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At least 451 records · Page 25Linked to original sources
USGS2013

LANDFIRE 2010 - updated data to support wildfire and ecological management

Wildfire is a global phenomenon that affects human populations and ecosystems. Wildfire effects occur at local to global scales impacting many people in different ways (Figure 1). Ecological concerns due to land use, fragmentation, and climate change impact natural resource use, allocation, and conservation. Access to consistent and current environmental data is a constant challenge, yet necessary for understanding the complexities of wildfire and ecological management. Data products and tools from the LANDFIRE Program help decision-makers to clarify problems and identify possible solutions when managing fires and natural resources. LANDFIRE supports the reduction of risk from wildfire to human lives and property, monitoring of fire danger, prediction of fire behavior on active incidents, and assessment of fire severity and impacts on natural systems [1] [2] [3]. LANDFIRE products are unique in that they are nationally consistent and provide the only complete geospatial dataset describing vegetation and wildland fuel information for the entire U.S. As such, LANDFIRE data are useful for many ecological applications [3]. For example, LANDFIRE data were recently integrated into a decision-support system for resource management and conservation decision-making along the Appalachian Trail. LANDFIRE is a joint effort between the U.S. Department of the Interior Office of Wildland Fire, U.S. Department of Agriculture Forest Service Fire & Aviation Management, and The Nature Conservancy. To date, seven versions of LANDFIRE data have been released, with each successive version improving the quality of the data, adding additional features, and/or updating the time period represented by the data. The latest version, LANDFIRE 2010 (LF 2010), released mid-2013, represents circa 2010 landscape conditions and succeeds LANDFIRE 2008 (LF 2008), which represented circa 2008 landscape conditions. LF 2010 used many of the same processes developed for the LF 2008 effort [3]. Ongoing refinement of the LANDFIRE vegetation and fuel data is necessary to improve the quality and usability of the data and to capture landscape disturbance. LANDFIRE relies on Landsat multi-spectral imagery to produce and update vegetation and fuel data. The deep Landsat archive provides data needed for vegetation classification, change analysis, and historical disturbance characterization, for which LANDFIRE has used more than 24,000 image scenes since the program’s inception. In addition, LF 2010 used airborne and spaceborne lidar, and spaceborne synthetic aperture radar (SAR) to map vegetation structure in areas where ground-based field information was lacking, including Alaska and U.S.-affiliated islands in the Caribbean and the Pacific. The mapping of insular areas is new for the 2010 data release; previous versions of LANDFIRE were limited to the conterminous U.S., Alaska, and Hawaii.

Earthzine↗
USGS2017

The value of information for woodland management: Updating a state–transition model

Value of information (VOI) analyses reveal the expected benefit of reducing uncertainty to a decision maker. Most ecological VOI analyses have focused on population models rarely addressing more complex community models. We performed a VOI analysis for a complex state–transition model of Box-Ironbark Forest and Woodland management. With three management alternatives (limited harvest/firewood removal (HF), ecological thinning (ET), and no management), managing the system optimally (for 150 yr) with the original information would, on average, increase the amount of forest in a desirable state from 19% to 35% (a 16-percentage point increase). Resolving all uncertainty would, on average, increase the final percentage to 42% (a 19-percentage point increase). However, only resolving the uncertainty for a single parameter was worth almost two-thirds the value of resolving all uncertainty. We found the VOI to depend on the number of management options, increasing as the management flexibility increased. Our analyses show it is more cost-effective to monitor low-density regrowth forest than other states and more cost-effective to experiment with the no-management alternative than the other management alternatives. Importantly, the most cost-effective strategies did not include either the most desired forest states or the least understood management strategy, ET. This implies that managers cannot just rely on intuition to tell them where the most VOI will lie, as critical uncertainties in a complex system are sometimes cryptic.

Victoria↗
USGS2004

Fishing for lobsters indirectly increases epidemics in sea urchins

Two ecological paradigms, the trophic cascade and the host-density threshold in disease, interact in the kelp-forest ecosystem to structure the community. To investigate what happens when a trophic cascade pushes a host population over a host-threshold density, I analyzed a 20-year data set of kelp forest communities at 16 sites in the region of the Channel Islands National Park, California, USA. Historically, lobsters, and perhaps other predators, kept urchin populations at low levels and kelp forests developed a community-level trophic cascade. In geographic areas where the main predators on urchins were fished, urchin populations increased to the extent that they overgrazed algae and starvation eventually limited urchin-population growth. Despite the limitation of urchin population size by food availability, urchin densities, at times, well exceeded the host-density threshold for epidemics. An urchin-specific bacterial disease entered the region after 1992 and acted as a density-dependent mortality source. Dense populations were more likely to experience epidemics and suffer higher mortality. Disease did not reduce the urchin population at a site to the density that predators previously did. Therefore, disease did not fully replace predators in the trophic cascade. These results indicate how fishing top predators can indirectly favor disease transmission in prey populations.

Ecological Applications↗
USGS1997

New approaches to the analysis of population trends in land birds: Comment

James et al. (1996, Ecology 77:13-27) used data from the North American Breeding Bird Survey (BBS) to examine geographic variability in patterns of population change for 26 species of wood warblers. They emphasized the importance of evaluating nonlinear patterns of change in bird populations, proposed LOESS-based non-parametric and semi-parametric analyses of BBS data, and contrasted their results with other analyses, including those of Robbins et al. (1989, Proceedings of the National Academy of Sciences 86: 7658-7662) and Peterjohn et al. (1995, Pages 3-39 in T. E. Martin and D. M. Finch, eds. Ecology and management of Neotropical migratory birds: a synthesis and review of critical issues. Oxford University Press, New York.). In this note, we briefly comment on some of the issues that arose from their analysis of BBS data, suggest a few aspects of the survey that should inspire caution in analysts, and review the differences between the LOESS-based procedures and other procedures (e.g., Link and Sauer 1994). We strongly discourage the use of James et al.'s completely non-parametric procedure, which fails to account for observer effects. Our comparisons of estimators adds to the evidence already present in the literature of the bias associated with omitting observer information in analyses of BBS data. Bias resulting from change in observer abilities should be a consideration in any analysis of BBS data.

Ecology↗
USGS2019

The importance of simulation assumptions when evaluating detectability in population models

Population monitoring is important for investigating a variety of ecological questions, and N-mixture models are increasingly used to model population size (N) and trends (lambda) while estimating detectability (p) from repeated counts within primary periods (when populations are closed to changes). Extending these models to dynamic processes with serial dependence across primary periods may relax the closure assumption, but simulations to evaluate models and inform effort (e.g., number of repeated counts) typically assume p is constant or random across sites and years. Thus, it is unknown how these models perform under scenarios where trends in p confound inferences on N and lambda, and conclusions regarding effort may be overoptimistic. Here, we used global positioning system (GPS) data from greater sage-grouse (Centrocercus urophasianus) to inform simulations of the detection process for lek counts of this species, and we created scenarios with and without linear annual trends in p. We then compared estimates of N and lambda from hierarchical population models either fit with single maximum counts or with detectability estimated from repeated counts (dynamic N-mixture models). We also explored using auxiliary data to correct counts for variation in detectability. Uncorrected count models consistently underestimated N by >50% whereas N-mixture models without auxiliary data underestimated N to a lesser degree due to unmodeled heterogeneity in p such as age. Nevertheless, estimates of lambda from both types of models were unbiased and similar for scenarios without trends in p. When p declined systematically across years, uncorrected count models underestimated lambda whereas N-mixture models estimated lambda with little bias when all sites were counted repeatedly. Auxiliary data also reduced bias in parameter estimates. Evaluating population models using scenarios with systematic variation in p may better reveal potential biases and inform effort than simulations that assume p is constant or random. Dynamic N-mixture models can distinguish between trends in p and N, but also require repeated counts within primary periods for accurate estimates. Auxiliary data may be useful when researchers lack repeated counts, wish to monitor more sites less intensively, or require unbiased estimates of N.

Ecosphere↗
USGS1996

Comparative biology of zebra mussels in Europe and North America: an overview

SYNOPSIS. Since the discovery of the zebra mussel, Dreissena polymorpha , in the Great Lakes in 1988 comparisons have been made with mussel populations in Europe and the former Soviet Union. These comparisons include: Population dynamics, growth and mortality rates, ecological tolerances and requirements, dispersal rates and patterns, and ecological impacts. North American studies, mostly on the zebra mussel and a few on a second introduced species, the quagga mussel, Dreissena bugensis , have revealed some similarities and some differences. To date it appears that North American populations of zebra mussels are similar to European populations in their basic biological characteristics, population growth and mortality rates, and dispersal mechanisms and rates. Relative to European populations differences have been demonstrated for: (1) individual growth rates; (2) life spans; (3) calcium and pH tolerances and requirements; (4) potential distribution limits; and (5) population densities of veligers and adults. In addition, studies on the occurrence of the two dreissenid species in the Great Lakes are showing differences in their modes of life, depth distributions, and growth rates. As both species spread throughout North America, comparisons between species and waterbodies will enhance our ability to more effectively control these troublesome species.

American Zoologist↗
USGS2022

Evaluating the effect of expert elicitation techniques on population status assessment in the face of large uncertainty

Population projection models are important tools for conservation and management. They are often used for population status assessments, for threat analyses, and to predict the consequences of conservation actions. Although conservation decisions should be informed by science, critical decisions are often made with very little information to support decision-making. Conversely, postponing decisions until better information is available may reduce the benefit of a conservation decision. When empirical data are limited or lacking, expert elicitation can be used to supplement existing data and inform model parameter estimates. The use of rigorous techniques for expert elicitation that account for uncertainty can improve the quality of the expert elicited values and therefore the accuracy of the projection models. One recurring challenge for summarizing expert elicited values is how to aggregate them. Here, we illustrate a process for population status assessment using a combination of expert elicitation and data from the ecological literature. We discuss the importance of considering various aggregation techniques, and illustrate this process using matrix population models for the wood turtle ( Glyptemys insculpta ) to assist U.S. Fish and Wildlife Service decision-makers with their Species Status Assessment. We compare estimates of population growth using data from the ecological literature and four alternative aggregation techniques for the expert-elicited values. The estimate of population growth rate based on estimates from the literature (λ mean = 0.952, 95% CI: 0.87–1.01) could not be used to unequivocally reject the hypotheses of a rapidly declining population nor the hypothesis of a stable, or even slightly growing population, whereas our results for the expert-elicited estimates supported the hypothesis that the wood turtle population will decline over time. Our results showed that the aggregation techniques used had an impact on model estimates, suggesting that the choice of techniques should be carefully considered. We discuss the benefits and limitations associated with each method and their relevance to the population status assessment. We note a difference in the temporal scope or inference between the literature-based estimates that provided insights about historical changes, whereas the expert-based estimates were forward looking. Therefore, conducting an expert-elicitation in addition to using parameter estimates from the literature improved our understanding of our species of interest.

Journal of Environmental Management↗
USGS2024

Using resiliency, redundancy, and representation in a Bayesian belief network to assess imperilment of riverine fishes

Conservation prioritization frameworks are used worldwide to identify species at greatest risk of extinction and to allocate limited resources across regions, species, and populations. Conservation prioritization can be impeded by ecological knowledge gaps and data deficiency, especially in freshwater species inhabiting highly complex aquatic ecosystems. Therefore, we developed a flexible approach that calculates a species' imperilment risk based on the conservation principles of resiliency, redundancy, and representation (i.e., the “three R's”). Our approach organizes data on species traits, distributions, population connectivity, and threats within a Bayesian belief network capable of predicting resiliency and redundancy within representative ecological settings. Empirical data and expert judgment inform the model to provide robust and repeatable risk assessments for rare and data-deficient species. The model calculates resiliency at hierarchical spatial scales from distributional trends and population strength. Redundancy is estimated from the connectivity and quantities of extant populations. Resiliency, redundancy, and species' inherent vulnerability based on species traits collectively estimate extirpation risk within each unique ecological setting. Extirpation risks across ecological settings characterize representation and are aggregated to estimate global imperilment risk. We demonstrate the model's utility with Piebald Madtom ( Noturus gladiator ), a species petitioned for listing under the U.S. Endangered Species Act. Our results revealed that resiliency, redundancy, and extirpation risks can vary spatially across the species' range while identifying populations where additional sampling could disproportionally reduce uncertainty in estimated global imperilment risk. Our approach could standardize and expedite conservation status assessments, identify opportunities for early management intervention of at-risk species and populations, and strategically reduce uncertainty by focusing monitoring and research on priority information gaps.

Ecosphere↗
USGS2016

Disease introduction is associated with a phase transition in bighorn sheep demographics

Ecological theory suggests that pathogens are capable of regulating or limiting host population dynamics, and this relationship has been empirically established in several settings. However, although studies of childhood diseases were integral to the development of disease ecology, few studies show population limitation by a disease affecting juveniles. Here, we present empirical evidence that disease in lambs constrains population growth in bighorn sheep ( Ovis canadensis ) based on 45 years of population-level and 18 years of individual-level monitoring across 12 populations. While populations generally increased (λ = 1.11) prior to disease introduction, most of these same populations experienced an abrupt change in trajectory at the time of disease invasion, usually followed by stagnant-to-declining growth rates (λ = 0.98) over the next 20 years. Disease-induced juvenile mortality imposed strong constraints on population growth that were not observed prior to disease introduction, even as adult survival returned to pre-invasion levels. Simulations suggested that models including persistent disease-induced mortality in juveniles qualitatively matched observed population trajectories, whereas models that only incorporated all-age disease events did not. We use these results to argue that pathogen persistence may pose a lasting, but under-recognized, threat to host populations, particularly in cases where clinical disease manifests primarily in juveniles.

Ecology↗
USGS1982

Ecology of avian brood parasitism at an early interfacing of host and parasite populations

The shiny cowbird (Molothrus bonariensis), a brood parasite, has recently spread into the Greater Antilles from South America via the Lesser Antilles. This species is a host generalist and upon reaching Puerto Rico exploited avian communities with no history of social parasitism. Forty-two percent of the resident non-raptorial land bird species were parasitized in mangrove habitat study areas. Cowbird parasitism affected hosts by (1) depressing nest success an average of 41 percent below non-parasitized nests, and (2) reducing host productivity. Parasitized hosts produced 12 percent fewer eggs and fledged 67 percent fewer of their own chicks than non-parasitized pairs. Growth rates of chicks of some host species were lower in parasitized nests compared with non-parasitized nests while growth of others was not affected by brood parasitism. Cowbird chick growth varied directly with host size; i.e., cowbird chicks grew faster and attained greater fledging weight and body size in nests of larger hosts. Factors important in shiny cowbird host selection were examined within the mangrove study community. Cowbirds did not parasitize avian species in proportion to their abundance. The cowbird breeding season coincided with that of its major hosts, which were high quality foster species, and did not extend into other periods even though nests of poor quality species were available. Food habits and egg size of cowbirds were similar to those of their hosts, suggesting that cowbirds choose hosts partly on the basis of this alignment. Cowbirds locate nests by cryptically watching activities of birds in likely habitat. Despite the recency of the cowbird's arrival in Puerto Rico, some nesting species have effective anti-parasite strategies, including alien egg rejection and nest guarding. Behavior effective in avoiding parasitism is similar to that used by certain birds in evading nest predators. It is suggested that anti-predator behavior is preadaptive to countering cowbird parasitism.

Book↗
USGS1982

Ecology of avian brood parasitism at an early interfacing of host and parasite populations

The shiny cowbird (Molothrus bonariensis), a brood parasite, has recently spread into the Greater Antilles from South America via the Lesser Antilles. This species is a host generalist and upon reaching Puerto Rico exploited avian communities with no history of social parasitism. Forty-two percent of the resident non-raptorial land bird species were parasitized in mangrove habitat study areas. Cowbird parasitism affected hosts by (1) depressing nest success an average of 41 percent below non-parasitized nests, and (2) reducing host productivity. Parasitized hosts produced 12 percent fewer eggs and fledged 67 percent fewer of their own chicks than non-parasitized pairs. Growth rates of chicks of some host species were lower in parasitized nests compared with non-parasitized nests while growth of others was not affected by brood parasitism. Cowbird chick growth varied directly with host size; i.e., cowbird chicks grew faster and attained greater fledging weight and body size in nests of larger hosts. Factors important in shiny cowbird host selection were examined within the mangrove study community. Cowbirds did not parasitize avian species in proportion to their abundance. The cowbird breeding season coincided with that of its major hosts, which were high quality foster species, and did not extend into other periods even though nests of poor quality species were available. Food habits and egg size of cowbirds were similar to those of their hosts, suggesting that cowbirds choose hosts partly on the basis of this alignment. Cowbirds locate nests by cryptically watching activities of birds in likely habitat. Despite the recency of the cowbird's arrival in Puerto Rico, some nesting species have effective anti-parasite strategies, including alien egg rejection and nest guarding. Behavior effective in avoiding parasitism is similar to that used by certain birds in evading nest predators. It is suggested that anti-predator behavior is preadaptive to countering cowbird parasitism.

Dissertation Abstracts International↗
USGS2020

Carrying capacity of a population diffusing in a heterogeneous environment

The carrying capacity of the environment for a population is one of the key concepts in ecology and it is incorporated in the growth term of reaction-diffusion equations describing populations in space. Analysis of reaction-diffusion models of populations in heterogeneous space have shown that, when the maximum growth rate and carrying capacity in a logistic growth function vary in space, conditions exist for which the total population size at equilibrium (i) exceeds the total population that which would occur in the absence of diffusion and (ii) exceeds that which would occur if the system were homogeneous and the total carrying capacity, computed as the integral over the local carrying capacities, was the same in the heterogeneous and homogeneous cases. We review here work over the past few years that has explained these apparently counter-intuitive results in terms of the way input of energy or another limiting resource (e.g., a nutrient) varies across the system. We report on both mathematical analysis and laboratory experiments confirming that total population size in a heterogeneous system with diffusion can exceed that in the system without diffusion. We further report, however, that when the resource of the population in question is explicitly modeled as a coupled variable, as in a reaction-diffusion chemostat model rather than a model with logistic growth, the total population in the heterogeneous system with diffusion cannot exceed the total population size in the corresponding homogeneous system in which the total carrying capacities are the same.

Mathematics and Computers in Modern Science - Acou↗
USGS2019

Factors influencing nesting ecology of lesser prairie-chickens

Lesser prairie-chicken ( Tympanuchus pallidicinctus ) populations have declined since the 1980s. Understanding factors influencing nest-site selection and nest survival are important for conservation and management of lesser prairie-chicken populations. However, >75% of the extant population is in the northern extent of the range where data on breeding season ecology are lacking. We tested factors influencing fine-scale and regional nest-site selection and nest survival across the northern portion of the lesser prairie-chicken range. We trapped and affixed satellite global positioning system and very high frequency transmitters to female lesser prairie-chickens ( n = 307) in south-central and western Kansas and eastern Colorado, USA. We located and monitored 257 lesser prairie-chicken nests from 2013 to 2016. We evaluated nest-site selection and nest survival in comparison to vegetation composition and structure. Overall, nest-site selection in relation to vegetation characteristics was similar across our study area. Lesser prairie-chickens selected nest microsites with 75% visual obstruction 2.0–3.5 dm tall and 95.7% of all nests were in habitat with ≥1 dm and ≤4 dm visual obstruction. Nests were located in areas with 6–8% bare ground, on average, avoiding areas with greater percent cover of bare ground. The type of vegetation present was less important than cover of adequate height. Nest survival was maximized when 75% visual obstruction was 2.0–4.0 dm. Nest survival did not vary spatially or among years and generally increased as intensity of drought decreased throughout the study although not significantly. To provide nesting cover considering yearly variation in drought conditions, it is important to maintain residual cover by managing for structural heterogeneity of vegetation. Managing for structural heterogeneity could be accomplished by maintaining or strategically applying practices of the Conservation Reserve Program, using appropriate fire and grazing disturbances in native working grasslands, and establishing site-specific monitoring of vegetation composition and structure.

Colorado, Kansas↗
USGS2024

Multi-decadal trophic shifts in Lake Erie yellow perch Perca flavescens

In Lake Erie, yellow perch Perca flavescens support vast commercial and recreational fisheries, yet populations have recently declined. Using N = 5889 yellow perch stomachs collected from 1997 to 2021, we explored trends in the feeding ecology and trophic level of yellow perch with generalized additive models. Models revealed a significant decrease in yellow perch trophic level (−0.15 trophic levels in the last decade), and significant dietary shifts. Yellow perch have shifted away from feeding on piscine prey and round goby Neogobius melanostomus over the 25-year period, and now feed on invertebrates more frequently—including invasive waterfleas ( Bythotrephes longimanus and Cercopagis pengoi ) and chironomids. Dietary patterns appear to reflect broad ecological changes—invasive waterfleas have proliferated while populations of forage fish and round goby have declined. Furthermore, hypoxia events have increased in duration and severity, which may explain observed increases in chironomid consumption, which are hypoxia tolerant. This study demonstrates trophic adaptability in yellow perch, which have changed feeding behavior and trophic position in response to novel invaders and changing environmental conditions.

Lake Erie↗
USGS2019

Conserving transboundary wildlife migrations: Recent insights from the Greater Yellowstone Ecosystem

Animal migrations are ecologically, culturally, and economically important. Ungulate populations in many parts of Africa, Asia, Europe, and the Americas migrate long distances to access seasonally available resources, traversing vast landscapes in large numbers. Yet some migrations are declining, raising concerns among scientists and natural resource managers. We synthesize recent advances in ungulate migration ecology with relevance to management and policy. Using case studies from the Greater Yellowstone Ecosystem (GYE), we show how new tools can be applied to map ungulate migrations and assess threats across multiple seasonal habitats, serving as a conservation roadmap. To help conserve ungulate migrations, we also propose a transboundary science, policy, and management framework that could be adapted beyond the GYE and that encompasses the needs of multiple species. The key elements of this framework consist of more widespread mapping and assessment of migrations, improved federal and state coordination across jurisdictional lines, increased investment in private land conservation, and strong engagement of local stakeholders positioned to sustain conservation activities over the long term.

Idaho, Montana, Wyoming↗
USGS2014

The southern megalopolis: using the past to predict the future of urban sprawl in the Southeast U.S.

The future health of ecosystems is arguably as dependent on urban sprawl as it is on human-caused climatic warming. Urban sprawl strongly impacts the urban ecosystems it creates and the natural and agro-ecosystems that it displaces and fragments. Here, we project urban sprawl changes for the next 50 years for the fast-growing Southeast U.S. Previous studies have focused on modeling population density, but the urban extent is arguably as important as population density per se in terms of its ecological and conservation impacts. We develop simulations using the SLEUTH urban growth model that complement population-driven models but focus on spatial pattern and extent. To better capture the reach of low-density suburban development, we extend the capabilities of SLEUTH by incorporating street-network information. Our simulations point to a future in which the extent of urbanization in the Southeast is projected to increase by 101% to 192%. Our results highlight areas where ecosystem fragmentation is likely, and serve as a benchmark to explore the challenging tradeoffs between ecosystem health, economic growth and cultural desires.

PLoS ONE↗
USGS2002

Analysis and Management of Animal Populations: Modeling, Estimation and Decision Making

This book deals with the processes involved in making informed decisions about the management of animal populations. It covers the modeling of population responses to management actions, the estimation of quantities needed in the modeling effort, and the application of these estimates and models to the development of sound management decisions. The book synthesizes and integrates in a single volume the methods associated with these themes, as they apply to ecological assessment and conservation of animal populations. KEY FEATURES * Integrates population modeling, parameter estimation and * decision-theoretic approaches to management in a single, cohesive framework * Provides authoritative, state-of-the-art descriptions of quantitative * approaches to modeling, estimation and decision-making * Emphasizes the role of mathematical modeling in the conduct of science * and management * Utilizes a unifying biological context, consistent mathematical notation, * and numerous biological examples

Book↗
USGS2011

Incorporating parametric uncertainty into population viability analysis models

Uncertainty in parameter estimates from sampling variation or expert judgment can introduce substantial uncertainty into ecological predictions based on those estimates. However, in standard population viability analyses, one of the most widely used tools for managing plant, fish and wildlife populations, parametric uncertainty is often ignored in or discarded from model projections. We present a method for explicitly incorporating this source of uncertainty into population models to fully account for risk in management and decision contexts. Our method involves a two-step simulation process where parametric uncertainty is incorporated into the replication loop of the model and temporal variance is incorporated into the loop for time steps in the model. Using the piping plover, a federally threatened shorebird in the USA and Canada, as an example, we compare abundance projections and extinction probabilities from simulations that exclude and include parametric uncertainty. Although final abundance was very low for all sets of simulations, estimated extinction risk was much greater for the simulation that incorporated parametric uncertainty in the replication loop. Decisions about species conservation (e.g., listing, delisting, and jeopardy) might differ greatly depending on the treatment of parametric uncertainty in population models.

Biological Conservation↗