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Predicting biotic interactions and their variability in a changing environment.

ABSTRACT: Global environmental change is altering the patterns of biodiversity worldwide. Observation and theory suggest that species' distributions and abundances depend on a suite of processes, notably abiotic filtering and biotic interactions, both of which are constrained by species' phylogenetic history. Models predicting species distribution have historically mostly considered abiotic filtering and are only starting to integrate biotic interaction. However, using information on present interactions to forecast the future of biodiversity supposes that biotic interactions will not change when species are confronted with new environments. Using bacterial microcosms, we illustrate how biotic interactions can vary along an environmental gradient and how this variability can depend on the phylogenetic distance between interacting species.

SUBMITTER: Kadowaki K

PROVIDER: S-EPMC4892238 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

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Predicting biotic interactions and their variability in a changing environment.

Kadowaki Kohmei K Barbera Claire G CG Godsoe William W Delsuc Frédéric F Mouquet Nicolas N

Biology letters 20160501 5

Global environmental change is altering the patterns of biodiversity worldwide. Observation and theory suggest that species' distributions and abundances depend on a suite of processes, notably abiotic filtering and biotic interactions, both of which are constrained by species' phylogenetic history. Models predicting species distribution have historically mostly considered abiotic filtering and are only starting to integrate biotic interaction. However, using information on present interactions ...[more]

PMID: 27220858

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Project description:Coastal urban infrastructure and water management programs are vulnerable to the impacts of long-term hydroclimatic changes and to the flooding and physical destruction of disruptive hurricanes and storm surge. Water resilience or, inversely, vulnerability depends on design specifications of the storm and inundation, against which water infrastructure and environmental assets are planned and operated. These design attributes are commonly derived from statistical modeling of historical measurements. Here we argue for the need to carefully examine the approach and associated design vulnerability in coastal areas because of the future hydroclimatic changes and large variability at local coastal watersheds. This study first shows significant spatiotemporal variations of design storm in the Chesapeake Bay of the eastern U.S. Atlantic coast, where the low-frequency high-intensity precipitations vary differently to the tropical cyclones and local orographic effects. Average and gust wind speed exhibited much greater spatial but far less temporal variability than the precipitation. It is noteworthy that these local variabilities are not fully described by the regional gridded precipitation used in CMIP5 climate downscaling and by NOAA's regional design guide Atlas-14. Up to 46.4% error in the gridded precipitation for the calibration period 1950-1999 is further exacerbated in the future design values by the ensemble of 132 CMIP5 projections. The total model projection error (δM) up to -61.8% primarily comes from the precipitation regionalization (δ1), climate downscaling (δ2), and a fraction from empirical data modeling (δE). Thus, a post-bias correction technique is necessary. The bias-corrected design wind speed for 10-yr to 30-yr storms has small changes <20% by the year 2100, but contains large spatial variations even for stations of close proximity. Bias-corrected design precipitations are characteristic of large spatial variability and a notable increase of 2-5 year precipitation in the future along western shores of the Lower and Middle Chesapeake Bay. All these accounts point to the potential vulnerability of water infrastructure and water program in coastal areas, when the hydrological design basis using regional values fails to account for significant spatiotemporal precipitation variations in local coastal watersheds.

Dataset Information

Predicting biotic interactions and their variability in a changing environment.

Publications

Predicting biotic interactions and their variability in a changing environment.

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