Range maps and species richness patterns: errors of commission and estimates of uncertainty

Range maps are often combined into “range overlap maps” to estimate spatial variation in species richness. Range maps are, in most cases, designed to represent a species’ maximum geographical extent and not patterns of occupancy within the range. As a consequence, range maps overestimate occupancy by presenting false occupancy (errors of commission) within the interior of the range. To assess the implications of errors of commission when developing and applying range overlap maps, we used neutral landscapes to simulate range maps and patterns of occupancy within ranges. We explored several scenarios based on combinations of six parameters defining biogeographical and cartographic factors typically encountered by investigators. Our results suggest that, in general, uncertainty is lowest when map resolutions are moderately fine, the majority of species have geographically restricted ranges, species occur throughout their range, patterns of occupancy within the range are not correlated among species, and geographically local and widespread species tend to occupy different regions. Several of these outcomes are associated with broad geographical extents, the scale at which range overlap maps are typically applied. Thus, under most circumstances, reasonably accurate and precise representation of species richness patterns can be achieved. However, these representations can be improved by enhancing occupancy data for widespread species – a primary source of uncertainty – and selecting a map resolution that captures relevant biological and environmental heterogeneity. Hence, by determining where a study is situated within the scenarios examined in our simulations, uncertainty and its sources and implications can be ascertained. With this knowledge, research goals, methods, and data sources can be reassessed and refined and, in the end, conclusions and recommendations can be qualified. Alternatively, unique regional, taxonomic, or cartographic factors could be included in future simulations to provide direct assessments of uncertainty.     

Development of a RIVPACS-type predictive model for bioassessment of wadeable streams in Wyoming

RIVPACS models produce a community-level measure of biological condition known as O/E, which is derived from a comparison of the observed (O) biota with those expected (E) to occur in the absence of anthropogenic stress. We used benthic macroinvertebrate and environmental data collected at 925 stream monitoring stations, from 1993 to 2001, to develop, validate, and apply a RIVPACS model to assess the biological condition of wadeable streams in Wyoming. From this dataset, 296 samples were identified as reference, 157 of which were used to calibrate the model, 46 to validate it, and 93 to examine temporal variability in reference site O/E-values. We used cluster analyses to group the model development reference sites into biologically similar classes of streams and multiple discriminant function analysis to determine which environmental variables best discriminated among reference groups. A suite of 14 categorical and continuous environmental variables best discriminated among 15 reference groups and explained a large proportion of the natural variability in biota within the reference dataset. Eleven of the predictor variables were derived from GIS. As expected, mean O/E-values for reference sites used in model development and validation were near unity and statistically similar. Temporal variability in O/E-values for reference sites was low. Test site values ranged from 0 to 1.45 (mean = 0.73). The model was accurate in both space and time and precise enough (S.D. of O/E-values for calibration data = 0.17) to detect modest alteration in biota associated with anthropogenic stressors. Our model was comparable in performance to other RIVPACS models developed in the United States and can produce effective assessments of biological condition over a broad, ecologically diverse region. We also provide convincing evidence that RIVPACS models can be developed primarily with GIS-based predictor variables. This framework not only simplifies the extraction of predictor variable information while potentially reducing expenditures of time and money in the collection of predictor variable information, but opens the door for development and/or application of RIVPACS models in regions where there is a paucity of local-scale, abiotic information.     

Individualistic species limitations of climate‐induced range expansions generated by meso‐scale dispersal barriers

Aim Evidence indicates that species are responding to climate change through distributional range shifts that track suitable climatic conditions. We aim to elucidate the role of meso‐scale dispersal barriers in climate‐tracking responses. Location South coast of England (the English Channel). Methods Historical distributional data of four intertidal invertebrate species were logistically regressed against sea surface temperature (SST) to determine a climate envelope. This envelope was used to estimate the expected climate‐tracking response since 1990 along the coast, which was compared with observed range expansions. A hydrodynamic modelling approach was used to identify dispersal barriers and explore disparities between expected and observed climate tracking. Results Range shifts detected by field survey over the past 20 years were less than those predicted by the changes that have occurred in SST. Hydrodynamic model simulations indicated that physical barriers produced by complex tidal currents have variably restricted dispersal of pelagic larvae amongst the four species. Main conclusions We provide the first evidence that meso‐scale hydrodynamic barriers have limited climate‐induced range shifts and demonstrate that life history traits affect the ability of species to overcome such barriers. This suggests that current forecasts may be flawed, both by overestimating range shifts and by underestimating climatic tolerances of species. This has implications for our understanding of climate change impacts on global biodiversity.     

The use of phylogeny to interpret cross-cultural patterns in plant use and guide medicinal plant discovery: an example from Pterocarpus (Leguminosae)

Background

The study of traditional knowledge of medicinal plants has led to discoveries that have helped combat diseases and improve healthcare. However, the development of quantitative measures that can assist our quest for new medicinal plants has not greatly advanced in recent years. Phylogenetic tools have entered many scientific fields in the last two decades to provide explanatory power, but have been overlooked in ethnomedicinal studies. Several studies show that medicinal properties are not randomly distributed in plant phylogenies, suggesting that phylogeny shapes ethnobotanical use. Nevertheless, empirical studies that explicitly combine ethnobotanical and phylogenetic information are scarce.

Methodology/Principal Findings

In this study, we borrowed tools from community ecology phylogenetics to quantify significance of phylogenetic signal in medicinal properties in plants and identify nodes on phylogenies with high bioscreening potential. To do this, we produced an ethnomedicinal review from extensive literature research and a multi-locus phylogenetic hypothesis for the pantropical genus Pterocarpus (Leguminosae: Papilionoideae). We demonstrate that species used to treat a certain conditions, such as malaria, are significantly phylogenetically clumped and we highlight nodes in the phylogeny that are significantly overabundant in species used to treat certain conditions. These cross-cultural patterns in ethnomedicinal usage in Pterocarpus are interpreted in the light of phylogenetic relationships.

Conclusions/Significance

This study provides techniques that enable the application of phylogenies in bioscreening, but also sheds light on the processes that shape cross-cultural ethnomedicinal patterns. This community phylogenetic approach demonstrates that similar ethnobotanical uses can arise in parallel in different areas where related plants are available. With a vast amount of ethnomedicinal and phylogenetic information available, we predict that this field, after further refinement of the techniques, will expand into similar research areas, such as pest management or the search for bioactive plant-based compounds.     

Dominance, biomass and extinction resistance determine the consequences of biodiversity loss for multiple coastal ecosystem processes

Key ecosystem processes such as carbon and nutrient cycling could be deteriorating as a result of biodiversity loss. However, currently we lack the ability to predict the consequences of realistic species loss on ecosystem processes. The aim of this study was to test whether species contributions to community biomass can be used as surrogate measures of their contribution to ecosystem processes. These were gross community productivity in a salt marsh plant assemblage and an intertidal macroalgae assemblage; community clearance of microalgae in sessile suspension feeding invertebrate assemblage; and nutrient uptake in an intertidal macroalgae assemblage. We conducted a series of biodiversity manipulations that represented realistic species extinction sequences in each of the three contrasting assemblages. Species were removed in a subtractive fashion so that biomass was allowed to vary with each species removal, and key ecosystem processes were measured at each stage of community disassembly. The functional contribution of species was directly proportional to their contribution to community biomass in a 1:1 ratio, a relationship that was consistent across three contrasting marine ecosystems and three ecosystem processes. This suggests that the biomass contributed by a species to an assemblage can be used to approximately predict the proportional decline in an ecosystem process when that species is lost. Such predictions represent "worst case scenarios" because, over time, extinction resilient species can offset the loss of biomass associated with the extinction of competitors. We also modelled a "best case scenario" that accounts for compensatory responses by the extant species with the highest per capita contribution to ecosystem processes. These worst and best case scenarios could be used to predict the minimum and maximum species required to sustain threshold values of ecosystem processes in the future.     

Epigenetic changes with dietary soy in cynomolgus monkeys

Nutritional interventions are important alternatives for reducing the prevalence of many chronic diseases. Soy is a good source of protein that contains isoflavones, including genistein and daidzein, and may alter the risk of obesity, Type 2 diabetes, osteoporosis, cardiovascular disease, and reproductive cancers. We have shown previously in nonhuman primates that soy protein containing isoflavones leads to improved body weight, insulin sensitivity, lipid profiles, and atherosclerosis compared to protein without soy isoflavones (casein), and does not increase the risk of cancer. Since genistein has been shown to alter DNA methylation, we compared the methylation profiles of cynomolgus monkeys, from multiple tissues, eating two high-fat, typical American diets (TAD) with similar macronutrient contents, with or without soy protein. DNA methylation status was successfully determined for 80.6% of the probes in at least one tissue using Illumina's HumanMethylation27 BeadChip. Overall methylation increased in liver and muscle tissue when monkeys switched from the TAD-soy to the TAD-casein diets. Genes involved in epigenetic processes, specifically homeobox genes (HOXA5, HOXA11, and HOXB1), and ABCG5 were among those that changed between diets. These data support the use of the HumanMethylation27 BeadChip in cynomolgus monkeys and identify epigenetic changes associated with dietary interventions with soy protein that may potentially affect the etiology of complex diseases.