Application of the Braun-Blanquet cover-abundance scale for vegetation analysis in land development studies

To document environmental impact predictions for land development, as required by United States government regulatory agencies, vegetation studies are conducted using a variety of methods. Density measurement (stem counts) is one method that is frequently used. However, density measurement of shrub and herbaceous vegetation is time-consuming and costly. As an alternative, the Braun-Blanquet cover-abundance scale was used to analyze vegetation in several ecological studies. Results from one of these studies show that the Braun-Blanquet method requires only one third to one fifth the field time required for the density method. Furthermore, cover-abundance ratings are better suited than density values to elucidate graphically species-environment relationships. For extensive surveys this method provides sufficiently accurate baseline data to allow environmental impact assessment as required by regulatory agencies.     

Nature apps: Waiting for the revolution

Apps are small task-orientated programs with the potential to integrate the computational and sensing capacities of smartphones with the power of cloud computing, social networking, and crowdsourcing. They have the potential to transform how humans interact with nature, cause a step change in the quantity and resolution of biodiversity data, democratize access to environmental knowledge, and reinvigorate ways of enjoying nature. To assess the extent to which this potential is being exploited in relation to nature, we conducted an automated search of the Google Play Store using 96 nature-related terms. This returned data on ~36 304 apps, of which ~6301 were nature-themed. We found that few of these fully exploit the full range of capabilities inherent in the technology and/or have successfully captured the public imagination. Such breakthroughs will only be achieved by increasing the frequency and quality of collaboration between environmental scientists, information engineers, computer scientists, and interested publics.     

Environmental and phylogenetic correlates of Eulemur behavior and ecology (Primates: Lemuridae)

The extent of diversity within closely related taxa may be a function of their shared evolutionary history or of selective forces causing adaptive changes. Examining variation among taxa within a single genus may help to identify flexibility in trait variation because recently diverged populations are more likely living in the environment of adaptation. This study examines correlates of diversity in Eulemur, a genus that has a wide distribution in a variety of habitat types throughout Madagascar. Previously published data were gathered from 11 long-term studies of Eulemur populations. Variables were categorized into multiple datasets: (1) environmental characteristics, (2) social organization, and (3) ecology, which included subsets for ranging behavior, diet, and activity budget. Molecular phylogenies from the literature were used to create the fourth and final dataset, a dissimilarity matrix of evolutionary distance among the 12 species and subspecies. Principal components and cluster analyses were implemented to examine the overall ecological similarity among Eulemur populations and to determine which variables contribute most to the variation among taxa. Partial Mantel tests were conducted to test for correlations among the dataset matrices. The results suggest ecological flexibility for the genus, in particular, populations in similar environments displayed similar activity patterns. In contrast, social organization showed no relationship with environment but was correlated with phylogenetic distance among populations. While Eulemur seems to demonstrate some flexibility for ecological adaptations, characteristics related to group size and sex ratio more closely track phylogeny and thus may be less flexible.Electronic supplementary material Supplementary material is available in the online version of this article at and is accessible to authorized users.     

Modeling freshwater fish distributions using multiscale landscape data: A case study of six narrow range endemics

Species distribution models (SDMs) have become integral tools in scientific research and conservation planning. Despite progress in the assessment of various statistical models for use in SDMs, little has been done in way of evaluating appropriate ecological models. In this paper, we evaluate the multiscale filter framework as a suitable theoretical model for predicting freshwater fish distributions in the upper Green River system (Ohio River drainage), USA. The spatial distributions of six fishes with contrasting biogeographies were modeled using boosted regression trees and multiscale landscape data. Species biogeography did not appear to affect predictive performance and all models performed well statistically with receiver operating characteristic area under the curve (AUC) ranging from 0.87 to 0.98. Predictive maps show accurate estimations of ranges for five of six species based on historical collections. The relative influence of each type of environmental feature and spatial scale varied markedly with between species. A hierarchical effect was detected for narrowly distributed species. These species were highly influenced by soil composition at larger spatial scales and land use/land cover (LULC) patterns at more proximal scales. Conversely, LULC pattern was the most influential feature for widely distributed at all spatial scales. Using multiscale data capable of capturing hierarchical landscape influences allowed production of accurate predictive models and provided further insight into factors controlling freshwater fish distributions.     

Trade-offs between time, predation risk and life history, and their implications for biogeography: A systems modelling approach with a primate case study

Group sizes are often considered to be the result of a trade-off between predation risk and the costs of feeding competition. We develop a model to explore the interaction between different ecological constraints on group sizes, using a primate (baboons) case study. The model uses climatic correlates of time budgets to predict maximum ecologically tolerable group size, and climatic predictors of predation risk (reflected mainly in predator density and female body mass) to predict minimum tolerable group size for any given habitat. As well as defining the range of sustainable group sizes for a given habitat, the model also allows us to reliably predict our exemplar taxon's biogeographical distribution across Africa. We also explore the life history implications of the model to ask whether baboons form group sizes which maximise survival or fecundity in the classic trade off between these two key life history variables. Our results indicate that, within the range of study sites in our sample, baboons prefer to maximise fecundity. However, the data indicate that in higher predation risk habitats they would switch to maximising survival at the expense of fecundity. We argue that this is due to the fact that interbirth interval and developmental rates have a ceiling that cannot be breached. Thus, while females can shorten interbirth intervals to compensate for increased predation risk, there is a limit to how much these life history variables can be altered, and when this is reached the best strategy is to maximise survivorship.     

Distinct community assembly processes underlie significant spatiotemporal dynamics of abundant and rare bacterioplankton in the Yangtze River

• Season and landform influenced spatiotemporal patterns of abundant and rare taxa. • Different stochastic processes dominated abundant and rare subcommunity assembly. • River flow and suspended solids regulated assembly processes of rare taxa. The rare microbial biosphere provides broad ecological services and resilience to various ecosystems. Nevertheless, the biogeographical patterns and assembly processes of rare bacterioplankton communities in large rivers remain uncertain. In this study, we investigated the biogeography and community assembly processes of abundant and rare bacterioplankton taxa in the Yangtze River (China) covering a distance of 4300 km. The results revealed similar spatiotemporal patterns of abundant taxa (AT) and rare taxa (RT) at both taxonomic and phylogenetic levels, and analysis of similarities revealed that RT was significantly influenced by season and landform than AT. Furthermore, RT correlated with more environmental factors than AT, whereas environmental and spatial factors explained a lower proportion of community shifts in RT than in AT. The steeper distance–decay slopes in AT indicated higher spatial turnover rates of abundant subcommunities than rare subcommunities. The null model revealed that both AT and RT were mainly governed by stochastic processes. However, dispersal limitation primarily governed the AT, whereas the undominated process accounted for a higher fraction of stochastic processes in RT. River flow and suspended solids mediated the balance between the stochastic and deterministic processes in RT. The spatiotemporal dynamics and assembly processes of total taxa were more similar as AT than RT. This study provides new insights into both significant spatiotemporal dynamics and inconsistent assembly processes of AT and RT in large rivers.     

Ecology of sandy beaches in Oman

The benthic macrofauna and physical features of 10 sandy beaches along the coast of Oman were surveyed quantitatively. This is a mesotidal regime mostly subject to low to moderate wave energy but more exposed in the south. Five northern beaches are tide-dominated, with low wave energy, and their profiles consist of a berm, a steep, swash-dominated upper shore and a broad tide-dominated terrace from mid-shore downwards. They are composed of moderately sorted fine to medium sands. Southern beaches experience greater wave energy, particularly during the summer southwest monsoon, and exhibit smoother, concave profiles with fine, fairly well sorted carbonate sand. 58 species and species groups were recorded, with crustanceans, polychaetes and molluscs dominant. In general species richness was high, at least 19–25 species per beach, but dry biomass moderate to low at 26–90g/m shoreline, with one high value of 450g/m. Total abundance was moderate at 3–73×10³ organisms/m of beach. Some zonation was evident with ocypodid crabs andTylos in the supralittoral, cirolanid isopods on the upper shore and a variety of species on the lower shore. The coast of Oman appears to constitute a single zoogeographic region, but with some regional differentiation between north and south due to varying physical conditions. Thus, OmanÕs beaches are characterized by tide-dominated morphodynamics and exceptionally high species richness.     

Climate change and the geography of weed damage: Analysis of U.S. maize systems suggests the potential for significant range transformations

By the end of the century, climate change projections under a “business-as-usual” emissions scenario suggest a globally averaged warming of 2.4–6.4 °C. If these forecasts are realized, cropping systems are likely to experience significant geographic range transformations among damaging endemic weed species and new vulnerabilities to exotic weed invasions. To anticipate these changes and to devise management strategies for proactively addressing them, it is necessary to characterize the environmental conditions that make specific weed species abundant, competitive, and therefore damaging the production of particular crops (i.e. defining the damage niche). In this study, U.S. maize is used as a model system to explore the implications of climate change on the distribution of damaging agricultural weeds. To accomplish this, we couple ensemble climate change projections of annual temperature and precipitation with survey data of troublesome weed species in maize. At the state scale, space-for-time substitution techniques are used to suggest the potential magnitude of change among damaging weed communities. To explore how the geography of damage for specific species may evolve over the next century, bioclimatic range rules were derived for two weed species that are pervasive in the Northern (Abutilon theophrasti Medicus, ABUTH) and Southern (Sorghum halepense (L.) Pers., SORHA) U.S. Results from both analyses suggest that the composition of damaging weed communities may be fundamentally altered by climate change. In some states, potential changes in the coming decades are commensurate to those possible by the end of the century. Regions such as the Northeastern U.S. may prove particularly vulnerable with emerging climate conditions favoring few weed species of present-day significance. In contrast, regions like the mid-South are likely to experience fewer shifts even with a similar magnitude in climate change. By the end of the century in the U.S. Corn Belt, cold-tolerant species like A. theophrasti may be of minor importance whereas S. halepense, a predominantly Southern U.S. weed species at present, may become common and damaging to maize production with its damage niche advancing 200–600 km north of its present-day distribution.     

Plant acclimation to elevated CO2—From simple regularities to biogeographic chaos

Upon exposure to altered levels of CO₂, plants express a variety of acclimations to CO₂ directly, over and above acclimations to indirect changes in temperature and water regimes. These acclimations commonly include increased photosynthetic CO₂ assimilation and increased water-use efficiency with reduced N content and reduced stomatal conductance. The robust generic acclimations are explicable by combining simple models of carboxylation, stomatal control, energy balance, and functional balance. Species- or genotype-specific acclimations are overlaid on these generic acclimations. Several such specific acclimations that are often seen are readily incorporated in an extended model. These specific acclimations generate a great spread of values in key performance measures of photosynthesis, water- and N-use efficiencies, and rates of water and N use, even among C₃ species that are the focus of this work. These performance measures contribute strongly to relative fitness and thus to evolving biogeographic distributions. The spread in fitness values is so large as to impend “chaotic” shifts in biogeography (and, ultimately, evolution) that are not understandable with models specific to species or functional groups; rather, a systematic study of key physiological and developmental parameters is merited. Also merited is a coherent extension of the model used here, or similar models, to include other phenomena, including mycorrhizal associations, transience in resource availability, etc. The composition of useful approximate fitness functions from physiological and allocational responses is a major challenge, with some leads originating from the model. In the search to extract patterns of responses, arguments based on the responses being close to optimal or adaptive will be misleading, in view of the absence of selection pressure to perform adaptively at high CO₂ for over 20 million years. I offer suggestions for more useful research designs.     

Human Influences on Water Quality in Great Lakes Coastal Wetlands

A better understanding of relationships between human activities and water chemistry is needed to identify and manage sources of anthropogenic stress in Great Lakes coastal wetlands. The objective of the study described in this article was to characterize relationships between water chemistry and multiple classes of human activity (agriculture, population and development, point source pollution, and atmospheric deposition). We also evaluated the influence of geomorphology and biogeographic factors on stressor-water quality relationships. We collected water chemistry data from 98 coastal wetlands distributed along the United States shoreline of the Laurentian Great Lakes and GIS-based stressor data from the associated drainage basin to examine stressor-water quality relationships. The sampling captured broad ranges (1.5–2 orders of magnitude) in total phosphorus (TP), total nitrogen (TN), dissolved inorganic nitrogen (DIN), total suspended solids (TSS), chlorophyll a (Chl a), and chloride; concentrations were strongly correlated with stressor metrics. Hierarchical partitioning and all-subsets regression analyses were used to evaluate the independent influence of different stressor classes on water quality and to identify best predictive models. Results showed that all categories of stress influenced water quality and that the relative influence of different classes of disturbance varied among water quality parameters. Chloride exhibited the strongest relationships with stressors followed in order by TN, Chl a, TP, TSS, and DIN. In general, coarse scale classification of wetlands by morphology (three wetland classes: riverine, protected, open coastal) and biogeography (two ecoprovinces: Eastern Broadleaf Forest [EBF] and Laurentian Mixed Forest [LMF]) did not improve predictive models. This study provides strong evidence of the link between water chemistry and human stress in Great Lakes coastal wetlands and can be used to inform management efforts to improve water quality in Great Lakes coastal ecosystems.