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Abstract A prominent challenge for managing migratory species is the development of conservation plans that accommodate spatiotemporally varying distributions throughout the year. Migratory networks are spatially‐explicit models that incorporate migratory assignment and seasonal abundance data to define patterns of connectivity between stages of the annual cycle. These models are particularly useful for widespread application because different types of migratory data can be used to quantify individual and population‐level movement across the annual cycle of migratory species. While there are clear benefits of combining migratory assignment and abundance data for the development of conservation strategies, there is a concurrent need for corresponding user‐friendly software to facilitate the integration of these data for conservation.Here, we presentmignette(migratory network tools ensemble), an R package for developing migratory network models to estimate network connectivity among migratory populations. We demonstrate the functionality ofmignettewith three empirical examples that highlight the use of different types of tracking data for migratory assignment.mignettefacilitates the modelling of migratory networks by providing R functions to: (1) define breeding and nonbreeding nodes, (2) assemble abundance and assignment data and (3) model the migratory network. Additionally,mignetteprovides R functions to visualize modelled migratory networks.With increasing availability of migratory assignment and abundance data,mignetterepresents a valuable tool for developing effective conservation strategies for migratory species. 

Abstract Tracking climatic conditions throughout the year is often assumed to be an adaptive behaviour underlying seasonal migration patterns in animal populations. We investigate this hypothesis using genetic markers data to map migratory connectivity for 27 genetically distinct bird populations from 7 species. We found that the variation in seasonal climate tracking across our suite of populations at a continental scale is more likely a consequence, rather than a direct driver, of migratory connectivity, which is primarily shaped by energy efficiency—i.e., optimizing the balance between accessing available resources and movement costs. However, our results also suggest that regional‐scale seasonal precipitation tracking affects population migration destinations, thus revealing a potential scale dependency of ecological processes driving migration. Our results have implications for the conservation of these migratory species under climate change, as populations tracking climate seasonally are potentially at higher risk if they adapt to a narrow range of climatic conditions. 

Abstract Global loss of biodiversity has placed new urgency on the need to understand factors regulating species response to rapid environmental change. While specialists are often less resilient to rapid environmental change than generalists, species‐level analyses may obscure the extent of specialization when locally adapted populations vary in climate tolerances. Until recently, quantification of the degree of climate specialization in migratory birds below the species level was hindered by a lack of genomic and tracking information, but recent technological advances have helped to overcome these barriers. Here we take a genome‐wide genetic approach to mapping population‐specific migratory routes and quantifying niche breadth within genetically distinct populations of a migratory bird, the willow flycatcher (Empidonax traillii), which exhibits variation in the severity of population declines across its breeding range. While our sample size is restricted to the number of genetically distinct populations within the species, our results support the idea that locally adapted populations of the willow flycatcher with narrow climatic niches across seasons are already federally listed as endangered or in steep decline, while populations with broader climatic niches have remained stable in recent decades. Overall, this work highlights the value of quantifying niche breadth within genetically distinct groups across time and space when attempting to understand the factors that facilitate or constrain the response of locally adapted populations to rapid environmental change.