Colloquium Papers: Climatic extremes improve predictions of spatial patterns of tree species

By N. E. Zimmermann, N. Yoccoz, THOMAS C. EDWARDS JR., Eliane Seraina Meier, Wilfried Thuiller, Antoine Guisan, Dirk R. Schmatz, P. Pearman. 2009

405 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/78d14d1ba9f92f7ec021c90b94085fae45d47c81

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Y. Vitasse
2. C. Körner
3. Tomás Václavík
4. Jane Elith
5. G. Hoch
6. D. Basler
7. Janet Franklin
8. I. Chuine

Citations in the corpus

• Predicting distributions of invasive species (2013, background): “I expect that predictors that characterise climate extremes and variability and climate close to the ground will be particularly useful for modelling invasive species because they characterise processes and impacts important to species’ persistence (e.g. Zimmermann et al., 2009).”
• The push and pull of climate change causes heterogeneous shifts in avian elevational ranges (2012, background): “…to competitive species interactions (Hughes, 2000; Lenoir et al., 2010), land-use changes (Archaux, 2004), changes in nontemperature environmental gradients (Tingley et al., 2009; Zimmermann et al., 2009; Crimmins et al., 2011), and stochastic fluctuations in population size (Lenoir et al., 2010).”
• Multiple Dimensions of Climate Change and Their Implications for Biodiversity (2014, unknown): “Teasing apart alternative dimensions of change to complement model-based assessments, or integrating them into models (110, 111), can bring valuable additional information.”
• Accounting for multi‐scale spatial autocorrelation improves performance of invasive species distribution modelling (iSDM) (2012, methodology): “We aggregated the monthly grids to the rainy season (December to May), the pathogen’s major reproductive period in California and Oregon (Davidson et al., 2005), but also used maximum July and minimum January temperatures to account for the effects of climate extremes (Zimmermann et al., 2009).”
• Climate, competition and connectivity affect future migration and ranges of European trees (2012, background): “Despite these three potential shortcomings, modelling transient dynamics across large spatial scales still provides valuable insights into the magnitude and the time-scale over which range shifts may occur, especially as little is known about the range restrictions of most species (Gaston, 2009), al”
• Where, why and how? Explaining the low‐temperature range limits of temperate tree species (2016, background): “For instance, the inclusion of extreme temperatures instead of means improves predictions of tree distribution (Zimmermann et al. 2009), with the exact mechanisms remaining unclear.”
• Beta diversity of plants, birds and butterflies is closely associated with climate and habitat structure (2017, methodology): “We averaged the temperature and precipitation data using all data of the years 1981– 2010 (for details, see Zellweger et al., 2016; Zimmermann et al., 2009).”
• Modelling horses for novel climate courses: insights from projecting potential distributions of native and alien Australian acacias with correlative and mechanistic models (2011, background): “Alternatively, variables could be developed based on extreme values rather than means (Zimmermann et al., 2009), especially given that most projections of future climates indicate that the frequencies of events currently considered extreme will increase (Frei et al., 2006).”
• Climate change and European forests: what do we know, what are the uncertainties, and what are the implications for forest management? (2014, background): “Indeed, an earlier study demonstrated that adding measures of climatic extremes to SDMs improved model projections (Zimmermann et al., 2009).”
• Biodiversity responses to climate and land-use change: A historical perspective (2015, unknown): “…characteristics play an important role when investigating current species distributions, as found in our variable importance analysis, and may also render insights when investigating future species distributions responses to climate change and future conservation actions (Zimmermann et al., 2009).”
• Going against the flow: potential mechanisms for unexpected downslope range shifts in a warming climate (2010, background): “These complex aspects of climate variability may heavily influence species range margins (Zimmermann et al. 2009), and thus more complex environment-competition interactions are likely to cause unexpected range shifts in response to climate warming.”