The evolution of different cranial kinesis types in modern birds has likely driven some spectacular adaptive radiations. However, in certain taxonomic groups, the functional role of new kinesis types remains unclear. This is the case of furnariids, a family of neotropical passerines known for their stunning nest diversity and ecomorphological disparity. These birds exhibit two types of kinesis, each showing different degrees of craniofacial modularity and representing a distinct regime of evolutionary convergence in both beak and neurocranium. Nevertheless, the extrinsic factors shaping the traits associated with kinesis remain unknown. In this study, we assessed correlations between shape, kinesis type, and six ecological variables, alongside the role of kinesis in transitions toward domed nests and open habitats. We found that nest type and diet shaped the evolution of beak and cranial kinesis traits, while diet, foraging behavior, foraging strata, and primary habitat structure influenced neurocranium evolution. Specifically, the emergence of rhynchokinesis predicts the evolution of domed nests and the colonization of less forested environments. We discuss the role of modularity in the association between shape and ecology, the evolution of functional novelties in both kinetic groups, and the hierarchical order of ecomorphological diversity evolution through stages of the adaptive radiation.

*Any references to Supplementary Figures and Appendices refer to materials included in the associated manuscript and are not part of the files deposited in this Dryad repository. Users should consult the published article to access these materials.

Morphological data and phylogenetic hypothesis

Variation in beak and neurocranium shape was quantified through geometric morphometrics (hereafter GM) using a previously published dataset of 83 species of Furnariidae (Stefanini et al., 2025). For this work, we sampled two additional species, namely, Ochetorynchus phoenicurus and Xiphorhynchus obsoletus (see Supplementary Table S1 for information on specimens used in this work).

A total of 17 anatomical landmarks and 33 curve semilandmarks were digitized on photographs taken in lateral view of each specimen using Stereomorph (v. 1.6.7) (Olsen & Westneat, 2015), as this view captures the main morphological features associated with cranial kinesis and beak function in birds. We used the landmark and sliding semilandmark configuration defined in Stefanini et al. (2025). Based on the craniofacial modularity results reported therein, beak and neurocranium landmarks were analyzed as separate datasets in the present study. Landmark positions and numbering used here are shown in Supplementary Figure S3 and described in Supplementary Table S2. Neurocranium landmarks correspond to landmarks 7–17 in Stefanini et al. (2025) but are renumbered here from 1 to 11 for clarity.

Curve semilandmarks (Bookstein, 1997) capturing the shape of the naris, tomium, and culmen, were slid until minimizing bending energy (Gunz et al., 2005). Differences in scale, position, and orientation among specimens were removed by means of Generalized Procrustes Analysis (hereafter GPA, Gower, 1975) performed separately in beak and neurocranium. Beak and neurocranium sizes were measured using the log-transformed centroid size (log-CS) of each specimen prior to GPA. To obtain species means of shapes and sizes, Procrustes shape coordinates and log-CS were averaged within each species. The mean Procrustes coordinates retrieved were subjected to a second round of GPA superimposition to obtain shape coordinates capturing the full intraspecific variation (hereafter full-shape). In addition, a second set of shape coordinates devoid of allometric variation (hereafter non-allometric shape) was estimated by computing the phylogenetically corrected shape residuals resulting from the linear regression of the full shape on log-CS (Klingenberg, 1996). To summarize shape variation, a principal component analysis was carried out for both datasets (i.e., full shape and non-allometric shape) in the neurocranium and beak (i.e., rostrum including the naris). Phylomorphospaces using the first two Principal Components were generated for the four datasets, to visualize the phenotypic change and its relationship with ecological variables in both evolutionary modules with and without the contribution of evolutionary allometry. All these analyses were performed within the R programming environment (R Core Team, 2022) using the Morpho (v. 2.12) (Schlager, 2017), geomorph (v. 4.0.8) (Baken et al., 2021), morphospace (v. 0.009) (Milla Carmona et al., 2025), and phytools (v. 2.3-0) (Revell, 2012) packages.

The phylogenetic relationships among furnariid species that we used in comparative analyses were obtained by trimming the phylogeny of suboscine passerines retrieved by Harvey et al. (2020). 

Cranial Kinesis quantification

The degree of intrarostral mobility of the furnariid skull was obtained from a semiquantitative variable called Kinetic Index (KI) (Claramunt, 2010), derived from a previously published dataset of 105 species, including the 83 species analyzed in the GM dataset described above plus 22 additional species (see Supplementary Table S1 and Stefanini et al., 2025). For this dataset, we also coded KI values for the two additional species mentioned above. The resulting dataset of 107 species represents 52 genera (covering 75% of all currently recognized genera; sensu Clements et al., 2022), three subfamilies (i.e., Sclerurinae, Dendrocolaptinae, and Furnariinae), and all monophyletic clades of Furnariidae (i.e., tribes; sensu Harvey et al., 2020). Kinetic Index comprises three morphological traits of the proximal region of the bony beak that are considered proxies of proximal rhynchokinesis: caudal extension of the nares when located posterior to the craniofacial hinge, a rostrally flattened ventral bar, 'slit-like gap' at the junction between the ventral and lateral bar of the nares (Claramunt, 2010; Stefanini et al., 2016; Stefanini et al., 2025, see Supplementary Figure S1). The sum of the states adopted by these three traits could range from 0 to 7, where 0 represents skulls without intrarostral mobility (i.e., solid prokinesis, sensu Claramunt 2010) and 7 represents skulls with the higher degree of intrarostral mobility (i.e., full-proximal rhynchokinesis, sensu Claramunt 2010; see Supplementary Figure S1 for more information about the states of each character and examples on how KI was scored). KI was developed by Claramunt (2010) to quantify variation in intrarostral kinetic capacities within the family Furnariidae. Consequently, the index is meaningful only when comparing prokinetic and proximal rhynchokinetic species, and akinetic skulls (in which cranial kinesis is absent) and distal or double rhynchokinesis (which involve greater intrarostral mobility than proximal rhynchokinesis) fall outside the range captured by KI. We used this index to assess different hypotheses of phylogenetic causal pathways among cranial kinesis, nest type and primary habitat in the 107 species, and to assess if the correlation between shape of skulls and the ecological variables of interest differs among the cranial kinesis types in the GM dataset composed by 85 species.

Ecological variables

Six ecological variables were used in this study: primary habitat, type of nest, nests attributes, dietary items, foraging strata and foraging behavior (see Supplementary Appendix S1 for more information). The first two variables were coded as univariate categorical vectors and the last four as multivariate matrices. The type of nest was scored as cavities (constructed and pre-existent cavities in trees and constructed and pre-existent burrows) and domed nests (closed vegetative nests, exposed or within cavities). Nests attributes comprise three categories: location of the nest, architecture (i.e., non-woven cavities versus different types of nests interwoven with plant material), and the kind of material used (Supplementary Appendix S1). Data of nests of each species was mainly taken from Narosky (1983), Zyskowski and Prum (1999), De La Peña (2013), and from Handbook of Birds of the World Alive (Winkler et al., 2020). We scored primary habitat following Tobias et al. (2014) into three structural categories: dense (closed-canopy forest), semi-open (open woodland/shrublands), and open (grasslands and deserts). Dietary items were scored into six categories (i.e., invertebrates, terrestrial vertebrates, fish, fruit, seeds, other plant material). Foraging strata was scored into four categories (i.e., ground, understory, mid-high and canopy). The categories for these two variables were taken and modified from Wilman et al. (2014), and were coded using the proportional representation of each dietary item consumed or the proportion of occurrence of each species foraging within a given stratum. The foraging behavior variable was constructed using 14 related categories developed by Felice et al. (2019), which combines information of diet, foraging microhabitat, foraging strategy, and foraging strata (Supplementary Appendix S1; see Felice et al., 2019 for information about the criteria used to construct the categories and the protocol followed to translate qualitative ecological information into semi-quantitative scores). Four of the 107 species (Roraimia adusta, Synallaxis cabanisi, Microxenops milleri, and Berlepschia rikeri) lacked data on nest type (Supplementary Appendix S1). Consequently, the nest-related variables (nest type and nest attributes) were compiled excluding these species. B. rikeri, unlike the other three, was part of the geometric morphometrics dataset of 85 species. Therefore, statistical analyses that incorporated nest information and geometric morphometric data were conducted using a subset excluding B. rikeri.

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