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The biodiversity and high productivity of coastal terrestrial and aquatic habitats are the foundation for important benefits to human societies around the world. These globally distributed habitats need frequent and broad systematic assessments, but field surveys only cover a small fraction of these areas. Satellite-based sensors can repeatedly record the visible and near-infrared reflectance spectra that contain the absorption, scattering, and fluorescence signatures of functional phytoplankton groups, colored dissolved matter, and particulate matter near the surface ocean, and of biologically structured habitats (floating and emergent vegetation, benthic habitats like coral, seagrass, and algae). These measures can be incorporated into Essential Biodiversity Variables (EBVs), including the distribution, abundance, and traits of groups of species populations, and used to evaluate habitat fragmentation. However, current and planned satellites are not designed to observe the EBVs that change rapidly with extreme tides, salinity, temperatures, storms, pollution, or physical habitat destruction over scales relevant to human activity. Making these observations requires a new generation of satellite sensors able to sample with these combined characteristics: (1) spatial resolution on the order of 30 to 100-m pixels or smaller; (2) spectral resolution on the order of 5 nm in the visible and 10 nm in the short-wave infrared spectrum (or at least two or more bands at 1,030, 1,240, 1,630, 2,125, and/or 2,260 nm) for atmospheric correction and aquatic and vegetation assessments; (3) radiometric quality with signal to noise ratios (SNR) above 800 (relative to signal levels typical of the open ocean), 14-bit digitization, absolute radiometric calibration <2%, relative calibration of 0.2%, polarization sensitivity <1%, high radiometric stability and linearity, and operations designed to minimize sunglint; and (4) temporal resolution of hours to days. We refer to these combined specifications as H4 imaging. Enabling H4 imaging is vital for the conservation and management of global biodiversity and ecosystem services, including food provisioning and water security. An agile satellite in a 3-d repeat low-Earth orbit could sample 30-km swath images of several hundred coastal habitats daily. Nine H4 satellites would provide weekly coverage of global coastal zones. Such satellite constellations are now feasible and are used in various applications., (© 2018 The Authors Ecological Applications published by Wiley Periodicals, Inc. on behalf of Ecological Society of America.)

Disturbance is a key factor shaping species abundance and diversity in plant communities. Here, we use a mechanistic model of vegetation diversity to show that different strengths of r- and K-selection result in different disturbance-diversity relationships. R- and K-selection constrain the range of viable species through the colonization-competition tradeoff, with strong r-selection favoring colonizers and strong K-selection favoring competitors, but the level of disturbance also affects the success of species. This interplay among r- and K-selection and disturbance results in different shapes of disturbance-diversity relationships, with little variation of diversity with no r- and no K-selection, a decrease in diversity with r-selection with disturbance rate, an increase in diversity with K-selection, and a peak at intermediate values with strong r- and K-selection. We conclude that different disturbance-diversity relationships found in observations may reflect different intensities of r- and K-selection within communities, which should be inferable from broader observations of community composition and their ecophysiological trait ranges.

Dynamic Global Vegetation Models (DGVMs) typically abstract the immense diversity of vegetation forms and functioning into a relatively small set of predefined semiempirical Plant Functional Types (PFTs). There is growing evidence, however, from the field ecology community as well as from modelling studies that current PFT schemes may not adequately represent the observed variations in plant functional traits and their effect on ecosystem functioning. In this paper, we introduce the Jena Diversity DGVM (JeDi-DGVM) as a new approach to global vegetation modelling with a richer representation of functional diversity than traditional modelling approaches based on a small number of fixed PFTs. JeDi-DGVM simulates the performance of a large number of randomly-generated plant growth strategies (PGSs), each defined by a set of 15 trait parameters which characterize various aspects of plant functioning including carbon allocation, ecophysiology and phenology. Each trait parameter is involved in one or more functional tradeoffs. These trade-offs ultimately determine whether a PGS is able to survive under the climatic conditions in a given model grid cell and its performance relative to the other PGSs. The biogeochemical fluxes and land-surface properties of the individual PGSs are aggregated to the grid cell scale using a mass-based weighting scheme. Simulated global biogeochemical and biogeographical patterns are evaluated against a variety of field and satellite-based observations following a protocol established by the Carbon-Land Model Intercomparison Project. The land surface fluxes and vegetation structural properties are reasonably well simulated by JeDi-DGVM, and compare favorably with other state-of-the-art terrestrial biosphere models. This is despite the parameters describing the ecophysiological functioning and allometry of JeDi-DGVM plants evolving as a function of vegetation survival in a given climate, as opposed to typical approaches that fix land surface parameters derived from observational datasets for each PFT. The approach implemented here in JeDi-DGVM sets the foundation for future applications that will explore the impacts of explicitly resolving diverse plant communities, allowing for a more flexible temporal and spatial representation of the structure and function of the terrestrial biosphere. [ABSTRACT FROM AUTHOR]

The global geographic distribution of biodiversity and biomes is determined by speciesspecific physiological tolerances to climatic constraints. Current models implement empirical bioclimatic relationships to predict present-day vegetation patterns and to forecast biodiversity changes and biome shifts under climatic change. In this paper, we consider plant functional trade-offs and their interactions with climatic changes to forecast and explain biodiversity changes and biome shifts. The Jena Diversity model (JeDi) simulates plant survival according to essential plant functional trade-offs, including eco-physiological processes such as water uptake, pho tosynthesis, allocation, reproduction and phenology. We apply JeDi to quantify biodiversity changes and biome shifts between present-day and a range of possible future climates from two scenarios (A2 and B1) and seven global climate models using metrics of plant functional richness and functional identity. Our results show (i) a significant biodiversity loss in the tropics, (ii) an increase in biodiversity at mid and high latitudes, and (iii) a poleward shift of biomes. While these results are consistent with the findings of empirical approaches, we are able to explain them in terms of the plant functional trade-offs involved in the allocation, metabolic and reproduction strategies of plants. We conclude that general aspects of plant physiological tolerances can be derived from plant functional trade-offs, which may provide a useful process and trait-based alternative to bioclimatic relationships in order to address questions about the causes of biodiversity changes and biome shifts. [ABSTRACT FROM AUTHOR]