Risk Factor Interactions, Non-High-Density Lipoprotein Cholesterol to Apolipoprotein B Ratio, and Severity of Coronary Arteriosclerosis in South Asian Individuals: An Observational Cohort Study.

Background South Asian individuals are at higher risk for arteriosclerotic cardiovascular disease and diabetes. The factors associated with arteriosclerotic cardiovascular disease severity and their interactions are unknown. Methods and Results This is a retrospective cohort study of the first 1162 South Asian participants enrolled in the South Asian Heart Center's AIM to Prevent Program who completed noncontrast coronary computed tomography scans. Using machine-learning algorithms, we identified and modeled the interaction of predictor variables with coronary artery calcification (CAC) severity in South Asian individuals. Anthropometric, laboratory, demographic, and lifestyle predictor variables were analyzed using continuous boosted regression trees to model the relationship with and in between predictor variables and CAC. Participants with CAC were older, predominately men, had smoking history, had personal histories of diabetes, hypertension, and hypercholesterolemia, and had family histories of coronary artery disease. Insulin, body mass index, blood pressure, fasting blood sugar, hemoglobin A1c, and waist-to-height ratio were associated with CAC but not low-density lipoprotein cholesterol or lipoprotein (a). The arteriosclerotic cardiovascular disease score failed to classify individuals. Only age, body mass index, non-high-density lipoprotein cholesterol/apolipoprotein B ratio, smoking risk, fasting blood sugar, and diastolic blood pressure were predictive, explaining 30.3% of CAC severity. A non-high-density lipoprotein cholesterol/apolipoprotein B ratio of 1.4 or less markedly increased coronary calcification. Conclusions Our findings highlight factors associated with dysmetabolism and cholesterol-depleted non-high-density lipoprotein cholesterol particles with coronary arteriosclerosis, possibly explaining the dual epidemics of diabetes and arteriosclerotic cardiovascular disease in this population. Markers of glucose dysmetabolism and the non-high-density lipoprotein cholesterol to apolipoprotein B ratio should become the focus of assessment for cardiovascular risk in South Asian individuals, with prevention strategies directed at improving glucose metabolic health.

Successful conservation of global waterbird populations depends on effective governance.

Understanding global patterns of biodiversity change is crucial for conservation research, policies and practices. However, for most ecosystems, the lack of systematically collected data at a global level limits our understanding of biodiversity changes and their local-scale drivers. Here we address this challenge by focusing on wetlands, which are among the most biodiverse and productive of any environments and which provide essential ecosystem services, but are also amongst the most seriously threatened ecosystems. Using birds as an indicator taxon of wetland biodiversity, we model time-series abundance data for 461 waterbird species at 25,769 survey sites across the globe. We show that the strongest predictor of changes in waterbird abundance, and of conservation efforts having beneficial effects, is the effective governance of a country. In areas in which governance is on average less effective, such as western and central Asia, sub-Saharan Africa and South America, waterbird declines are particularly pronounced; a higher protected area coverage of wetland environments facilitates waterbird increases, but only in countries with more effective governance. Our findings highlight that sociopolitical instability can lead to biodiversity loss and undermine the benefit of existing conservation efforts, such as the expansion of protected area coverage. Furthermore, data deficiencies in areas with less effective governance could lead to underestimations of the extent of the current biodiversity crisis.

Making spatial prioritizations robust to climate change uncertainties: a case study with North American birds.

Spatial prioritizations are essential tools for conserving biodiversity in the face of accelerating climate change. Uncertainty about species' responses to changing climates can complicate prioritization efforts, however, and delay conservation investment. In an effort to facilitate decision-making, we identified three hypotheses about species' potential responses to climate change based on distinct biological assumptions related to niche flexibility and colonization ability. Using 314 species of North American birds as a test case, we tuned separate spatial prioritizations to each hypothesis and assessed the degree to which assumptions about biological responses affected the perceived conservation value of the landscape and prospects for individual taxa. We also developed a bet-hedging prioritization to minimize the chance that incorrect assumptions would lead to valuable landscapes and species being overlooked in multispecies prioritizations. Collectively, these analyses help to quantify the sensitivity of spatial prioritizations to different assumptions about species' responses to climate change and provide a framework for enabling efficient conservation investment despite substantial biological uncertainty.

Conservation Status of North American Birds in the Face of Future Climate Change.

Human-induced climate change is increasingly recognized as a fundamental driver of biological processes and patterns. Historic climate change is known to have caused shifts in the geographic ranges of many taxa and future climate change is expected to result in even greater redistributions of species. As a result, predicting the impact of climate change on future patterns of biodiversity will greatly aid conservation planning. Using the North American Breeding Bird Survey and Audubon Christmas Bird Count, two of the most comprehensive continental datasets of vertebrates in the world, and correlative distribution modeling, we assessed geographic range shifts for 588 North American bird species during both the breeding and non-breeding seasons under a range of future emission scenarios (SRES A2, A1B, B2) through the end of the century. Here we show that 314 species (53%) are projected to lose more than half of their current geographic range across three scenarios of climate change through the end of the century. For 126 species, loss occurs without concomitant range expansion; whereas for 188 species, loss is coupled with potential to colonize new replacement range. We found no strong associations between projected climate sensitivities and existing conservation prioritizations. Moreover, species responses were not clearly associated with habitat affinities, migration strategies, or climate change scenarios. Our results demonstrate the need to include climate sensitivity into current conservation planning and to develop adaptive management strategies that accommodate shrinking and shifting geographic ranges. The persistence of many North American birds will depend on their ability to colonize climatically suitable areas outside of current ranges and management actions that target climate adaptation.

Using community-level metrics to monitor the effects of marine protected areas on biodiversity.

Marine protected areas (MPAs) are used to protect species, communities, and their associated habitats, among other goals. Measuring MPA efficacy can be challenging, however, particularly when considering responses at the community level. We gathered 36 abundance and 14 biomass data sets on fish assemblages and used meta-analysis to evaluate the ability of 22 distinct community diversity metrics to detect differences in community structure between MPAs and nearby control sites. We also considered the effects of 6 covariates-MPA size and age, MPA size and age interaction, latitude, total species richness, and level of protection-on each metric. Some common metrics, such as species richness and Shannon diversity, did not differ consistently between MPA and control sites, whereas other metrics, such as total abundance and biomass, were consistently different across studies. Metric responses derived from the biomass data sets were more consistent than those based on the abundance data sets, suggesting that community-level biomass differs more predictably than abundance between MPA and control sites. Covariate analyses indicated that level of protection, latitude, MPA size, and the interaction between MPA size and age affect metric performance. These results highlight a handful of metrics, several of which are little known, that could be used to meet the increasing demand for community-level indicators of MPA effectiveness.

Global patterns of marine mammal, seabird, and sea turtle bycatch reveal taxa-specific and cumulative megafauna hotspots.

Recent research on ocean health has found large predator abundance to be a key element of ocean condition. Fisheries can impact large predator abundance directly through targeted capture and indirectly through incidental capture of nontarget species or bycatch. However, measures of the global nature of bycatch are lacking for air-breathing megafauna. We fill this knowledge gap and present a synoptic global assessment of the distribution and intensity of bycatch of seabirds, marine mammals, and sea turtles based on empirical data from the three most commonly used types of fishing gears worldwide. We identify taxa-specific hotspots of bycatch intensity and find evidence of cumulative impacts across fishing fleets and gears. This global map of bycatch illustrates where data are particularly scarce--in coastal and small-scale fisheries and ocean regions that support developed industrial fisheries and millions of small-scale fishers--and identifies fishing areas where, given the evidence of cumulative hotspots across gear and taxa, traditional species or gear-specific bycatch management and mitigation efforts may be necessary but not sufficient. Given the global distribution of bycatch and the mitigation success achieved by some fleets, the reduction of air-breathing megafauna bycatch is both an urgent and achievable conservation priority.

Prediction of fishing effort distributions using boosted regression trees.

Concerns about bycatch of protected species have become a dominant factor shaping fisheries management. However, efforts to mitigate bycatch are often hindered by a lack of data on the distributions of fishing effort and protected species. One approach to overcoming this problem has been to overlay the distribution of past fishing effort with known locations of protected species, often obtained through satellite telemetry and occurrence data, to identify potential bycatch hotspots. This approach, however, generates static bycatch risk maps, calling into question their ability to forecast into the future, particularly when dealing with spatiotemporally dynamic fisheries and highly migratory bycatch species. In this study, we use boosted regression trees to model the spatiotemporal distribution of fishing effort for two distinct fisheries in the North Pacific Ocean, the albacore (Thunnus alalunga) troll fishery and the California drift gillnet fishery that targets swordfish (Xiphias gladius). Our results suggest that it is possible to accurately predict fishing effort using < 10 readily available predictor variables (cross-validated correlations between model predictions and observed data -0.6). Although the two fisheries are quite different in their gears and fishing areas, their respective models had high predictive ability, even when input data sets were restricted to a fraction of the full time series. The implications for conservation and management are encouraging: Across a range of target species, fishing methods, and spatial scales, even a relatively short time series of fisheries data may suffice to accurately predict the location of fishing effort into the future. In combination with species distribution modeling of bycatch species, this approach holds promise as a mitigation tool when observer data are limited. Even in data-rich regions, modeling fishing effort and bycatch may provide more accurate estimates of bycatch risk than partial observer coverage for fisheries and bycatch species that are heavily influenced by dynamic oceanographic conditions.

Multitaxonomic diversity patterns along a desert riparian-upland gradient.

Riparian areas are noted for their high biodiversity, but this has rarely been tested across a wide range of taxonomic groups. We set out to describe species richness, species abundance, and community similarity patterns for 11 taxonomic groups (forbs & grasses, shrubs, trees, solpugids, spiders, scarab beetles, butterflies, lizards, birds, rodents, and mammalian carnivores) individually and for all groups combined along a riparian-upland gradient in semiarid southeastern Arizona, USA. Additionally, we assessed whether biological characteristics could explain variation in diversity along the gradient using five traits (trophic level, body size, life span, thermoregulatory mechanism, and taxonomic affiliation). At the level of individual groups diversity patterns varied along the gradient, with some having greater richness and/or abundance in riparian zones whereas others were more diverse and/or abundant in upland zones. Across all taxa combined, riparian zones contained significantly more species than the uplands. Community similarity between riparian and upland zones was low, and beta diversity was significantly greater than expected for most taxonomic groups, though biological traits explained little variance in diversity along the gradient. These results indicate heterogeneity amongst taxa in how they respond to the factors that structure ecological communities in riparian landscapes. Nevertheless, across taxonomic groups the overall pattern is one of greater species richness and abundance in riparian zones, coupled with a distinct suite of species.

Mapping the bycatch seascape: multispecies and multi-scale spatial patterns of fisheries bycatch.

Fisheries bycatch is a worldwide conservation issue. Despite a growing awareness of bycatch problems in particular ocean regions, there have been few efforts to identify spatial patterns in bycatch events. Furthermore, many studies of fisheries bycatch have been myopic, focusing on a single species or a single region. Using a range of analytical approaches to identify spatial patterns in bycatch data, we demonstrate the utility and applications of area and point pattern analyses to single and multispecies bycatch seascapes of pelagic longline fisheries in the Atlantic and Pacific Oceans. We find clear evidence of spatial clustering within bycatch species in both ocean basins, both in terms of the underlying pattern of the locations of bycatch events relative to fishing locations and for areas of high bycatch rates. Furthermore, we find significant spatial overlap in the pattern of bycatch across species relative to the spatial distribution in fishing effort and target catch. These results point to the importance of considering spatial patterns of both single and multispecies bycatch to meet the ultimate goal of reducing bycatch encounters. These analyses also highlight the importance of considering bycatch relative to target catch as a way of identifying areas where fishing effort reduction may help to reduce multispecies bycatch with minimal impact on target catch.

Species abundance distributions: moving beyond single prediction theories to integration within an ecological framework.

Species abundance distributions (SADs) follow one of ecology's oldest and most universal laws--every community shows a hollow curve or hyperbolic shape on a histogram with many rare species and just a few common species. Here, we review theoretical, empirical and statistical developments in the study of SADs. Several key points emerge. (i) Literally dozens of models have been proposed to explain the hollow curve. Unfortunately, very few models are ever rejected, primarily because few theories make any predictions beyond the hollow-curve SAD itself. (ii) Interesting work has been performed both empirically and theoretically, which goes beyond the hollow-curve prediction to provide a rich variety of information about how SADs behave. These include the study of SADs along environmental gradients and theories that integrate SADs with other biodiversity patterns. Central to this body of work is an effort to move beyond treating the SAD in isolation and to integrate the SAD into its ecological context to enable making many predictions. (iii) Moving forward will entail understanding how sampling and scale affect SADs and developing statistical tools for describing and comparing SADs. We are optimistic that SADs can provide significant insights into basic and applied ecological science.