All life on earth

Madingley’s focus at its conception – and first appearance in the academic arena – was an effort to model ‘all life on earth’. An exciting endeavour and something any recently-graduated, aspiring PhD student would jump to be involved in. Cue my entrance three years ago. The reasonable success of Madingley’s broad reconstruction of trophic systems across the globe opened up opportunities for more detailed, and more applied, studies. In our recent Proceedings of the Royal Society B publication, we used Madingley’s ecological systems to study the effects of habitat loss and fragmentation in Kenyan grassland ecosystems – an area of the world where imperious animals such as elephants, giraffes, rhinoceros, and leopards still roam under the protection of reserves.

As demand for land by people increases – partly for living space but more so for new farmland – we have a choice in how we arrange fragments of unmodified animal habitat. There has been widespread concern that fragmenting habitat into many small pieces is detrimental for conservation. However, it has been difficult for scientists to properly separate the effect of fragmenting habits from the more obvious problem of loss of habitat area. It’s unusual for habitat to become fragmented without also becoming smaller, and this question has been at the core of many policies including designing protected areas.

Using the Madingley model, we weren’t constrained by the real-world problems of habitat loss and fragmentation always happening together. We compared how ecosystems in large and small areas of Kenyan savannah responded to different amounts of habitat loss with or without habitat fragmentation. We hoped that Madingley’s full interacting ecosystem would provide good predictive clues as to what kinds of changes accompany habitat loss, and how bad fragmentation may be. Following three years of interrogating model outcomes and much personal scientific growth (a reminder that real people are on the other side of a published paper!), Madingley had played its part in showing us some expected – and a few surprising – predictions about how ecosystems cope with habitat loss and fragmentation.

Fragmentation was a definitively detrimental force in determining how ecosystems respond, but crucially, it acted synergistically with habitat loss – the effect of both fragmentation and loss together made for more ecological changes than considering them alone. The most obvious losers in these changes were the largest animals – the ‘megafauna’ – in the ecosystem. Many conservationist worry that the biggest and most iconic animals are the most sensitive to habitat changes, and our study supports that. If we want to protect our largest animals – such as our giraffes and leopards, fewer big reserves appear to be better than many smaller ones.

The sensitivity of these largest animals, and the synergistic forces of habitat loss and fragmentation, revealed cascading ecological effects where the loss of large animals greatly changed the ecosystem food web. One surprising outcome of this was an apparent overgrowth

of plants – where following the clearing of plants as part of habitat loss, the remaining greenery in the ecosystem was able to compensate for the loss – in the most extreme cases having 70% more plant matter in the ecosystem than expected. As far as we know, our study is the first time this effect has been characterised in its magnitude, and could be crucial in understanding carbon storage and therefore climate change. Mechanisms behind this effect warrant further investigation – it seems apparent that the effect comes about because of changes in the trophic network. For example, the loss of larger herbivores could drive predators to predate smaller prey, reducing overall herbivore numbers and therefore reducing grazing. This kind of surprising finding is exactly the sort of gain to be made from using Madingley – and other models like it; without all trophic levels, these types of feedbacks may not be revealed. Ecology is never simple, and as we can use more complicated models, so more of these important phenomena will likely appear.

Written by Lewis Bartlett @BeesAndBaking Lewis began this work whilst interning at UNEP-WCMC in July 2013. He is now a PhD researcher working on infectious disease evolution and honey bee management at UC Berkeley, California and University of Exeter, UK.

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