Individual energetics scale up to community coexistence: Movement, metabolism and biodiversity dynamics in fragmented landscapes.

Unravelling the intricate mechanisms that govern community coexistence remains a daunting challenge, particularly amidst ongoing environmental change. Individual physiology and metabolism are often studied to understand the response of individual animals to environmental change. However, this perspective is currently largely lacking in community ecology. We argue that the integration of individual metabolism into community theory can offer new insights into coexistence. We present the first individual-based metabolic community model for a terrestrial mammal community to simulate energy dynamics and home range behaviour in different environments. Using this model, we investigate how ecologically similar species coexist and maintain their energy balance under food competition. Only if individuals of different species are able to balance their incoming and outgoing energy over the long-term will they be able to coexist. After thoroughly testing and validating the model against real-world patterns such as of home range dynamics and field metabolic rates, we applied it as a case study to scenarios of habitat fragmentation - a widely discussed topic in biodiversity research. First, comparing single-species simulations with community simulations, we find that the effect of habitat fragmentation on populations is strongly context-dependent. While populations of species living alone in the landscape were mostly positively affected by fragmentation, the diversity of a community of species was highest under medium fragmentation scenarios. Under medium fragmentation, energy balance and reproductive investment were also most similar among species. We therefore suggest that similarity in energy balance among species promotes coexistence. We argue that energetics should be part of community ecology theory, as the relative energetic status and reproductive investment can reveal why and under what environmental conditions coexistence is likely to occur. As a result, landscapes can potentially be protected and designed to maximize coexistence. The metabolic community model presented here can be a promising tool to investigate other scenarios of environmental change or other species communities to further disentangle global change effects and preserve biodiversity.

Schumann resonance and cardiovascular hospital admission in the area of Granada, Spain: An event coincidence analysis approach.

The study of bio-effects of Schumann resonances is a very complex issue. There is a need to identify mechanisms and pathways that explain how Extremely Low Frequency magnetic fields affect biology or human health. This particular study tries to identify statistical associations between ELF magnetic fields in the province of Granada (Spain) and cardiovascular related hospital admission in the same province for the period April, 1st 2013 to March, 31st 2014. Research is developed under an epidemiological approach based on an Event Coincidence Analysis statistical method. Clustered events, statistically significant (ECA shuffle-surrogate test p = .01 and p < .01), were found for the minimum values of the first and the third Schuman resonances frequency on east-west and north-south directions, and for the amplitude parameter of the second resonance and the total signal energy in the north-south direction. Empirical measurements of SR parameters were recorded at the Sierra Nevada Mountain in Granada province (Spain). Results show a clear coincidence of the events for the minima amplitudes of Shuman resonances and energy in the north-south orientation and the number of the cardiovascular related hospital admissions. Further research is needed with longer temporal series and a new approach based on gender seems to be also interesting for future studies.