The rise of animal biotelemetry and genetics research data integration

Abstract

The advancement and availability of innovative animal biotelemetry and genomic technologies are improving our understanding of how the movements of individuals influence gene flow within and between populations and ultimately drive evolutionary and ecological processes. There is a growing body of work that is integrating what were once disparate fields of biology, and here, we reviewed the published literature up until January 2023 (139 papers) to better understand the drivers of this research and how it is improving our knowledge of animal biology. The review showed that the predominant drivers for this research were as follows: (1) understanding how individual-based movements affect animal populations, (2) analyzing the relationship between genetic relatedness and social structuring, and (3) studying how the landscape affects the flow of genes, and how this is impacted by environmental change. However, there was a divergence between taxa as to the most prevalent research aim and the methodologies applied. We also found that after 2010 there was an increase in studies that integrated the two data types using innovative statistical techniques instead of analyzing the data independently using traditional statistics from the respective fields. This new approach greatly improved our understanding of the link between the individual, the population, and the environment and is being used to better conserve and manage species. We discuss the challenges and limitations, as well as the potential for growth and diversification of this research approach. The paper provides a guide for researchers who wish to consider applying these disparate disciplines and advance the field.

Keywords: animal tracking; biotelemetry; genetics; genomics; individual‐based movement; movement ecology.

FIGURE 1

Distribution of bird (a), fish (b), mammal (c), amphibian, and reptile (d) studies according to the country where they were carried out and the year of publication. The overall sample size was 139, but one study had two study species belonging to different taxa (mammals and birds), thus adding up to 140.

FIGURE 2

Number of publications within five‐year intervals for each study outcome category along with the linear trend of individual‐based and population‐based studies. Detailed descriptions of each category can be found in Figure 5.

FIGURE 3

Discriminant correspondence analysis (DiCA) outcomes. (a) Distribution of latent variable data points inferred from observed data, grouped according to taxa, along with marginal density plots. (b) Contribution of each variable included in the DiCA model to the two dimensions of the data. Those variables explaining a significant amount of the variance in both dimensions are colored in dark blue. The fixed model, used as the training set, showed a classification accuracy of 84%, whereas the random model, used as the validation model (leave‐one‐out), had an accuracy of 70%. λ = eigenvalues, τ = variance explained (%).

FIGURE 4

Temporal distribution of publications according to the research aim (a), the statistical analyses used on the genetic data (b), the genetic markers (c), and the tracking technology used (d) for the three main vertebrate taxa (birds, fish, and mammals). For some variables, the studies could fall into more than one category, thus not adding up to the total number of papers for each taxon. The category ‘Other’ within Genetic markers includes markers that were present in <2 studies (whole genome, polymorphic loci, transcriptomics, and allozymes). The statistical analyses used on the telemetry data did not show any clear temporal patterns, thus not being included in the figure.

FIGURE 5

Proportion of studies falling within each outcome category along with descriptions and examples. The percentages for the overall outcome categories are for the total number of studies (n = 139), whereas the research aim percentages are within each category (linked/nonlinked).

FIGURE A1

PRISMA diagram showing the number of papers included and excluded at each stage.

FIGURE A2

Distribution of studies according to the sample size for the genetics (a) and telemetry (b) data, and the temporal extent for the genetics (c) and telemetry (d) data collection.