Why large-scale climate indices seem to predict ecological processes better than local weather

被引:429
|
作者
Hallett, TB
Coulson, T
Pilkington, JG
Clutton-Brock, TH
Pemberton, JM
Grenfell, BT
机构
[1] Univ London Imperial Coll Sci Technol & Med, Dept Biol Sci, Ascot SL5 7PY, Berks, England
[2] Univ Cambridge, Dept Zool, Cambridge CB2 3EJ, England
[3] Univ Edinburgh, Inst Cell Anim & Populat Biol, Edinburgh EH9 3JT, Midlothian, Scotland
基金
英国自然环境研究理事会; 英国生物技术与生命科学研究理事会; 英国工程与自然科学研究理事会; 英国惠康基金;
关键词
D O I
10.1038/nature02708
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Large-scale climatic indices such as the North Atlantic Oscillation(1) are associated with population dynamics(2), variation in demographic rates(3) and values of phenotypic traits(4,5) in many species. Paradoxically, these large-scale indices can seem to be better predictors of ecological processes than local climate(5-8). Using detailed data from a population of Soay sheep(9,10), we show that high rainfall, high winds or low temperatures at any time during a 3-month period can cause mortality either immediately or lagged by a few days. Most measures of local climate used by ecologists fail to capture such complex associations between weather and ecological process, and this may help to explain why large-scale, seasonal indices of climate spanning several months can outperform local climatic factors. Furthermore, we show why an understanding of the mechanism by which climate influences population ecology is important. Through simulation we demonstrate that the timing of bad weather within a period of mortality can have an important modifying influence on intra-specific competition for food, revealing an interaction between climate and density dependence(11) that the use of large-scale climatic indices or inappropriate local weather variables might obscure.
引用
收藏
页码:71 / 75
页数:5
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