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At least 631 records · Page 35Linked to original sources

How well do existing surveys track fish community performance measures in the St. Clair-Detroit River System?

The St. Clair-Detroit River System (SCDRS) connects Lake Huron to Lake Erie and provides important habitats for many fishes of economic and ecological importance. Portions of the SCDRS are designated as Great Lakes Areas of Concern and fish production and conservation may be compromised. Efforts to address beneficial use impairments have focused on restoring habitat for native fishes and improving aquatic ecosystem health. Considerable site-specific research and long-term, annual fish surveys have examined responses to habitat improvements. However, there is uncertainty surrounding whether individual studies and surveys can assess (1) population-level benefits of habitat enhancements and (2) whether management objectives are being met. To identify monitoring gaps and inform long-term monitoring program development, we compared outputs from SCDRS fish monitoring surveys (based on discussions with regional agencies) with performance measures specified in management plans (obtained through gray literature searches). Performance measures for harvested species aligned well with outputs of existing surveys. In contrast, at-risk fishes often had objectives and performance measures that reflected knowledge gaps and study needs. Although harvested species were well-monitored relative to specified performance measures, at-risk fishes were less reliably collected by existing surveys, except for lake sturgeon Acipenser fulvescens . Effective evaluation of restoration efforts for at-risk fishes may require additional survey efforts that target species-specific habitat use and life history characteristics.

Michigan↗

Great Lakes coastal fish habitat classification and assessment

Basin-scale assessment of fish habitat in Great Lakes coastal ecosystems would increase our ability to prioritize fish habitat management and restoration actions. As a first step in this direction, we identified key habitat factors associated with highest probability of occurrence for several societally and ecologically important coastal fish species as well as community metrics, using data from the Great Lakes Aquatic Habitat Framework (GLAHF), Great Lakes Environmental Indicators (GLEI) and Coastal Wetland Monitoring Program (CWMP). Secondly, we assessed whether species-specific habitat was threatened by watershed-level anthropogenic stressors. In the southern Great Lakes, key habitat factors for determining presence/absence of several species of coastal fish were chlorophyll concentrations, turbidity, and wave height, whereas in the northern ecoprovince temperature was the major habitat driver for most of the species modeled. Habitat factors best explaining fish richness and diversity were bottom slope and chlorophyll a . These models could likely be further improved with addition of high-resolution submerged macrophytecomplexity data which are currently unavailable at the basin-wide scale. Proportion of invasive species was correlated primarily with increasing maximum observed inorganic turbidity and chlorophyll a . We also demonstrate that preferred habitat for several coastal species and high-diversity areas overlap with areas of high watershed stress. Great Lakes coastal wetland fish are a large contributor to ecosystem services as well as commercial and recreational fishery harvest, and scalable basin-wide habitat models developed in this study may be useful for informing management actions targeting specific species or overall coastal fish biodiversity.

Great Lakes↗

A method for assigning species into groups based on generalized Mahalanobis distance between habitat model coefficients

Habitat association models are commonly developed for individual animal species using generalized linear modeling methods such as logistic regression. We considered the issue of grouping species based on their habitat use so that management decisions can be based on sets of species rather than individual species. This research was motivated by a study of western landbirds in northern Idaho forests. The method we examined was to separately fit models to each species and to use a generalized Mahalanobis distance between coefficient vectors to create a distance matrix among species. Clustering methods were used to group species from the distance matrix, and multidimensional scaling methods were used to visualize the relations among species groups. Methods were also discussed for evaluating the sensitivity of the conclusions because of outliers or influential data points. We illustrate these methods with data from the landbird study conducted in northern Idaho. Simulation results are presented to compare the success of this method to alternative methods using Euclidean distance between coefficient vectors and to methods that do not use habitat association models. These simulations demonstrate that our Mahalanobis-distance- based method was nearly always better than Euclidean-distance-based methods or methods not based on habitat association models. The methods used to develop candidate species groups are easily explained to other scientists and resource managers since they mainly rely on classical multivariate statistical methods. ?? 2008 Springer Science+Business Media, LLC.

Environmental and Ecological Statistics↗

Regional high-frequency monitoring revealed chloride concentrations in exceedance of ecological benchmarks in urban streams across the Delaware River Basin, USA

Rising chloride concentrations pose critical risks to freshwater stream ecosystems in temperate regions like the Delaware River Basin (DRB), USA, where winter deicer applications ( i.e. , road salt) are common. Increasing chloride concentrations have been documented in the region, but the extent to which chloride exceeds regulatory benchmarks remains unclear because detection of exceedances requires continuous monitoring of chloride ( i.e. , hourly or daily). A network of 82 non-tidal continuous specific conductance (SC) monitoring sites, spanning varied land use and geological settings, was established across the DRB to address this research need. First, a cluster analysis was conducted to group sites based on their watershed characteristics. Next, regression models for sites and clusters were developed to predict chloride using SC as a proxy. Finally, daily mean and hourly mean chloride concentration predictions were made for a three-year period (2020–2022) at the 82 study sites and analyzed to determine where and when chloride exceeded federal regulatory benchmarks. Chloride exceedance events occurred at 35% of the sites, all of which had 5% impervious cover or greater. Seasonally elevated chloride also was predicted at sites with less than 5% impervious cover. Variability in chloride patterns likely was influenced by deicer material types, winter weather patterns, geological settings, and gaps in data coverage. This study demonstrated the value of SC as a proxy for predicting chloride concentrations and showed how SC-chloride regression relationships vary across settings. More broadly, this study highlighted the value of continuous water quality monitoring to assess effects of freshwater salinization at a regional scale.

Delaware, Maryland, New Jersey, New York, Pennsylv↗

Maintaining and restoring sustainable ecosystems in southern Nevada

Managers in southern Nevada are challenge with determining appropriate goals and objectives and developing viable approaches for maintaining and restoring sustainable ecosystems in a time of rapid socio-ecological and environmental change. Sustainable or "healthy" ecosystems supply clean air, water and habitat for a diverse array of plants and animals. As described in Chapter 1, sustainable ecosystems retain characteristic processes like hydrological flux and storage, geomorphic processes, biogeochemical cycling and storage, biological activity and productivity, and population regeneration and reproduction over the normal cycle of disturbance events (modified from Chapin and others 1996 and Christensen and others 1996). Ecological restoration of stressed or disturbed ecosystems in an integral part of managing for sustainable ecosystems. The Society of Ecological Restoration International (SERI) defines ecological restoration as the process of assisting the recovery of an ecosystem that has been degraded, damaged, or destroyed (SERI 2004). Many of the southern Nevada's ecosystems are being subjected to anthropogenic stressors that span global, regional, and local scales (Chapter 2)., and are crossing ecological thresholds to new alternative states (Chapter 4 and Chapter 5). These alternative states often represent novel communities with disturbance regimes that differ significantly from historic conditions. Past management and restoration goals often focused on returning ecosystems to pre-disturbance conditions (Harris and others 2006). This approach assumes stable or equilibrium conditions and ignores changes in ecosystems processes due to land uses, increases in CO 2 concentrations, and climate change. A more realistic approach is to base management and restoration goals on the current potential of an ecosystem to support a given set of ecological conditions, and on the likelihood of future change due to warming climate (Harris and others 2006). This approach requires understanding ecosystem resilience to anthropogenic disturbance and climate change, the alternative states that exist for ecosystems, and the factors that result in threshold crossing (Bestelmeyer and others 2009; Hobbs and Harris 2001; Stingham and others 2003; Whisemnant 1999). It also requires the ability to predict how climate is likely to influence ecosystems in the future (Harris and others 2006). This chapter addresses the restoration aspects of Sub-goal 1.3 in the SNAP Science Research Strategy which is to restore and sustain proper function of southern Nevada's watersheds and landscapes (able 1.3; Turner and others 2009). The effects of global, regional and local stresses on southern Nevada ecosystems are presented in Chapter 2. Here, we discuss appropriate objectives and develop guidelines for maintaining and restoring southern Nevada ecosystems. We then discuss the differences in ecological resilience to stress and disturbance and resistance to invasive species in southern Nevada ecosystems and describe restoration and management approaches for the different ecosystem types. We conclude with knowledge gaps and management implications.

Nevada↗

Environmental and ecological conditions surrounding the production of large year classes of walleye ( Sander vitreus ) in Saginaw Bay, Lake Huron

The Saginaw Bay walleye population ( Sander vitreus ) has not fully recovered from a collapse that began in the 1940s and has been dependent on stocking with only limited natural reproduction. Beginning in 2003, and through at least 2005, reproductive success of walleye surged to unprecedented levels. The increase was concurrent with ecological changes in Lake Huron and we sought to quantitatively model which factors most influenced this new dynamic. We developed Ricker stock-recruitment models for both wild and stock fish and evaluated them with second-order Akaike's information criterion to find the best model. Independent variables included adult alewife ( Alosa pseudoharengus ) abundance, spring water temperatures, chlorophyll a levels and total phosphorus levels. In all, 14 models were evaluated for production of wild age-0 walleyes and eight models for stocked age-0 walleyes. For wild walleyes, adult alewife abundance was the dominant factor, accounting for 58% of the variability in age-0 abundance. Production of wild age-0 fish increased when adult alewives were scarce. The only other plausible factor was spring water temperature. Predictably, alewife abundance was not important to stocked fish; instead temperature and adult walleye abundance were more significant variables. The surge in reproductive success for walleyes during 2003–2005 was most likely due to large declines in adult alewives in Lake Huron. While relatively strong year classes (age-1 and up) have been produced as a result of increased age-0 production during 2003–2005, the overall magnitude has not been as great as the initial age-0 abundance originally suggested. It appears that over-winter mortality is higher than in the past and may stem from higher predation or slower growth (lower condition for enduring winter thermal stress). From this it appears that low alewife abundance does not assure strong walleye year classes in Saginaw Bay but may be a prerequisite for them.

Journal of Great Lakes Research↗

Gaps and hotspots in the state of knowledge of pinyon-juniper communities

Pinyon-juniper (PJ) plant communities cover a large area across North America and provide critical habitat for wildlife, biodiversity and ecosystem functions, and rich cultural resources. These communities occur across a variety of environmental gradients, disturbance regimes, structural conditions and species compositions, including three species of juniper and two species of pinyon. PJ communities have experienced substantial changes in recent decades and identifying appropriate management strategies for these diverse communities is a growing challenge. Here, we surveyed the literature and compiled 441 studies to characterize patterns in research on PJ communities through time, across geographic space and climatic conditions, and among focal species. We evaluate the state of knowledge for three focal topics: 1) historical stand dynamics and responses to disturbance, 2) land management actions and their effects, and 3) potential future responses to changing climate. We identified large and potentially important gaps in our understanding of pinyon-juniper communities both geographically and topically. The effect of drought on Pinus edulis, the pinyon pine species in eastern PJ communities was frequently addressed, while few studies focused on drought effects on Pinus monophylla , which occurs in western PJ communities. The largest proportion of studies that examined land management actions only measured their effects for one year. Grazing was a common land-use across the geographic range of PJ communities yet was rarely studied. We found only 39 studies that had information on the impacts of anthropogenic climate change and most were concentrated on Pinus edulis . These results provide a synthetic perspective on PJ communities that can help natural resource managers identify relevant knowledge needed for decision-making and researchers design new studies to fill important knowledge gaps.

Arizona, California, Colorado, Nevada, New Mexico,↗

Encapsulating model complexity and landscape-scale analyses of state-and-transition simulation models: an application of ecoinformatics and juniper encroachment in sagebrush steppe ecosystems

State-and-transition simulation modeling relies on knowledge of vegetation composition and structure (states) that describe community conditions, mechanistic feedbacks such as fire that can affect vegetation establishment, and ecological processes that drive community conditions as well as the transitions between these states. However, as the need for modeling larger and more complex landscapes increase, a more advanced awareness of computing resources becomes essential. The objectives of this study include identifying challenges of executing state-and-transition simulation models, identifying common bottlenecks of computing resources, developing a workflow and software that enable parallel processing of Monte Carlo simulations, and identifying the advantages and disadvantages of different computing resources. To address these objectives, this study used the ApexRMS® SyncroSim software and embarrassingly parallel tasks of Monte Carlo simulations on a single multicore computer and on distributed computing systems. The results demonstrated that state-and-transition simulation models scale best in distributed computing environments, such as high-throughput and high-performance computing, because these environments disseminate the workloads across many compute nodes, thereby supporting analysis of larger landscapes, higher spatial resolution vegetation products, and more complex models. Using a case study and five different computing environments, the top result (high-throughput computing versus serial computations) indicated an approximate 96.6% decrease of computing time. With a single, multicore compute node (bottom result), the computing time indicated an 81.8% decrease relative to using serial computations. These results provide insight into the tradeoffs of using different computing resources when research necessitates advanced integration of ecoinformatics incorporating large and complicated data inputs and models. - See more at: http://aimspress.com/aimses/ch/reader/view_abstract.aspx?file_no=Environ2015030&flag=1#sthash.p1XKDtF8.dpuf

AIMS Environmental Science↗

Statistical power of dynamic occupancy models to identify temporal change: Informing the North American Bat Monitoring Program

Dynamic occupancy models provide a flexible framework for estimating and mapping species occupancy patterns over space and time for large-scale monitoring programs (e.g., the North American Bat Monitoring Program (NABat), the Amphibian Research and Monitoring Initiative). Challenges for designing surveys using the dynamic occupancy modeling framework include defining appropriate derived trend parameters, and providing usable tools for researchers to conduct project-specific sample size investigations. We present a simulation-based power analysis framework for dynamic occupancy models that allows for the incorporation of the underlying environmental space (i.e., as covariates) within a specific study region to inform sample size estimation. We investigate two definitions of temporal trend: (1) a gradual, sustained (linear or nonlinear) change over a period of many years, and (2) an abrupt increase or decrease between two time periods. We draw upon pilot data collected following NABat protocols to inform assumed data generating values in a demonstration of our approach. Due to the complicated parameter structure of dynamic occupancy models, we emphasize the importance of visualizing simulated changes over time based on different parameter settings prior to conducting a power analysis. Our simulations revealed that the linearity of short-term trends (five years in our investigation) conferred higher power with lower sample size than longer trends where occupancy probabilities approached zero (ten years in our investigation). We provide an example of how to use our tools to conduct customized investigations using questions posed by NABat, and in doing so, we shed light on general guidelines that can be applied to programs monitoring species occupancy for other taxa. Importantly, we created an R package to execute our approach for informing program-, species-, and study-specific investigations aimed at identifying changes in species occupancy.

Ecological Indicators↗

Response of juvenile Chinook Salmon to an experimental reservoir operation to facilitate downstream migration

Objectives High-head dams and storage reservoirs impact ecological processes, impeding recovery efforts of Pacific salmon Oncorhynchus spp. in the western United States. These projects can delay migration, increase risks of predation and disease, and induce mortality for juvenile Pacific salmon during downstream passage. To mitigate these negative effects, large-scale changes to dam operations have been proposed as interim measures or alternatives to engineered fish passage solutions. A novel deep drawdown operation of the Lookout Point Project (two dams and reservoirs) in Oregon serves as a case study for learning from a large-scale management experiment. Beginning in July 2024, Lookout Point Reservoir was slowly lowered to attain minimal levels from mid-November to mid-December with the intent of expediting downstream passage through the project for juvenile Chinook Salmon Oncorhynchus tshawytscha . We evaluated the impacts of the months-long operation on two life histories of juvenile Chinook Salmon with different rearing environments and growth rates. Methods Acoustic telemetry was used to monitor juvenile Chinook Salmon in the Lookout Point Project. Environmental data, including water temperature and hydrological conditions, were collected. We fitted a time-integrated migration survival model to these data to estimate the effects of management-influenced covariates and fish length on apparent survival and residence time in each reach of the Lookout Point Project. Results Larger fish had higher survival than smaller fish in each reach of the Lookout Point Project. Apparent survival through each dam of the Lookout Point Project was highest and forebay residence times lowest during the latter part of the drawdown (late November). However, early periods of the drawdown (September) were associated with a transition from a thermally stratified reservoir to a warm isothermal reservoir that negatively impacted reservoir survival. Conclusions The deep drawdown of the Lookout Point Project achieved the management intent to improve downstream passage for juvenile Chinook Salmon at the lowest reservoir elevations but also caused unintended changes in the reservoir rearing environment prior to full drawdown. Further research could resolve remaining uncertainties regarding the overall effectiveness of drawdown operations with respect to the population dynamics of different juvenile life history strategies. Understanding these factors would help optimize future management actions aimed at Pacific salmon recovery above the Lookout Point Project.

Oregon↗

Multimodel inference and adaptive management

Ecology is an inherently complex science coping with correlated variables, nonlinear interactions and multiple scales of pattern and process, making it difficult for experiments to result in clear, strong inference. Natural resource managers, policy makers, and stakeholders rely on science to provide timely and accurate management recommendations. However, the time necessary to untangle the complexities of interactions within ecosystems is often far greater than the time available to make management decisions. One method of coping with this problem is multimodel inference. Multimodel inference assesses uncertainty by calculating likelihoods among multiple competing hypotheses, but multimodel inference results are often equivocal. Despite this, there may be pressure for ecologists to provide management recommendations regardless of the strength of their study’s inference. We reviewed papers in the Journal of Wildlife Management (JWM) and the journal Conservation Biology (CB) to quantify the prevalence of multimodel inference approaches, the resulting inference (weak versus strong), and how authors dealt with the uncertainty. Thirty-eight percent and 14%, respectively, of articles in the JWM and CB used multimodel inference approaches. Strong inference was rarely observed, with only 7% of JWM and 20% of CB articles resulting in strong inference. We found the majority of weak inference papers in both journals (59%) gave specific management recommendations. Model selection uncertainty was ignored in most recommendations for management. We suggest that adaptive management is an ideal method to resolve uncertainty when research results in weak inference.

Journal of Environmental Management↗

Use of dynamic occupancy models to assess the response of Darters (Teleostei: Percidae) to varying hydrothermal conditions in a southeastern United States tailwater

During the past 100 years, most large rivers in North America have been altered for flood control, hydropower, navigation or water supply development. Although these activities clearly provide important human services, their associated environmental disturbances can profoundly affect stream-dwelling organisms. We used dynamic multi-species occupancy models combined with a trait-based approach to estimate the influence of site-level and species-level characteristics on patch dynamic rates for 15 darter species native to the Elk River, a large, flow-regulated Tennessee River tributary in Tennessee and Alabama. Dynamic occupancy modelling results indicated that for every 2.5 °C increase in stream temperature, darters were 3.94 times more likely to colonize previously unoccupied stream reaches. Additionally, large-bodied darter species were 3.72 times more likely to colonize stream reaches compared with small-bodied species, but crevice-spawning darter species were 5.24 times less likely to colonize previously unoccupied stream reaches. In contrast, darters were 2.21 times less likely to become locally extinct for every 2.5 °C increase in stream temperature, but high stream discharge conditions elevated the risk of local extinction. Lastly, the presence of populations in neighbouring upstream study reaches contributed to a lower risk of extinction, whereas the presence of populations in neighbouring downstream study reaches contributed to higher rates of colonization. Our study demonstrates the application of a trait-based approach combined with a metapopulation framework to assess the patch dynamics of darters in a regulated river. Results from our study will provide a baseline for evaluating the ecological consequences of alternative dam operations.

River Research and Applications↗

Growth form and lifespan of herbaceous species mediate the role of traits in short-term drought response

Increased climate variability is expected to intensify short-term drought events. Plants have evolved stress tolerance strategies involving trade-offs in resource conservation, mycorrhizal collaboration and plant size, yet how these strategies promote drought resistance across different herbaceous plant groups remains unknown. Leveraging 63 globally distributed grassland and shrubland sites from the International Drought Experiment, we identified plant traits linked to drought resistance in 661 populations of 421 species after 1 year of extreme drought. We assessed how traits, site precipitation and drought severity affected cover change across growth forms and lifespans, and how trait–environment interactions influenced drought resistance. Across all species, leaf N (an acquisitive trait) was associated with drought resistance, whereas in forbs, drought resistance was also associated with a conservative root trait and plant size. In addition, interactions among traits mediated drought resistance; root traits predicted performance only in concert with other traits. Environmental variables influenced trait effects on drought resistance, notably for annuals in wetter sites, suggesting that drought-escape strategies in annuals may be advantageous only under mild stress. Our study highlights variability in traits that predict drought resistance across herbaceous plant groups, emphasizing the importance of species context, environmental stress and the selection of traits in research and management.

Nature Ecology and Evolution↗

A three-dimensional mapping of the ocean based on environmental data

The existence, sources, distribution, circulation, and physicochemical nature of macroscale oceanic water bodies have long been a focus of oceanographic inquiry. Building on that work, this paper describes an objectively derived and globally comprehensive set of 37 distinct volumetric region units, called ecological marine units (EMUs). They are constructed on a regularly spaced ocean point-mesh grid, from sea surface to seafloor, and attributed with data from the 2013 World Ocean Atlas version 2. The point attribute data are the means of the decadal averages from a 57-year climatology of six physical and chemical environment parameters (temperature, salinity, dissolved oxygen, nitrate, phosphate, and silicate). The database includes over 52 million points that depict the global ocean in x, y, and z dimensions. The point data were statistically clustered to define the 37 EMUs, which represent physically and chemically distinct water volumes based on spatial variation in the six marine environmental characteristics used. The aspatial clustering to produce the 37 EMUs did not include point location or depth as a determinant, yet strong geographic and vertical separation was observed. Twenty-two of the 37 EMUs are globally or regionally extensive, and account for 99% of the ocean volume, while the remaining 15 are smaller and shallower, and occur around coastal features. We assessed the vertical distribution of EMUs in the water column and placed them into classical depth zones representing epipelagic (0 m to 200 m), mesopelagic (200 m to 1,000 m), bathypelagic (1,000 m to 4,000 m) and abyssopelagic (>4,000 m) layers. The mapping and characterization of the EMUs represent a new spatial framework for organizing and understanding the physical, chemical, and ultimately biological properties and processes of oceanic water bodies. The EMUs are an initial objective partitioning of the ocean using long-term historical average data, and could be extended in the future by adding new classification variables and by introducing functionality to develop time-specific EMU distribution maps. The EMUs are an open-access resource, and as both a standardized geographic framework and a baseline physicochemical characterization of the oceanic environment, they are intended to be useful for disturbance assessments, ecosystem accounting exercises, conservation priority setting, and marine protected area network design, along with other research and management applications.

Oceanography↗

Diverse portfolios: Investing in tributaries for restoration of large river fishes in the Anthropocene

Rehabilitation of large Anthropocene rivers requires engagement of diverse stakeholders across a broad range of sociopolitical boundaries. Competing objectives often constrain options for ecological restoration of large rivers whereas fewer competing objectives may exist in a subset of tributaries. Further, tributaries contribute toward building a “portfolio” of river ecosystem assets through physical and biological processes that may present opportunities to enhance the resilience of large river fishes. Our goal is to review roles of tributaries in enhancing mainstem large river fish populations. We present case histories from two greatly altered and distinct large-river tributary systems that highlight how tributaries contribute four portfolio assets to support large-river fish populations: 1) habitat diversity, 2) connectivity, 3) ecological asynchrony, and 4) density-dependent processes. Finally, we identify future research directions to advance our understanding of tributary roles and inform conservation actions. In the Missouri River United States, we focus on conservation efforts for the state endangered lake sturgeon, which inhabits large rivers and tributaries in the Midwest and Eastern United States. In the Colorado River, Grand Canyon United States, we focus on conservation efforts for recovery of the federally threatened humpback chub. In the Missouri River, habitat diversity focused on physical habitats such as substrate for reproduction, and deep-water habitats for refuge, whereas augmenting habitat diversity for Colorado River fishes focused on managing populations in tributaries with minimally impaired thermal and flow regimes. Connectivity enhancements in the Missouri River focused on increasing habitat accessibility that may require removal of physical structures like low-head dams; whereas in the Colorado River, the lack of connectivity may benefit native fishes as the disconnection provides refuge from non-native fish predation. Hydrologic variability among tributaries was present in both systems, likely underscoring ecological asynchrony. These case studies also described density dependent processes that could influence success of restoration actions. Although actions to restore populations varied by river system, these examples show that these four portfolio assets can help guide restoration activities across a diverse range of mainstem rivers and their tributaries. Using these assets as a guide, we suggest these can be transferable to other large river-tributary systems.

Frontiers in Environmental Science↗

A method for the use of landscape metrics in freshwater research and management

Freshwater research and management efforts could be greatly enhanced by a better understanding of the relationship between landscape-scale factors and water quality indicators. This is particularly true in urban areas, where land transformation impacts stream systems at a variety of scales. Despite advances in landscape quantification methods, several studies attempting to elucidate the relationship between land use/land cover (LULC) and water quality have resulted in mixed conclusions. However, these studies have largely relied on compositional landscape metrics. For urban and urbanizing watersheds in particular, the use of metrics that capture spatial pattern may further aid in distinguishing the effects of various urban growth patterns, as well as exploring the interplay between environmental and socioeconomic variables. However, to be truly useful for freshwater applications, pattern metrics must be optimized based on characteristic watershed properties and common water quality point sampling methods. Using a freely available LULC data set for the Santa Clara Basin, California, USA, we quantified landscape composition and configuration for subwatershed areas upstream of individual sampling sites, reducing the number of metrics based on: (1) sensitivity to changes in extent and (2) redundancy, as determined by a multivariate factor analysis. The first two factors, interpreted as (1) patch density and distribution and (2) patch shape and landscape subdivision, explained approximately 85% of the variation in the data set, and are highly reflective of the heterogeneous urban development pattern found in the study area. Although offering slightly less explanatory power, compositional metrics can provide important contextual information.

Landscape Ecology↗

How characteristic is the species characteristic selection scale?

Aim The importance of framing investigations of organism–environment relationships to interpret patterns at relevant spatial scales is increasingly recognized. However, most research related to environmental relationships is single-scaled, implicitly or explicitly assuming that a “species characteristic selection scale” exists. We tested the premise that a single characteristic scale exists to understand species–environment relationships within species by asking (a) what are the characteristic scales of species’ relationships with environmental predictors, and (b) is within-species, cross-predictor consistency in characteristic scales a general phenomenon. Location Nebraska, USA. Time period 2016. Major taxa studied Birds. Methods We used data from 86 species at > 500 locations to build hierarchical N-mixture models relating species abundance to land cover variables. By incorporating Bayesian latent indicator scale selection, we identified the spatial scales that best explain species–environment relationships with each land cover predictor. We quantified the extent of cross-predictor consistency in characteristic scales, and contrasted this to the expectation given a single species’ characteristic scale. Results We found no evidence for a characteristic spatial scale explaining all abundance–environment relationships within species, rather we found substantial variation in scale-dependence across multiple environmental attributes. Furthermore, 33% of species displayed evidence of multiple important spatial scales within environmental attributes. Major conclusions Within species there is little evidence for a single characteristic scale of environmental relationships and considerable variation in species’ scale dependencies. Because species may respond to multiple environmental attributes at different spatial scales, or single environmental attributes at multiple scales, we caution against any unoptimized single-scale studies. Our results demonstrate that until a framework is developed to predict the scales at which species respond to environmental characteristics, multi-scale investigations must be performed to identify and account for multi-scale dependencies. Natural selection acting on species’ response to distinct environmental attributes, rather than natural selection acting on species’ perception of spatial scales per se, may have shaped patterns of scale dependency and is an area ripe for investigation.

Nebraska↗

Comparing the role of fuel breaks across southern California national forests

Fuel treatment of wildland vegetation is the primary approach advocated for mitigating fire risk at the wildland–urban interface (WUI), but little systematic research has been conducted to understand what role fuel treatments play in controlling large fires, which factors influence this role, or how the role of fuel treatments may vary over space and time. We assembled a spatial database of fuel breaks and fires from the last 30 years in four southern California national forests to better understand which factors are consistently important for fuel breaks in the control of large fires. We also explored which landscape features influence where fires and fuel breaks are most likely to intersect. The relative importance of significant factors explaining fuel break outcome and number of fire and fuel break intersections varied among the forests, which reflects high levels of regional landscape diversity. Nevertheless, several factors were consistently important across all the forests. In general, fuel breaks played an important role in controlling large fires only when they facilitated fire management, primarily by providing access for firefighting activities. Fire weather and fuel break maintenance were also consistently important. Models and maps predicting where fuel breaks and fires are most likely to intersect performed well in the regions where the models were developed, but these models did not extend well to other regions, reflecting how the environmental controls of fire regimes vary even within a single ecoregion. Nevertheless, similar mapping methods could be adopted in different landscapes to help with strategic location of fuel breaks. Strategic location of fuel breaks should also account for access points near communities, where fire protection is most important.

California↗