Migratory Connectivity

Migratory connectivity describes how populations co-occur throughout the annual cycle. The ability to study migratory connectivity has increased dramatically in the past decade, thanks to technological advances for documenting large-scale animal movement (e.g., GPS tracking, band recoveries, genetics). There are two components of migratory connectivity:

  1. Pattern: Linking the geography of where individuals and populations occur between seasons.
  2. Strength: The extent, or strength, of co-occurrence of individuals and populations between seasons.

Our migratory connectivity research makes use of banding-reencounter datasets, tracking, intrinsic markers (stable isotopes, genetics), and data integration methodologies. Much of our ongoing migratory connectivity work is in collaboration with the Bird Genoscape Project, Migratory Connectivity Project, and U.S. Fish and Wildlife Service, Migratory Bird Program.

MigConnectivity R package

This package was developed to advance the field with the MC metric to standardize quantification of the strength of migratory connectivity across species, study designs types of data, and phases of the annual cycle. MC incorporates uncertainty from sources of sampling error inherent to different data types and accounts for the relative abundance of populations across a species’ breeding or non-breeding range. See: Cohen, Hostetler et al. (2018)

The package’s vignette gives examples and further details.

Download the Package: https://github.com/SMBC-NZP/MigConnectivity#readme

Methods blog post: Sticking Together or Drifting Apart? Quantifying the Strength of Migratory Connectivity

Methods video abstract: How Can We Quantify the Strength of Migratory Connectivity?

MigConnectivity Data Integration

Here we introduce new analytical approaches for estimating both the pattern and strength of migratory connectivity through data integration. We provide methods for using any combination of GPS/telemetry, light-level geolocator, stable isotope, genetics (genoscape), and band reencounter data collected from the same or different individual animals to estimate patterns and strength between any two phases of the annual cycle. Using simulation, we assess when data integration can improve accuracy including the role of sampling relative to abundance, incomplete sampling, and sample size. See new package updates here: https://github.com/SMBC-NZP/MigConnectivity#readme

En Route Migratory Connectivity

The strength of migratory connectivity is a measure of the cohesion of populations among phases of the annual cycle, including between breeding, migratory, and wintering phases. We found support for a temporal component to migratory connectivity strength with southern breeding populations migrating earlier along the same routes than northern breeding populations. However, this pattern of temporal differentiation varied among species and routes. This work addresses an essential gap in methodology and understanding of the extent to which populations remain together during migration, information critical for a full annual cycle perspective on the population dynamics and conservation of migratory animals. See: Cohen et al. (2019)

Publications

Hostetler JA, Cohen EB, Bossu CM, Scarpignato AL, Ruegg K, Contina A, Rushing CS, Hallworth MT (in review) Challenges and opportunities for data integration to improve estimation of migratory connectivity. Methods in Ecology and Evolution

Roberts A, Scarpignato AL, Huysman A, Hostetler JA, Cohen EB (2023) Migratory connectivity of North American waterfowl across administrative flyways. Ecological Applications 33: e2788

Marra PP, Cohen EB, Harrison A-L, Studds CE, and Webster M (2019) Migratory Connectivity. Chapter in Choe, J (ed) Encyclopedia of Animal Behavior. Oxford: Oxford Academic Press. Pages 643-654.

Cohen, EB, Rushing CR, Moore FR, Hallworth MT, Hostetler JA, Gutierrez Ramirez M, Marra PP (2019) The strength of migratory connectivity for birds en route to breeding through the Gulf of Mexico. Ecography 42: 658-669

Cohen EB, Hostetler JA, Hallworth MT, Rushing CS, Sillett TS, and Marra PP (2018) Quantifying the strength of migratory connectivity. Methods in Ecology and Evolution 9: 513-524

Culp LA, Cohen EB, Scarpignato A, and Marra PP (2017) Full annual cycle climate change vulnerability assessments. Ecosphere 8: e01565

Marra PP, Cohen EB, Loss SR, Rutter JE, and Tonra CM (2015) A call for full annual cycle research in animal ecology. Biology Letters 11: 20150552

Thorup K, Korner-Nievergelt F, Cohen EB, and Baillie SR (2014) Large-scale spatial analysis of ringing and re-encounter data to infer movement patterns: A review including methodological perspectives. Methods in Ecology and Evolution 5: 1337–1350

Cohen EB, Hostetler JA, Royle JA, Marra PP (2014) Estimating migratory connectivity of birds when encounter probabilities are heterogeneous. Ecology and Evolution 4: 1659-1670

 

Cover Photo by Claire Nemes