Abstract
Aim: Global biomes are often classified by mean annual temperature and precipitation, but there is significant overlap between biomes, making it difficult to interpret the role of climate in the distribution of biomes globally. Climate predictability (including long-term reliability of both seasonality and inter-annual variability) varies considerably between biomes and regulates biodiversity distribution, adaptation and evolution, but its global pattern has rarely been investigated. The aim of this study was to characterize climatic space quantitatively for major biomes of the world using temperature and precipitation predictability, and to interpret its biological implications under future climate change. Methods: We calculated global gridded temperature and precipitation predictability based on an information theory approach, and compared climatic spaces defined by these measures within and across biomes. Results: We show that temperature predictability has a clear latitudinal gradient, whereas precipitation predictability is geographically variable. We further show that temperature and precipitation predictability form distinct climatic spaces for major biomes across the globe, and importantly, temperature and precipitation predictability can robustly distinguish biomes that are overlapping in mean annual climate statistics. Main conclusions: Climatic space created by temperature and precipitation predictability supplements the traditional biome-specific climatic spaces created by annual mean temperature and total precipitation. Quantifying measures of climate predictability helps us to understand adaptation strategies adopted by local organisms within and across biomes. Our results show that quantifying climate predictability is a simple and effective way to delineate more robustly biome climate space and its influences on macroecology and evolutionary biology, which in turn could underpin conservation efforts under future climate change, especially when prevailing climates are comparable in terms of magnitude.
Original language | English |
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Pages (from-to) | 1270-1282 |
Number of pages | 13 |
Journal | Global Ecology and Biogeography |
Volume | 26 |
Issue number | 11 |
DOIs | |
Publication status | Published - 2017 |
Keywords
- biodiversity
- climatic changes
- precipitation
- temperature
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Global gridded temperature and precipitation predictability dataset
Jiang, M., Felzer, B. S., Nielsen, U. & Medlyn, B., Western Sydney University, 23 May 2017
DOI: 10.4225/35/5923990324167, https://research-data.westernsydney.edu.au/published/30b83130519411ecb15399911543e199
Dataset