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At least 163 records · Page 9Linked to original sources

USGS2011

Using data from an encounter sampler to model fish dispersal

A method to estimate speed of free-ranging fishes using a passive sampling device is described and illustrated with data from the Everglades, U.S.A. Catch per unit effort (CPUE) from minnow traps embedded in drift fences was treated as an encounter rate and used to estimate speed, when combined with an independent estimate of density obtained by use of throw traps that enclose 1 m 2 of marsh habitat. Underwater video was used to evaluate capture efficiency and species-specific bias of minnow traps and two sampling studies were used to estimate trap saturation and diel-movement patterns; these results were used to optimize sampling and derive correction factors to adjust species-specific encounter rates for bias and capture efficiency. Sailfin mollies Poecilia latipinna displayed a high frequency of escape from traps, whereas eastern mosquitofish Gambusia holbrooki were most likely to avoid a trap once they encountered it; dollar sunfish Lepomis marginatus were least likely to avoid the trap once they encountered it or to escape once they were captured. Length of sampling and time of day affected CPUE; fishes generally had a very low retention rate over a 24 h sample time and only the Everglades pygmy sunfish Elassoma evergladei were commonly captured at night. Dispersal speed of fishes in the Florida Everglades, U.S.A., was shown to vary seasonally and among species, ranging from 0.05 to 0.15 m s -1 for small poeciliids and fundulids to 0.1 to 1.8 m s -1 for L. marginatus . Speed was generally highest late in the wet season and lowest in the dry season, possibly tied to dispersal behaviours linked to finding and remaining in dry-season refuges. These speed estimates can be used to estimate the diffusive movement rate, which is commonly employed in spatial ecological models.

Florida↗

USGS2011

Estimating seasonal evapotranspiration from temporal satellite images

Estimating seasonal evapotranspiration (ET) has many applications in water resources planning and management, including hydrological and ecological modeling. Availability of satellite remote sensing images is limited due to repeat cycle of satellite or cloud cover. This study was conducted to determine the suitability of different methods namely cubic spline, fixed, and linear for estimating seasonal ET from temporal remotely sensed images. Mapping Evapotranspiration at high Resolution with Internalized Calibration (METRIC) model in conjunction with the wet METRIC (wMETRIC), a modified version of the METRIC model, was used to estimate ET on the days of satellite overpass using eight Landsat images during the 2001 crop growing season in Midwest USA. The model-estimated daily ET was in good agreement ( R 2 = 0.91) with the eddy covariance tower-measured daily ET. The standard error of daily ET was 0.6 mm (20%) at three validation sites in Nebraska, USA. There was no statistically significant difference ( P > 0.05) among the cubic spline, fixed, and linear methods for computing seasonal (July–December) ET from temporal ET estimates. Overall, the cubic spline resulted in the lowest standard error of 6 mm (1.67%) for seasonal ET. However, further testing of this method for multiple years is necessary to determine its suitability.

Irrigation Science↗

USGS2015

Factors affecting individual foraging specialization and temporal diet stability across the range of a large “generalist” apex predator

Individual niche specialization (INS) is increasingly recognized as an important component of ecological and evolutionary dynamics. However, most studies that have investigated INS have focused on the effects of niche width and inter- and intraspecific competition on INS in small-bodied species for short time periods, with less attention paid to INS in large-bodied reptilian predators and the effects of available prey types on INS. We investigated the prevalence, causes, and consequences of INS in foraging behaviors across different populations of American alligators ( Alligator mississippiensis ), the dominant aquatic apex predator across the southeast US, using stomach contents and stable isotopes. Gut contents revealed that, over the short term, although alligator populations occupied wide ranges of the INS spectrum, general patterns were apparent. Alligator populations inhabiting lakes exhibited lower INS than coastal populations, likely driven by variation in habitat type and available prey types. Stable isotopes revealed that over longer time spans alligators exhibited remarkably consistent use of variable mixtures of carbon pools (e.g., marine and freshwater food webs). We conclude that INS in large-bodied reptilian predator populations is likely affected by variation in available prey types and habitat heterogeneity, and that INS should be incorporated into management strategies to efficiently meet intended goals. Also, ecological models, which typically do not consider behavioral variability, should include INS to increase model realism and applicability.

Oecologia↗

USGS2026

Identifying headwater streams across the conterminous United States

Headwater streams play critical roles in hydrologic and biogeochemical processes and functions, yet their spatial distribution and land cover context remain poorly understood at continental scales, and no dedicated geospatial dataset exists. Building from a high-resolution conterminous United States (CONUS) hydrography network dataset, we quantified the spatial extent, density, and upstream catchment characteristics of headwater stream segments across the CONUS. We identified approximately 8.4 million kilometers of headwater streams, finding that 77% of the total stream network consists of headwaters, nearly double the total length represented in prior estimates. Stream density varied fivefold across regions, from < 1 km·km −2 in arid basins to > 5 km·km −2 in humid, forested areas. Over 73% of the CONUS landmass drains from headwater streams. The majority of headwater stream length occurred in forested and cultivated catchments across the CONUS, while substantial regional differences were evident for headwater stream distribution in other land cover classes (for example, wetlands, urban areas, shrublands, and herbaceous-dominated catchments). The dedicated and novel geospatial dataset, HELiOS (HEadwater streams and Low-Order Systems) is introduced for management and research use. The HELiOS dataset provides the first continental-scale, high-resolution characterization of headwater streams, offering new insights and opportunities for hydrologic modeling, ecological assessments, and environmental policy.

conterminous United States↗

USGS2021

Forecasting ecological responses for wetland restoration planning in Florida's Everglades

The Everglades wetland was once a river of grass, with water flowing slowly through the sawgrass, southward across the landscape. As developers took hold of south Florida, water was sent away from the heart of the Everglades through canals and levees to protect the former wetland for residential and agricultural development. In the 1990s, planning began to restore the Everglades in what is the largest hydrologic restoration undertaking in the world. With billions of taxpayer dollars at stake, restoration planners benefit from forecasting tools to inform restoration planning. To meet this need, scientists developed predictive ecological models and other decision support tools tailored to this dynamic ecosystem as well as to the needs of restoration planning teams. Predictive modeling has been able to take advantage of well-understood relationships between species of interest and hydrologic dynamics in the Everglades. Recent modeling advances include multi-species approaches that consider interactions among species as well as explicit consideration of trade-offs among species from potential water management actions. Scientists are also starting to look at ecosystem-wide vulnerabilities with explicit consideration of future change such as sea level rise. Modeling tools and approaches continue to be refined to meet decision making needs for Everglades restoration. However, more work is needed to consider additional complexities of this dynamic wetland as well as to consider the broader socio-environmental system.

Florida↗

USGS2015

Implementation of a framework for multi-species, multi-objective adaptive management in Delaware Bay

Decision analytic approaches have been widely recommended as well suited to solving disputed and ecologically complex natural resource management problems with multiple objectives and high uncertainty. However, the difference between theory and practice is substantial, as there are very few actual resource management programs that represent formal applications of decision analysis. We applied the process of structured decision making to Atlantic horseshoe crab harvest decisions in the Delaware Bay region to develop a multispecies adaptive management (AM) plan, which is currently being implemented. Horseshoe crab harvest has been a controversial management issue since the late 1990s. A largely unregulated horseshoe crab harvest caused a decline in crab spawning abundance. That decline coincided with a major decline in migratory shorebird populations that consume horseshoe crab eggs on the sandy beaches of Delaware Bay during spring migration. Our approach incorporated multiple stakeholders, including fishery and shorebird conservation advocates, to account for diverse management objectives and varied opinions on ecosystem function. Through consensus building, we devised an objective statement and quantitative objective function to evaluate alternative crab harvest policies. We developed a set of competing ecological models accounting for the leading hypotheses on the interaction between shorebirds and horseshoe crabs. The models were initially weighted based on stakeholder confidence in these hypotheses, but weights will be adjusted based on monitoring and Bayesian model weight updating. These models were used together to predict the effects of management actions on the crab and shorebird populations. Finally, we used a dynamic optimization routine to identify the state dependent optimal harvest policy for horseshoe crabs, given the possible actions, the stated objectives and our competing hypotheses about system function. The AM plan was reviewed, accepted and implemented by the Atlantic States Marine Fisheries Commission in 2012 and 2013. While disagreements among stakeholders persist, structured decision making enabled unprecedented progress towards a transparent and consensus driven management plan for crabs and shorebirds in Delaware Bay.

Biological Conservation↗

USGS2022

Bioclimatic variables dataset for baseline and future climate scenarios for climate change studies in Hawai'i

Gridded bioclimatic variables representing yearly, seasonal, and monthly means and extremes in temperature and precipitation have been widely used for ecological modeling purposes and in broader climate change impact and biogeographical studies. As a result of their utility, numerous sets of bioclimatic variables have been developed on a global scale (e.g., WorldClim) but rarely represent the finer regional scale pattern of climate in Hawai'i. Recognizing the value of having such regionally downscaled products, we integrated more detailed projections from recent climate models developed for Hawai'i with current climatological datasets to generate updated regionally defined bioclimatic variables. We derived updated bioclimatic variables from new projections of baseline and future monthly minimum, mean, and maximum temperature (T min , T mean , T max ) and mean precipitation (P mean ) data at 250 m resolution. We used the most up-to-date dynamically downscaled projections based on the Weather Research and Forecasting (WRF) model from the International Pacific Research Center (IPRC) and the National Center for Atmospheric Research (NCAR). We summarized the monthly data from these two climate projections into a suite of 19 standard bioclimatic variables that provide detailed information about annual and seasonal mean climatic conditions for the Hawaiian Islands. These bioclimatic variables are available for three climate scenarios: baseline climate (1990-2009) and future climate (2080-2099) under representative concentration pathway (RCP) 4.5 (IPRC projections only) and RCP 8.5 (both IPRC and NCAR projections) climate scenarios. The resulting dataset provides a more robust set of climate products that can be used for modeling purposes, impact studies, and management planning.

Hawaii↗

USGS2020

Near-term spatial hydrologic forecasting in Everglades, USA for landscape planning and ecological forecasting

Operational ecological forecasting is an emerging field that leverages ecological models in a new, cross-disciplinary way – using a real-time or nearly real-time climate forecast to project near-term ecosystem states. These applications give decision-makers lead time to anticipate and manage state changes that degrade ecosystem functions or directly impact humans. The Everglades Forecasting model (EverForecast) is an operational forecast model designed specifically for conservation management purposes including water management. It provides up to six-month forecasts of daily projected, spatially continuous stage values across the Everglades. We validated EverForecast quarterly to measured historical values at 207 gages (1 Jan 2000 – 31 Dec 2019). EverForecast hindcasted water stage accurately captured measured stage variation, with a low percentage of measured stage exceeding hindcasted values. Over the whole spatial extent, the mean RMSE is 20.98 cm, the mean MAE is 14.42 cm, and the mean MBE is 0.91 cm.

Florida↗

USGS2012

Estimating aboveground biomass in interior Alaska with Landsat data and field measurements

Terrestrial plant biomass is a key biophysical parameter required for understanding ecological systems in Alaska. An accurate estimation of biomass at a regional scale provides an important data input for ecological modeling in this region. In this study, we created an aboveground biomass (AGB) map at 30-m resolution for the Yukon Flats ecoregion of interior Alaska using Landsat data and field measurements. Tree, shrub, and herbaceous AGB data in both live and dead forms were collected in summers and autumns of 2009 and 2010. Using the Landsat-derived spectral variables and the field AGB data, we generated a regression model and applied this model to map AGB for the ecoregion. A 3-fold cross-validation indicated that the AGB estimates had a mean absolute error of 21.8 Mg/ha and a mean bias error of 5.2 Mg/ha. Additionally, we validated the mapping results using an airborne lidar dataset acquired for a portion of the ecoregion. We found a significant relationship between the lidar-derived canopy height and the Landsat-derived AGB (R 2 = 0.40). The AGB map showed that 90% of the ecoregion had AGB values ranging from 10 Mg/ha to 134 Mg/ha. Vegetation types and fires were the primary factors controlling the spatial AGB patterns in this ecoregion.

Alaska↗

USGS2007

Temporal and spatial aspects of peatland initiation following deglaciation in North America

A set of simple ecological models accounts well for the cumulative initiation of peatlands throughout North America in relation to glacial retreat. The most parsimonious form incorporates, first, a delay term to account for the lag during which newly deglaciated land became suitable for peatland initiation and, second, an intrinsic rate of initiation related to the probability of migration and establishment of plant propagules from elsewhere. The goodness of fit of the models, based on 1680 basal-peat dates throughout the continent, allows projection of past trends into the future. Factors contributing to the lag of about 4000 years between deglaciation and peatland initiation are suggested and data on colonization of deglaciated land by beavers (known to initiate peatlands) are presented. The rate of peatland initiation peaked between 7000 and 8000 years ago, but remains appreciable today. A marked depression of peatland initiation (8360-8040 BP) interrupted the peak rate. The time of the interruption matches the 8200 BP cold-dry event recorded in Greenland ice cores, and suggests that this event caused a substantial, continent-wide depression of an important ecosystem function, i.e., carbon sequestration from the atmosphere by peat deposition. Spontaneous initiation of new peatlands is projected to continue for millennia to come. ?? 2006 Elsevier Ltd. All rights reserved.

Quaternary Science Reviews↗

USGS1998

Assessing map accuracy in a remotely sensed, ecoregion-scale cover map

Landscape- and ecoregion-based conservation efforts increasingly use a spatial component to organize data for analysis and interpretation. A challenge particular to remotely sensed cover maps generated from these efforts is how best to assess the accuracy of the cover maps, especially when they can exceed 1000 s/km2 in size. Here we develop and describe a methodological approach for assessing the accuracy of large-area cover maps, using as a test case the 21.9 million ha cover map developed for Utah Gap Analysis. As part of our design process, we first reviewed the effect of intracluster correlation and a simple cost function on the relative efficiency of cluster sample designs to simple random designs. Our design ultimately combined clustered and subsampled field data stratified by ecological modeling unit and accessibility (hereafter a mixed design). We next outline estimation formulas for simple map accuracy measures under our mixed design and report results for eight major cover types and the three ecoregions mapped as part of the Utah Gap Analysis. Overall accuracy of the map was 83.2% (SE=1.4). Within ecoregions, accuracy ranged from 78.9% to 85.0%. Accuracy by cover type varied, ranging from a low of 50.4% for barren to a high of 90.6% for man modified. In addition, we examined gains in efficiency of our mixed design compared with a simple random sample approach. In regard to precision, our mixed design was more precise than a simple random design, given fixed sample costs. We close with a discussion of the logistical constraints facing attempts to assess the accuracy of large-area, remotely sensed cover maps.

Remote Sensing of Environment↗

USGS2026

Hydrological control on soil redox condition and carbon loss of coastal wetland under sea-kevel rise

Coastal wetlands are critical carbon sinks with their biogeochemical and ecological functioning shaped by dynamic hydrological conditions that are increasingly influenced by climate change. A key unresolved question is how hydrologic flow, vegetation response, and rising sea levels interact to regulate soil redox condition and carbon loss in coastal wetlands. Using a field-tested hydrological–biogeochemical–ecological modeling framework, we reveal how the interplay between terrestrial groundwater discharge and tidal fluctuations generates complex groundwater flow patterns at the terrestrial–aquatic interface, and how these patterns modulate soil redox conditions, in turn influencing soil organic matter decomposition and carbon loss. Notably, rising sea levels suppress soil CO 2 emissions while reducing lateral dissolved carbon losses, thereby enhancing litter carbon sequestration under anoxic conditions. As vegetation responds to sea-level rise and carbon inputs diminish, litter carbon subsequently declines. These findings underscore a critical hydrological control on carbon cycling, advancing our understanding of coastal ecosystem resilience in a warming world.

Louisiana↗

USGS2021

Native American fire management at an ancient wildland–urban interface in the Southwest United States

The intersection of expanding human development and wildland landscapes—the “wildland–urban interface” or WUI—is one of the most vexing contexts for fire management because it involves complex interacting systems of people and nature. Here, we document the dynamism and stability of an ancient WUI that was apparently sustainable for more than 500 y. We combine ethnography, archaeology, paleoecology, and ecological modeling to infer intensive wood and fire use by Native American ancestors of Jemez Pueblo and the consequences on fire size, fire–climate relationships, and fire intensity. Initial settlement of northern New Mexico by Jemez farmers increased fire activity within an already dynamic landscape that experienced frequent fires. Wood harvesting for domestic fuel and architectural uses and abundant, small, patchy fires created a landscape that burned often but only rarely burned extensively. Depopulation of the forested landscape due to Spanish colonial impacts resulted in a rebound of fuels accompanied by the return of widely spreading, frequent surface fires. The sequence of more than 500 y of perennial small fires and wood collecting followed by frequent “free-range” wildland surface fires made the landscape resistant to extreme fire behavior, even when climate was conducive and surface fires were large. The ancient Jemez WUI offers an alternative model for fire management in modern WUI in the western United States, and possibly other settings where local management of woody fuels through use (domestic wood collecting) coupled with small prescribed fires may make these communities both self-reliant and more resilient to wildfire hazards.

Arizona, New Mexico↗

USGS2021

Is there tree senescence? The fecundity evidence

Despite its importance for forest regeneration, food webs, and human economies, changes in tree fecundity with tree size and age remain largely unknown. The allometric increase with tree diameter assumed in ecological models would substantially overestimate seed contributions from large trees if fecundity eventually declines with size. Current estimates are dominated by overrepresentation of small trees in regression models. We combined global fecundity data, including a substantial representation of large trees. We compared size–fecundity relationships against traditional allometric scaling with diameter and two models based on crown architecture. All allometric models fail to describe the declining rate of increase in fecundity with diameter found for 80% of 597 species in our analysis. The strong evidence of declining fecundity, beyond what can be explained by crown architectural change, is consistent with physiological decline. A downward revision of projected fecundity of large trees can improve the next generation of forest dynamic models.

Proceedings of the National Academy of Sciences↗

USGS2023

Food caching by a solitary large carnivore reveals importance of intermediate-sized prey

Pumas ( Puma concolor ) are solitary large carnivores that exhibit high energetic investments while hunting prey that often take multiple days to consume. Therefore, pumas should behave in a way to maximize their energetic gains, including using caching, which is a behavior used by many mammal species to preserve and store food or to conceal it from conspecifics and scavengers to limit their losses. Yet pumas do not always cache their kills. In order to understand caching behavior, we used variables associated with the kills such as prey mass, search time, climate, and habitat to test 20 ecological models (representing four a priori hypotheses: food perishability, resource pulse, consumption time, and kleptoparasitism deterrence) in an information-theoretic approach of model selection to explore factors related to the caching behavior. Models were run with information from tracked radio-collared pumas in California over a 2.5-year period and identified a total of 352 kills. Overall, we documented pumas caching 61.5% of their kills, including 71.6% of Black-tailed Deer ( Odocoileus hemionus columbianus ), their primary prey in the study area. The model with a quadratic effect of adjusted mass of prey on puma caching probability had all of the empirical support ( w = 1.00). Specifically, pumas were most likely to cache intermediate-sized prey, such as yearling and adult female deer, and also fed from cached kills for longer periods of time. Larger prey may be too large to easily cache, making it less energetically efficient—while small prey can often be consumed quickly enough to not require caching. This suggests that intermediate-sized prey may be the optimal size for caching, allowing a puma to feed for multiple days while not greatly increasing energetic output. The hypotheses we tested were not mutually exclusive and pumas caching their prey may occur for several reasons; nevertheless, our study demonstrated that pumas use caching to extend their foraging time and maximize energetic gains when preying on intermediate-sized prey.

California↗

USGS2005

Are all prey created equal? A review and synthesis of differential predation on prey in substandard condition

Our understanding of predator-prey interactions in fishes has been influenced largely by research assuming that the condition of the participants is normal. However, fish populations today often reside in anthropogenically altered environments and are subjected to many kinds of stressors, which may reduce their ecological performance by adversely affecting their morphology, physiology, or behaviour. One consequence is that either the predator or prey, or both, may be in a substandard condition at the time of an interaction. We reviewed the literature on predator-prey interactions in fishes where substandard prey were used as experimental groups. Although most of this research indicates that such prey are significantly more vulnerable to predation, prey condition has rarely been considered in ecological theory regarding predator-prey interactions. The causal mechanisms for increased vulnerability of substandard prey to predation include a failure to detect predators, lapses in decision-making, poor fast-start performance, inability to shoal effectively, and increased prey conspicuousness. Despite some problems associated with empirical predator-prey studies using substandard prey, their results can have theoretical and applied uses, such as in ecological modelling or justification of corrective measures to be implemented in the wild. There is a need for more corroborative field experimentation, a better understanding of the causal mechanisms behind differential predation, and increased incorporation of prey condition into the research of predator-prey modellers and theoreticians. If the concept of prey condition is considered in predator-prey interactions, our understanding of how such interactions influence the structure and dynamics of fish communities is likely to change, which should prove beneficial to aquatic ecosystems.

Journal of Fish Biology↗

USGS2015

Effects of climate change on long-term population growth of pronghorn in an arid environment

Climate often drives ungulate population dynamics, and as climates change, some areas may become unsuitable for species persistence. Unraveling the relationships between climate and population dynamics, and projecting them across time, advances ecological understanding that informs and steers sustainable conservation for species. Using pronghorn ( Antilocapra americana ) as an ecological model, we used a Bayesian approach to analyze long-term population, precipitation, and temperature data from 18 populations in the southwestern United States. We determined which long-term (12 and 24 months) or short-term (gestation trimester and lactation period) climatic conditions best predicted annual rate of population growth (λ). We used these predictions to project population trends through 2090. Projections incorporated downscaled climatic data matched to pronghorn range for each population, given a high and a lower atmospheric CO 2 concentration scenario. Since the 1990s, 15 of the pronghorn populations declined in abundance. Sixteen populations demonstrated a significant relationship between precipitation and λ, and in 13 of these, temperature was also significant. Precipitation predictors of λ were highly seasonal, with lactation being the most important period, followed by early and late gestation. The influence of temperature on λ was less seasonal than precipitation, and lacked a clear temporal pattern. The climatic projections indicated that all of these pronghorn populations would experience increased temperatures, while the direction and magnitude of precipitation had high population-specific variation. Models predicted that nine populations would be extirpated or approaching extirpation by 2090. Results were consistent across both atmospheric CO 2 concentration scenarios, indicating robustness of trends irrespective of climatic severity. In the southwestern United States, the climate underpinning pronghorn populations is shifting, making conditions increasingly inhospitable to pronghorn persistence. This realization informs and steers conservation and management decisions for pronghorn in North America, while exemplifying how similar research can aid ungulates inhabiting arid regions and confronting similar circumstances elsewhere.

Ecosphere↗

USGS2013

Fort Collins Science Center Ecosystem Dynamics branch--interdisciplinary research for addressing complex natural resource issues across landscapes and time

The Ecosystem Dynamics Branch of the Fort Collins Science Center offers an interdisciplinary team of talented and creative scientists with expertise in biology, botany, ecology, geology, biogeochemistry, physical sciences, geographic information systems, and remote-sensing, for tackling complex questions about natural resources. As demand for natural resources increases, the issues facing natural resource managers, planners, policy makers, industry, and private landowners are increasing in spatial and temporal scope, often involving entire regions, multiple jurisdictions, and long timeframes. Needs for addressing these issues include (1) a better understanding of biotic and abiotic ecosystem components and their complex interactions; (2) the ability to easily monitor, assess, and visualize the spatially complex movements of animals, plants, water, and elements across highly variable landscapes; and (3) the techniques for accurately predicting both immediate and long-term responses of system components to natural and human-caused change. The overall objectives of our research are to provide the knowledge, tools, and techniques needed by the U.S. Department of the Interior, state agencies, and other stakeholders in their endeavors to meet the demand for natural resources while conserving biodiversity and ecosystem services. Ecosystem Dynamics scientists use field and laboratory research, data assimilation, and ecological modeling to understand ecosystem patterns, trends, and mechanistic processes. This information is used to predict the outcomes of changes imposed on species, habitats, landscapes, and climate across spatiotemporal scales. The products we develop include conceptual models to illustrate system structure and processes; regional baseline and integrated assessments; predictive spatial and mathematical models; literature syntheses; and frameworks or protocols for improved ecosystem monitoring, adaptive management, and program evaluation. The descriptions in this fact sheet provide snapshots of our three research emphases, followed by descriptions of select current projects.

Fact Sheet↗