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At least 1,117 records · Page 62Linked to original sources
USGS2012

Tidal and groundwater fluxes to a shallow, microtidal estuary: Constraining inputs through field observations and hydrodynamic modeling

Increased nutrient loading to estuaries has led to eutrophication, degraded water quality, and ecological transformations. Quantifying nutrient loads in systems with significant groundwater input can be difficult due to the challenge of measuring groundwater fluxes. We quantified tidal and freshwater fluxes over an 8-week period at the entrance of West Falmouth Harbor, Massachusetts, a eutrophic, groundwater-fed estuary. Fluxes were estimated from velocity and salinity measurements and a total exchange flow (TEF) methodology. Intermittent cross-sectional measurements of velocity and salinity were used to convert point measurements to cross-sectionally averaged values over the entire deployment (index relationships). The estimated mean freshwater flux (0.19 m 3 /s) for the 8-week period was mainly due to groundwater input (0.21 m 3 /s) with contributions from precipitation to the estuary surface (0.026 m 3 /s) and removal by evaporation (0.048 m 3 /s). Spring–neap variations in freshwater export that appeared in shorter-term averages were mostly artifacts of the index relationships. Hydrodynamic modeling with steady groundwater input demonstrated that while the TEF methodology resolves the freshwater flux signal, calibration of the index–salinity relationships during spring tide conditions only was responsible for most of the spring–neap signal. The mean freshwater flux over the entire period estimated from the combination of the index-velocity, index–salinity, and TEF calculations were consistent with the model, suggesting that this methodology is a reliable way of estimating freshwater fluxes in the estuary over timescales greater than the spring–neap cycle. Combining this type of field campaign with hydrodynamic modeling provides guidance for estimating both magnitude of groundwater input and estuarine storage of freshwater and sets the stage for robust estimation of the nutrient load in groundwater.

Massachusetts↗
USGS2019

Employing an ecosystem services framework to deliver decision ready science

Public land managers have limited information to allow for the integration and balancing of multiple objectives in land management decisions including the social (cultural and health), economic (monetary and nonmonetary), and environmental aspects. In this article, we document an approach to consider the many facets of decision making by incorporating them into a decision context using an ecosystem services framework. This analysis is based on a multi-partner project led by the US Geological Survey and the US Fish and Wildlife Service to provide land management decision support for the Great Dismal Swamp National Wildlife Refuge. It is an integrated ecologic-economic analysis of baseline (current) and potential future quantities, qualities, and values of selected ecosystem services from the Refuge. Alternative management scenarios are modeled to consider the impact of specific management actions or natural disturbances on priority ecosystem services. We examine the benefits and challenges of using this framework. Key lessons learned from this effort include the mismatch in timing between physical and social science; the challenge of integrating methods from multiple disciplines; the importance of frequent communication to overcome siloed research; and the utility of an integrating framework for ecosystem services and supporting tools such as the dynamic ecosystem model.

Advances in Ecological Research↗
USGS2016

A moving target—incorporating knowledge of the spatial ecology of fish into the assessment and management of freshwater fish populations

Freshwater fish move vertically and horizontally through the aquatic landscape for a variety of reasons, such as to find and exploit patchy resources or to locate essential habitats (e.g., for spawning). Inherent challenges exist with the assessment of fish populations because they are moving targets. We submit that quantifying and describing the spatial ecology of fish and their habitat is an important component of freshwater fishery assessment and management. With a growing number of tools available for studying the spatial ecology of fishes (e.g., telemetry, population genetics, hydroacoustics, otolith microchemistry, stable isotope analysis), new knowledge can now be generated and incorporated into biological assessment and fishery management. For example, knowing when, where, and how to deploy assessment gears is essential to inform, refine, or calibrate assessment protocols. Such information is also useful for quantifying or avoiding bycatch of imperiled species. Knowledge of habitat connectivity and usage can identify critically important migration corridors and habitats and can be used to improve our understanding of variables that influence spatial structuring of fish populations. Similarly, demographic processes are partly driven by the behavior of fish and mediated by environmental drivers. Information on these processes is critical to the development and application of realistic population dynamics models. Collectively, biological assessment, when informed by knowledge of spatial ecology, can provide managers with the ability to understand how and when fish and their habitats may be exposed to different threats. Naturally, this knowledge helps to better evaluate or develop strategies to protect the long-term viability of fishery production. Failure to understand the spatial ecology of fishes and to incorporate spatiotemporal data can bias population assessments and forecasts and potentially lead to ineffective or counterproductive management actions.

Environmental Monitoring and Assessment↗
USGS2010

Sharing the floodplain: Mediated modeling for environmental management

Complex ecosystems, such as the Upper Mississippi River (UMR), present major management challenges. Such systems often provide a range of ecosystem services that are differentially valued by stakeholders representing distinct interests (e.g., agriculture, conservation, navigation) or institutions (e.g., federal and state agencies). When no single entity has the knowledge or authority to resolve conflicts over shared resource use, stakeholders may struggle to jointly understand the scope of the problem and to reach reasonable compromises. This paper explores mediated modeling as a group consensus building process for understanding relationships between ecological, economic and cultural well-being in the UMR floodplain. We describe a workshop structure used to engage UMR stakeholders that may be extended to resource use conflicts in other complex ecosystems. We provide recommendations for improving on these participatory methods in structuring future efforts. In conclusion, we suggest that tools which facilitate collaborative learning, such as mediated modeling, need to be incorporated at an institutional level as a vital element of integrated ecosystem management. ?? 2008 Elsevier Ltd.

Environmental Modelling and Software↗
USGS2017

Using expert knowledge to incorporate uncertainty in cause-of-death assignments for modeling of cause-specific mortality

Implicit and explicit use of expert knowledge to inform ecological analyses is becoming increasingly common because it often represents the sole source of information in many circumstances. Thus, there is a need to develop statistical methods that explicitly incorporate expert knowledge, and can successfully leverage this information while properly accounting for associated uncertainty during analysis. Studies of cause-specific mortality provide an example of implicit use of expert knowledge when causes-of-death are uncertain and assigned based on the observer's knowledge of the most likely cause. To explicitly incorporate this use of expert knowledge and the associated uncertainty, we developed a statistical model for estimating cause-specific mortality using a data augmentation approach within a Bayesian hierarchical framework. Specifically, for each mortality event, we elicited the observer's belief of cause-of-death by having them specify the probability that the death was due to each potential cause. These probabilities were then used as prior predictive values within our framework. This hierarchical framework permitted a simple and rigorous estimation method that was easily modified to include covariate effects and regularizing terms. Although applied to survival analysis, this method can be extended to any event-time analysis with multiple event types, for which there is uncertainty regarding the true outcome. We conducted simulations to determine how our framework compared to traditional approaches that use expert knowledge implicitly and assume that cause-of-death is specified accurately. Simulation results supported the inclusion of observer uncertainty in cause-of-death assignment in modeling of cause-specific mortality to improve model performance and inference. Finally, we applied the statistical model we developed and a traditional method to cause-specific survival data for white-tailed deer, and compared results. We demonstrate that model selection results changed between the two approaches, and incorporating observer knowledge in cause-of-death increased the variability associated with parameter estimates when compared to the traditional approach. These differences between the two approaches can impact reported results, and therefore, it is critical to explicitly incorporate expert knowledge in statistical methods to ensure rigorous inference.

Ecology and Evolution↗
USGS2017

Animal movement: Statistical models for telemetry data

The study of animal movement has always been a key element in ecological science, because it is inherently linked to critical processes that scale from individuals to populations and communities to ecosystems. Rapid improvements in biotelemetry data collection and processing technology have given rise to a variety of statistical methods for characterizing animal movement. The book serves as a comprehensive reference for the types of statistical models used to study individual-based animal movement.

Book↗
USGS2017

Using multiple data types and integrated population models to improve our knowledge of apex predator population dynamics

Current management of large carnivores is informed using a variety of parameters, methods, and metrics; however, these data are typically considered independently. Sharing information among data types based on the underlying ecological, and recognizing observation biases, can improve estimation of individual and global parameters. We present a general integrated population model (IPM), specifically designed for brown bears ( Ursus arctos ), using three common data types for bear ( U . spp.) populations: repeated counts, capture–mark–recapture, and litter size. We considered factors affecting ecological and observation processes for these data. We assessed the practicality of this approach on a simulated population and compared estimates from our model to values used for simulation and results from count data only. We then present a practical application of this general approach adapted to the constraints of a case study using historical data available for brown bears on Kodiak Island, Alaska, USA. The IPM provided more accurate and precise estimates than models accounting for repeated count data only, with credible intervals including the true population 94% and 5% of the time, respectively. For the Kodiak population, we estimated annual average litter size (within one year after birth) to vary between 0.45 [95% credible interval: 0.43; 0.55] and 1.59 [1.55; 1.82]. We detected a positive relationship between salmon availability and adult survival, with survival probabilities greater for females than males. Survival probabilities increased from cubs to yearlings to dependent young ≥2 years old and decreased with litter size. Linking multiple information sources based on ecological and observation mechanisms can provide more accurate and precise estimates, to better inform management. IPMs can also reduce data collection efforts by sharing information among agencies and management units. Our approach responds to an increasing need in bear populations’ management and can be readily adapted to other large carnivores.

Ecology and Evolution↗
USGS2023

A river basin spatial model to quantitively advance understanding of riverine tree response dynamics to water availability and hydrological management

Ecological condition continues to decline in arid and semi-arid river basins globally due to hydrological over-abstraction combined with changing climatic conditions. Whilst provision of water for the environment has been a primary approach to alleviate ecological decline, how to accurately monitor changes in riverine trees at fine spatial and temporal scales, remains a substantial challenge. This is further complicated by constantly changing water availability across expansive river basins with varying climatic zones. Within, we combine rare, fine-scale, high frequency temporal in-situ field collected data with machine learning and remote sensing, to provide a robust model that enables broadscale monitoring of physiological tree water stress response to environmental changes via actual evapotranspiration (ET). Physiological variation of Eucalyptus camaldulensis (River Red Gum) and E. largiflorens (Black Box) trees across 10 study locations in the southern Murray-Darling Basin, Australia, was captured instantaneously using sap flow sensors, substantially reducing tree response lags encountered by monitoring visual canopy changes. Actual ET measurement of both species was used to bias correct a national spatial ET product where a Random Forest model was trained using continuous timeseries of in-situ data of up to four years. Precise monthly AMLETT ( A ustralia-wide M achine L earning ET for T rees) ET outputs in 30 m pixel resolution from 2012 to 2021, were derived by incorporating additional remote sensing layers such as soil moisture, land surface temperature, radiation and EVI and NDVI in the Random Forest model. Landsat and Sentinal-2 correlation results between in-situ ET and AMLETT ET returned R 2 of 0.94 (RMSE 6.63 mm period −1 ) and 0.92 (RMSE 6.89 mm period −1 ), respectively. In comparison, correlation between in-situ ET and a national ET product returned R 2 of 0.44 (RMSE 34.08 mm period −1 ) highlighting the need for bias correction to generate accurate absolute ET values. The AMLETT method presented here, enhances environmental management in river basins worldwide. Such robust broadscale monitoring can inform water accounting and importantly, assist decisions on where to prioritize water for the environment to restore and protect key ecological assets and preserve floodplain and riparian ecological function.

The Journal of Environmental Management↗
USGS2020

Quantifying and mapping inundation regimes within a large river‐floodplain ecosystem for ecological and management applications

Spatial information on the distribution of ecosystem patterns and processes can be a critical component of designing and implementing effective management programs in river‐floodplain ecosystems. For example, translating how flood pulses detected within a stream gauge record are spatially manifested across a river‐valley bottom can be used to evaluate whether the current distribution of physical conditions has the potential to support priority habitats or if intervention is needed to meet desired goals. The size and complexity of large river‐floodplain systems can make mapping inundation dynamics a challenging task. We used a geospatial model to simulate 40 years (1972–2011) of daily surface‐water inundation depths for 11,331 km 2 of the Upper Mississippi River System floodplain. We identified discrete inundation events at each 4‐m × 4‐m pixel in the model as sequential days of submergence. We then quantified and mapped four aspects of inundation regime – event frequency, duration, magnitude, and timing – for each pixel. The spatial distribution of inundation regime attributes varied within and among multiple levels of river organization, including navigation pools and geomorphic reaches, but only event timing exhibited a strong down‐river trend. Non‐linear relations among inundation attributes and their geospatial distributions likely reflect complex interactions among topographic, hydrologic, and anthropogenic constraints on flooding dynamics. Together, our results reveal spatial gradients in inundation dynamics not captured by hydrologic data alone. Characterizing such diversity in inundation dynamics is important for testing hypotheses about ecological processes, developing models of ecosystem functions, and informing management actions.

Illinois, Indiana, Iowa, Minnesota, Missouri, Wisc↗
USGS2019

Projected urban growth in the Southeastern USA puts small streams at risk

Future land-use development has the potential to profoundly affect the health of aquatic ecosystems in the coming decades. We developed regression models predicting the loss of sensitive fish (R2=0.39) and macroinvertebrate (R2=0.64) taxa as a function of urban and agricultural land uses and applied them to projected urbanization of the rapidly urbanizing Piedmont ecoregion of the southeastern USA for 2030 and 2060. The regression models are based on a 2014 investigation of water quality and ecology of 75 wadeable streams across the region. Based on these projections, stream kilometers experiencing >50% loss of sensitive fish and invertebrate taxa will nearly quadruple to 19,500 and 38,950 km by 2060 (16 and 32% of small stream kilometers in the region), respectively. Uncertainty was assessed using the 20 and 80% probability of urbanization for the land-use projection model and using the 95% confidence intervals for the regression models. Adverse effects on stream health were linked to elevated concentrations of contaminants and nutrients, low dissolved oxygen, and streamflow alteration, all associated with urbanization. The results of this analysis provide a warning of potential risks from future urbanization and perhaps some guidance on how those risks might be mitigated.

PLoS ONE↗
USGS2006

A method for landscape analysis of forestry guidelines using bird habitat models and the Habplan harvest scheduler

Wildlife-habitat relationship models have sometimes been linked with forest simulators to aid in evaluating outcomes of forest management alternatives. However, linking wildlife-habitat models with harvest scheduling software would provide a more direct method for assessing economic and ecological implications of alternative harvest schedules in commercial forest operations. We demonstrate an approach for frontier analyses of wildlife benefits using the Habplan harvest scheduler and spatially explicit wildlife response models in the context of operational forest planning. We used the Habplan harvest scheduler to plan commercial forest management over a 40-year horizon at a landscape scale under five scenarios: unmanaged, an unlimited block-size option both with and without riparian buffers, three cases with different block-size restrictions, and a set-asides scenario in which older stands were withheld from cutting. The potential benefit to wildlife was projected based on spatial models of bird guild richness and species probability of detection. Harvested wood volume provided a measure of scenario costs, which provides an indication of management feasibility. Of nine species and guilds, none appeared to benefit from 50 m riparian buffers, response to an unmanaged scenario was mixed and expensive, and block-size restrictions (maximum harvest unit size) provided no apparent benefit and in some cases were possibly detrimental to bird richness. A set-aside regime, however, appeared to provide significant benefits to all species and groups, probably through increased landscape heterogeneity and increased availability of older forest. Our approach shows promise for evaluating costs and benefits of forest management guidelines in commercial forest enterprises and improves upon the state of the art by utilizing an optimizing harvest scheduler as in commercial forest management, multiple measures of biodiversity (models for multiple species and guilds), and spatially explicit wildlife response models. ?? 2006 Elsevier B.V. All rights reserved.

Forest Ecology and Management↗
USGS2009

Relationship of stream ecological conditions to simulated hydraulic metrics across a gradient of basin urbanization

The relationships among urbanization, stream hydraulics, and aquatic biology were investigated across a gradient of urbanization in 30 small basins in eastern Wisconsin, USA. Simulation of hydraulic metrics with 1-dimensional unsteady flow models was an effective means for mechanistically coupling the effects of urbanization with stream ecological conditions (i.e., algae, invertebrates, and fish). Urbanization, characterized by household, road, and urban land density, was positively correlated with the lowest shear stress for 2 adjacent transects in a reach for the low-flow summer (p < 0.001) and autumn (p < 0.01) periods. Urbanization also was positively correlated with Reynolds number and % exposed stream bed during months with moderate to low flows. Our study demonstrated the value of temporally and spatially explicit hydraulic models for providing mechanistic insight into the relationships between hydraulic variables and biological responses. For example, the positive correlation between filter-feeding invertebrate richness and minimum 2-transect shear stress observed in our study is consistent with a higher concentration of water-column particulates available for filtration. The strength of correlations between hydraulic and biological metrics is related to the time period (annual, seasonal, or monthly) considered. The hydraulic modeling approach, whether based on hourly or daily flow data, allowed documentation of the effects of a spatially variable response within a reach, and the results suggest that stream response to urbanization varies with hydraulic habitat type. ?? North American Benthological Society.

Journal of the North American Benthological Societ↗
USGS2024

Identifying indicators of polar bear population status

Monitoring trends in large mammal populations is a fundamental component of wildlife management and conservation. However, direct estimates of population size and vital rates of large mammals can be logistically challenging and expensive. Indicators that reflect trends in abundance, therefore, can be valuable tools for supporting population monitoring. Polar bears have a relatively simple life history such that a few key variables may be effective indicators for tracking changes in body condition and recruitment that affect abundance. Direct estimates of polar bear abundance are difficult to obtain due to their large home ranges in remote Arctic habitats. Changes in abundance associated with environmental conditions appear to affect polar bears largely via effects on female body condition which influence reproduction and cub survival (i.e., recruitment). Loss of sea ice habitat is further limiting researcher access for population monitoring creating a need for alternative approaches. Here we used relationships established from eight years (2008–2017) of data collected on 439 polar bears in the Chukchi Sea, to transform previously published individual-based relationships with annually available sea ice, atmospheric circulation, and prey body condition variables to predict annual mean body condition and recruitment during 2018–2022. Although annual sample sizes were limited for verifying predicted body condition and recruitment via techniques such as cross-validation, in most cases predicted annual means were closely correlated with observed means for 2008–2017. Summer sea ice and prey body condition remained within or increased relative to levels observed during 2008–2017 and predicted polar bear body condition and recruitment during 2018–2022 were largely within or above observed annual means during 2008–2017. A lack of trend in environmental and ecological variables or polar bear body condition and recruitment metrics during 2008–2022 is suggestive that the Chukchi Sea polar bear population was likely stable during this time. Our results provide support for developing models that predict important population parameters of large mammals based on environmental and ecological indicators. Given that trend information is lacking for 10 of the 19 recognized polar bear populations and is outdated for others, the use of environmental and ecological indicators may be particularly useful for augmenting direct estimates of polar bear vital rates in between periods of data collection. Although demographic assessments for polar bears have primarily focused on correlations with sea ice availability, our study and others highlight that prey health is also an important indicator of polar bear population status.

Ecological Indicators↗
USGS2016

Tidal hydrodynamics under future sea level rise and coastal morphology in the Northern Gulf of Mexico

This study examines the integrated influence of sea level rise (SLR) and future morphology on tidal hydrodynamics along the Northern Gulf of Mexico (NGOM) coast including seven embayments and three ecologically and economically significant estuaries. A large-domain hydrodynamic model was used to simulate astronomic tides for present and future conditions (circa 2050 and 2100). Future conditions were simulated by imposing four SLR scenarios to alter hydrodynamic boundary conditions and updating shoreline position and dune heights using a probabilistic model that is coupled to SLR. Under the highest SLR scenario, tidal amplitudes within the bays increased as much as 67% (10.0 cm) because of increases in the inlet cross-sectional area. Changes in harmonic constituent phases indicated that tidal propagation was faster in the future scenarios within most of the bays. Maximum tidal velocities increased in all of the bays, especially in Grand Bay where velocities doubled under the highest SLR scenario. In addition, the ratio of the maximum flood to maximum ebb velocity decreased in the future scenarios (i.e., currents became more ebb dominant) by as much as 26% and 39% in Weeks Bay and Apalachicola, respectively. In Grand Bay, the flood-ebb ratio increased (i.e., currents became more flood dominant) by 25% under the lower SLR scenarios, but decreased by 16% under the higher SLR as a result of the offshore barrier islands being overtopped, which altered the tidal prism. Results from this study can inform future storm surge and ecological assessments of SLR, and improve monitoring and management decisions within the NGOM.

Florida, Louisiana↗
USGS2020

2023 Coastal master plan: Model improvement plan, ICM-wetlands, vegetation, and soil

As part of the model improvement effort for the 2023 Coastal Master Plan, the wetland processes captured by the morphology and vegetation models used during previous master plans were reevaluated to assess how Integrated Compartment Model (ICM) subroutines could be improved. This process considered technical reviews, comments, and suggested improvements provided by model developers, advisory groups, and other experts during previous master plan cycles. The availability of new data and information that could be used to make model improvements was also considered. In many cases, the team considered and tested multiple options or approaches. As a result of this effort, recommended improvements are provided here. The improvements recommended to be included in the 2023 Coastal Master Plan include: adjusting marsh collapse thresholds, refining organic matter accretion calculations, developing an unstructured grid for modeling vegetation, improving flotant marsh and forested wetlands algorithms, creating and applying an updated map of existing vegetation, adjusting model code, and updating the submerged aquatic vegetation (SAV) module. This report describes the team’s work through a series of 7 distinct activities to identify and test options for model improvements to ensure the updated ICM used for the 2023 Coastal Master Plan appropriately captures ecological and morphological processes observed in Coastal Louisiana. As appropriate, relevant literature and data are discussed. Test runs to evaluate how changes influence model outputs are also documented. A final list of recommended updates, taking into account consideration of all options and results from test runs, is summarized at the end of the report. A later report will describe the final ICM-LAVegMod and ICM-Morph subroutines for the 2023 Coastal Master Plan, detailing the updates that have been incorporated.

Louisiana↗
USGS1997

The role of mesocosm studies in ecological risk analysis

Mesocosms have been primarily used as research tools for the evaluation of the fate and effects of xenobiotic chemicals at the population, community, and ecosystem levels of biological organization. This paper provides suggestions for future applications of mesocosm research. Attention should be given to the configuration of mesocosm parameters to explicitly study regional questions of ecological interest. The initial physical, chemical, and biological conditions within mesocosms should be considered as factors shaping the final results of experiments. Certain fundamental questions such as the ecological inertia and resilience of systems with different initial ecological properties should be addressed. Researchers should develop closer working relationships with mathematical modelers in linking computer models to the outcomes of mesocosm studies. Mesocosm tests, linked with models, could enable managers and regulators to forecast the regional consequences of chemicals released into the environment.

Ecological Applications↗
USGS2025

The tortoise and the antilocaprid: Adapting GPS tracking and terrain data to model wildlife walking functions

Context The relationship between slope and terrestrial animal locomotion is key to landscape ecology but underexplored across species. This is partly due to a lack of scalable methodology that applies to a diversity of wildlife. Objectives This study investigates the slope-speed relationship for two species, Texas tortoise ( Gopherus berlandieri ) and pronghorn ( Antilocapra americana ), through the combined application of remote sensing, GPS tracking, behavior models, and parametric distribution. While using readily available Digital Elevation Models (DEM) for pronghorn, we explore the use of very high-resolution lidar Digital Terrain Models (DTM) from Unoccupied Aerial Systems (UAS) to characterize tortoise movements at micro-scales. Methods After classifying animal behavior with GPS tracking data and Hidden Markov Models (HMMs), we analyzed the relationship between the speed of the animals and the slope of the terrain using a 30-m DEM for pronghorn, and a fine-scale UAS DTM for Texas tortoise, and three nonlinear models: Laplace, Gauss, and Lorentz. Results High-resolution DTM, coupled with GPS tracking, accurately models the relationship of speed and slope at a micro-scale, while a DEM is suitable for a larger scale. Laplace models best predicted the speed of both the Texas tortoise and pronghorn. Models showed tortoises, which are not known for rapid and agile movement like the pronghorn, have a broader tolerance for varying slopes at a fine scale. Conclusions These findings enhance understanding of species-specific movement offering valuable insights for habitat management and conservation tailored to species’ behaviors and capabilities.

Colorado, Texas, Wyoming↗
USGS2011

Restoring and rehabilitating sagebrush habitats

Less than half of the original habitat of the Greater Sage-Grouse (Centrocercus uropha-sianus) currently exists. Some has been perma-nently lost to farms and urban areas, but the remaining varies in condition from high quality to no longer adequate. Restoration of sagebrush (Artemisia spp.) grassland ecosystems may be pos-sible for resilient lands. However, Greater Sage-Grouse require a wide variety of habitats over large areas to complete their life cycle. Effective restoration will require a regional approach for prioritizing and identifying appropriate options across the landscape. A landscape triage method is recommended for prioritizing lands for restora-tion. Spatial models can indicate where to protect and connect intact quality habitat with other simi-lar habitat via restoration. The ecological site con-cept of land classification is recommended for characterizing potential habitat across the region along with their accompanying state and transi-tion models of plant community dynamics. These models assist in identifying if passive, manage-ment-based or active, vegetation manipulation?based restoration might accomplish the goals of improved Greater Sage-Grouse habitat. A series of guidelines help formulate questions that manag-ers might consider when developing restoration plans: (1) site prioritization through a landscape triage; (2) soil verification and the implications of soil features on plant establishment success; (3) a comparison of the existing plant community to the potential for the site using ecological site descriptions; (4) a determination of the current successional status of the site using state and transition models to aid in predicting if passive or active restoration is necessary; and (5) implemen-tation of post-treatment monitoring to evaluate restoration effectiveness and post-treatment man-agement implications to restoration success.

Book chapter↗