Author
Steven I. Higgins
Other affiliations: University of the Witwatersrand, Helmholtz Centre for Environmental Research - UFZ, Technische Universität München ...read more
Bio: Steven I. Higgins is an academic researcher from University of Bayreuth. The author has contributed to research in topics: Vegetation & Biome. The author has an hindex of 55, co-authored 121 publications receiving 13944 citations. Previous affiliations of Steven I. Higgins include University of the Witwatersrand & Helmholtz Centre for Environmental Research - UFZ.
Papers published on a yearly basis
Papers
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Max Planck Society1, National University of Cordoba2, Centre national de la recherche scientifique3, Macquarie University4, University of Paris-Sud5, University of Western Sydney6, University of Minnesota7, 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
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Colorado State University1, Council of Scientific and Industrial Research2, United States Forest Service3, United States Geological Survey4, École Normale Supérieure5, University of Lyon6, Commonwealth Scientific and Industrial Research Organisation7, Lund University8, University of Dar es Salaam9, Princeton University10, University of Nairobi11, University of Virginia12, University of Cape Town13, University of Zimbabwe14, Mammal Research Institute15, University of Wisconsin-Madison16, Wageningen University and Research Centre17, University of Botswana18, University of Potsdam19, South African National Parks20
TL;DR: It is shown, using data from 854 sites across Africa, that maximum woody cover in savannas receiving a mean annual precipitation (MAP) of less than ∼650 mm is constrained by, and increases linearly with, MAP.
Abstract: Savannas are globally important ecosystems of great significance to human economies. In these biomes, which are characterized by the co-dominance of trees and grasses, woody cover is a chief determinant of ecosystem properties1–3. The availability of resources (water, nutrients) and disturbance regimes (fire, herbivory) are thought to be important in regulating woody cover1,2,4,5, but perceptions differ on which of these are the primary drivers of savanna structure. Here we show, using data from 854 sites across Africa, that maximum woody cover in savannas receiving a mean annual precipitation (MAP) of less than ,650mm is constrained by, and increases linearly with, MAP. These arid and semi-arid savannas may be considered ‘stable' systems in which water constrains woody cover and permits grasses to coexist, while fire, herbivory and soil properties interact to reduce woody cover below the MAP-controlled upper bound. Above a MAP of ,650mm, savannas are ‘unstable' systems in which MAP is sufficient for woody canopy closure, and disturbances (fire, herbivory) are required for the coexistence of trees and grass. These results provide insights into the nature of African savannas and suggest that future changes in precipitation6 may considerably affect their distribution and dynamics.
1,740 citations
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TL;DR: Understanding grass–tree interactions in savanna requires consideration of the long-term effects of life history–disturbance interactions on demography, rather than the fine-scale effects of resource competition on physiological performance.
Abstract: Summary
1 Savanna ecosystems are characterized by the codominance of two different life forms: grasses and trees. An operational understanding of how these two different life forms coexist is essential for understanding savanna function and for predicting its response to future environmental change.
2 The existing model, which proposes that grasses and trees coexist by a separation of rooting niches, is not supported by recent empirical investigations. Our aim was to define an alternative mechanism of grass–tree coexistence in savanna ecosystems. The model we have built concentrates on life history–disturbance interactions between grasses and trees.
3 The model demonstrates coexistence for a wide range of environmental conditions, and exhibits long periods of slow decline in adult tree numbers interspersed with relatively infrequent recruitment events. Recruitment is controlled by rainfall, which limits seedling establishment, and fire, which prevents recruitment into adult size classes. Decline in adult tree numbers is the result of continuing, but low levels, of adult mortality. Both aspects of the dynamics are consistent with an established non-equilibrium mechanism of coexistence (the storage effect).
4 A sensitivity analysis indicated that data on tree resprouting ability, stem growth rates and the relationship between seedling establishment and wet season drought are essential for predicting both the range of conditions for which coexistence is possible and the response of savanna ecosystems to environmental change.
5 Our analysis suggests that understanding grass–tree interactions in savanna requires consideration of the long-term effects of life history–disturbance interactions on demography, rather than the fine-scale effects of resource competition on physiological performance.
1,034 citations
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TL;DR: Although dispersal had the strongest effect on the predicted spread rate, it was showed that dispersal interacts strongly with plant life history, disturbance, and habitat loss in influencing the predicted rate of spread.
Abstract: Models of plant migration based on estimates of biological parameters severely underestimate the rate of spread when compared to empirical estimates of plant migration rates. This is disturbing, since an ability to predict migration and colonization rates is needed for predicting how native species will distribute themselves in response to habitat loss and climate change and how rapidly invasive species will spread. Part of the problem is the difficulty of formally including rare long‐distance dispersal events in spread models. In this article, we explore the process of making predictions about plant migration rates. In particular, we examine the links between data, statistical models, and ecological predictions. We fit mixtures of Weibull distributions to several dispersal data sets and show that statistical and biological criteria for selecting the most appropriate statistical model conflict. Fitting a two‐component mixture model to the same data increases the spread‐rate prediction by an aver...
577 citations
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University of Edinburgh1, Macquarie University2, Wake Forest University3, National Centre for Biological Sciences4, University of Leeds5, Goethe University Frankfurt6, University of Otago7, University of the Witwatersrand8, Council for Scientific and Industrial Research9, North Carolina State University10, South Dakota State University11, Commonwealth Scientific and Industrial Research Organisation12, University of Queensland13, University of Brasília14, Charles Darwin University15, Venezuelan Institute for Scientific Research16, Simón Bolívar University17, University of Toulouse18, University of Tasmania19, University of Cape Town20
TL;DR: Using data from 2154 sites in savannas across Africa, Australia, and South America, it is found that increasing moisture availability drives increases in fire and tree basal area, whereas fire reduces tree basal Area.
Abstract: Ecologists have long sought to understand the factors controlling the structure of savanna vegetation. Using data from 2154 sites in savannas across Africa, Australia, and South America, we found that increasing moisture availability drives increases in fire and tree basal area, whereas fire reduces tree basal area. However, among continents, the magnitude of these effects varied substantially, so that a single model cannot adequately represent savanna woody biomass across these regions. Historical and environmental differences drive the regional variation in the functional relationships between woody vegetation, fire, and climate. These same differences will determine the regional responses of vegetation to future climates, with implications for global carbon stocks.
500 citations
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01 Jan 2016
TL;DR: The modern applied statistics with s is universally compatible with any devices to read, and is available in the digital library an online access to it is set as public so you can download it instantly.
Abstract: Thank you very much for downloading modern applied statistics with s. As you may know, people have search hundreds times for their favorite readings like this modern applied statistics with s, but end up in harmful downloads. Rather than reading a good book with a cup of coffee in the afternoon, instead they cope with some harmful virus inside their laptop. modern applied statistics with s is available in our digital library an online access to it is set as public so you can download it instantly. Our digital library saves in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Kindly say, the modern applied statistics with s is universally compatible with any devices to read.
5,249 citations
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University of Michigan1, College of William & Mary2, McGill University3, Western Washington University4, Arizona State University5, Imperial College London6, University of Minnesota7, Swedish University of Agricultural Sciences8, Stanford University9, Centre national de la recherche scientifique10, United States Geological Survey11, University of British Columbia12, Columbia University13
TL;DR: It is argued that human actions are dismantling the Earth’s ecosystems, eliminating genes, species and biological traits at an alarming rate, and the question of how such loss of biological diversity will alter the functioning of ecosystems and their ability to provide society with the goods and services needed to prosper is asked.
Abstract: The most unique feature of Earth is the existence of life, and the most extraordinary feature of life is its diversity. Approximately 9 million types of plants, animals, protists and fungi inhabit the Earth. So, too, do 7 billion people. Two decades ago, at the first Earth Summit, the vast majority of the world's nations declared that human actions were dismantling the Earth's ecosystems, eliminating genes, species and biological traits at an alarming rate. This observation led to the question of how such loss of biological diversity will alter the functioning of ecosystems and their ability to provide society with the goods and services needed to prosper.
5,244 citations
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TL;DR: Species distribution models (SDMs) as mentioned in this paper are numerical tools that combine observations of species occurrence or abundance with environmental estimates, and are used to gain ecological and evolutionary insights and to predict distributions across landscapes, sometimes requiring extrapolation in space and time.
Abstract: Species distribution models (SDMs) are numerical tools that combine observations of species occurrence or abundance with environmental estimates. They are used to gain ecological and evolutionary insights and to predict distributions across landscapes, sometimes requiring extrapolation in space and time. SDMs are now widely used across terrestrial, freshwater, and marine realms. Differences in methods between disciplines reflect both differences in species mobility and in “established use.” Model realism and robustness is influenced by selection of relevant predictors and modeling method, consideration of scale, how the interplay between environmental and geographic factors is handled, and the extent of extrapolation. Current linkages between SDM practice and ecological theory are often weak, hindering progress. Remaining challenges include: improvement of methods for modeling presence-only data and for model selection and evaluation; accounting for biotic interactions; and assessing model uncertainty.
5,076 citations
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TL;DR: In this paper, a hierarchical modeling framework is proposed through which some of these limitations can be addressed within a broader, scale-dependent framework, and it is proposed that, although the complexity of the natural system presents fundamental limits to predictive modelling, the bioclimate envelope approach can provide a useful first approximation as to the potentially dramatic impact of climate change on biodiversity.
Abstract: Modelling strategies for predicting the potential impacts of climate change on the natural distribution of species have often focused on the characterization of a species’ bioclimate envelope. A number of recent critiques have questioned the validity of this approach by pointing to the many factors other than climate that play an important part in determining species distributions and the dynamics of distribution changes. Such factors include biotic interactions, evolutionary change and dispersal ability. This paper reviews and evaluates criticisms of bioclimate envelope models and discusses the implications of these criticisms for the different modelling strategies employed. It is proposed that, although the complexity of the natural system presents fundamental limits to predictive modelling, the bioclimate envelope approach can provide a useful first approximation as to the potentially dramatic impact of climate change on biodiversity. However, it is stressed that the spatial scale at which these models are applied is of fundamental importance, and that model results should not be interpreted without due consideration of the limitations involved. A hierarchical modelling framework is proposed through which some of these limitations can be addressed within a broader, scale-dependent
3,847 citations
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TL;DR: This paper provides an international methodological protocol aimed at standardising this research effort, based on consensus among a broad group of scientists in this field, and features a practical handbook with step-by-step recipes, for 28 functional traits recognised as critical for tackling large-scale ecological questions.
Abstract: There is growing recognition that classifying terrestrial plant species on the basis of their function (into 'functional types') rather than their higher taxonomic identity, is a promising way forward for tackling important ecological questions at the scale of ecosystems, landscapes or biomes. These questions include those on vegetation responses to and vegetation effects on, environmental changes (e.g. changes in climate, atmospheric chemistry, land use or other disturbances). There is also growing consensus about a shortlist of plant traits that should underlie such functional plant classifications, because they have strong predictive power of important ecosystem responses to environmental change and/or they themselves have strong impacts on ecosystem processes. The most favoured traits are those that are also relatively easy and inexpensive to measure for large numbers of plant species. Large international research efforts, promoted by the IGBP–GCTE Programme, are underway to screen predominant plant species in various ecosystems and biomes worldwide for such traits. This paper provides an international methodological protocol aimed at standardising this research effort, based on consensus among a broad group of scientists in this field. It features a practical handbook with step-by-step recipes, with relatively brief information about the ecological context, for 28 functional traits recognised as critical for tackling large-scale ecological questions.
3,288 citations