The Plant Diversity Sampling Design for The National Ecological Observatory Network

The National Ecological Observatory Network (NEON) is designed to facilitate an understanding of the impact of environmental change on ecological systems. Observations of plant diversity—responsive to changes in climate, disturbance, and land use, and ecologically linked to soil, biogeochemistry, and organisms—result in NEON data products that cross a range of organizational levels. Collections include samples of plant tissue to enable investigations of genetics, plot-based observations of incidence and cover of native and non-native species, observations of plant functional traits, archived vouchers of plants, and remote sensing airborne observations. Spatially integrating many ecological observations allows a description of the relationship of plant diversity to climate, land use, organisms, and substrates. Repeating the observations over decades and across the United States will iteratively improve our understanding of those relationships and allow for the testing of system-level hypotheses as well as the development of predictions of future conditions

Megafauna extinction, tree species range reduction, and carbon storage in Amazonian forests

During the Late Pleistocene and early Holocene 59 species of South American megafauna went extinct. Their extinction potentially triggered population declines of large-seeded tree species dispersed by the large-bodied frugivores with which they co-evolved, a theory first proposed by Janzen and Martin (1982). We tested this hypothesis using species range maps for 257 South American tree species, comparing 63 species thought to be primarily distributed by megafauna with 194 distributed by other animals. We found a highly significant (p 95% following disperser extinction. A numerical gap dynamic simulations suggests that over a 10 000 yr period following the disperser extinctions, the average convex hull range size of large-seeded tree species decreased by ∼ 31%, while the estimated decrease in population size was ∼ 54%, indicating a likely greater decrease in species population size than indicated by the empirical range patterns. Finally, we found a positive correlation between seed size and wood density of animal-dispersed tree species implying that the Late Pleistocene and early Holocene megafaunal extinctions reduced carbon content in the Amazon by ∼ 1.5 ± 0.7%. In conclusion, we 1) provide some empirical evidence that megafauna distributed fruit species have a smaller mean range size than wind, water or other animal-dispersed species, 2) demonstrate mathematically that such range reductions are expected from megafauna extinctions ca 12 000 yr ago, and 3) illustrate that these extinctions may have reduced the Amazon's carbon storage capacity

Continental scale structuring of forest and soil diversity via functional traits.

Trait-based ecology claims to offer a mechanistic approach for explaining the drivers that structure biological diversity and predicting the responses of species, trophic interactions and ecosystems to environmental change. However, support for this claim is lacking across broad taxonomic groups. A framework for defining ecosystem processes in terms of the functional traits of their constituent taxa across large spatial scales is needed. Here, we provide a comprehensive assessment of the linkages between climate, plant traits and soil microbial traits at many sites spanning a broad latitudinal temperature gradient from tropical to subalpine forests. Our results show that temperature drives coordinated shifts in most plant and soil bacterial traits but these relationships are not observed for most fungal traits. Shifts in plant traits are mechanistically associated with soil bacterial functional traits related to carbon (C), nitrogen (N) and phosphorus (P) cycling, indicating that microbial processes are tightly linked to variation in plant traits that influence rates of ecosystem decomposition and nutrient cycling. Our results are consistent with hypotheses that diversity gradients reflect shifts in phenotypic optima signifying local temperature adaptation mediated by soil nutrient availability and metabolism. They underscore the importance of temperature in structuring the functional diversity of plants and soil microbes in forest ecosystems and how this is coupled to biogeochemical processes via functional traits

Biogeographic patterns of soil diazotrophic communities across six forests in North America.

Soil diazotrophs play important roles in ecosystem functioning by converting atmospheric N2 into biologically available ammonium. However, the diversity and distribution of soil diazotrophic communities in different forests and whether they follow biogeographic patterns similar to macroorganisms still remain unclear. By sequencing nifH gene amplicons, we surveyed the diversity, structure and biogeographic patterns of soil diazotrophic communities across six North American forests (126 nested samples). Our results showed that each forest harboured markedly different soil diazotrophic communities and that these communities followed traditional biogeographic patterns similar to plant and animal communities, including the taxa-area relationship (TAR) and latitudinal diversity gradient. Significantly higher community diversity and lower microbial spatial turnover rates (i.e. z-values) were found for rainforests (~0.06) than temperate forests (~0.1). The gradient pattern of TARs and community diversity was strongly correlated (r(2)  > 0.5) with latitude, annual mean temperature, plant species richness and precipitation, and weakly correlated (r(2)  < 0.25) with pH and soil moisture. This study suggests that even microbial subcommunities (e.g. soil diazotrophs) follow general biogeographic patterns (e.g. TAR, latitudinal diversity gradient), and indicates that the metabolic theory of ecology and habitat heterogeneity may be the major underlying ecological mechanisms shaping the biogeographic patterns of soil diazotrophic communities

The ecological causes of functional distinctiveness in communities

Recent work has shown that evaluating functional trait distinctiveness, the average trait distance of a species to other species in a community offers promising insights into biodiversity dynamics and ecosystem functioning. However, the ecological mechanisms underlying the emergence and persistence of functionally distinct species are poorly understood. Here, we address the issue by considering a heterogeneous fitness landscape whereby functional dimensions encompass peaks representing trait combinations yielding positive population growth rates in a community. We identify four ecological cases contributing to the emergence and persistence of functionally distinct species. First, environmental heterogeneity or alternative phenotypic designs can drive positive population growth of functionally distinct species. Second, sink populations with negative population growth can deviate from local fitness peaks and be functionally distinct. Third, species found at the margin of the fitness landscape can persist but be functionally distinct. Fourth, biotic interactions (positive or negative) can dynamically alter the fitness landscape. We offer examples of these four cases and guidelines to distinguish between them. In addition to these deterministic processes, we explore how stochastic dispersal limitation can yield functional distinctiveness. Our framework offers a novel perspective on the relationship between fitness landscape heterogeneity and the functional composition of ecological assemblages

Sizing Up Allometric Scaling Theory

Metabolic rate, heart rate, lifespan, and many other physiological properties vary with body mass in systematic and interrelated ways. Present empirical data suggest that these scaling relationships take the form of power laws with exponents that are simple multiples of one quarter. A compelling explanation of this observation was put forward a decade ago by West, Brown, and Enquist (WBE). Their framework elucidates the link between metabolic rate and body mass by focusing on the dynamics and structure of resource distribution networks—the cardiovascular system in the case of mammals. Within this framework the WBE model is based on eight assumptions from which it derives the well-known observed scaling exponent of 3/4. In this paper we clarify that this result only holds in the limit of infinite network size (body mass) and that the actual exponent predicted by the model depends on the sizes of the organisms being studied. Failure to clarify and to explore the nature of this approximation has led to debates about the WBE model that were at cross purposes. We compute analytical expressions for the finite-size corrections to the 3/4 exponent, resulting in a spectrum of scaling exponents as a function of absolute network size. When accounting for these corrections over a size range spanning the eight orders of magnitude observed in mammals, the WBE model predicts a scaling exponent of 0.81, seemingly at odds with data. We then proceed to study the sensitivity of the scaling exponent with respect to variations in several assumptions that underlie the WBE model, always in the context of finite-size corrections. Here too, the trends we derive from the model seem at odds with trends detectable in empirical data. Our work illustrates the utility of the WBE framework in reasoning about allometric scaling, while at the same time suggesting that the current canonical model may need amendments to bring its predictions fully in line with available datasets

The taxonomic name resolution service : an online tool for automated standardization of plant names

© The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in BMC Bioinformatics 14 (2013): 16, doi:10.1186/1471-2105-14-16.The digitization of biodiversity data is leading to the widespread application of taxon names that are superfluous, ambiguous or incorrect, resulting in mismatched records and inflated species numbers. The ultimate consequences of misspelled names and bad taxonomy are erroneous scientific conclusions and faulty policy decisions. The lack of tools for correcting this ‘names problem’ has become a fundamental obstacle to integrating disparate data sources and advancing the progress of biodiversity science. The TNRS, or Taxonomic Name Resolution Service, is an online application for automated and user-supervised standardization of plant scientific names. The TNRS builds upon and extends existing open-source applications for name parsing and fuzzy matching. Names are standardized against multiple reference taxonomies, including the Missouri Botanical Garden's Tropicos database. Capable of processing thousands of names in a single operation, the TNRS parses and corrects misspelled names and authorities, standardizes variant spellings, and converts nomenclatural synonyms to accepted names. Family names can be included to increase match accuracy and resolve many types of homonyms. Partial matching of higher taxa combined with extraction of annotations, accession numbers and morphospecies allows the TNRS to standardize taxonomy across a broad range of active and legacy datasets. We show how the TNRS can resolve many forms of taxonomic semantic heterogeneity, correct spelling errors and eliminate spurious names. As a result, the TNRS can aid the integration of disparate biological datasets. Although the TNRS was developed to aid in standardizing plant names, its underlying algorithms and design can be extended to all organisms and nomenclatural codes. The TNRS is accessible via a web interface at http://tnrs.iplantcollaborative.org/ webcite and as a RESTful web service and application programming interface. Source code is available at https://github.com/iPlantCollaborativeOpenSource/TNRS/ webcite.BJE was supported by NSF grant DBI 0850373 and TR by CSIRO Marine and Atmospheric Research, Australia,. BB and BJE acknowledge early financial support from Conservation International and TEAM who funded the development of early prototypes of taxonomic name resolution. The iPlant Collaborative (http://www.iplantcollaborative.org) is funded by a grant from the National Science Foundation (#DBI-0735191)

In Vivo and Ex Vivo Evaluation of L-Type Calcium Channel Blockers on Acid β-Glucosidase in Gaucher Disease Mouse Models

Gaucher disease is a lysosomal storage disease caused by mutations in acid β-glucosidase (GCase) leading to defective hydrolysis and accumulation of its substrates. Two L-type calcium channel (LTCC) blockers—verapamil and diltiazem—have been reported to modulate endoplasmic reticulum (ER) folding, trafficking, and activity of GCase in human Gaucher disease fibroblasts. Similarly, these LTCC blockers were tested with cultured skin fibroblasts from homozygous point-mutated GCase mice (V394L, D409H, D409V, and N370S) with the effect of enhancing of GCase activity. Correspondingly, diltiazem increased GCase protein and facilitated GCase trafficking to the lysosomes of these cells. The in vivo effects of diltiazem on GCase were evaluated in mice homozygous wild-type (WT), V394L and D409H. In D409H homozygotes diltiazem (10 mg/kg/d via drinking water or 50–200 mg/kg/d intraperitoneally) had minor effects on increasing GCase activity in brain and liver (1.2-fold). Diltiazem treatment (10 mg/kg/d) had essentially no effect on WT and V394L GCase protein or activity levels (<1.2-fold) in liver. These results show that LTCC blockers had the ex vivo effects of increasing GCase activity and protein in the mouse fibroblasts, but these effects did not translate into similar changes in vivo even at very high drug doses