Where do Animals Spend Their Time and Energy? Theory, Simulations and GPS Trackers Can Help Us Find Out

Post provided by MATT MALISHEV (@DARWINANDDAVIS)

 An adult sleepy lizard with a GPS tracker and body temperature logger strapped to her tail. ©Mike Bull.


An adult sleepy lizard with a GPS tracker and body temperature logger strapped to her tail. ©Mike Bull.

Changes in temperature and available food determine where and when animals move, reproduce, and survive. Our understanding of how environmental change impacts biodiversity and species survival is well-established at the landscape, country and global scales. But, we know less about what could happen at finer space and time scales, such as within habitats, where behavioural responses by animals are crucial for daily survival.

Simulating Movement and Daily Survival with Individual-Based Movement Models

Key questions at these scales are how the states of individuals (things like body temperature and nutritional condition) influence movement decisions in response to habitat change, and how these decisions relate to patchiness in microclimates and food. So we need tools to make reliable forecasts of how fine-scale habitat use will change under future environments. Individual-based movement simulation models are powerful tools for these kinds of studies. They let you construct habitats that vary in temperature and food conditions in both space and time and ask ‘what if’ questions. By populating these models with activity, behaviour, and movement data of animals, we can simulate different habitat conditions and predict how animals will respond to future change. Continue reading

Issue 7.8

Issue 7.8 is now online!

The August issue of Methods is now online!

This month’s issue contains two Applications articles and two Open Access articles, all of which are freely available.

Plant-O-Matic: A free iOS application that combines the species distribution models with the location services built into a mobile device to provide users with a list of all plant species expected to occur in the 100 × 100 km geographic grid cell corresponding to the user’s location.

RClone: An R package built upon genclone software which includes functions to handle clonal data sets, allowing:

  • Checking for data set reliability to discriminate multilocus genotypes (MLGs)
  • Ascertainment of MLG and semi-automatic determination of clonal lineages (MLL)
  • Genotypic richness and evenness indices calculation based on MLGs or MLLs
  • Describing several spatial components of clonality

Continue reading