Landscape Correlates of Breeding Bird Richness Across the United States Mid-Atlantic Region

Using a new set of landscape indicator data generated by the U.S.EPA, and a comprehensive breeding bird database from the National Breeding Bird Survey, we evaluated associations between breeding bird richness and landscape characteristics across the entire mid-Atlantic region of the United States. We evaluated how these relationships varied among different groupings (guilds) of birds based on functional, structural, and compositional aspects of individual species demographics. Forest edge was by far the most important landscape attribute affecting the richness of the lumped specialist and generalist guilds; specialist species richness was negatively associated with forest edge and generalist richness was positively associated with forest edge. Landscape variables (indicators) explained a greater proportion of specialist species richness than the generalist guild (46% and 31%, respectively). The lower value in generalists may reflect finer-scale distributions of open habitat that go undetected by the Landsat satellite, open habitats created by roads (the areas from which breeding bird data are obtained), and the lumping of a wide variety of species into the generalist category. A further breakdown of species into 16 guilds showed considerable variation in the response of breeding birds to landscape conditions; forest obligate species had the strongest association with landscape indicators measured in this study (55% of the total variation explained) and forest generalists and open ground nesters the lowest (17% of the total variation explained). The variable response of guild species richness to landscape pattern suggests that one must consider species' demographics when assessing the consequences of landscape change on breeding birds.     

Assessing the regional impacts of increased energy maize cultivation on farmland birds

The increasing cultivation of energy crops in Germany substantially affects the habitat function of agricultural landscapes. Precise ex ante evaluations regarding the impacts of this cultivation on farmland bird populations are rare. The objective of this paper was to implement a methodology to assess the regional impacts of increasing energy maize cultivation on the habitat quality of agricultural lands for farmland birds. We selected five farmland bird indicator species with varying habitat demands. Using a crop suitability modelling approach, we analysed the availability of potential habitat areas according to different land use scenarios for a real landscape in Northeast Germany. The model was based on crop architecture, cultivation period, and landscape preconditions. Our results showed that the habitat suitability of different crops varied between bird species, and scenario calculations revealed an increase and a decrease in the size of the potential breeding and feeding habitats, respectively. The effects observed in scenario 1 (increased energy maize by 15 %) were not reproduced in all cases in scenario 2 (increased energy maize by 30 %). Spatial aggregation of energy maize resulted in a negative effect for some species. Changes in the composition of the farmland bird communities, the negative effects on farmland bird species limited in distribution and spread and the relevance of the type of agricultural land use being replaced by energy crops are also discussed. In conclusion, we suggest a trade-off between biodiversity and energy targets by identifying biodiversity-friendly energy cropping systems.     

Visually determined stream mesohabitats influence benthic macroinvertebrate assessments in headwater streams

Mesohabitat components such as substrate and surface flow types are intimately related to benthic macroinvertebrate assemblages in streams. Visual assessments of the distribution of these components provide a means of evaluating physical habitat heterogeneity and aid biodiversity surveys and monitoring. We determined the degree to which stream site and visually assessed mesohabitat variables explain variability (i.e., beta-diversity) in the relative abundance and presence-absence of all macroinvertebrate families and of Ephemeroptera, Plecoptera, and Trichoptera (EPT) genera. We systematically sampled a wide variety of mesohabitat arrangements as they occured in stream sites. We also estimated how much of the explanation given by mesohabitat was associated with substrate or surface flow types. We performed variation partitioning to determine fractions of explained variance through use of partial redundancy analysis (pRDA). Mesohabitats and stream sites explained together from 23 to 32 % of the variation in the four analyses. Stream site explained 8–11 % of that variation, and mesohabitat variables explained 13–20 %. Surface flow types accounted for >60 % of the variation provided by the mesohabitat component. These patterns are in accordance with those obtained in previous studies that showed the predominance of environmental variables over spatial location in explaining macroinvertebrate distribution. We conclude that visually assessed mesohabitat components are important predictors of assemblage composition, explaining significant amounts of beta-diversity. Therefore, they are critical to consider in ecological and biodiversity assessments involving macroinvertebrates.     

Relationship Between Bird Abundances and Landscape Characteristics: The Influence of Scale

Scale is important to consider when investigating effects of the environment on a species. Breeding Bird Survey (BBS) data and landscape metrics derived from aerial photographs were evaluated to determine how relationships of bird abundances with landscape variables changed over a continuous range of 16 spatial scales. We analyzed the average number of birds per stop (1985–1994) for five songbird species (family Cardinalidae) for each of 50 stops on 198 BBS transects throughout six states in the Central Plains, USA. Land along each transect was categorized into six cover types, and landscape metrics of fractal dimension (a measure of shape complexity of habitat patches), edge density, patch density, and percent area were calculated, with principal components used to construct composite environmental variables. Associations of bird abundances and landscape variables changed in accordance with small scale changes. Abundances of three species were correlated with edge density and one with component I, which subsumes initial variables of patch density for urban, closed forest, open forest, and open country. Fractal dimension and component II (summarizing amount of closed forest versus open country) were associated with the most species. Correlation patterns of fractal dimension with northern cardinal (Cardinalis cardinalis) and painted bunting (Passerina ciris) abundances were similar, with highest correlations at intermediate to small scales, suggesting indirectly that these species thrive in areas where local habitat conditions are most important. Multiscale analysis can provide insight into the spatial scale(s) at which species respond, a topic of intrinsic scientific interest with applied implications for researchers establishing protocols to assess and monitor avian populations.     

Biodiversity and bird surveys in Finnish environmental impact assessments and follow-up monitoring

Environmental Impact Assessments (EIAs) that are applied in the planning phases of large land-use and construction projects are aimed at aiding decision-making and mitigating significant environmental impacts. In light of the global biodiversity crisis, conducting high-quality biodiversity impact assessments is important, as biodiversity information, among other factors, has the potential to influence how projects will be implemented in the end. We investigated the biodiversity and bird surveys conducted and the number of bird species of conservation concern in peat extraction and wind farm projects to which an EIA was applied to in 1995–2016 in Finland and compared whether these factors differed between the project types and between implemented and unimplemented projects. We also studied the availability of follow-up monitoring data of biodiversity impacts within the two project types. The number of nationally threatened breeding birds was significantly lower in implemented than in unimplemented peat extraction projects. The overall probability of being implemented was significantly negatively associated with the year the EIA began for both project types. All permitted peat extraction projects and 22% of wind farm projects conducted post-construction biodiversity monitoring; however, only some projects enabled before-after comparisons. Our results are in line with earlier findings that demonstrate the difficulty of showing the direct impacts of biodiversity information on EIA decision-making and to what extent it is related to project approval or rejection. The role of follow-up monitoring in the EIA and project development could also be strengthened.     

Vegetation, Soil, and Animal Indicators of Rangeland Health

We studied indicators of rangeland health on benchmark sites with long, well documented records of protection from stress by domestic livestock or histories of environmental stress and vegetation change. We measured ecosystem properties (metrics) that were clearly linked to ecosystem processes. We focused on conservation of soil and water as key processes in healthy ecosystems, and on maintenance of biodiversity and productivity as important functions of healthy ecosystems. Measurements from which indicators of rangeland health were derived included: sizes of unvegetated patches, cover and species composition of perennial grasses, cover and species composition of shrubs and herbaceous perennials, soil slaking, and abundance and species composition of the bird fauna. Indicators that provided an interpretable range of values over the gradient from irreversibly degraded sites to healthy sites included: bare patch index, cover of long-lived grasses, palatability index, and weighted soil surface stability index. Indicators for which values above a threshold may serve as an indicator of rangeland health include: cover of plant species toxic to livestock, cover of exotic species, and cover of increaser species. Several other indicator metrics were judged not sensitive nor interpretable. Examples of application of rangeland health indicators to evaluate the success of various restoration efforts supported the contention that a suite of indicators are required to assess rangeland health. Bird species diversity and ant species diversity were not related to the status of the sample site and were judged inadequate as indicators of maintenance of biodiversity.     

Evaluating Ecological Indicators: Lakes In The Northeastern United States

We use data from a survey of several hundred lakes in the northeastern United States by the U.S. Environmental Protection Agency to illustrate an approach to identifying promising indicators of lake condition. We construct a hypothetical gold standard of water quality from the first principal component of 16 chemical variables measured in the lakes, and examine its associations with 71 candidate indicators based on measurements of human activity, birds, fish and zooplankton in the lakes or their watersheds. Nonparametric summaries of these associations – based on rank correlations and receiver-operating-characteristic curves – suggest that variables summarizing the extent of human disturbance are generally the strongest indicators. To the extent that our water-quality variable is a useful proxy for ecological condition, our results suggest that easily-obtained measures of human activity are at least as predictive as many of the harder-to-measure biological indicators that have been proposed.     

Marine Birds as Indicators of Arctic Marine Ecosystem Health: Linking the Northern Ecosystem Initiative to Long-Term Studies

Marine birds are sensitive indicators of the condition of marine ecosystems in the Arctic, partly because they feed at the top of the arctic food chain. The Northern Ecosystem Initiative (NEI) recently supported four separate studies that investigated aspects of Arctic marine bird science which simultaneously addressed goals of the NEI to better understand northern ecosystems and their response to environmental stressors. The projects used both scientific and traditional knowledge to examine the relationship between sea-ice, contaminants, and the ecology of marine birds, and to transfer environmental knowledge to students. Results from these investigations confirm that changes are occurring in Arctic environments, and that these are captured through marine bird research. Collectively these studies provided new data that supported NEI objectives of monitoring the health of the Arctic ecosystem, and contributed to Canada's international obligations for Arctic science.     

Atmospheric influences on water quality: a simulation of nutrient loading for the Pearl River Basin, USA

Knowledge of water quality conditions is essential in assessing the health of riverine ecosystems. The goal of this study is to determine the degree to which water quality variables are related to precipitation and air temperature conditions for a segment of the Pearl River Basin near Bogalusa, LA, USA. The AQUATOX ecological fate simulation model is used to estimate daily total nitrogen, total phosphorus, and dissolved oxygen concentrations over a 2-year period. Daily modeled output for each variable was calibrated against reliably measured data to assess the accuracy. Observed data were plotted against simulated data for controlled and perturbed models for validation, and stepwise multiple regression analysis was used to quantify the relationships between the water quality and meteorological variables. Results suggest that daily dissolved oxygen is significantly negatively correlated to concurrent daily mean air temperature with a total explained variance of 0.679 (p?<?0.01), and monthly dissolved oxygen is significantly negatively correlated to monthly mean air temperature with a total explained variance of 0.567 (p?<?0.01). Total mean monthly phosphorus concentration is significantly positively related to the previous month's precipitation with a total explained variance of 0.302 (p?<?0.01). These relationships suggest that atmospheric conditions have a strong influence on water quality in the Pearl Basin. Therefore, environmental planners should expect that future climatic changes are likely to alter water quality.     

Local versus landscape spatial influence on biodiversity: a case study across five European industrialized areas

Land use change—mostly habitat loss and fragmentation—has been recognized as one of the major drivers of biodiversity loss worldwide. According to the habitat amount hypothesis, these phenomena are mostly driven by the habitat area effect. As a result, species richness is a function of both the extent of suitable habitats and their availability in the surrounding landscape, irrespective of the dimension and isolation of patches of suitable habitat. In this context, we tested how the extent of natural areas, selected as proxies of suitable habitats for biodiversity, influences species richness in highly anthropogenic landscapes. We defined five circular sampling areas of 5 km radius, including both natural reserves and anthropogenic land uses, centred in five major industrial sites in France, Italy and Germany. We monitored different biodiversity indicators for both terrestrial and aquatic ecosystems, including breeding birds, diurnal butterflies, grassland vegetation, odonata, amphibians, aquatic plants and benthic diatoms. We studied the response of the different indicators to the extent of natural land uses in the sampling area (local effect) and in the surrounding landscape (landscape effect), identified as a peripheral ring encircling the sampling area. Results showed a positive response of five out of seven biodiversity indicators, with aquatic plants and odonata responding positively to the local effect, while birds, vegetation and diatoms showed a positive response to the landscape effect. Diatoms also showed a significant combined response to both effects. We conclude that surrounding landscapes act as important biodiversity sources, increasing the local biodiversity in highly anthropogenic contexts.     

Small mammals as indicators of short-term and long-term disturbance in mixed prairie

Disturbance by military maneuvers over short and long time scales may have differential effects on grassland communities. We assessed small mammals as indicators of disturbance by military maneuvers in a mixed prairie in southern Oklahoma USA. We examined sites on two soil series, Foard and Lawton, across a gradient of disturbance intensity. A MANOVA showed that abundance of small mammals was associated (p = 0.03) with short-term (cover of vehicle tracks) disturbance but was not associated (p = 0.12) with long-term (loss of soil organic carbon, SOC) disturbance intensity. At the individual species level, Sigmodon hispidus (cotton rat) and Peromyscus maniculatus (deer mouse) occurred across all levels of disturbance and in both soil types. Only P. maniculatus abundance changed (p < 0.01) with short-term disturbance and increased by about one individual per 5% of additional track-cover. Abundance of P. maniculatus also increased (p = 0.04) by about three individuals per 1% increase in soil carbon. Chaetodipus hispidus (hispid pocket mouse) and Reithrodontomys fulvescens (fulvous harvest mouse) only occurred in single soil types limiting their potential as more general indicators. Abundance of P. maniculatus was positively related to shifts in plant species composition and likely reflected changes in vegetation structure (i.e. litter depth) and forage availability resulting from disturbance. Peromyscus maniculatus may be a useful biological indicator of ecosystem change because it responded predictably to both long-term and short-term disturbance and, when coupled with soil, plant, and disturbance history variables, can reveal land condition trends.     

Effects of the Conservation Reserve Program on northern bobwhite and grassland birds

The Conservation Reserve Program (CRP) has converted just over 36 million acres of cropland into potential wildlife habitat, primarily grassland. Thus, the CRP should benefit grassland songbirds, a group of species that is declining across the United States and is of conservation concern. Additionally, the CRP is an important part of multi-agency, regional efforts to restore northern bobwhite populations. However, comprehensive assessments of the wildlife benefits of CRP at regional scales are lacking. We used Breeding Bird Survey and National Resources Inventory data to assess the potential for the CRP to benefit northern bobwhite and other grassland birds with overlapping ranges and similar habitat associations. We built regression models for 15 species in seven different ecological regions. Forty-nine of 108 total models contained significant CRP effects (P < 0.05), and 48 of the 49 contained positive effects. Responses to CRP varied across ecological regions. Only eastern meadowlark was positively-related to CRP in all the ecological regions, and western meadowlark was the only species never related to CRP. CRP was a strong predictor of bird abundance compared to other land cover types. The potential for CRP habitat as a regional conservation tool to benefit declining grassland bird populations should continue to be assessed at a variety of spatial scales. We caution that bird-CRP relations varied from region to region and among species. Because the NRI provides relatively coarse resolution information on CRP, more detailed information about CRP habitats (spatial arrangement, age of the habitat (time since planting), specific conservation practices used) should be included in future assessments to fully understand where and to what extent CRP can benefit grassland birds.     

Development of a Grassland Integrity Index Based on Breeding Bird Assemblages

We utilized landscape and breeding bird assemblage data from three Breeding Bird Survey (BBS) routes sampled from 1965–1995 to develop and test a grassland integrity index (GII) in a mixed-grass prairie area of Oklahoma. The overall study region is extensively fragmented from long-term agricultural activity, and native habitat remnants have been degraded by recent encroachment of woody vegetation, namely eastern redcedar (Juniperus virginiana L.). The 50 individual bird survey points along the BBS routes, known as stops, were used as sample sites. Our process first focused on developing a grassland disturbance index (GDI) as a measure of cumulative landscape disturbances for these sites. The GDI was based on five key landscape variables identified in an earlier species-level study of long-term avian community dynamics: total tree, shrub, and herbaceous vegetation cover indices, overall mean landscape patch size, and grassland patch core size. The GII was then developed based on breeding bird assemblage data. Assemblages were based on commonly used response guilds reflective of five avian life history parameters: foraging mode/location, nesting location, habitat specificity, migratory pattern, and dietary guild. We tested the response of 78 candidate assemblage metrics to the GDI, and eliminated those with no or poor response or with high correlations (redundant), resulting in 13 metrics for use in the final index. Individual metric scores were scaled to fall between 0 and 10, and the cumulative index to range from 0 to 100. Although broader application and refinement are possible, the avian-based GII has an advantage over labor-intensive, habitat-based monitoring in that the GII is derived from readily available long-term BBS data. Therefore, the GII shows promise as an inexpensive tool that could easily be applied over other areas to monitor changes in regional grassland conditions.     

Including biodiversity in life cycle assessment – State of the art,gaps and research needs

PurposeFor over 20 years the feasibility of including man-made impacts on biodiversity in the context of Life Cycle Assessment (LCA) has been explored. However, a comprehensive biodiversity impact assessment has so far not been performed. The aim of this study is to analyse how biodiversity is currently viewed in LCA, to highlight limitations and gaps and to provide recommendations for further research.MethodFirstly, biodiversity indicators are examined according to the level of biodiversity they assess (genetic, species, ecosystem) and to their usefulness for LCA. Secondly, relevant pressures on biodiversity that should be included in LCA are identified and available models (in and outside of an LCA context) for their assessment are discussed. Thirdly, existing impact assessment models are analysed in order to determine whether and how well pressures are already integrated into LCA. Finally, suggestions on how to include relevant pressures and impacts on biodiversity in LCA are provided and the necessary changes in each LCA phase that must follow are discussed.ResultsThe analysis of 119 indicators shows that 4% of indicators represent genetic diversity, 40% species diversity and 35% ecosystem diversity. 21% of the indicators consider further biodiversity-related topics. Out of the indicator sample, 42 indicators are deemed useful as impact indicators in LCA. Even though some identified pressures are already included in LCA with regard to their impacts on biodiversity (e.g. land use, carbon dioxide emissions etc.), other proven pressures on biodiversity have not yet been considered (e.g. noise, artificial light).ConclusionFurther research is required to devise new options (e.g. impact assessment models) for integrating biodiversity into LCA. The final goal is to cover all levels of biodiversity and include all missing pressures in LCA. Tentative approaches to achieve this goal are outlined.     

Community analysis in stream biomonitoring: what we measure and what we don't

Diatom assemblages from 83 epilithic samples taken from the Mesta River, Bulgaria, were regressed against three sets of predictor variables, i.e. environmental, spatial, and temporal. Redundancy analysis (RDA) of species and environmental data explained 36% of the diatom variance and extracted several important gradients of species distribution, associated with a downstream increase in nutrient levels, pH, temperature, and organic pollution. The inclusion of spatial and temporal variables in the RDA model captured additional 24% of the diatom variance and revealed three more gradients, a spatial gradient represented by higher order polynomial terms of latitude and longitude, and two temporal gradients of annual and seasonal variation. Partial RDAs demonstrated that the unique contribution of each predictor set to the explained diatom variance was the highest in the spatial dataset (16%), followed by the environmental (9%), and the temporal (7%) datasets. The remaining 28% of the variance was explained by the covariance of the predictor sets. This suggests that in biomonitoring of single stream basins, the cheap and simple account of space and time would explain most of the variance in assemblage composition obviating the necessity of expensive and time-consuming environmental assessments. The nature of the underlying environmental mechanisms can be easily inferred from the diatom composition itself.     

Establishment of a structural equation model for ground-level ozone: a case study at an urban roadside site

This study established a cause–effect relationship between ground-level ozone and latent variables employing partial least-squares analysis at an urban roadside site in four distinct seasons. Two multivariate analytic methods, factor analysis, and cluster analysis were adopted to cite and identify suitable latent variables from 14 observed variables (i.e., meteorological factors, wind and primary air pollutants) in 2008–2010. Analytical results showed that the first six components explained 80.3 % of the variance, and eigenvalues of the first four components were greater than 1. The effectiveness of this model was empirically confirmed with three indicators. Except for surface pressure, factor loadings of observed variables were 0.303–0.910 and reached statistical significance at the 5 % level. Composite reliabilities for latent variables were 0.672–0.812 and average variances were 0.404–0.547, except for latent variable “primary” in spring; thus, discriminant validity and convergent validity were marginally accepted. The developed model is suitable for the assessment of urban roadside surface ozone, considering interactions among meteorological factors, wind factors, and primary air pollutants in each season.     

Statistically Extracted Fundamental Watershed Variables for Estimating the Loads of Total Nitrogen in Small Streams

Accurate estimation of total nitrogen loads is essential for evaluating conditions in the aquatic environment. Extrapolation of estimates beyond measured streams will greatly expand our understanding of total nitrogen loading to streams. Recursive partitioning and random forest regression were used to assess 85 geospatial, environmental, and watershed variables across 636 small (<585 km²) watersheds to determine which variables are fundamentally important to the estimation of annual loads of total nitrogen. Initial analysis led to the splitting of watersheds into three groups based on predominant land use (agricultural, developed, and undeveloped). Nitrogen application, agricultural and developed land area, and impervious or developed land in the 100-m stream buffer were commonly extracted variables by both recursive partitioning and random forest regression. A series of multiple linear regression equations utilizing the extracted variables were created and applied to the watersheds. As few as three variables explained as much as 76 % of the variability in total nitrogen loads for watersheds with predominantly agricultural land use. Catchment-scale national maps were generated to visualize the total nitrogen loads and yields across the USA. The estimates provided by these models can inform water managers and help identify areas where more in-depth monitoring may be beneficial.     

Effects of geomorphology, habitat, and spatial location on fish assemblages in a watershed in Ohio, USA

In this paper, we evaluate relationships between in-stream habitat, water chemistry, spatial distribution within a predominantly agricultural Midwestern watershed and geomorphic features and fish assemblage attributes and abundances. Our specific objectives were to: (1) identify and quantify key environmental variables at reach and system wide (watershed) scales; and (2) evaluate the relative influence of those environmental factors in structuring and explaining fish assemblage attributes at reach scales to help prioritize stream monitoring efforts and better incorporate all factors that influence aquatic biology in watershed management programs. The original combined data set consisted of 31 variables measured at 32 sites, which was reduced to 9 variables through correlation and linear regression analysis: stream order, percent wooded riparian zone, drainage area, in-stream cover quality, substrate quality, gradient, cross-sectional area, width of the flood prone area, and average substrate size. Canonical correspondence analysis (CCA) and variance partitioning were used to relate environmental variables to fish species abundance and assemblage attributes. Fish assemblages and abundances were explained best by stream size, gradient, substrate size and quality, and percent wooded riparian zone. Further data are needed to investigate why water chemistry variables had insignificant relationships with IBI scores. Results suggest that more quantifiable variables and consideration of spatial location of a stream reach within a watershed system should be standard data incorporated into stream monitoring programs to identify impairments that, while biologically limiting, are not fully captured or elucidated using current bioassessment methods.     

Atmospheric Change and Biodiversity

Strategies to conserve biodiversity need to include the monitoring, modelling, adaptation and regulation of the composition of the atmosphere. Atmospheric issues include climate variability and extremes; climate change; stratospheric ozone depletion; acid deposition; photochemical pollution; suspended particulate matter; and hazardous air pollutants. Coarse filter and fine filter approaches have been used to understand the complexity of the interactions between the atmosphere and biodiversity. In the first approach, climate-based models, using GIS technology, helped create future biodiversity scenarios under a 2 × CO₂ atmosphere. In the second approach, the SI/MAB forest biodiversity monitoring protocols helped calibrate the climate-forest biodiversity baseline and, as global diagnostics, helped identify where the biodiversity was in equilibrium with the present climate. Forest climate monitoring, an enhancing protocol, was used in a co-location approach to define the thermal buffering capacity of forest ecosystems and their ability to reduce and ameliorate global climate variability, extremes and change.