scispace - formally typeset
T

Thomas Hickler

Researcher at Goethe University Frankfurt

Publications -  230
Citations -  21394

Thomas Hickler is an academic researcher from Goethe University Frankfurt. The author has contributed to research in topics: Climate change & Vegetation. The author has an hindex of 64, co-authored 218 publications receiving 17490 citations. Previous affiliations of Thomas Hickler include Lund University & American Museum of Natural History.

Papers
More filters
Journal ArticleDOI

TRY - a global database of plant traits

Jens Kattge, +136 more
TL;DR: TRY as discussed by the authors is a global database of plant traits, including morphological, anatomical, physiological, biochemical and phenological characteristics of plants and their organs, which can be used for a wide range of research from evolutionary biology, community and functional ecology to biogeography.
Journal ArticleDOI

Predicting global change impacts on plant species' distributions: Future challenges

TL;DR: This review proposes two main avenues to progress the understanding and prediction of the different processes occurring on the leading and trailing edge of the species' distribution in response to any global change phenomena and concludes with clear guidelines on how such modelling improvements will benefit conservation strategies in a changing world.
Journal ArticleDOI

TRY plant trait database : Enhanced coverage and open access

Jens Kattge, +754 more
TL;DR: The extent of the trait data compiled in TRY is evaluated and emerging patterns of data coverage and representativeness are analyzed to conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements.
Journal ArticleDOI

Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model

TL;DR: In this article, the LPJ-GUESS dynamic vegetation model was extended to include plant and soil N dynamics, and the implications of accounting for C-N interactions on predictions and performance of the model were analyzed.