Demography and Big Data

Post provided by BRITTANY TELLER, KRISTIN HULVEY and ELISE GORNISH

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To understand how species survive in nature, demographers pair field-collected life history data on survival, growth and reproduction with statistical inference. Demographic approaches have significantly contributed to our understanding of population biology, invasive species dynamics, community ecology, evolutionary biology and much more.

As ecologists begin to ask questions about demography at broader spatial and temporal scales and collect data at higher resolutions, demographic analyses and new statistical methods are likely to shed even more light on important ecological mechanisms.

Population Processes

Midsummer Opuntia cactus in eastern Idaho, USA. © B. Teller.

Midsummer Opuntia cactus in eastern Idaho, USA. © B. Teller.

Traditionally, demographers collect life history data on species in the field under one or more environmental conditions. This approach has significantly improved our understanding of basic biological processes. For example, rosette size is a significant predictor of survival for plants like wild teasel (Werner 1975 – links to all articles are at the end of the post), and desert annual plants hedge their bets against poor years by optimizing germination strategies (Gremer & Venable 2014).

Demographers also include temporal and spatial variability in their models to help make realistic predictions of population dynamics. We now know that temporal variability in carrying capacity dramatically improves population growth rates for perennial grasses and provides a better fit to data than models with varying growth rates because of this (Fowler & Pease 2010). Moreover, spatial heterogeneity and environmental stochasticity have similar consequences for plant populations (Crone 2016). Continue reading

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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