Basal Metabolic Rate and Maternal Energetic Investment Durations in Mammals

Background The Metabolic Theory of Ecology (MTE) predicts that gestation duration, lactation duration, and their sum, total development time, are constrained by mass-specific basal metabolic rate such that they should scale with body mass with an exponent of 0.25. However, tests of the MTE’s predictions have yielded mixed results. In an effort to resolve this uncertainty, we used phylogenetically-controlled regression to investigate the allometries of gestation duration, lactation duration, and total development time in four well-studied mammalian orders, Artiodactyla, Carnivora, Primates, and Rodentia. Results The results we obtained are not consistent with the predictions of the MTE. Gestation duration scaling exponents are below 0.25 in all four orders. The scaling exponent for lactation duration is below 0.25 in Carnivora and Rodentia, indistinguishable from 0.25 in Artiodactyls, and steeper than 0.25 in Primates. Total development time scales with body mass as predicted by the MTE in Primates, but not in artiodactyls, carnivores, and rodents. In the latter three orders, the exponent is 0.15. Conclusions Together, these results indicate that the influence of basal metabolic rate on mammalian maternal investment durations must be more complicated than the MTE envisages, and that other factors must play an important role. Future research needs to allow for the possibility that different factors drive gestation duration and lactation duration, and that the drivers of the two durations may differ among orders

Quantifying biodiversity trade-offs in the face of widespread renewable and unconventional energy development

The challenge of balancing biodiversity protection with economic growth is epitomized by the development of renewable and unconventional energy, whose adoption is aimed at stemming the impacts of global climate change, yet has outpaced our understanding of biodiversity impacts. We evaluated the potential conflict between biodiversity protection and future electricity generation from renewable (wind farms, run-of-river hydro) and non-renewable (shale gas) sources in British Columbia (BC), Canada using three metrics: greenhouse gas (GHG) emissions, electricity cost, and overlap between future development and conservation priorities for several fish and wildlife groups - small-bodied vertebrates, large mammals, freshwater fish - and undisturbed landscapes. Sharp trade-offs in global versus regional biodiversity conservation exist for all energy technologies, and in BC they are currently smallest for wind energy: low GHG emissions, low-moderate overlap with top conservation priorities, and competitive energy cost. GHG emissions from shale gas are 1000 times higher than those from renewable sources, and run-of-river hydro has high overlap with conservation priorities for small-bodied vertebrates. When all species groups were considered simultaneously, run-of-river hydro had moderate overlap (0.56), while shale gas and onshore wind had low overlap with top conservation priorities (0.23 and 0.24, respectively). The unintended cost of distributed energy sources for regional biodiversity suggest that trade-offs based on more diverse metrics must be incorporated into energy planning.Peer reviewe

Effects of anthropogenic disturbance on sensitive wildlife and habitats

The cumulative ecological impacts of broad-scale anthropogenic disturbances, such as forestry or energy development, are a challenge to predict and evaluate. Here, I evaluate the potential of future run-of-river (ROR) hydropower development to impact riparian ecosystems in British Columbia, Canada. I found the projected spatial footprint of ROR in the riparian zone to be 40 times smaller than the footprint of existing disturbance from forestry, roads, and powerlines, but concentrated in watersheds that currently have low levels of disturbance. Habitat degradation for small riparian vertebrates from ROR development was cumulative with substantial existing impacts. I also tested whether harvest data in Species Distribution Models can aid in evaluating species responses to logging at different scales and sensitivity levels using a simulation framework. I found that logging becomes a strong predictor of species distributions at landscape scales, or when the spatial heterogeneity of forestry exceeds that of other variables (e.g. climatic or topographical) in the model