Search

Coastal wetland responses to sea-level rise are greatly influenced by biogeomorphic processes that affect wetland surface elevation. Small changes in elevation relative to sea level can lead to comparatively large changes in ecosystem structure, function, and stability. The surface elevation table-marker horizon (SET-MH) approach is being used globally to quantify the relative contributions of processes affecting wetland elevation change. Historically, SET-MH measurements have been obtained at local scales to address site-specific research questions. However, in the face of accelerated sea-level rise, there is an increasing need for elevation change network data that can be incorporated into regional ecological models and vulnerability assessments. In particular, there is a need for long-term, high-temporal resolution data that are strategically distributed across ecologically-relevant abiotic gradients. Here, we quantify the distribution of SET-MH stations along the northern Gulf of Mexico coast (USA) across political boundaries (states), wetland habitats, and ecologically-relevant abiotic gradients (i.e., gradients in temperature, precipitation, elevation, and relative sea-level rise). Our analyses identify areas with high SET-MH station densities as well as areas with notable gaps. Salt marshes, intermediate elevations, and colder areas with high rainfall have a high number of stations, while salt flat ecosystems, certain elevation zones, the mangrove-marsh ecotone, and hypersaline coastal areas with low rainfall have fewer stations. Due to rapid rates of wetland loss and relative sea-level rise, the state of Louisiana has the most extensive SET-MH station network in the region, and we provide several recent examples where data from Louisiana’s network have been used to assess and compare wetland vulnerability to sea-level rise. Our findings represent the first attempt to examine spatial gaps in SET-MH coverage across abiotic gradients. Our analyses can be used to transform a broadly disseminated and unplanned collection of SET-MH stations into a coordinated and strategic regional network. This regional network would provide data for predicting and preparing for the responses of coastal wetlands to accelerated sea-level rise and other aspects of global change. [ABSTRACT FROM AUTHOR]

US national parks are challenged by climate and other forms of broad-scale environmental change that operate beyond administrative boundaries and in some instances are occurring at especially rapid rates. Here, we evaluate the climate change exposure of 289 natural resource parks administered by the US National Park Service (NPS), and ask which are presently (past 10 to 30 years) experiencing extreme (<5th percentile or >95th percentile) climates relative to their 1901–2012 historical range of variability (HRV). We consider parks in a landscape context (including surrounding 30 km) and evaluate both mean and inter-annual variation in 25 biologically relevant climate variables related to temperature, precipitation, frost and wet day frequencies, vapor pressure, cloud cover, and seasonality. We also consider sensitivity of findings to the moving time window of analysis (10, 20, and 30 year windows). Results show that parks are overwhelmingly at the extreme warm end of historical temperature distributions and this is true for several variables (e.g., annual mean temperature, minimum temperature of the coldest month, mean temperature of the warmest quarter). Precipitation and other moisture patterns are geographically more heterogeneous across parks and show greater variation among variables. Across climate variables, recent inter-annual variation is generally well within the range of variability observed since 1901. Moving window size has a measureable effect on these estimates, but parks with extreme climates also tend to exhibit low sensitivity to the time window of analysis. We highlight particular parks that illustrate different extremes and may facilitate understanding responses of park resources to ongoing climate change. We conclude with discussion of how results relate to anticipated future changes in climate, as well as how they can inform NPS and neighboring land management and planning in a new era of change. [ABSTRACT FROM AUTHOR]

Local and regional-scale knowledge of climate change is needed to model ecosystem responses, assess vulnerabilities and devise effective adaptation strategies. High-resolution gridded historical climate (GHC) products address this need, but come with multiple sources of uncertainty that are typically not well understood by data users. To better understand this uncertainty in a region with a complex climatology, we conducted a ground-truthing analysis of two 4 km GHC temperature products (PRISM and NRCC) for the US Northeast using 51 Cooperative Network (COOP) weather stations utilized by both GHC products. We estimated GHC prediction error for monthly temperature means and trends (1980–2009) across the US Northeast and evaluated any landscape effects (e.g., elevation, distance from coast) on those prediction errors. Results indicated that station-based prediction errors for the two GHC products were similar in magnitude, but on average, the NRCC product predicted cooler than observed temperature means and trends, while PRISM was cooler for means and warmer for trends. We found no evidence for systematic sources of uncertainty across the US Northeast, although errors were largest at high elevations. Errors in the coarse-scale (4 km) digital elevation models used by each product were correlated with temperature prediction errors, more so for NRCC than PRISM. In summary, uncertainty in spatial climate data has many sources and we recommend that data users develop an understanding of uncertainty at the appropriate scales for their purposes. To this end, we demonstrate a simple method for utilizing weather stations to assess local GHC uncertainty and inform decisions among alternative GHC products. [ABSTRACT FROM AUTHOR]

Human mortality exhibits a strong seasonal pattern with deaths in winter far exceeding those in the summer. While the pattern itself is clear, there have been very few studies examining whether the magnitude or timing of seasonal mortality varies considerably across space. Thus, the goal of this study is to conduct a comprehensive geographic analysis of seasonal mortality across the United States and to uncover systematic regional differences in such mortality. Unique seasonal mortality curves were created for 28 metropolitan statistical areas across the United States, and the amplitude and timing of mortality peaks were determined. The findings here indicate that the seasonality of mortality exhibits strong spatial variation with the largest seasonal mortality amplitudes found in the southwestern United States and the smallest in the North, along with South Florida. In addition, there were strong intra-regional similarities that exist among the examined cities, implying that environmental factors are more important than social factors in determining seasonal mortality response. This work begins to fill a large gap within the scientific literature concerning the geographic variation and underlying causes of seasonal mortality across the United States. [ABSTRACT FROM AUTHOR]

The global trade of goods is associated with a virtual transfer of the water required for their production. The way changes in trade affect the virtual redistribution of freshwater resources has been recently documented through the analysis of the virtual water network. It is, however, unclear how these changes are contributed by different types of products and regions of the world. Here we show how the global patterns of virtual water transport are contributed by the trade of different commodity types, including plant, animal, luxury (e.g., coffee, tea, and alcohol), and other products. Major contributors to the virtual water network exhibit different trade patterns with regard to these commodity types. The net importers rely on the supply of virtual water from a small percentage of the global population. However, discrepancies exist among the different commodity networks. While the total virtual water flux through the network has increased between 1986 and 2010, the proportions associated with the four commodity groups have remained relatively stable. However, some of the major players have shown significant changes in the virtual water imports and exports associated with those commodity groups. For instance, China has switched from being a net exporter of virtual water associated with other products (non-edible plant and animal products typically used for manufacturing) to being the largest importer, accounting for 31% of the total water virtually transported with these products. Conversely, in the case of The United states of America, the commodity proportions have remained overall unchanged throughout the study period: the virtual water exports from The United States of America are dominated by plant products, whereas the imports are comprised mainly of animal and luxury products. [ABSTRACT FROM AUTHOR]

Bacteria from the genus Polaromonas are dominant phylotypes in clone libraries and culture collections from polar and high-elevation environments. Although Polaromonas has been found on six continents, we do not know if the same phylotypes exist in all locations or if they exhibit genetic isolation by distance patterns. To examine their biogeographic distribution, we analyzed all available, long-read 16S rRNA gene sequences of Polaromonas phylotypes from glacial and periglacial environments across the globe. Using genetic isolation by geographic distance analyses, including Mantel tests and Mantel correlograms, we found that Polaromonas phylotypes are globally distributed showing weak isolation by distance patterns at global scales. More focused analyses using discrete, equally sampled distances classes, revealed that only two distance classes (out of 12 total) showed significant spatial structuring. Overall, our analyses show that most Polaromonas phylotypes are truly globally distributed, but that some, as yet unknown, environmental variable may be selecting for unique phylotypes at a minority of our global sites. Analyses of aerobiological and genomic data suggest that Polaromonas phylotypes are globally distributed as dormant cells through high-elevation air currents; Polaromonas phylotypes are common in air and snow samples from high altitudes, and a glacial-ice metagenome and the two sequenced Polaromonas genomes contain the gene hipA, suggesting that Polaromonas can form dormant cells. [ABSTRACT FROM AUTHOR]