Conditional Occupancy Design Explained

Occupancy surveys are widely used in ecology to study wildlife and plant habitat use. To account for imperfect detection probability many researchers use occupancy models. But occupancy probability estimates for rare species tend to be biased because we’re unlikely to observe the animals at all and as a result, the data aren’t very informative.

In their new article – ‘Occupancy surveys with conditional replicates: An alternative sampling design for rare species‘ – Specht et al. developed a new “conditional” occupancy survey design to improve occupancy estimates for rare species, They also compare it to standard and removal occupancy study designs. In this video two of the authors, Hannah Specht and Henry Reich, explain how their new conditional occupancy survey design works. 

This video is based on the article ‘Occupancy surveys with conditional replicates: An alternative sampling design for rare species‘ by Specht et al.

 

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Statistical Ecology Virtual Issue

StatEcolVI_WebAdAt the last ISEC, in Montpellier in 2014, an informal survey suggested that Methods in Ecology and Evolution was the most cited journal in talks. This reflects the importance of statistical methods in ecology and it is one reason for the success of the journal. For this year’s International Statistcal Ecology Conference in Seattle we have produced a virtual issue that presents some of our best recent papers which cross the divide between statistics and ecology. They range over most of the topics covered at ISEC, from statistical theory to abundance estimation and distance sampling.

We hope that Methods in Ecology and Evolution will be equally well represented in talks in Seattle, and also – just as in Montpellier – some of the work presented will find its way into the pages of the journal in the future.

Without further ado though, here is a brief overview of the articles in our Statistical Ecology Virtual Issue: Continue reading

On the Tail of Reintroduced Canada Lynx: Leveraging Archival Telemetry Data to Model Animal Movement

Post provided by FRANCES E. BUDERMAN

Animal Movement

218 Canada lynx were reintroduced to the San Juan Mountains between 1999 and 2006 with VHF/Argos collars. © Colorado Parks and Wildlife

218 Canada lynx were reintroduced to the San Juan Mountains between 1999 and 2006 with VHF/Argos collars. © Colorado Parks and Wildlife

Animal movement is a driving factor underlying many ecological processes including disease transmission, extinction risk and range shifts. Understanding why, when and how animals traverse a landscape can provide much needed information for landscape-level conservation and management practices.

The theoretical underpinnings for modelling animal movement were developed about seventy years ago. Technological developments followed, with radio-collars initially deployed on large mammals such as grizzly bears and elk. We can now monitor animal movement of a wide variety of species, including those as small as a honeybee, at an unprecedented temporal and spatial scale.

However, location-based data sets are often time consuming and costly to collect. For many species, especially those that are rare and elusive, pre-existing data sets may be the only viable data source to inform management decisions. Continue reading