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In an environment of uncertain climatic change, there is an urgent need to develop robust reserve networks, i.e., networks that conserve species across multiple climatic futures. Using climatic envelopes based on multiple future climatic scenarios, we first estimate the impacts that these scenarios might have on the distributions of 63 native tree species in the Province of Ontario. Next, an optimization model is applied to expand an existing system of reserves in this province by determining the minimum number of optimal locations for additional reserves both with and without the need for migration. The optimization model formulated differs from previous work in that it meets the need for present and future distributions to occur in the same reserve and accommodates multiple differing climate change scenarios rather than a single scenario. The reserve selection approach described here can be applied anywhere that species' distributions and environmental grids are available. Although this approach is designed to produce a robust solution to the uncertainties over future climatic scenarios, it does not eliminate these uncertainties because the proposed solutions inherit the uncertainties of the global climate change models. Dans un contexte d'incertitude face au changement climatique, il est urgent de mettre sur pied des réseaux robustes de réserves, c.-à-d. des réseaux qui préservent les espèces face à un éventail d'avenirs climatiques plausibles. À l'aide d'enveloppes climatiques basées sur un ensemble de scénarios climatiques futurs, nous estimons d'abord l'impact que ces scénarios pourraient avoir sur la répartition géographique de 63 espèces indigènes arborescentes dans la province d'Ontario. Ensuite, un modèle d'optimisation est appliqué pour étendre le système existant de réserves dans cette province en déterminant le nombre minimum de localisations optimales pour des réserves additionnelles avec et sans besoin de migration. Le modèle d'optimisation qui a été développé diffère des modèles précédents en ce qu'il répond à la nécessité que les répartitions actuelle et future se retrouvent dans la même réserve et qu'il tient compte de plusieurs scénarios de changement climatique différents plutôt que d'un seul. L'approche présentée ici pour choisir des réserves peut être appliquée partout où la répartition des espèces et des grilles environnementales sont disponibles. Bien que cette approche soit conçue pour produire une solution robuste aux incertitudes inhérentes aux scénarios climatiques futurs, elle n'élimine pas ces incertitudes parce que les solutions proposées héritent des incertitudes des modèles de changement climatique planétaire. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Forest Research is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Empirical models for predicting the distribution of organisms from environmental data have often focused on principles of ecological niche theory. However, even at large scales, there is little agreement over how to represent the dimensions of a species’ niche. The performance of such models is greatly affected by the nature of species distributional and environmental data. Regional scale distribution models were developed for 30 willow species in Ontario to examine (i) the predictive ability of logistic regression analysis, and (ii) the effects of using different distributional and environmental data sets. Two original measures of model accuracy and over-prediction were employed and evaluated using independent data. Models based on unique combinations of monthly climate data predicted distributions most accurately for all species. Models based on a fixed set of variables, while generating the highest average probabilities of occurrence for certain species with limited ranges, resulted in the greatest under- and over-estimates of willow distributions. Comparisons of models demonstrated climatic patterns among willows of differing habit and habitat. The distribution of dwarf willow species, present only in the Ontario arctic, followed gradients of summer maximum temperatures. The distribution of the tree species in the southerly portions of the province followed gradients of fall and winter minimum temperatures. Regardless of distributional and environmental data input, no algorithm maximized model performance for all species. Individual species models require individual approaches; i.e., the variable selection technique, the set of environmental factors used as predictors, and the nature of species distributional data must be carefully matched to the intended application. An understanding of evolutionary processes enhances the meaningful interpretation of individual species models. Unless sampling bias and species prevalence can be accounted for, models based on collection point data are best used to guide field surveys. While inferred range data may be better suited to determine potential ecological niches, overestimation of species prevalence and environmental tolerance must be recognized. A combination of available distributional data types is recommended to best determine species niches, an important step in developing conservation strategies. [Copyright &y& Elsevier]

Copyright of Canadian Journal of Forest Research is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Canadian Journal of Botany is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Canadian Journal of Forest Research is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)