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Writing SMART objectives for natural resource and environmental management

In natural resource and environmental management, well-written objectives are critical for effective decision-making and the achievement of desired outcomes. This article aims to improve practitioners' ability to identify and write SMART ( S pecific, M easurable, A chievable, R elevant, T ime-bound) objectives for natural resource and environmental management. We differentiate between research and management objectives, define each SMART criterion, and introduce a template to help write management objectives. We demonstrate the use of the SMART management objectives template with a hypothetical example and two recent applications. The template simplifies the process of writing SMART management objectives. It is applicable to popular management frameworks like management by objectives and structured decision making. The implementation of SMART criteria and the provided template can lead to better outcomes in natural resource and environmental management, benefiting current and future generations.

Ecological Solutions and Evidence↗

SPCIS: Standardized Plant Community with Introduced Status database

The movement of plant species across the globe exposes native communities to new species introductions. While introductions are pervasive, two aspects of variability underlie patterns and processes of biological invasions at macroecological scales. First, only a portion of introduced species become invaders capable of substantially impacting ecosystems. Second, species that do become invasive at one location may not be invasive in others; impacts depend on invader abundance and recipient species and conditions. Accounting for these phenomena is essential to accurately understand the patterns of plant invasion and explain the idiosyncratic results reflected in the literature on biological invasions. The lack of community-level richness and the abundance of data spanning broad scales and environmental conditions have until now hindered our understanding of invasions at a macroecological scale. To address this limitation, we leveraged quantitative surveys of plant communities in the USA and integrated and harmonized nine datasets into the Standardized Plant Community with Introduced Status (SPCIS) database. The database contains 14,056 unique taxa identified within 83,391 sampling units, of which 52.6% have at least one introduced species. The SPCIS database includes comparable information on plant species occurrence, abundance, and native status across the 50 U.S. States and Puerto Rico. SPCIS can be used to answer macro-scale questions about native plant communities and interactions with invasive plants. There are no copyright restrictions on the data, and we ask the users of this dataset to cite this paper, the respective paper(s) corresponding to the dataset sampling design (all references are provided in Data S1: Metadata S1: Class II-B-2), and the references described in Data S1: Metadata S1: Class III-B-4 as applicable to the dataset being utilized.

Ecology↗

Adaptive resource management: Achieving functional eradication of invasive snakes to benefit avian conservation

Natural resource management often co-occurs with considerable uncertainty. One approach to mitigating uncertainty is through adaptive resource management (ARM), a specialized form of structured decision-making that modifies management decisions or actions through monitoring and implementation. Here, we present a case study on the attempted eradication of an invasive brown treesnake ( Boiga irregularis ) in a 5-ha enclosure on Guam with uncertainty in approach. We applied an ARM process across three field phases of snake removal and evaluated whether (1) eradication was achievable and (2) eradication was necessary to achieve an avian response. Field phases included the application of aerial toxic baits, toxicant baiting large mouse and birds, trapping with live mouse and bird lures and hand capture. We found that each removal technique improved control by either removing many individuals or targeting a subset of individuals that resisted prior control approaches. Although the effort did not result in eradication, the evaluation of identified indicators allowed for timely adjustments to removal using the ARM process. The snake removal efforts yielded an avian response in the treatment area after integrating live birds as snake lures, suggesting functional eradication of snakes may be possible. We also, however, observed a release of invasive rodents following snake control, with birds being more sensitive to the presence of snakes than rodents. Synthesis and applications . We suggest that using adaptive resource management to evaluate each phase of action in relation to established goals allowed us to measure outcomes and was successful in eliminating uncertainty in the application of control tools for wildlife conservation. We were able to create a documented and successful approach towards removing snakes inside a snake-exclusion barrier by following the ARM process.

Journal of Applied Ecology↗

Projecting the long-term effects of large-scale human influence on the spatial and functional persistence of extant longleaf pine ecosystems in the Florida Flatwoods Pyrome

Decades of human activities and fire suppression have adversely affected longleaf pine ( Pinus palustris ) ecosystems, which are home to high levels of diversity and endemism. These iconic ecosystems also now face challenges from urbanization and climate change, which will alter conservation outcomes over the remainder of the 21st century. To explore how long-term, large-scale human influences could affect the spatial and functional persistence of extant longleaf pine ecosystems in the Florida Flatwoods Pyrome, we extracted a set of 2400 longleaf pine patches ≥40 ha in size from the Florida Longleaf Pine Ecosystem Geodatabase. Projections from the FUTURES urban growth model and the Florida 2070 project indicate that development will lead to losses of existing longleaf pine habitat, reductions in longleaf pine patch size, and patches that are predominantly located in close proximity to developed areas. Finer-scale patterns of longleaf pine loss in three focal landscapes highlighted differences in land protection, ecological setting, and development pressure and the value of using of multiple urbanization iterations. The occurrence of suitable conditions to conduct prescribed fires, a crucial tool for maintaining, improving, and restoring longleaf pine ecosystems, is projected to decrease seasonally throughout the study area. As a result, the functional persistence of ecosystems is at risk due to climate changes that increase barriers to the safe and reliable application of intentional fire. The long-term viability of this critical ecosystem will warrant the evaluation of adaptive strategies that explicitly account for the individual and compounding effects of urban development and changing fire management conditions when considering options for ecosystem protection, management, and restoration.

Florida↗

Detecting shrub recovery in sagebrush steppe: Comparing Landsat-derived maps with field data on historical wildfires

Background The need for basic information on spatial distribution and abundance of plant species for research and management in semiarid ecosystems is frequently unmet. This need is particularly acute in the large areas impacted by megafires in sagebrush steppe ecosystems, which require frequently updated information about increases in exotic annual invaders or recovery of desirable perennials. Remote sensing provides one avenue for obtaining this information. We considered how a vegetation model based on Landsat satellite imagery (30 m pixel resolution; annual images from 1985 to 2018) known as the National Land Cover Database (NLCD) “Back-in-Time” fractional component time-series, compared with field-based vegetation measurements. The comparisons focused on detection thresholds of post-fire emergence of fire-intolerant Artemisia L . species, primarily A. tridentata Nutt. (big sagebrush). Sagebrushes are scarce after fire and their paucity over vast burn areas creates challenges for detection by remote sensing. Measurements were made extensively across the Great Basin, USA, on eight burn scars encompassing ~500 000 ha with 80 plots sampled, and intensively on a single 113 000 ha burned area where we sampled 1454 plots. Results Estimates of sagebrush cover from the NLCD were, as a mean, 6.5% greater than field-based estimates, and variance around this mean was high. The contrast between sagebrush cover measurements in field data and NLCD data in burned landscapes was considerable given that maximum cover values of sagebrush were ~35% in the field. It took approximately four to six years after the fire for NLCD to detect consistent, reliable signs of sagebrush recovery, and sagebrush cover estimated by NLCD ranged from 3 to 13% (equating to 0 to 7% in field estimates) at these times. The stabilization of cover and presence four to six years after fire contrasted with previous field-based studies that observed fluctuations over longer time periods. Conclusions While results of this study indicated that further improvement of remote sensing applications would be necessary to assess initial sagebrush recovery patterns, they also showed that Landsat satellite imagery detects the influence of burns and that the NLCD data tend to show faster rates of recovery relative to field observations.

Oregon, Idaho, Nevada, Utah↗

Inference about density and temporary emigration in unmarked populations

Few species are distributed uniformly in space, and populations of mobile organisms are rarely closed with respect to movement, yet many models of density rely upon these assumptions. We present a hierarchical model allowing inference about the density of unmarked populations subject to temporary emigration and imperfect detection. The model can be fit to data collected using a variety of standard survey methods such as repeated point counts in which removal sampling, double‐observer sampling, or distance sampling is used during each count. Simulation studies demonstrated that parameter estimators are unbiased when temporary emigration is either “completely random” or is determined by the size and location of home ranges relative to survey points. We also applied the model to repeated removal sampling data collected on Chestnut‐sided Warblers ( Dendroica pensylvancia ) in the White Mountain National Forest, USA. The density estimate from our model, 1.09 birds/ha, was similar to an estimate of 1.11 birds/ha produced by an intensive spot‐mapping effort. Our model is also applicable when processes other than temporary emigration affect the probability of being available for detection, such as in studies using cue counts. Functions to implement the model have been added to the R package unmarked .

New Hampshire↗

A synthesis of thresholds for focal species along the U.S. Atlantic and Gulf Coasts: A review of research and applications

The impacts from climate change are increasing the possibility of vulnerable coastal species and habitats crossing critical thresholds that could spur rapid and possibly irreversible changes. For species of high conservation concern, improved knowledge of quantitative thresholds could greatly improve management. To meet this need, we synthesized information pertaining to biological responses as tipping points to sea level rise (SLR) and coastal storms for 45 fish, wildlife, and plant species along the U.S. Atlantic and Gulf Coasts and Caribbean through a literature review and expert elicitation. Although these species were selected based on their ecological, economic, and cultural importance, just over half (56%, n = 25) have quantitative threshold data currently available that can be used to assess the effects of SLR and storms during some aspect of their life history. Birds, reptiles, and plants represent the best studied coastal species. Thirteen of the species (29%) are projected to lose at least 50% of their population or habitat (e.g., foraging, nesting, spawning, or resting habitat) in some areas with a 0.5 m or greater rise in sea levels by 2100. Two species (a bird and reptile) may gain habitat from projected SLR and be resilient to future impacts. Numeric thresholds were not available for the remaining 20 species we searched for. Coastal fishes, mammals, and amphibians were among the groups representing a major information gap in this field of research. In addition, quantitative threshold responses to coastal storms were scarce for all taxa. While vulnerability assessments and qualitative research related to the impacts of SLR and storms on coastal species and habitats are increasing, work that incorporates quantitative thresholds as response and impact metrics remains limited. Additional monitoring, modeling, and research that provides multiple quantitative thresholds across species' life stages and/or latitudinal gradients is ideal to support robust coastal management and decision-making across spatio-temporal scales in the face of climate change.

Ocean and Coastal Management↗

U.S. Geological Survey ecosystems science strategy—Advancing discovery and application through collaboration

Executive Summary Ecosystem science is critical to making informed decisions about natural resources that can sustain our Nation’s economic and environmental well-being. Resource managers and policymakers are faced with countless decisions each year at local, regional, and national levels on issues as diverse as renewable and nonrenewable energy development, agriculture, forestry, water supply, and resource allocations at the urban-rural interface. The urgency for sound decisionmaking is increasing dramatically as the world is being transformed at an unprecedented pace and in uncertain directions. Environmental changes are associated with natural hazards, greenhouse gas emissions, and increasing demands for water, land, food, energy, mineral, and living resources. At risk is the Nation’s environmental capital, the goods and services provided by resilient ecosystems that are vital to the health and wellbeing of human societies. Ecosystem science—the study of systems of organisms interacting with their environment and the consequences of natural and human-induced change on these systems—is necessary to inform decisionmakers as they develop policies to adapt to these changes. This Ecosystems Science Strategy is built on a framework that includes basic and applied science. It highlights the critical roles that U.S. Geological Survey (USGS) scientists and partners can play in building scientific understanding and providing timely information to decisionmakers. The strategy underscores the connection between scientific discoveries and the application of new knowledge, and it integrates ecosystem science and decisionmaking, producing new scientific outcomes to assist resource managers and providing public benefits. We envision the USGS as a leader in integrating scientific information into decisionmaking processes that affect the Nation’s natural resources and human well-being. The USGS is uniquely positioned to play a pivotal role in ecosystem science. With its wide range of expertise, the Bureau can bring holistic, cross-scale, interdisciplinary capabilities to the design and conduct of monitoring, research, and modeling and to new technologies for data collection, management, and visualization. Collectively, these capabilities can be used to reveal ecological patterns and processes, explain how and why ecosystems change, and forecast change over different spatial and temporal scales. USGS science can provide managers with options and decision-support tools to use resources sustainably. The USGS has long-standing, collaborative relationships with the Department of the Interior (DOI) and other partners in the natural sciences, in both conducting science and applying the results. The USGS engages these partners in cooperative investigations that otherwise would lack the necessary support or be too expensive for a single bureau to conduct. The heart of this strategy is a framework for USGS ecosystems science that focuses on five long-term goals, which are seen as interconnected components that reinforce our vision of the USGS providing science that is at the forefront of decisionmaking: Improve understanding of ecosystem structure, function, and processes. The focus for this goal is an understanding of how ecosystems work, including the dynamics of species, their populations, interactions, and genetics, and how they change across spatial and temporal scales. Advance understanding of how drivers influence ecosystem change. The challenges here are explaining the drivers of ecosystem change, their spatio-temporal patterns, their uncertainties and interactions, and their influence on ecosystem processes and dynamics. Improve understanding of the services that ecosystems provide to society. Here the emphasis is on the measurement of environmental capital and ecosystem services, and the identification of sources and patterns of change in space and time. Develop tools, technologies, and capacities to inform decisionmaking about ecosystems. This includes developing new technologies and approaches for conducting applications-oriented ecosystem science. A principal challenge will be how to quantify uncertainty and incorporate it in decision analysis. Apply science to enhance strategies for management, conservation, and restoration of ecosystems. These challenges include development of novel approaches to monitoring, assessment, and restoration of ecosystems; new methods to address species of concern and communities at risk; and innovations in decision analysis and support to address imminent ecosystem changes or those that are underway. Closely integrated with the five goals are four strategic approaches that provide the path forward for the USGS Ecosystems Mission Area. These approaches cross-cut all of the goals and are seen as essential to the implementation of this strategy: Assess information needs for ecosystem science through enhanced partnerships. Work with the DOI and other agencies and institutions to identify, design, and implement priority decision-driven ecological research. Promote the use of interdisciplinary ecosystem science. Design and conduct interdisciplinary process-oriented research in ecosystem science. Enhance modeling and forecasting. Build models to forecast ecosystem change, assess future management scenarios, and reduce uncertainties through an adaptive learning process. Support decisionmaking. Use quantitative approaches to assess the vulnerabilities of ecosystems, habitats, and species, and evaluate strategies for adaptation, restoration, and sustainable management. Following the four strategic approaches are a set of proposed actions that represent a sampling of specific USGS activities that align with this strategy and that address the Nation’s most pressing environmental needs. The strategy emphasizes coordination of activities across the USGS mission areas pursuant to these goals. Ecosystem science is inherently interdisciplinary and requires a broad perspective that incorporates the biological and physical sciences, climate science, information technology, and scientific capacity in mission areas across the Bureau. With its emphasis on coordination, this strategy can provide a critical underpinning for integrated science efforts with scientists from multiple mission areas of the USGS working together. Of course, the USGS will continue to conduct discipline-specific and interdisciplinary investigations, and both will continue to be vital parts of the ecosystem science portfolio. Finally, the strategy stresses the importance of coordination with other Federal agencies and organizations in the natural resources community. The USGS collaborates with resource agencies in the DOI and other organizations throughout the world to meet societal needs for species and ecosystem management. Working with these agencies and organizations, the USGS will play a key role in guiding sound decisionmaking during the next decade by advancing the scientific foundation for sustaining the natural resources that diverse, productive, resilient ecosystems provide.

Circular↗

How will predicted land-use change affect waterfowl spring stopover ecology? Inferences from an individual-based model

Habitat loss, habitat fragmentation, overexploitation and climate change pose familiar and new challenges to conserving natural populations throughout the world. One approach conservation planners may use to evaluate the effects of these challenges on wildlife populations is scenario planning. We developed an individual-based model to evaluate the effects of future land use and land cover changes on spring-migrating dabbling ducks in North America. We assessed the effects of three Intergovernmental Panel on Climate Change emission scenarios (A1B, A2 and B1) on dabbling duck stopover duration, movement distances and mortality. We specifically focused on migration stopover duration because previous research has demonstrated that individuals arriving earlier on the nesting grounds exhibit increased reproductive fitness. Compared to present conditions, all three scenarios increased stopover duration and movement distances of agent ducks. Although all three scenarios presented migrating ducks with increased amounts of wetland habitat, scenarios also contained substantially less cropland, which decreased overall carrying capacity of the study area. Synthesis and applications . Land-use change may increase waterfowl spring migration stopover duration in the midcontinent region of North America due to reduced landscape energetic carrying capacity. Climate change will alter spatial patterns of crop distributions with corn and rice production areas shifting to different regions. Thus, conservation planners will have to address population-level energetic implications of shifting agricultural food resources and increased uncertainty in yearly precipitation patterns within the next 50 years.

Journal of Applied Ecology↗

A biological condition gradient for Caribbean coral reefs: Part II. Numeric rules using sessile benthic organisms

The Biological Condition Gradient (BCG) is a conceptual model used to describe incremental changes in biological condition along a gradient of increasing anthropogenic stress. As coral reefs collapse globally, scientists and managers are focused on how to sustain the crucial structure and functions, and the benefits that healthy coral reef ecosystems provide for many economies and societies. We developed a numeric (quantitative) BGC model for the coral reefs of Puerto Rico and the US Virgin Islands to transparently facilitate ecologically meaningful management decisions regarding these fragile resources. Here, reef conditions range from natural, undisturbed conditions to severely altered or degraded conditions. Numeric decision rules were developed by an expert panel for scleractinian corals and other benthic assemblages using multiple attributes to apply in shallow-water tropical fore reefs with depths <30 m. The numeric model employed decision rules based on metrics (e.g., % live coral cover, coral species richness, pollution-sensitive coral species, unproductive and sediment substrates, % cover by Orbicella spp.) used to assess coral reef condition. Model confirmation showed the numeric BCG model predicted the panel’s median site ratings for 84% of the sites used to calibrate the model and 89% of independent validation sites. The numeric BCG model is suitable for adaptive management applications and supports bioassessment and criteria development. It is a robust assessment tool that could be used to establish ecosystem condition that would aid resource managers in evaluating and communicating current or changing conditions, protect water and habitat quality in areas of high biological integrity, or develop restoration goals with stakeholders and other public beneficiaries.

Ecological Indicators↗

Long-term lesser prairie-chicken nest ecology in response to grassland management

Long-term population and range declines from habitat loss and fragmentation caused the lesser prairie-chicken ( Tympanuchus pallidicinctus ) to be a species of concern throughout its range. Current lesser prairie-chicken range in New Mexico and Texas is partially restricted to sand shinnery oak ( Quercus havardii ; hereafter shinnery oak) prairies, on which cattle grazing is the main socioeconomic driver for private landowners. Cattle producers within shinnery oak prairies often focus land management on shrub eradication using the herbicide tebuthiuron to promote grass production for forage; however, herbicide application alone, and in combination with grazing, may affect nest site selection and nest survival of lesser prairie-chickens through the reduction of shinnery oak and native grasses. We used a controlled, paired, completely randomized design study to assess the influence of grazing and tebuthiuron application and their combined use on nest site selection and nest survival from 2001 to 2010 in Roosevelt County, New Mexico, USA at 2 spatial scales (i.e., treatment and microhabitat) in 4 treatments: tebuthiuron with grazing, tebuthiuron without grazing, no tebuthiuron with grazing, and a control of no tebuthiuron and no grazing. Grazing treatment was a short-duration system in which plots were grazed once during the dormant season and once during the growing season. Stocking rate was calculated each season based on measured forage production and applied to remove &le;25% of available herbaceous material per season. At the treatment scale, we compared nest site selection among treatments using 1-way &chi; 2 tests and nest survival among treatments using a priori candidate nest survival models in Program MARK. At the microhabitat scale, we identified important habitat predictors of nest site selection and nest survival using logistic regression and a priori candidate nest survival models in Program MARK, respectively. Females typically used treatments as expected and we did not detect trends in selection. Nest survival did not differ among treatments. At the microhabitat scale, nest sites had less bare ground ( P&thinsp; =&thinsp;0.001) and greater angles of obstruction ( P &thinsp;&le;&thinsp;0.001) compared to random sites. There was a high degree of model selection uncertainty among our candidate models at the microhabitat scale and survival estimates were similar among habitat covariates. Results suggest a tebuthiuron application rate of 0.60&thinsp;kg/ha, short-duration grazing, and a combination of these management techniques were not detrimental to lesser prairie-chicken nest site selection or nest survival. However, intensified management that increases bare ground or reduces overhead cover may negatively affect lesser prairie-chicken nesting habitat and nest survival.

Journal of Wildlife Management↗

Greater sage-grouse respond positively to intensive post-fire restoration treatments

Habitat loss is the most prevalent threat to biodiversity in North America. One of the most threatened landscapes in the United States is the sagebrush ( Artemisia spp.) ecosystem, much of which has been fragmented or converted to non-native grasslands via the cheatgrass-fire cycle. Like many sagebrush obligates, greater sage-grouse ( Centrocercus urophasianus ) depend upon sagebrush for food and cover and are affected by changes to this ecosystem. We investigated habitat selection by 28 male greater sage-grouse during each of 3 years after a 113,000-ha wildfire in a sagebrush steppe ecosystem in Idaho and Oregon. During the study period, seeding and herbicide treatments were applied for habitat restoration. We evaluated sage-grouse responses to vegetation and post-fire restoration treatments. Throughout the 3 years post-fire, sage-grouse avoided areas with high exotic annual grass cover but selected strongly for recovering sagebrush and moderately strongly for perennial grasses. By the third year post-fire, they preferred high-density sagebrush, especially in winter when sagebrush is the primary component of the sage-grouse diet. Sage-grouse preferred forb habitat immediately post-fire, especially in summer, but this selection preference was less strong in later years. They also selected areas that were intensively treated with herbicide and seeded with sagebrush, grasses, and forbs, although these responses varied with time since treatment. Wildfire can have severe consequences for sagebrush-obligate species due to loss of large sagebrush plants used for food and for protection from predators and thermal extremes. Our results show that management efforts, including herbicide application and seeding of plants, directed at controlling exotic annual grasses after a wildfire can positively affect habitat selection by sage-grouse.

Ecology and Evolution↗

A new genomic resource to enable standardized surveys of SNPs across the native range of brook trout (Salvelinus fontinalis)

Understanding how genetic diversity is distributed across spatiotemporal scales in species of conservation or management concern is critical for identifying large-scale mechanisms affecting local conservation status and implementing large-scale biodiversity monitoring programmes. However, cross-scale surveys of genetic diversity are often impractical within single studies, and combining datasets to increase spatiotemporal coverage is frequently impeded by using different sets of molecular markers. Recently developed molecular tools make surveys based on standardized single-nucleotide polymorphism (SNP) panels more feasible than ever, but require existing genomic information. Here, we conduct the first survey of genome-wide SNPs across the native range of brook trout (Salvelinus fontinalis), a cold-adapted species that has been the focus of considerable conservation and management effort across eastern North America. Our dataset can be leveraged to easily design SNP panels that allow datasets to be combined for large-scale analyses. We performed restriction site-associated DNA sequencing for wild brook trout from 82 locations spanning much of the native range and domestic brook trout from 24 hatchery strains used in stocking efforts. We identified over 24,000 SNPs distributed throughout the brook trout genome. We explored the ability of these SNPs to resolve relationships across spatial scales, including population structure and hatchery admixture. Our dataset captures a wide spectrum of genetic diversity in native brook trout, offering a valuable resource for developing SNP panels. We highlight potential applications of this resource with the goal of increasing the integration of genomic information into decision-making for brook trout and other species of conservation or management concern.

Molecular Ecology Resources↗

Animal movement models for migratory individuals and groups

Animals often exhibit changes in their behaviour during migration. Telemetry data provide a way to observe geographic position of animals over time, but not necessarily changes in the dynamics of the movement process. Continuous‐time models allow for statistical predictions of the trajectory in the presence of measurement error and during periods when the telemetry device did not record the animal's position. However, continuous‐time models capable of mimicking realistic trajectories with sufficient detail are computationally challenging to fit to large datasets. Furthermore, basic continuous‐time model specifications (e.g. Brownian motion) lack realism in their ability to capture nonstationary dynamics. We present a unified class of animal movement models that are computationally efficient and provide a suite of approaches for accommodating nonstationarity in continuous trajectories due to migration and interactions among individuals. Our approach uses process convolutions to allow for flexibility in the movement process while facilitating implementation and incorporating location uncertainty. We show how to nest convolution models to incorporate interactions among migrating individuals to account for nonstationarity and provide inference about dynamic migratory networks. We demonstrate these approaches in two case studies involving migratory birds. Specifically, we used process convolution models with temporal deformation to account for heterogeneity in individual greater white‐fronted goose migrations in Europe and Iceland, and we used nested process convolutions to model dynamic migratory networks in sandhill cranes in North America. The approach we present accounts for various forms of temporal heterogeneity in animal movement and is not limited to migratory applications. Furthermore, our models rely on well‐established principles for modelling‐dependent data and leverage modern approaches for modelling dynamic networks to help explain animal movement and social interaction.

Methods in Ecology and Evolution↗

Trend estimation in populations with imperfect detection

1. Trends of animal populations are of great interest in ecology but cannot be directly observed owing to imperfect detection. Binomial mixture models use replicated counts to estimate abundance, corrected for detection, in demographically closed populations. Here, we extend these models to open populations and illustrate them using sand lizard Lacerta agilis counts from the national Dutch reptile monitoring scheme. 2. Our model requires replicated counts from multiple sites in each of several periods, within which population closure is assumed. Counts are described by a hierarchical generalized linear model, where the state model deals with spatio-temporal patterns in true abundance and the observation model with imperfect counts, given that true state. We used WinBUGS to fit the model to lizard counts from 208 transects with 1&ndash;10 (mean 3) replicate surveys during each spring 1994&ndash;2005. 3. Our state model for abundance contained two independent log-linear Poisson regressions on year for coastal and inland sites, and random site effects to account for unexplained heterogeneity. The observation model for detection of an individual lizard contained effects of region, survey date, temperature, observer experience and random survey effects. 4. Lizard populations increased in both regions but more steeply on the coast. Detectability increased over the first few years of the study, was greater on the coast and for the most experienced observers, and highest around 1 June. Interestingly, the population increase inland was not detectable when the observed counts were analysed without account of detectability. The proportional increase between 1994 and 2005 in total lizard abundance across all sites was estimated at 86% (95% CRI 35&ndash;151). 5. Synthesis and applications . Open-population binomial mixture models are attractive for studying true population dynamics while explicitly accounting for the observation process, i.e. imperfect detection. We emphasize the important conceptual benefit provided by temporal replicate observations in terms of the interpretability of animal counts.

Journal of Applied Ecology↗

Vegetation responses to sagebrush-reduction treatments measured by satellites

Time series of vegetative indices derived from satellite imagery constitute tools to measure ecological effects of natural and management-induced disturbances to ecosystems. Over the past century, sagebrush-reduction treatments have been applied widely throughout western North America to increase herbaceous vegetation for livestock and wildlife. We used indices from satellite imagery to 1) quantify effects of prescribed-fire, herbicide, and mechanical treatments on vegetative cover, productivity, and phenology, and 2) describe how vegetation changed over time following these treatments. We hypothesized that treatments would increase herbaceous cover and accordingly shift phenologies towards those typical of grass-dominated systems. We expected prescribed burns would lead to the greatest and most-prolonged effects on vegetative cover and phenology, followed by herbicide and mechanical treatments. Treatments appeared to increase herbaceous cover and productivity, which coincided with signs of earlier senescence − signals expected of grass-dominated systems, relative to sagebrush-dominated systems. Spatial heterogeneity for most phenometrics was lower in treated areas relative to controls, which suggested treatment-induced homogenization of vegetative communities. Phenometrics that explain spring migrations of ungulates mostly were unaffected by sagebrush treatments. Fire had the strongest effect on vegetative cover, and yielded the least evidence for sagebrush recovery. Overall, treatment effects were small relative to those reported from field-based studies for reasons most likely related to sagebrush recovery, treatment specification, and untreated patches within mosaicked treatment applications. Treatment effects were also small relative to inter-annual variation in phenology and productivity that was explained by temperature, snowpack, and growing-season precipitation. Our results indicated that cumulative NDVI, late-season phenometrics, and spatial heterogeneity of several phenometrics may serve as useful indicators of vegetative change in sagebrush ecosystems.

Wyoming↗

Physical modeling of river spanning rock structures: Evaluating interstitial flow, local hydraulics, downstream scour development, and structure stability

Rock weir and ramp structures uniquely serve a necessary role in river management: to meet water deliveries in an ecologically sound manner. Uses include functioning as low head diversion dams, permitting fish passage, creating habitat diversity, and stabilizing stream banks and profiles. Existing information on design and performance of in-stream rock structures does not provide the guidance necessary to implement repeatable and sustainable construction and retrofit techniques. As widespread use of rock structures increases, the need for reliable design methods with a broad range of applicability at individual sites grows as well. Rigorous laboratory testing programs were implemented at the U.S. Bureau of Reclamation (Reclamation) and at Colorado State University (CSU) as part of a multifaceted research project focused on expanding the current knowledge base and developing design methods to improve the success rate of river spanning rock structures in meeting project goals. Physical modeling at Reclamation is being used to measure, predict, and reduce interstitial flow through rock ramps. CSU is using physical testing to quantify and predict scour development downstream of rock weirs and its impact on the stability of rock structures. ?? 2009 ASCE.

Conference Paper↗

Calibrating biomonitors to ecological disturbance: a new technique for explaining metal effects in natural waters

Bioaccumulated toxic metals in tolerant biomonitors are indicators of metal bioavailability and can be calibrated against metal‐specific responses in sensitive species, thus creating a tool for defining dose–response for metals in a field setting. Dose–response curves that define metal toxicity in natural waters are rare. Demonstrating cause and effect under field conditions and integrated chemical measures of metal bioavailability from food and water is problematic. The total bioaccumulated metal concentration in any organism that is a net accumulator of the metal is informative about metal bioavailability summed across exposure routes. However, there is typically no one universal metal concentration that is indicative of toxicity, especially across species, largely because of interspecies differences in detoxification. Stressed organisms are also only present across a narrow range in the dose–response curve, limiting the use of singles species as both biomonitors and bioindicator of stress. Herein we show, in 3 field settings, that bioaccumulated Cu concentrations in a metal‐tolerant, riverine biomonitor (species of the caddisfly genus Hydropsyche spp.) can be calibrated against metal‐specific ecological responses across very wide ranges of contamination. Using the calibrated dose–response, we show that reduced abundance of species and individuals from particularly sensitive mayfly families (heptageniid mayflies) is more than 2‐fold more sensitive to bioavailable Cu than other traditional measures of stress like EPT or total number of benthic macroinvertebrate species. We propose that this field dose‐response curve be tested more widely for general application, and that calibrations against other stress responses be developed for biomonitors from lakes, estuaries, and coastal marine ecosystems.

Integrated Environmental Assessment and Management↗