Showing papers by "Steven I. Higgins published in 2011"
Max Planck Society1, National University of Cordoba2, Centre national de la recherche scientifique3, Macquarie University4, University of Paris-Sud5, University of Minnesota6, University of Western Sydney7, VU University Amsterdam8, University of Arizona9, University of California, Berkeley10, University of Guelph11, Australian National University12, University of Innsbruck13, University of Leeds14, University of Groningen15, Universidade Federal do Rio Grande do Sul16, University of Cape Town17, University of Wollongong18, New Jersey Institute of Technology19, Centro Agronómico Tropical de Investigación y Enseñanza20, Lawrence Berkeley National Laboratory21, University of Alaska Fairbanks22, University of Cambridge23, Kansas State University24, Helmholtz Centre for Environmental Research - UFZ25, Arizona State University26, University of Giessen27, Autonomous University of Barcelona28, University of Maryland, College Park29, Universidad del Tolima30, University of São Paulo31, University of La Réunion32, University of York33, University of Sydney34, Harvard University35, Goethe University Frankfurt36, University of Sheffield37, University of Ulm38, State University of Campinas39, Kenyon College40, Royal Botanic Gardens41, University of Florida42, University of Oldenburg43, University of Nebraska–Lincoln44, Tohoku University45, Northern Arizona University46, University of Wisconsin–Eau Claire47, Naturalis48, James Cook University49, Institut national de la recherche agronomique50, Newcastle University51, University of New South Wales52, Leipzig University53, Columbia University54, Estonian University of Life Sciences55, Polish Academy of Sciences56, Moscow State University57, Kyushu University58, Wageningen University and Research Centre59, Spanish National Research Council60, University of Regensburg61, University of Rennes62, Université du Québec à Trois-Rivières63, Potsdam Institute for Climate Impact Research64, Technical University of Denmark65, University of California, Los Angeles66, Hokkaido University67, Université de Sherbrooke68, Syracuse University69, Empresa Brasileira de Pesquisa Agropecuária70, University of Aberdeen71, Michigan State University72, Oak Ridge National Laboratory73, University of Leicester74, Utah State University75, Smithsonian Institution76, University of Missouri77
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.
Abstract: Plant traits – the morphological, anatomical, physiological, biochemical and phenological characteristics of plants and their organs – determine how primary producers respond to environmental factors, affect other trophic levels, influence ecosystem processes and services and provide a link from species richness to ecosystem functional diversity. Trait data thus represent the raw material for a wide range of research from evolutionary biology, community and functional ecology to biogeography. Here we present the global database initiative named TRY, which has united a wide range of the plant trait research community worldwide and gained an unprecedented buy-in of trait data: so far 93 trait databases have been contributed. The data repository currently contains almost three million trait entries for 69 000 out of the world's 300 000 plant species, with a focus on 52 groups of traits characterizing the vegetative and regeneration stages of the plant life cycle, including growth, dispersal, establishment and persistence. A first data analysis shows that most plant traits are approximately log-normally distributed, with widely differing ranges of variation across traits. Most trait variation is between species (interspecific), but significant intraspecific variation is also documented, up to 40% of the overall variation. Plant functional types (PFTs), as commonly used in vegetation models, capture a substantial fraction of the observed variation – but for several traits most variation occurs within PFTs, up to 75% of the overall variation. In the context of vegetation models these traits would better be represented by state variables rather than fixed parameter values. The improved availability of plant trait data in the unified global database is expected to support a paradigm shift from species to trait-based ecology, offer new opportunities for synthetic plant trait research and enable a more realistic and empirically grounded representation of terrestrial vegetation in Earth system models.
2,017 citations
TL;DR: In this article, a suite of morphological, physiological and life-history traits that are likely to differ between tropical mesic savanna and forest species are identified and used to distinguish between these ecosystems and thereby aid their appropriate management and conservation.
Abstract: Savannas are defined based on vegetation structure, the central concept being a discontinuous tree cover in a continuous grass understorey. However, at the high-rainfall end of the tropical savanna biome, where heavily wooded mesic savannas begin to structurally resemble forests, or where tropical forests are degraded such that they open out to structurally resemble savannas, vegetation structure alone may be inadequate to distinguish mesic savanna from forest. Additional knowledge of the functional differences between these ecosystems which contrast sharply in their evolutionary and ecological history is required. Specifically, we suggest that tropical mesic savannas are predominantly mixed tree–C4 grass systems defined by fire tolerance and shade intolerance of their species, while forests, from which C4 grasses are largely absent, have species that are mostly fire intolerant and shade tolerant. Using this framework, we identify a suite of morphological, physiological and life-history traits that are likely to differ between tropical mesic savanna and forest species. We suggest that these traits can be used to distinguish between these ecosystems and thereby aid their appropriate management and conservation. We also suggest that many areas in South Asia classified as tropical dry forests, but characterized by fire-resistant tree species in a C4 grass-dominated understorey, would be better classified as mesic savannas requiring fire and light to maintain the unique mix of species that characterize them.
343 citations
TL;DR: It is shown that grasses and trees have different leaf deployment strategies, and leaf flush in the tree strategies appears to pre-empt rainfall, whereas grass leaf flush follows the rain.
Abstract: Aim It has been proposed that, in tropical savannas, trees deploy their leaves earlier in the growing season and grasses deploy their leaves later. This hypothesis implies a mechanism that facilitates the coexistence of trees and grasses in savannas. If true, this hypothesis would also allow algorithms to use differences in the phenological timing of grass and tree leaves to partition the relative contribution of grasses and trees to net primary production. In this study we examine whether a temporal niche separation between grasses and trees exists in savanna.
Location A semi-arid, subtropical savanna, Kruger National Park, South Africa.
Methods We use a multi-spectral camera to track through an entire growing season the normalized difference vegetation index (NDVI) of individual canopies of grasses and trees at eight sites arranged along a precipitation and temperature gradient.
Results Among trees, we identified two distinct phenological syndromes: an early flushing syndrome and a late-flushing syndrome. Leaf flush in the tree strategies appears to pre-empt rainfall, whereas grass leaf flush follows the rain. The growing season of trees is 20 (late-flushing trees) to 27 (early flushing trees) days longer than that of the grasses.
Main conclusions We show that grasses and trees have different leaf deployment strategies. Trees deployed leaves at lower temperatures than grasses and retained them for longer at the end of the growing season. The timing of the increase in NDVI is, however, similar between grasses and late-flushing trees and this complicates the separation of grass and tree signals from multi-spectral satellite imagery.
65 citations
TL;DR: It is shown that herbivores modify tree allometry and that the pattern of allometric modification contains information regarding herbivore foraging behavior and the resultant alteration of plant architecture.
Abstract: Theories of plant allometry provide a general description of allometric scaling that is supposedly applicable across a wide array of environmental conditions. Scaling theories, however, ignore disturbances such as herbivory in their derivation. Here we examine the influence of herbivores on the scaling of height and diameter of two common African savanna tree species. Using Bayesian piecewise regressions, we show that herbivores modify tree allometry. We also show that the pattern of allometric modification contains information regarding herbivore foraging behavior and the resultant alteration of plant architecture. Interpreting realized allometries in the light of theoretical predictions based on assumptions of zero disturbances may help reveal the degree of herbivore impacts. However, predictions of plant form and function that fail to include disturbances such as herbivory may struggle to find general applicability.
48 citations
TL;DR: It is shown that saplings of the common and locally dominant savanna tree T. sericea manage to coexist with grasses without avoiding competition through spatial root separation, and the two-layer hypothesis for explaining tree–grass coexistence in this mesic savanna is not supported.
40 citations
University of North Dakota1, Colorado State University2, North Carolina State University3, Council for Scientific and Industrial Research4, University of Maryland, College Park5, University of Twente6, Aberystwyth University7, Lund University8, Goethe University Frankfurt9, University of Queensland10, University College London11, Charles Darwin University12
TL;DR: In this article, the authors summarized the state of knowledge, key issues and capacity for tree-grass systems modeling using remote sensing, and contributed to a NASA workshop on remote sensing and modeling savannas.
Abstract: Tree-grass systems occupy nearly a quarter of the terrestrial surface (27 million km2). They face an uncertain future given pressures from land use change and climate change. Serious systems analysis, modeling, scenario development and ecosystems futures assessment for savannas is needed to avoid past mistakes in land management. Integration of measurement from field and remote sensing with multi-scale modeling is required to realize this. This paper summarizes the state of knowledge, key issues and capacity for savanna systems modeling using remote sensing. The authors contributed to a NASA workshop on remote sensing and modeling savannas.
13 citations