Summary 1.The biases and shortcomings of stepwise multiple regression are well established within the statistical literature. However, an examination of papers published in 2004 by three leading ecological and behavioural journals suggested that the use of this technique remains widespread: of 65 papers in which a multiple regression approach was used, 57% of studies used a stepwise procedure. 2. The principal drawbacks of stepwise multiple regression include bias in parameter estimation, inconsistencies among model selection algorithms, an inherent (but often overlooked) problem of multiple hypothesis testing, and an inappropriate focus or reliance on a single best model. We discuss each of these issues with examples. 3. We use a worked example of data on yellowhammer distribution collected over 4 years to highlight the pitfalls of stepwise regression. We show that stepwise regression allows models containing significant predictors to be obtained from each year's data. In spite of the significance of the selected models, they vary substantially between years and suggest patterns that are at odds with those determined by analysing the full, 4-year data set. 4. An information theoretic (IT) analysis of the yellowhammer data set illustrates why the varying outcomes of stepwise analyses arise. In particular, the IT approach identifies large numbers of competing models that could describe the data equally well, showing that no one model should be relied upon for inference.

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Shifts in species' distribution and abundance in response to climate change have been well documented, but the underpinning processes are still poorly understood. We present the results of a systematic literature review and meta-analysis investigating the frequency and importance of different mechanisms by which climate has impacted natural populations. Most studies were from temperate latitudes of North America and Europe; almost half investigated bird populations. We found significantly greater support for indirect, biotic mechanisms than direct, abiotic mechanisms as mediators of the impact of climate on populations. In addition, biotic effects tended to have greater support than abiotic factors in studies of species from higher trophic levels. For primary consumers, the impact of climate was equally mediated by biotic and abiotic mechanisms, whereas for higher level consumers the mechanisms were most frequently biotic, such as predation or food availability. Biotic mechanisms were more frequently supported in studies that reported a directional trend in climate than in studies with no such climatic change, although sample sizes for this comparison were small. We call for more mechanistic studies of climate change impacts on populations, particularly in tropical systems.