Coastal wetlands reduce the damaging effects of hurricanes on coastal communities. A regression model using 34 major US hurricanes since 1980 with the natural log of damage per unit gross domestic product in the hurricane swath as the dependent variable and the natural logs of wind speed and wetland area in the swath as the independent variables was highly significant and explained 60% of the variation in relative damages. A loss of 1 ha of wetland in the model corresponded to an average USD 33,000 (median = USD 5000) increase in storm damage from specific storms. Using this relationship, and taking into account the annual probability of hits by hurricanes of varying intensities, we mapped the annual value of coastal wetlands by 1 km x 1 km pixel and by state. The annual value ranged from USD 250 to USD 51,000 ha(-1) yr(-1), with a mean of USD 8240 ha(-1) yr(-1) (median = USD 3230 ha(-1) yr(-1)) significantly larger than previous estimates. Coastal wetlands in the US were estimated to currently provide USD 23.2 billion yr(-1) in storm protection services. Coastal wetlands function as valuable, selfmaintaining "horizontal levees" for storm protection, and also provide a host of other ecosystem services that vertical levees do not. Their restoration and preservation is an extremely cost-effective strategy for society.
Numerous technologies have been proposed as partial solutions to our declining fossil energy stocks. There is a significant need for consistent metrics to compare the desirability of different technologies. The ratio of energy produced to energy consumed by an energy production technology-known as the energy return on investment (EROI)-is an important first indicator of the potential benefits to society. However, EROI analysis lacks a consistent framework and has therefore yielded apparently conflicting results. In this article, we establish a theoretical framework for EROI analysis that encompasses the various methodologies extant in the literature. We establish variations of EROI analysis in two different dimensions based on the costs they include and their handling of nonenergy resources. We close by showing the implications of the different measures of EROI upon estimating the desirability of a technology as well as for estimating its ultimate net energy capacity.
Tick microbiomes may play an important role in pathogen transmission. However, the drivers of microbiome variation are poorly understood, and this limitation has impeded mechanistic understanding of the functions of microbial communities for pathogen acquisition. The goal of this research was to characterize the role of the blood meal host in structuring the microbiome of Ixodes scapularis, the primary vector of Lyme disease in the eastern United States, and to determine if ticks that fed from different host species harbor distinct bacterial communities. We performed high-throughput 16S rDNA amplicon sequencing on I. scapularis nymphs that fed as larvae from known wildlife hosts: raccoon, Virginia opossum, striped skunk, red squirrel or gray squirrel. Using Analysis of Similarity, we found significant differences in the abundance-weighted Unifrac distance matrix among ticks fed from different host species (p = 0.048) and a highly significant difference in the weighted and unweighted Unifrac matrices for individuals within species (p < 0.01). This finding of associations between the blood meal host and I. scapularis microbiome demonstrates that the blood meal host may be a driver of microbiome variation that should be accounted for in studies of pathogen acquisition by ticks.
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