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In this study, we examined influences of maternal traits on offspring birth mass, growth rate, and weaning mass for two populations of Columbian ground squirrels (Spernophilus columbianus). We tested relationships between maternal body condition, structural size, change in mass (during gestation, during lactation, and during the entire reproductive period), timing of reproduction, and litter size on offspring traits using path analyses. To assess whether maternal investment in offspring traits extended beyond the period of direct maternal care, we examined associations between offspring traits and overwinter survival of pups. In general, females in better condition raised pups that were heavier at weaning and that had faster growth rates during lactation. Litter size had a negative effect on mass and growth rate, and only litter size had a significant effect on birth mass. For both populations, the average weaning mass of pups within a litter had a positive effect on the number of pups that survived to yearling age. In a population for which birth masses and growth rates were available, pups with faster growth rates survived better to yearling age, whereas birth mass had no effect on the number of surviving offspring in litters. We found substantial maternal influences on offspring growth and size, and evidence that these influences may extend beyond the juvenile period and constitute influences on fitness. The key to arriving at these conclusions was to take the number of offspring into account before testing for maternal effects. [ABSTRACT FROM AUTHOR]

Forecasting how climate change will impact biological systems represents a grand challenge for biologists. However, climate change biology lacks an effective framework for anticipating and resolving uncertainty. Here, we introduce the concept of climate change wildcards: biological or bioclimatic processes with a high degree of uncertainty and a large impact on our ability to address the biotic consequences of climate change. Wildcards may occur at multiple points in the progression of research—from understanding, to predicting, to forecasting biological responses. Our understanding of biological responses is limited by the components and processes we exclude to make research tractable. Our ability to predict biological responses often requires integration between biological levels of organization, across multiple stressors, and from specific cases to general systems. However, these types of integration can be dramatically affected by, respectively, differences between biological levels in their critical points, nonadditivity of the effects of different stressors, and historical and geographic contingency. Finally, our ability to forecast biological responses to climate change requires incorporating climatic projections in bioclimatic models. Such forecasts are vulnerable to the compounding of biological and climatic uncertainty, especially when biological responses occur in novel areas of bioclimatic parameter space. Both biological responses and climate change are dynamic processes; the potential of biological systems to be buffered against or rescued from the effects of climate change depends on the relative timing of biological and climatic effects—one of the least predictable aspects of both systems. In sum, our framework identifies stress points in the research process where we should anticipate and forestall wildcards. Focusing on universal currencies, like energy and elements, and universal structures, like functional traits and ecological networks, will improve our ability to generalize results. Most importantly, by modeling and communicating uncertainty, climate change biology can identify critical foci for future research. [ABSTRACT FROM AUTHOR]