Global Models for Predicting Woody Plant Richness From Climate: Development and Evaluation

Field, Richard; O’Brien, Eileen M.; Whittaker, Robert J.

doi:10.1890/04-1910

Cited by 149 publications

(233 citation statements)

References 15 publications

(56 reference statements)

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“…This bioinformatic database has recently been compiled ) at a spatial resolution of 0.58Â 0.58 cells (approx. 55.5 km) and contains 228 grid cells, of which 160 cells are included here as these are known to provide reasonable estimates of bird and woody plant species richness (Field et al 2005;. Distribution information on 1005 breeding bird species and 1417 woody plant species was included, and species richness of both taxa was estimated from this information for each grid cell.…”

Section: Materials and Methods (A) Species-richness Datamentioning

confidence: 99%

“…Vagrant bird species and species represented only by anecdotal records (n ¼ 60 species) were not included . Similarly, plants that are nonnative, 2.5 m or less in height at maturity, or that are not truly woody were excluded (Field et al 2005). To our knowledge, this database currently contains the most comprehensive information on bird and woody plant distributions at a regional scale in tropical Africa.…”

Section: Materials and Methods (A) Species-richness Datamentioning

confidence: 99%

“…All three variables have previously been shown to be important determinants of species richness of birds and woody plants across Kenya , and more generally at broad spatial scales (Jetz & Rahbek 2002;Hawkins et al 2003;Field et al 2005;Luoto & Heikkinen 2008). Mean values of PREC and TEMP were calculated at 0.58 resolution from the CRU TS 2.1 dataset for the period 1960(Mitchell & Jones 2005.…”

Section: (B) Environmental Variablesmentioning

confidence: 99%

“…Thus, it measures water that is directly available to plants. TEMP was used to measure ambient energy input (Hawkins et al 2003), and in Kenya correlates almost perfectly with Thornthwaite's formulation of potential evapotranspiration, which is used in the interim general models of O'Brien (1998) and Field et al (2005). TOPO was measured as altitudinal range (maximum minus minimum elevation per grid cell) and included to characterize habitat heterogeneity and within-cell climatic variability (O'Brien et al 2000;Luoto & Heikkinen 2008).…”

Section: (B) Environmental Variablesmentioning

confidence: 99%

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Woody plants and the prediction of climate-change impacts on bird diversity

Kissling

Field

Korntheuer

et al. 2010

Phil. Trans. R. Soc. B

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Current methods of assessing climate-induced shifts of species distributions rarely account for species interactions and usually ignore potential differences in response times of interacting taxa to climate change. Here, we used species-richness data from 1005 breeding bird and 1417 woody plant species in Kenya and employed model-averaged coefficients from regression models and median climatic forecasts assembled across 15 climate-change scenarios to predict bird species richness under climate change. Forecasts assuming an instantaneous response of woody plants and birds to climate change suggested increases in future bird species richness across most of Kenya whereas forecasts assuming strongly lagged woody plant responses to climate change indicated a reversed trend, i.e. reduced bird species richness. Uncertainties in predictions of future bird species richness were geographically structured, mainly owing to uncertainties in projected precipitation changes. We conclude that assessments of future species responses to climate change are very sensitive to current uncertainties in regional climate-change projections, and to the inclusion or not of time-lagged interacting taxa. We expect even stronger effects for more specialized plant -animal associations. Given the slow response time of woody plant distributions to climate change, current estimates of future biodiversity of many animal taxa may be both biased and too optimistic.

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Section: Materials and Methods (A) Species-richness Datamentioning

confidence: 99%

Section: Materials and Methods (A) Species-richness Datamentioning

confidence: 99%

Section: (B) Environmental Variablesmentioning

confidence: 99%

Section: (B) Environmental Variablesmentioning

confidence: 99%

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Woody plants and the prediction of climate-change impacts on bird diversity

Kissling

Field

Korntheuer

et al. 2010

Phil. Trans. R. Soc. B

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“…A number of studies have shown a remarkably strong association between contemporary climate and species richness (4,5,7,11,16,(26)(27)(28). According to the ''water-energy dynamics hypothesis,'' species richness at higher latitudes is controlled by the availability of ambient heat, whereas, in the thermally suitable tropics, water-and humidity-related variables are the main driving factors (4,5,28).…”

mentioning

confidence: 99%

Global patterns and determinants of vascular plant diversity

Kreft

Jetz²

2007

Proc. Natl. Acad. Sci. U.S.A.

1,165

1,205

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Plants, with an estimated 300,000 species, provide crucial primary production and ecosystem structure. To date, our quantitative understanding of diversity gradients of megadiverse clades such as plants has been hampered by the paucity of distribution data. Here, we investigate the global-scale species-richness pattern of vascular plants and examine its environmental and potential historical determinants. Across 1,032 geographic regions worldwide, potential evapotranspiration, the number of wet days per year, and measurements of topographical and habitat heterogeneity emerge as core predictors of species richness. After accounting for environmental effects, the residual differences across the major floristic kingdoms are minor, with the exception of the uniquely diverse Cape Region, highlighting the important role of historical contingencies. Notably, the South African Cape region contains more than twice as many species as expected by the global environmental model, confirming its uniquely evolved flora. A combined multipredictor model explains Ϸ70% of the global variation in species richness and fully accounts for the enigmatic latitudinal gradient in species richness. The models illustrate the geographic interplay of different environmental predictors of species richness. Our findings highlight that different hypotheses about the causes of diversity gradients are not mutually exclusive, but likely act synergistically with water-energy dynamics playing a dominant role. The presented geostatistical approach is likely to prove instrumental for identifying richness patterns of the many other taxa without single-species distribution data that still escape our understanding.biodiversity ͉ historical contingency ͉ latitudinal gradient ͉ macroecology ͉ species richness

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Latitudinal Diversity Gradients

Gough

Field

2007

Encyclopedia of Life Sciences

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The diversity of organisms tends to increase from the poles to the equator, a trend that is consistent over space and time. More than 30 hypotheses have been advanced to explain the phenomenon and although no consensus has yet been reached, support for the role of contemporary climate dominates the current literature. However, an integration of contemporary ecological and historical (phylogeny‐based) explanations is increasingly advocated. Most hypotheses are likely to be valid at some range of spatial scales, with mechanisms often showing interdependencies at different scales. With a continuing rise in the number of hypotheses, there is an increasing emphasis on empirical testing and falsification.

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Global Models for Predicting Woody Plant Richness From Climate: Development and Evaluation

Cited by 149 publications

References 15 publications

Woody plants and the prediction of climate-change impacts on bird diversity

Woody plants and the prediction of climate-change impacts on bird diversity

Global patterns and determinants of vascular plant diversity

Latitudinal Diversity Gradients

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