvement were identified, including 1) selecting alternative modeling approach(es); 2) detecting and resolving statistical issues; and 3) improving model fit and evaluation. Multiple options for each component were explored, which resulted in a proposed multi-step phased approach for model improvement. This proposed approach entails improving the generalized linear models used for the 2017 water quality SIs and then, if desired, comparing them to alternative model approaches (e.g., generalized additive models) to explore model performance and select the best approach to use for the 2023 Coastal Master Plan HSI models. All of the existing master plan HSI models include literature-based SIs, which use information from published studies of species-habitat associations to derive suitability relationships. Similar to previous master plans, these literature-based SIs should be updated and improved for the 2023 Coastal Master Plan using recent literature and new ecological knowledge. Preliminary reviews were conducted and recent information was found that could be used to improve the eastern oyster, crayfish, and potentially brown pelican HSI models; but no appropriate recent literature was located for improvement of the American alligator, gadwall, and mottled duck HSI models. However, it is recommended that the literature reviews and information searches be continued. In addition to the statistical-based water quality SI, the 2017 fish, shrimp, and blue crab HSI models also included a structural habitat SI that was based on literature showing high densities of these species in fragmented marsh. The relationship used for this SI, however, did not account for the effects of other estuarine habitats, such as submerged aquatic vegetation and oyster reefs, which are also important to these species. Therefore, a meta-analysis approach is proposed that would estimate the relative importance of these habitats for each species, and the results of this analysis could be used to calculate a new structural habitat SI for the 2023 Coastal Master Plan.

Report

Habitat suitability index model improvements

Habitat suitability index (HSI) models were developed for the 2023 Coastal Master Plan to evaluate the potential effects of coastal restoration and protection projects on habitat for key coastal fish, shellfish, and wildlife species. These species included: eastern oyster, brown shrimp, white shrimp, blue crab, crayfish, gulf menhaden, spotted seatrout, largemouth bass, American alligator, gadwall, mottled duck, brown pelican, seaside sparrow, and bald eagle. Most of these species were included in the 2017 Coastal Master Plan analyses, and the HSI models from that effort were refined and improved following the recommendations described in the technical memorandum: 2023 Coastal Master Plan Habitat Suitability Index Model Improvement Recommendations (Sable et al., 2019). In addition to model improvements, HSI models were created for seaside sparrow and bald eagle, both of which are new species for the master plan analyses. For the HSI models that are primarily literature-based, literature reviews were conducted for recent studies that could be used to improve the suitability index (SI) relationships that compose the models. As a result of this review, modifications were made to the salinity-related SIs of the oyster model including: expanding the time period used for salinity effects to spawning; adjusting the range of suitable annual average salinity to be more representative of Louisiana populations; and making oyster’s minimum salinity tolerance temperature dependent. In addition, a new SI was incorporated in the oyster HSI model that accounts for the effects of sediment deposition on oysters. The crayfish HSI model was improved by adjusting the time periods used for the SIs that describe the hydrology required for the crayfish life cycle, and the soil characteristics SI that was part of the 2017 crayfish model was removed because soil conditions do not appear to be limiting for crayfish burrow construction in coastal Louisiana. The other literature-based HSI models from the 2017 Coastal Master Plan, i.e., American alligator, gadwall, mottled duck, and brown pelican, were unchanged, with the exception of a small adjustment made to the suitability of forested wetlands for gadwall. Lastly, a literature-based HSI model was created for seaside sparrow that consists of SIs related to vegetated habitat type, marsh vegetation coverage, and marsh elevation. Statistical-based HSI models were developed for brown shrimp (both small and large juvenile stages), white shrimp (small and large juvenile stages), blue crab (juvenile stage), gulf menhaden (juvenile and adult stages), spotted seatrout (juvenile and adult stages), largemouth bass, and bald eagle. The bald eagle HSI model was developed from a bald eagle nest probability of occurrence model that related nest occurrence from survey data with land cover type. The resulting model showed that combinations of forested wetlands, flotant marsh, and open water habitats were most suitable for nesting bald eagles. The 2023 fish, shrimp, and blue crab HSI models were developed using new approaches for the formulation of the water quality and structural habitat SIs that compose the models. For the 2017 models, the water quality SI was derived using only generalized linear mixed models (GLMMs) to estimate the relationship between salinity, water temperature, and species’ catch. For the 2023 models, however, multiple GLMMs and generalized additive models (GAMMs) were created for each species or life stage. These alternative models were compared and a single model that performed well statistically and was ecologically reasonable was selected for the species’ water quality SI. The structural habitat SI was developed using a meta-analysis of published literature to estimate the relative importance of various estuarine habitats to the fish and shellfish species. The results of this analysis were then used to modify the 2017 structural habitat SI relationship to account for the added habitat value of submerged aquatic vegetation and oyster reefs, which are also important habitats for juvenile fish and shellfish. Similar to the 2017 fish, shrimp, and blue crab models, the water quality and structural habitat SIs were then combined to create the 2023 HSI models. The 2023 Coastal Master Plan HSI models were integrated with the Integrated Compartment Model (and are referred to as ICM-HSIs) and tested using environmental output from the 2017 Coastal Master Plan Future Without Action scenario. The tests showed that, in general, the models produced reasonable representations of species’ habitat distribution. Furthermore, the improvements made to the oyster, crayfish, fish, shrimp, and blue crab HSI models generally yielded more realistic results compared to the 2017 HSI models.

Report

Small mammal responses to wetland restoration in the Greater Everglades ecosystem

Wetlands have experienced dramatic losses in extent around the world, disrupting ecosystem function, habitat, and biodiversity. In Florida’s Greater Everglades, a massive restoration effort costing billions of dollars and spanning multiple decades is underway. As Everglades restoration is implemented in incremental projects, scientists and planners monitor the outcomes of projects. In this study, we evaluated the progress of a restoration project in the southwestern Everglades. We aimed to determine whether the presence and density of small mammals differed between areas with hydrologic restoration of the ecosystem and areas without restoration. Our three focal species were: marsh rice rat ( Oryzomys palustris ), hispid cotton rat ( Sigmodon hispidus ), and cotton mouse ( Peromyscus gossypinus ). Using spatially explicit capture‐recapture models, we found greater densities of cotton mouse in restored habitat and lower densities of hispid cotton rat in sites with higher water levels. Additionally, we found an increase in the presence of the marsh rice rat in restored areas compared to unrestored, but captures were too low to reliably assess significance. Our study provides evidence that ongoing restoration in the southwestern Everglades is already impacting the small mammal community.

Florida