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Biology subjects

Kimberley, A.

Publications and source records attributed to Kimberley, A..

2 recordsLinked to original sources

Mutation accumulation underpins evolution of lifespan extension by dietary restriction

Dietary restriction (DR) extends lifespan in animals and plants, but its evolutionary causes are elusive. Adaptive hypotheses posit that DR extends lifespan because organisms reallocate resources from reproduction to survival ( disposable soma) or recycle cellular waste to maximize either their immediate reproduction ( nutrient recycling) or survival ( clean cupboards). We developed an experimental paradigm that tricks Caenorhabditis elegans nematodes into increasing their reproductive effort under DR via food odour, thus allowing us to test these hypotheses. We found that experimentally increased reproduction under DR does not affect immediate or long-term survival benefits compared to DR animals that did not reproduce, thus refuting all three adaptive hypotheses. Our data suggest that a large part of suppressed fertility under DR is a result of organisms refraining from producing offspring in a poor environment. We developed a model based on Hamiltonian forces of selection to show that lifespan extension under DR evolves because DR suppresses fertility, directly increasing selection against mortality in DR environment. Our analytical approach suggests that DR-driven lifespan extension can evolve under a broader range of conditions not previously anticipated, such as a relaxed need for physiological or genetic trade-offs. Instead, we show how reduced survival on plentiful food can evolve via mutation accumulation.

evolutionary biology↗

HistMapR: Rapid digitization of historical land-use maps in R

1. Habitat destruction and degradation represent serious threats to biodiversity, and quantification of land-use change over time is important for understanding the consequences of these changes to organisms and ecosystem service provision.\n\n2. Comparing land use between maps from different time periods allows estimation of the magnitude of habitat change in an area. However, digitizing historical maps manually is time-consuming and analyses of change are usually carried out at small spatial extents or at low resolutions.\n\n3. We developed a method to semi-automatically digitize historical land-use maps using the R environment. We created a number of functions that use the existing raster package to classify land use according to a maps colours, as defined by the RGB channels of the raster image. The method was tested on three different types of historical land-use map and results were compared to manual digitisations.\n\n4. Our method is fast, and agreement with manually-digitised maps of around 80-92% meets common targets for image classification. We hope that the ability to quickly classify large areas of historical land-use will promote the inclusion of land-use change into analyses of biodiversity, species distributions and ecosystem services.

ecology↗