Four degrees and beyond: the potential for a global ... - Amper

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140 P. Zelazowski et al. by Cook & Vizy [38]) is inadequate to describe the broad distribution and variability of climatic factors and risks. Small-scale variation, notably linked to topography, may facilitate greater ecosystem resilience than what the models suggest [39,40]. In this study, we explore the possibility for retraction or expansion of HTFs under twenty-first century anthropogenic global warming. First, we take an empirical approach to defining the current climatological niche of HTFs. We then use projections from 17 coupled AOGCMs, downscaled using contemporary climatological data, to explore (i) the potential variation of this niche, assuming no impact of new climate regimes on plant water demand, and (ii) the consequences of potential change in plant water demand. Specifically, we ask the following questions: — Which scalable climatological indices best define the current boundaries of the HTF biome, and what are the appropriate threshold values of these indices? — What is the spatial pattern and magnitude of potential humid forest expansion and retraction considered over 17 different climate models? — What does the consideration of higher resolution climatological patterns add to our understanding of potential risk regions and potential HTFs refugia that are resilient to climate change? — How does the introduction of environmental controls on the plant physiology, which influence water demand, affect the likelihood and pattern of potential niche contraction or expansion? The novel contributions in this work arise from a combination of (i) the empirical derivation of the hydrological threshold for tropical forests worldwide, (ii) consideration of multiple climate models, (iii) consideration of fine-scale variation in climate patterns, and (iv) inclusion of effects of new climate regimes on plant water-use efficiency. It is worth noting that this analysis focuses on ecosystem water demand and its potential variation, as inferred from the canopy conductance and photosynthesis model. It does not consider all ecophysiological influences of atmospheric change, for example high CO2 altering the competitive balance between C3 photosynthesis-dominated forests and C4-dominated grasslands. Such ecophysiological considerations could be incorporated by employing a dynamic vegetation model, but are limited by a poor understanding of what the ecophysiological responses and thresholds are, and the extent to which plant processes can acclimate to higher temperatures. The merits and uncertainties of incorporating other ecophysiological processes are presented in §4. 2. Methods (a) Contemporary distribution of humid tropical forests and their niche Spatial distribution of tropical vegetation biomes was assessed based on the Global Land Cover 2000 dataset ([41]; figure 1) derived from satellite data. It employed the Land Cover Classification System of the FAO in which Phil. Trans. R. Soc. A (2011) Downloaded from rsta.royalsocietypublishing.org on November 30, 2010
(a) Humid tropical forests on a warmer planet 141 (b) (c) MCWD 100 0 mm –1200 (d) annual precipitation (e) >4000 (f) dry-season length (g) mm 0 0 months 12 MCWD HTF annual-temperature range perhumidity index flooded forest (freshwater) broadleaved evergreen forest broadleaved deciduous closed forest broadleaved deciduous open forest shrub herbaceous herbaceous/shrub sparse bare outside temperature niche Figure 1. (a) Vegetation classes in the tropics. Areas too cold for lowland HTFs are shaded in blue. White areas within continents are covered by either anthropogenic or mixed land-cover types, and were not used in the analysis. (b–g) Key climate variables linked to the distribution of tropical biomes (see also table 1). Underlying data source: Global Land Cover 2000 and WorldClim datasets. vegetation types are based on vegetation form (e.g. trees, shrubs), density, leaf type and phenology. HTFs were assumed to be represented by a class of evergreen broadleaved forests and forests flooded by freshwater, both within the tropics. A number of variables related to surface precipitation and temperature were considered for the definition of climatological niche of the contemporary HTFs. The explanatory power of each variable in terms of the distribution of HTFs and other tropical vegetation types (non-evergreen forest types, dense non-forest vegetation and sparse non-forest vegetation) was assessed using multi-nomial logistic regression. Each variable’s range, specific to a region within the tropics (Americas, Africa and south and insular Asia, referred to as ‘Asia’) was split into 44 equal bins (except for the dry-season length with only 12 bins), which were represented by a high number of vegetation-type counts (pixels). The assessment included three criteria: (i) deviance, which depicts the variable’s overall capacity to predict the composition of vegetation types, (ii) the root mean-squared error (RMSE), calculated for HTFs, reflecting the difference between the predicted and actual contribution from HTFs across the variable’s gradient, and (iii) the predictor’s ability to capture both high and low probability of HTF occurrence, as inferred from the shape of the fitted curve. The considered climatic predictors included 19 variables of the Worldclim dataset [42], and 10 additional variables derived for this study, which included MCWD ([12]; equation (2.1)), PI [17], dry-season length (defined as in [1,8]; see §1), annual actual evapotranspiration (ET), and minimum and maximum mean monthly temperature (and the resulting annual-temperature range). Phil. Trans. R. Soc. A (2011) Downloaded from rsta.royalsocietypublishing.org on November 30, 2010 0 mm –1850 0 °C 40 24 –24
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ISSN 1364-503X volume 369 number 19
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Phil. Trans. R. Soc. A (2011) 369,
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Editorial David Garner Phil. Trans.
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Four degrees and beyond: the potent
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Preface 5 commitments might give us
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8 M. New et al. In the final plenar
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10 M. New et al. supports the messa
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12 M. New et al. Table 1. Impacts a
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14 M. New et al. actors (NNSAs)—r
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16 M. New et al. as permanent crop
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18 M. New et al. 24 Boe, J. L., Hal
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Beyond 'dangerous' climate change:
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Beyond dangerous climate change 21
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(i) Energy and industrial process e
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(a) 50 (b) GtCO 2e yr -1 40 30 20 1
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Table 1. Summary of scenario pathwa
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Cumulative carbon emissions, emissi
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46 N. H. A. Bowerman et al. althoug
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emissions (GtC) Review. Global warm
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global surface warming (°C) 6 5 4
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temperature (relative to 1861-1890
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°C above pre-industrial 8 7 6 5 4
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Regional temperature and precipitat
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88 M. G. Sanderson et al. Table 1.
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REVIEW Phil. Trans. R. Soc. A (2011
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Review. Interactions in a 4 ◦ C w
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spread in mosquitoborne disease may
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[89,94,95] further acidification by
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Editorial Editorial 3 D. Garner Pre
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