Song repertoire structure, organization, and use were studied in 68 male Canada Warblers (Cardellina canadensis) in a breeding population in New Hampshire in 2010-2011. On average, males had complex repertoires of 12 phrases and 55 variants. Repertoire sharing was negatively related to distance between territories, and positively related to longer territory tenure, evidence that males learn songs from neighbours. Males used two singing modes: (I) slow, regular delivery of less variable songs, and (II) fast, intermittent delivery of more variable songs interspersed with chips. Males used Mode I when unpaired and when near females, and Mode II at dawn and during territory disputes, a pattern similar to other warbler species with two song categories. Detectability (whether a male sang) differed little between 1-, 3-, 5-, and 10-min count intervals. Song output and detectability were highest at dawn and in unpaired males, and lowest in paired males late in the season.

Understanding migratory connectivity is essential for assessing the drivers behind population dynamics and for implementing effective management in migratory species. Genetic markers provide a means to describe migratory connectivity, as well as incorporate population genetic analyses, however genetic markers can be uninformative for species with weak genetic structure. In this study, we evaluate range-wide population genetic structure and migratory connectivity in the prothonotary warbler, Protonotaria citrea, a wetland-dependent neotropical migratory songbird, using high-resolution genetic markers. We reveal regional genetic structure between sampling sites in the Mississippi River Valley and the Atlantic Seaboard with overall weak genetic differentiation among populations (FST = 0.0051). By ranking loci by FST and using subsets of the most differentiated genetic markers (200 – 3000), we identify a maximum assignment accuracy (89.7% to site, 94.3% to region) using 600 single nucleotide polymorphisms. We assign samples from unknown origin nonbreeding sites to a breeding region, illustrating weak migratory connectivity between prothonotary warbler breeding and nonbreeding grounds. Our results highlight the importance of using high-resolution markers in studies of migratory connectivity with species exhibiting weak genetic structure. Using similar techniques, studies may begin to describe population genetic structure that was previously undocumented, allowing us to infer the migratory patterns of an increasing number of species.

<p dir="ltr">Global forest ecosystems provide essential ecosystem services that contribute to water and climate regulation, food production, recreation, and raw materials. They also serve as crucial habitats for numerous terrestrial species of amphibians, birds, and mammals worldwide. However, recent decades have witnessed unprecedented changes in forest ecosystems due to climate change, shifts in species distribution patterns, increased planted forest areas, and various disturbances such as forest fires, insect infestations, and urbanization. These changes can have far-reaching impacts on ecological networks, human well-being, and the well-being of global forest ecosystems. To address these challenges, I present four studies to quantify forest dynamics through mapping, classification, and projection, using artificial intelligence tools in combination with a vast amount of training data. (I) I present a spatially continuous map of planted forest distribution across East Asia, produced by integrating multiple sources of planted and natural forest data. I found that China contributed 87% of the total planted forest areas in East Asia, most of which are located in the lowland tropical/subtropical regions and Sichuan Basin. I also estimated the dominant genus in each planted forest location. (II) I used continent-wide forest inventory data to compare the range shifts of forest types and their constituent tree species in North America in the past 50 years. I found that forest types shifted more than three times as fast as the average of their constituent tree species. This marked difference was attributable to a predominant positive covariance between tree species ranges and the change of species relative abundance. (III) Based on individual-level field surveys of trees and breeding birds across North America, I characterized New World wood-warbler (<i>Parulidae</i>) species richness and its potential drivers. I identified forest type as the most powerful predictor of New World wood-warbler species richness, which adds valuable evidence to the ongoing physiognomy versus composition debate among ornithologists. (IV) In the appendix, I utilized continent-wide forest inventory data from North America and South America and the combination of supervised and unsupervised machine learning algorithms to produce the first data-driven map of forest types in the Americas. I revealed the distribution of forest types, which are useful for cost-effective forest and biodiversity management and planning. Taken together, these studies provide insight into the dynamics of forest ecosystems at a large geographic scale and have implications for effective decision-making in conservation, management, and global restoration programs in the midst of ongoing global change.</p>