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At least 739 records · Page 41Linked to original sources

Rangeland health attributes and indicators for qualitative assessment

Panels of experts from the Society for Range Management and the National Research Council proposed that status of rangeland ecosystems could be ascertained by evaluating an ecological site's potential to conserve soil resources and by a series of indicators for ecosystem processes and site stability. Using these recommendations as a starting point, we developed a rapid, qualitative method for assessing a moment-in-time status of rangelands. Evaluators rate 17 indicators to assess 3 ecosystem attributes (soil and site stability, hydrologic function, and biotic integrity) for a given location. Indicators include rills, water flow patterns, pedestals and terracettes, bare ground, gullies, wind scour and depositional areas, litter movement, soil resistance to erosion, soil surface loss or degradation, plant composition relative to infiltration, soil compaction, plant functional/structural groups, plant mortality, litter amount, annual production, invasive plants, and reproductive capability. In this paper, we detail the development and evolution of the technique and introduce a modified ecological reference worksheet that documents the expected presence and amount of each indicator on the ecological site. In addition, we review the intended applications for this technique and clarify the differences between assessment and monitoring that lead us to recommend this technique be used for moment-in-time assessments and not be used for temporal monitoring of rangeland status. Lastly, we propose a mechanism for adapting and modifying this technique to reflect improvements in understanding of ecosystem processes. We support the need for quantitative measures for monitoring rangeland health and propose some measures that we believe may address some of the 17 indicators.

Journal of Range Management↗

A review of differentiation in Great Lakes ciscoes

Seven species of ciscoes (Coregonus, subgenus Leucichthys) were found in the Great Lakes as recently as the early 1950's. Variation within and among species of Great Lakes ciscoes indicates that much of the divergence occurred within lakes. Following postglacial colonization by perhaps two or three species, population differentiation began with homing and reproduction at different localities and times. Physiological interaction between temperature (depth) and maturation time, as well as behavioral tendencies to home to spawning grounds and mate with related individuals, are the basis of premating reproductive separation. Phenotypic differences between populations indicate that ecological character displacement has been an important mechanism in the divergence. Introgression has obscured morphological species boundaries at the same time as intralacustrine speciation has created local subgroups, providing an unresolvable conflict between species definitions based on morphological and other characters and definitions dominated by inferred reproductive isolation. Species should be considered as the smallest diagnosable units within a phylogenetic framework, in which diagnoses are strictly by derived characters. Ecological and seasonal species could be recognized by application of a trinomial, equivalent to the subspecies trinomial.

Polskie Archiwum Hydrobiologii↗

Mapping wetlands on beaver flowages with 35-mm photography

Beaver flowages and associated wetlands on the Chippewa National Forest, north-central Minnesota, were photographed from the ground and from the open side window of a small high-wing monoplane. The 35-mm High Speed Ektachrome transparencies obtained were used to map the cover-type associations visible on the aerial photographs. Nearly vertical aerial photos were rectified by projecting the slides onto a base map consisting ofcontrol points located by plane-table survey. Maps were prepared by tracing the recognizable stands of vegetation in the rectified projection at the desired map scale. Final map scales ranging from 1:260 to 1:571 permitted identification and mapping of 26 cover-type associations on 10 study flowages in 1971. This cover-mapping technique was economical and substituted for detailed ground surveys. Comparative data from 10 flowages were collected serially throughout the entire open-water season. Although developed for analysis of waterfowl habitat, the technique has application to other areas of wildlife management and ecological investigation.

Canadian Field-Naturalist↗

Structural equation modeling: Building and evaluating causal models

Scientists frequently wish to study hypotheses about causal relationships, rather than just statistical associations. This chapter addresses the question of how scientists might approach this ambitious task. Here we describe structural equation modeling (SEM), a general modeling framework for the study of causal hypotheses. Our goals are to (a) concisely describe the methodology, (b) illustrate its utility for investigating ecological systems, and (c) provide guidance for its application. Throughout our presentation, we rely on a study of the effects of human activities on wetland ecosystems to make our description of methodology more tangible. We begin by presenting the fundamental principles of SEM, including both its distinguishing characteristics and the requirements for modeling hypotheses about causal networks. We then illustrate SEM procedures and offer guidelines for conducting SEM analyses. Our focus in this presentation is on basic modeling objectives and core techniques. Pointers to additional modeling options are also given.

Book chapter↗

Flow-ecology relationships are spatially structured and differ among flow regimes

In streams, hydrology is a predominant driver of ecological structure and function. Providing adequate flows to support aquatic life, or environmental flows, is therefore a top management priority in stream systems. Flow regime classification is a widely accepted approach for establishing environmental flow guidelines. However, it is surprisingly difficult to quantify relationships between hydrology and ecology (flow–ecology relationships) while describing how these relationships vary across classified flow regimes. Developing such relationships is complicated by several sources of spatial bias, such as autocorrelation due to spatial design, flow regime classification and other environmental or ecological sources of spatial bias. We used mixed moving‐average spatial stream network models to develop flow–ecology relationships across classified flow regimes and to assess spatial patterns of these relationships. We compared relationships between fish traits and life‐history strategies with hydrologic metrics across flow regimes and assessed whether spatial autocorrelation influenced these relationships. Trait–hydrology relationships varied between flow regimes and across all streams combined. Some relationships between traits and hydrologic metrics fit predictions based on life‐history theory, while others exhibited unexpected relationships with hydrology. Spatial factors described a large proportion of variability in fish traits and different patterns of spatial autocorrelation were observed in different flow regimes. Synthesis and applications. Further work is needed to understand why flow–ecology relationships vary across classified flow regimes and why these relationships may not fit predictions based on life‐history theories. Managers determining environmental flow standards need to be aware that different hydrologic metrics are often important drivers of fish trait diversity in different flow regimes. Flow–ecology relationships may therefore be confounded by spatial structure inherent in flow regime classification and much existing biological data. Complex patterns of spatial bias should be considered when managing stream systems within an environmental flows framework.

Journal of Applied Ecology↗

Statistical power for detecting trends with applications to seabird monitoring

Power analysis is helpful in defining goals for ecological monitoring and evaluating the performance of ongoing efforts. I examined detection standards proposed for population monitoring of seabirds using two programs (MONITOR and TRENDS) specially designed for power analysis of trend data. Neither program models within- and among-years components of variance explicitly and independently, thus an error term that incorporates both components is an essential input. Residual variation in seabird counts consisted of day-to-day variation within years and unexplained variation among years in approximately equal parts. The appropriate measure of error for power analysis is the standard error of estimation (S.E.est) from a regression of annual means against year. Replicate counts within years are helpful in minimizing S.E.est but should not be treated as independent samples for estimating power to detect trends. Other issues include a choice of assumptions about variance structure and selection of an exponential or linear model of population change. Seabird count data are characterized by strong correlations between S.D. and mean, thus a constant CV model is appropriate for power calculations. Time series were fit about equally well with exponential or linear models, but log transformation ensures equal variances over time, a basic assumption of regression analysis. Using sample data from seabird monitoring in Alaska, I computed the number of years required (with annual censusing) to detect trends of -1.4% per year (50% decline in 50 years) and -2.7% per year (50% decline in 25 years). At ??=0.05 and a desired power of 0.9, estimated study intervals ranged from 11 to 69 years depending on species, trend, software, and study design. Power to detect a negative trend of 6.7% per year (50% decline in 10 years) is suggested as an alternative standard for seabird monitoring that achieves a reasonable match between statistical and biological significance.

Alaska↗

How do accuracy and model agreement vary with versioning, scale, and landscape heterogeneity for satellite-derived vegetation maps in sagebrush steppe?

Maps of the distribution and abundance of dominant plants derived from satellite data are essential for ecological research and management, particularly in the vast semiarid shrub-steppe. Appropriate application of these maps requires an understanding of model accuracy and precision, and how it might vary across space, time, and different vegetation types. For a 113 k Ha burn area, we compared modeled maps of different vegetation cover types created from satellite data to ‘benchmark” models based on intensive field sampling (~1500-2000 plots resampled annually for 5 years) for three new satellite-derived models: USDA Rangeland Analysis Platform (RAP), the USGS Rangeland Condition Monitoring Assessment and Projection (RCMAP), and USGS fractional estimate of exotic annual grass cover (USGS-fractional-EAG). We assessed out-of-sample point accuracy and asked if and how accuracy changed each year due to vegetation shifts, new images, and model improvements (i.e. model versions). We also assessed how map agreement between satellite-based and field-based models changed with scale of application, topography, and time since fire. Accuracy and map agreement varied considerably among the vegetation types and across time and space (r 2 ranging from 0 to 0.53), and some of the variability was predictable. All models tended to over or underestimate cover when field-measured cover was relatively low or high, respectively, i.e. a “false moderating effect”. Accuracy was greater and improved with newer versions of RAP (+0.05 to 0.29 r 2 ) compared to RCMAP and USGS fractional model estimates, and in some cases was greater than field-based models. Variability in map agreement tended to decrease with larger areas sampled (particularly in areas >12 km), and this scale dependency was more evident in RAP and USGS-fractional-EAG models. Creating a “fair” basis for comparison of spatial models of low-statured semiarid vegetation derived from satellite compared to field data is not trivial because scaling the field data to the scale of large satellite pixels (or downscaling satellite-based models to field scale) requires modeling and associated model uncertainty. Accuracy can vary considerably and understanding the variation can help guide application of the models to the appropriate time, place, and variables.

Idaho, Oregon↗

Ecological feedbacks can reduce population-level efficacy of wildlife fertility control

1. Anthropogenic stress on natural systems, particularly the fragmentation of landscapes and the extirpation of predators from food webs, has intensified the need to regulate abundance of wildlife populations with management. Controlling population growth using fertility control has been considered for almost four decades, but nearly all research has focused on understanding effects of fertility control agents on individual animals. Questions about the efficacy of fertility control as a way to control populations remain largely unanswered. 2. Collateral consequences of contraception can produce unexpected changes in birth rates, survival, immigration and emigration that may reduce the effectiveness of regulating animal abundance. The magnitude and frequency of such effects vary with species-specific social and reproductive systems, as well as connectivity of populations. Developing models that incorporate static demographic parameters from populations not controlled by contraception may bias predictions of fertility control efficacy. 3. Many population-level studies demonstrate that changes in survival and immigration induced by fertility control can compensate for the reduction in births caused by contraception. The most successful cases of regulating populations using fertility control come from applications of contraceptives to small, closed populations of gregarious and easily accessed species. 4. Fertility control can result in artificial selection pressures on the population and may lead to long-term unintentional genetic consequences. The magnitude of such selection is dependent on individual heritability and behavioural traits, as well as environmental variation. 5. Synthesis and applications . Understanding species' life-history strategies, biology, behavioural ecology and ecological context is critical to developing realistic expectations of regulating populations using fertility control. Before time, effort and funding are invested in wildlife contraception, managers may need to consider the possibility that many species and populations can compensate for reduction in fecundity, and this could minimize any reduction in population growth rate.

Journal of Applied Ecology↗

Hydrologic modeling for flow-ecology science in the Southeastern United States and Puerto Rico

An understanding of the applicability and utility of hydrologic models is critical to support the effective management of water resources throughout the Southeastern United States (SEUS) and Puerto Rico (PR). Hydrologic models have the capacity to provide an estimate of the quantity of available water at ungauged locations (i.e., areas of the country where a U.S. Geological Survey [USGS] continuous record gauge is not installed) and provide the baseline flow information necessary to develop the linkages between water availability and characteristics of streamflow that support ecological communities (i.e., support the development of flow-ecology response models). This report inventories and then directly examines and compares a subset of hydrologic models used to estimate streamflow at a number of gauged basins across the SEUS and PR. This effort was designed to evaluate, quantify, and compare the magnitude of error and to investigate the potential causes of error associated with predicted streamflows from seven hydrologic models of varying complexity and calibration strategy. This was accomplished by computing and then comparing classical hydrologic model fit statistics (e.g., mean bias, coefficient of determination [R2], root mean squared error [RMSE], Nash-Sutcliffe Efficiency [NSE]) and understanding the bias in the prediction in these and a subset of ecologically relevant flow metrics (ERFMs). Additionally, streamflow predictions from a larger regional-scale hydrologic model were compared to those of several fine-scale hydrologic models under a range of hypothetical climate change scenarios to determine the range of predicted streamflow responses to fixed climate perturbations. A pilot study was conducted using predicted streamflow and boosted regression trees to develop a set of predictive flow-ecology response models to assess the potential change in fish species richness in the North Carolina Piedmont under several scenarios of water availability change. This report is intended to provide a general assessment of all the tools and techniques available to support hydrologic modeling for flow-ecology science in the SEUS and PR. It is our hope that the approach used herein to understand differences in streamflow predictions among a subset of hydrologic models that have been applied in the SEUS for developing flow-ecology response models will provide water resource managers and stakeholders with an informed pathway for developing the capacity to link streamflow and ecological response and an understanding of some of the limitations associated with these type of modeling efforts.

Alabama, Florida, Georgia, Mississippi, North Caro↗

Witnessing history: Comparison of a century of sedimentary and written records in a California protected area

We use a combination of proxy records from a high-resolution analysis of sediments from Searsville Lake and adjacent Upper Lake Marsh and historical records to document over one and a half centuries of vegetation and socio-ecological change—relating to logging, agricultural land use change, dam construction, chemical applications, recreation, and other drivers—on the San Francisco Peninsula. A relatively open vegetation with minimal oak ( Quercus ) and coast redwood ( Sequoia sempervirens ) in the late 1850s reflects widespread logging and grazing during the nineteenth century. Forest and woodland expansion occurred in the early twentieth century, with forests composed of coast redwood and oak, among other taxa, as both logging and grazing declined. Invasive species include those associated with pasturage ( Rume x , Plantago ), landscape disturbance ( Urtica , Amaranthaceae), planting for wood production and wind barriers ( Eucalyptus ), and agriculture. Agricultural species, including wheat, rye, and corn, were more common in the early twentieth century than subsequently. Wetland and aquatic pollen and fungal spores document a complex hydrological history, often associated with fluctuating water levels, application of algaecides, raising of Searsville Dam, and construction of a levee. By pairing the paleoecological and historical records of both lakes, we have been able to reconstruct the previously undocumented impacts of socio-ecological influences on this drainage, all of which overprinted known climate changes. Recognizing the ecological manifestations of these impacts puts into perspective the extent to which people have interacted with and transformed the environment in the transition into the Anthropocene.

California↗

Advances in interpretation of subsurface processes with time-lapse electrical imaging

Electrical geophysical methods, including electrical resistivity, time-domain induced polarization, and complex resistivity, have become commonly used to image the near subsurface. Here, we outline their utility for time-lapse imaging of hydrological, geochemical, and biogeochemical processes, focusing on new instrumentation, processing, and analysis techniques specific to monitoring. We review data collection procedures, parameters measured, and petrophysical relationships and then outline the state of the science with respect to inversion methodologies, including coupled inversion. We conclude by highlighting recent research focused on innovative applications of time-lapse imaging in hydrology, biology, ecology, and geochemistry, among other areas of interest.

Hydrological Processes↗

Standardized phenology monitoring methods to track plant and animal activity for science and resource management applications

Phenology offers critical insights into the responses of species to climate change; shifts in species’ phenologies can result in disruptions to the ecosystem processes and services upon which human livelihood depends. To better detect such shifts, scientists need long-term phenological records covering many taxa and across a broad geographic distribution. To date, phenological observation efforts across the USA have been geographically limited and have used different methods, making comparisons across sites and species difficult. To facilitate coordinated cross-site, cross-species, and geographically extensive phenological monitoring across the nation, the USA National Phenology Network has developed in situ monitoring protocols standardized across taxonomic groups and ecosystem types for terrestrial, freshwater, and marine plant and animal taxa. The protocols include elements that allow enhanced detection and description of phenological responses, including assessment of phenological “status”, or the ability to track presence–absence of a particular phenophase, as well as standards for documenting the degree to which phenological activity is expressed in terms of intensity or abundance. Data collected by this method can be integrated with historical phenology data sets, enabling the development of databases for spatial and temporal assessment of changes in status and trends of disparate organisms. To build a common, spatially, and temporally extensive multi-taxa phenological data set available for a variety of research and science applications, we encourage scientists, resources managers, and others conducting ecological monitoring or research to consider utilization of these standardized protocols for tracking the seasonal activity of plants and animals.

International Journal of Biometeorology↗

A review of the relationships between drought and forest fire in the United States

The historical and pre-settlement relationships between drought and wildfire are well documented in North America, with forest fire occurrence and area clearly increasing in response to drought. There is also evidence that drought interacts with other controls (forest productivity, topography, fire weather, management activities) to affect fire intensity, severity, extent, and frequency. Fire regime characteristics arise across many individual fires at a variety of spatial and temporal scales, so both weather and climate—including short- and long-term droughts—are important and influence several, but not all, aspects of fire regimes. We review relationships between drought and fire regimes in United States forests, fire-related drought metrics and expected changes in fire risk, and implications for fire management under climate change. Collectively, this points to a conceptual model of fire on real landscapes: fire regimes, and how they change through time, are products of fuels and how other factors affect their availability (abundance, arrangement, continuity) and flammability (moisture, chemical composition). Climate, management, and land use all affect availability, flammability, and probability of ignition differently in different parts of North America. From a fire ecology perspective, the concept of drought varies with scale, application, scientific or management objective, and ecosystem.

Global Change Biology↗

Evaluation of trap capture in a geographically closed population of brown treesnakes on Guam

1. Open population mark-recapture analysis of unbounded populations accommodates some types of closure violations (e.g. emigration, immigration). In contrast, closed population analysis of such populations readily allows estimation of capture heterogeneity and behavioural response, but requires crucial assumptions about closure (e.g. no permanent emigration) that are suspect and rarely tested empirically. 2. In 2003, we erected a double-sided barrier to prevent movement of snakes in or out of a 5-ha semi-forested study site in northern Guam. This geographically closed population of >100 snakes was monitored using a series of transects for visual searches and a 13 ?? 13 trapping array, with the aim of marking all snakes within the site. Forty-five marked snakes were also supplemented into the resident population to quantify the efficacy of our sampling methods. We used the program mark to analyse trap captures (101 occasions), referenced to census data from visual surveys, and quantified heterogeneity, behavioural response, and size bias in trappability. Analytical inclusion of untrapped individuals greatly improved precision in the estimation of some covariate effects. 3. A novel discovery was that trap captures for individual snakes consisted of asynchronous bouts of high capture probability lasting about 7 days (ephemeral behavioural effect). There was modest behavioural response (trap happiness) and significant latent (unexplained) heterogeneity, with small influences on capture success of date, gender, residency status (translocated or not), and body condition. 4. Trapping was shown to be an effective tool for eradicating large brown treesnakes Boiga irregularis (>900 mm snout-vent length, SVL). 5. Synthesis and applications. Mark-recapture modelling is commonly used by ecological managers to estimate populations. However, existing models involve making assumptions about either closure violations or response to capture. Physical closure of our population on a landscape scale allowed us to determine the relative importance of covariates influencing capture probability (body size, trappability periods, and latent heterogeneity). This information was used to develop models in which different segments of the population could be assigned different probabilities of capture, and suggests that modelling of open populations should incorporate easily measured, but potentially overlooked, parameters such as body size or condition. ?? 2008 The Authors.

Journal of Applied Ecology↗

Denning chronology and design of effective bear management units

Reports on the effectiveness of using late fall hunting seasons to reduce the proportion of female black bears (Ursus americanus) in the harvest are limited, and the geographic scale over which the technique functions as intended has not been examined. During 1992-2000, we radio-equipped black bears in New Mexico, USA, obtained estimates of 175 den entry and 137 den emergence dates, and used New Mexico Department of Game and Fish harvest data (1985-2000) to test for differences in proportion of females in the harvest relative to denning chronology. Bears in northern New Mexico entered dens earlier and emerged later than bears in southern New Mexico (P ??? 0.001). In northern New Mexico bears displayed the typical pattern of earlier entry and later emergence by reproductive females, proportion of females in the harvest varied over time as expected, and late fall seasons were effective (P ??? 0.10). In contrast, denning chronology did not differ by sex in southern New Mexico, proportion of females in the harvest did not change over time, and late fall seasons were not effective (P ??? 0.18). Manipulation of hunting season dates to influence female mortality can be an effective tool, however our study provides an example of an area where denning chronology did not differ by sex and late seasons were not effective. We also observed regional differences in timing of entrance and emergence, which suggest that scale of application may be key. In management jurisdictions that encompass ecologically distinct areas, cover a wide range of latitudes, or are mountainous, successful use of the technique may depend on knowledge of denning chronology at multiple locations and appropriate designation of hunting unit boundaries, season dates, and data analysis units.

Journal of Wildlife Management↗

EAARL coastal topography - Northern Gulf of Mexico

These remotely sensed, geographically referenced elevation measurements of Lidar-derived coastal topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. One objective of this research is to create techniques to survey areas for the purposes of geomorphic change studies following major storm events. The USGS Coastal and Marine Geology Program's National Assessment of Coastal Change Hazards project is a multi-year undertaking to identify and quantify the vulnerability of U.S. shorelines to coastal change hazards such as effects of severe storms, sea-level rise, and shoreline erosion and retreat. Airborne Lidar surveys conducted during periods of calm weather are compared to surveys collected following extreme storms in order to quantify the resulting coastal change. Other applications of high-resolution topography include habitat mapping, ecological monitoring, volumetric change detection, and event assessment. The purpose of this project is to provide highly detailed and accurate datasets of the northern Gulf of Mexico coastal areas, acquired on September 19, 2004, immediately following Hurricane Ivan. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Airborne Advanced Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532 nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking RGB (red-green-blue) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers and an integrated miniature digital inertial measurement unit which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system on September 19, 2004. The survey resulted in the acquisition of 3.2 gigabytes of data. The data were processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for pre-survey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is routinely used to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of 'last return' elevations.

Alabama, Florida, Mississippi↗

An automated geographic information system-based hydraulic modeling tool for developing preliminary culvert designs for stream crossings in Massachusetts

Introduction Currently (2026), many of the about 25,000 roadway crossing structures over rivers and streams in Massachusetts are undersized. Undersized culverts and bridges can be detrimental to fish and wildlife movement, habitat continuity, and the health of aquatic organisms. Undersized culverts also can lack the resiliency needed to withstand large floods, which could be worsened by potential increases in flood magnitude and frequency due to climate change. Improving culvert and bridge designs for stream crossing projects may improve aquatic organism passage, stream continuity, and resiliency during future floods by decreasing upstream overbank flooding, road flooding and erosion, and degradation of aquatic habitat. The U.S. Geological Survey (USGS), Massachusetts Department of Environmental Protection (MassDEP), and University of Massachusetts Amherst began a series of cooperative studies in July 2019 to develop an automated geographic information system (GIS) hydraulic modeling tool for preliminary culvert designs for stream crossings. The USGS plans to provide preliminary culvert designs in the web-based StreamStats application, which enables municipalities and engineers to view potential designs and related information for stream crossing replacement projects in Massachusetts. This application can (a) provide information on hydrology, hydraulics, and ecological conditions at stream crossing sites, (b) provide users with potential culvert designs to improve aquatic organism passage and flood resiliency, and (c) assist MassDEP in implementing the Massachusetts Wetlands Protection Act regulations for stream crossing projects.

Massachusetts↗

Impacts of temporal revisit designs on the power to detect trend with a linear mixed model: An application to long-term monitoring of Sierra Nevada lakes

Long-term ecological monitoring programs often use linear mixed models to estimate trend in an ecological indicator sampled across large landscapes. A linear mixed model is versatile for estimating a linear trend in time as well as components of spatial and temporal variationin the case of unbalanced data structures , which are common in complex monitoring designs where limited sampling effort must be optimized over time and space. A power analysis was used to inform a lake chemistry monitoring design, including selecting the most appropriate temporal revisit design. Pilot data from surveys of lakes across large wilderness national parks (Sequoia, Kings Canyon, and Yosemite national parks) were used to obtain variance components for a Monte Carlo power simulation. Using a linear mixed model for a range of temporal revisit designs, sample sizes, and trend magnitudes, we evaluated the power to detect trend, the trend test size, and the relative bias of trend coefficient estimates for four continuous and normally distributed indicators. Contrary to prior research based on large-sample approximations that identified a single panel of sites visited annually as the revisit design generating the highest power, we found that the power to detect a 12-year trend based on the Wald t-test from a linear mixed model may be optimized by obtaining unbalanced data sets with limited to no annual replication. We emphasize the importance of examining variance composition, sample size, and the power and size of the trend test with Monte Carlo simulation when allocating sampling effort over time and space.

Ecological Indicators↗