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Kusch, E.

Publications and source records attributed to Kusch, E..

2 recordsLinked to original sources

MOSAIC: A Unified Trait Database to Complement Structured Population Models

O_LIThe ecological sciences have joined the big data revolution. However, despite exponential growth in data availability, broader interoperability amongst datasets is still needed to unlock the potential of open access. The interface of demography and functional traits is well-positioned to benefit from said interoperability. Trait-based ecological approaches have been criticised because of their inability to predict fitness components, the core of demography; likewise, demographic approaches are data-hungry, and so using traits as ecological shortcuts to understanding and forecasting population viability could offer great value. C_LIO_LIHere, we introduce MOSAIC, an open-access trait database that unlocks the demographic potential stored in the COMADRE, COMPADRE, and PADRINO open-access databases. MOSAIC data have been digitised and curated through a combination of existing datasets and additional taxonomic and/or trait records sourced from primary literature. In its first release, MOSAIC (v. 1.0.0) includes 14 trait fields for 300 animal and plant species: biomass, height, growth determination, regeneration, sexual dimorphism, mating system, hermaphrodism, sequential hermaphrodism, dispersal capacity, type of dispersal, mode of dispersal, dispersal classes, volancy, and aquatic habitat dependency. MOSAIC also includes species-level phylogenies for 1,359 species and population-specific climate data where locations are recorded. C_LIO_LIUsing MOSAIC, we highlight a taxonomic mismatch of widely used trait databases with existing structured population models. Despite millions of trait records available in open-access databases, taxonomic overlap between open-access demographic and trait databases is <5%. We identify where traits of interest to ecologists can benefit from database integration and start to quantify traits that are poorly quantified (e.g., growth determination, modularity). C_LIO_LIThe MOSAIC database evidences the importance of improving interoperability in open-access efforts in ecology as well as the need for complementary digitisation to fill targeted taxonomic gaps. In addition, MOSAIC highlights emerging challenges associated with the disparity between locations where different trait records are sourced. C_LI

ecology↗

Vegetation memory effects and their association with vegetation resilience in global drylands

AO_SCPLOWBSTRACTC_SCPLOWO_LIVegetation memory describes the effect of antecedent environmental and ecological conditions on the present ecosystem state and has been proposed as an important proxy for vegetation resilience. In particular, strong vegetation-memory effects have been identified in dryland regions, but the factors underlying the spatial patterns of vegetation memory remain unknown. C_LIO_LIWe aim to map the components and drivers of vegetation memory in dryland regions using state-of-the-art climate reanalysis data and refined approaches to identify vegetation-memory characteristics across dryland regions worldwide. C_LIO_LIUsing a framework which distinguishes between intrinsic and extrinsic ecological memory, we show that: (i) intrinsic memory is a much stronger component than extrinsic memory in the majority of dryland regions; and (ii) climate reanalysis data sets change the detection of extrinsic vegetation memory effects in some global dryland regions. C_LIO_LISynthesis. Our study offers a global picture of the vegetation response to two climate forcing variables using satellite data, information which is potentially relevant for mapping components and properties of vegetation responses worldwide. However, the large differences in the spatial patterns in intrinsic vegetation memory in our study compared to previous analyses show the overall sensitivity of this component in particular to the initial choice of extrinsic forcing variables. As a result, we caution against using the oversimplified link between intrinsic vegetation-memory and vegetation recovery rates at large spatial scales. C_LI

ecology↗