Reply to response to Dyck et al. (2007) on polar bears and climate change in western Hudson Bay by Stirling et al. (2008)

We address the three main issues raised by Stirling et al. [Stirling, I., Derocher, A.E., Gough, W.A., Rode, K., in press. Response to Dyck et al. (2007) on polar bears and climate change in western Hudson Bay. Ecol. Complexity]: (1) evidence of the role of climate warming in affecting the western Hudson Bay polar bear population, (2) responses to suggested importance of human–polar bear interactions, and (3) limitations on polar bear adaptation to projected climate change. We assert that our original paper did not provide any “alternative explanations [that] are largely unsupported by the data” or misrepresent the original claims by Stirling et al. [Stirling, I., Lunn, N.J., Iacozza, I., 1999. Long-term trends in the population ecology of polar bears in western Hudson Bay in relation to climate change. Arctic 52, 294–306], Derocher et al. [Derocher, A.E., Lunn, N.J., Stirling, I., 2004. Polar bears in a warming climate. Integr. Comp. Biol. 44, 163–176], and other peer-approved papers authored by Stirling and colleagues. In sharp contrast, we show that the conclusion of Stirling et al. [Stirling, I., Derocher, A.E., Gough, W.A., Rode, K., in press. Response to Dyck et al. (2007) on polar bears and climate change in western Hudson Bay. Ecol. Complexity] – suggesting warming temperatures (and other related climatic changes) are the predominant determinant of polar bear population status, not only in western Hudson (WH) Bay but also for populations elsewhere in the Arctic – is unsupportable by the current scientific evidence.The commentary by Stirling et al. [Stirling, I., Derocher, A.E., Gough, W.A., Rode, K., in press. Response to Dyck et al. (2007) on polar bears and climate change in western Hudson Bay. Ecol. Complexity] is an example of uni-dimensional, or reductionist thinking, which is not useful when assessing effects of climate change on complex ecosystems. Polar bears of WH are exposed to a multitude of environmental perturbations including human interference and factors (e.g., unknown seal population size, possible competition with polar bears from other populations) such that isolation of any single variable as the certain root cause (i.e., climate change in the form of warming spring air temperatures), without recognizing confounding interactions, is imprudent, unjustified and of questionable scientific utility. Dyck et al. [Dyck, M.G., Soon, W., Baydack, R.K., Legates, D.R., Baliunas, S., Ball, T.F., Hancock, L.O., 2007. Polar bears of western Hudson Bay and climate change: Are warming spring air temperatures the “ultimate” survival control factor? Ecol. Complexity, 4, 73–84. doi:10.1016/j.ecocom.2007.03.002] agree that some polar bear populations may be negatively impacted by future environmental changes; but an oversimplification of the complex ecosystem interactions (of which humans are a part) may not be beneficial in studying external effects on polar bears. Science evolves through questioning and proposing hypotheses that can be critically tested, in the absence of which, as Krebs and Borteaux [Krebs, C.J., Berteaux, D., 2006. Problems and pitfalls in relating climate variability to population dynamics. Clim. Res. 32, 143–149] observe, “we will be little more than storytellers.”     

The timing of food-deceptive flowers: a commentary on Internicola et al. (2008)

A recent article presents a study of pollinator visitation behaviour that is used to evaluate the selective pressure that pollinator visitation rate might have on the timing of the production of nonrewarding flowers. Here we take issue with the conclusions of the paper that there should be selection pressure for nonrewarding flowers to be available earlier in the season in order to avoid dissimilar sympatric rewarding species. Consideration of selection pressure must take into account temporal variation in total pollinator availability, pollinator longevity and unlearned response, and the stability of plant communities over time, as well as the learned responses of individual pollinators that the original study focused on. Learning alone would not necessarily select for early flowering by nonrewarders if temporal variation in pollinator numbers is strong or naïve pollinators consistently appear throughout the flowering season. Further, we argue that early flowering could simply be a natural corollary of longevity of flowers needed to combat negative frequency‐dependent selection and low overall visitation rates by pollinators, rather than a trait that has been specifically selected to reduce temporal overlap with competing rewarding species.     

Comments of Y. Barenholz et al

Abstract

This forum is dedicated to various aspects of liposomal vaccines. Its editor, Professor Gregory Gregoriadis, did an excellent job in assembling a group of papers dealing in detail with the most important and relevant subjects of liposome vaccinology.     

Comments on Bartolino et al. (2011): limits of cumulative relative frequency distribution curves for hotspot identification

The recent paper by Bartolino et al. (Popul Ecol 53:351–359, 2011) presents a new method to objectively select hotspots using cumulative relative frequency distribution (CRFD) curves. This method is presented as being independent from the selection of any threshold and, therefore, less arbitrary than traditional approaches. We argue that this method, albeit mathematically sound, is based on likewise arbitrary decisions regarding threshold selection. Specifically, the use of the CRFD curve approach requires the occurrence of two criteria for the method to be applied correctly: the selection of a 45° tangent to the curve, and the need to consider the highest relative value of the study parameter corresponding to a 45° slope tangent to the curve. Using two case studies (dealing with species richness and abundance of a particular species), we demonstrate that these two criteria are really unrelated to the underlying causes that shape the spatial pattern of the phenomena under study, but rather related to sampling design and spatial scale; hence, one could likewise use different but valid criteria. Consequently, the CRFD curve approach is based on the selection of a pre-defined threshold that has little, if any, ecological justification, and that heavily influences the final hotspot selection. Therefore, we conclude that the CRFD curve approach itself is not necessarily better and more objective than any of the global methods typically used for hotspot identification. Indeed, mathematical and/or statistical approaches should not be viewed as a panacea to solve conservation problems, but rather used in combination with biological, practical, economic and social considerations.