DOI: 10.5061/dryad.bg79cnpbb
title: Biodiversity scale-dependence and opposing multi-level correlations underlie differences among taxonomic, phylogenetic, and functional diversity

description: Aim: Biodiversity is a multi-dimensional property of biological
 communities that represents different information depending on how it is
 measured, but how dimensions relate to one another and under what
 conditions is not well understood. We explore how taxonomic, phylogenetic,
 and functional diversity can differ in scale-of-effect dependence and
 habitat-biodiversity relationships, and subsequently how spatial
 differences among biodiversity dimensions may arise. Location: Nebraska,
 United States Time period: May-July 2016, 2017 Major taxa studied: Birds
 Methods: Across 2016 and 2017, we conducted 2,641 point counts at 781
 sites. We modeled the occupancy of 141 species using Bayesian
 Bernoulli-Bernoulli hierarchical logistic regressions. We calculated
 species richness (SR), phylogenetic diversity (PD), and functional
 diversity (FD) for each site and year based on predicted occupancy,
 accounting for imperfect detection. Using Bayesian latent indicator scale
 selection and multivariate modeling, we quantified the spatial
 scales-of-effect that best explained the relationships between
 environmental characteristics and SR, PD, and FD. Additionally, we
 decomposed the residual between- and within-site biodiversity correlations
 using our repeated measures design. Results: We demonstrate spatial
 differences among biodiversity predictions, arising from scale-dependence
 in habitat-biodiversity relationships and variation in correlation
 structure among biodiversity dimensions. Although relationships between
 specific land cover types and SR, PD and FD were qualitatively similar,
 the spatial scales at which these variables were important in explaining
 biodiversity differed among dimensions. Between-site residual biodiversity
 correlations were negative, yet within-site biodiversity residual
 correlations were positive. Main conclusions: Our results demonstrate how
 spatial differences among biodiversity dimensions may arise from
 biodiversity-specific scale-dependent habitat relationships, low shared
 environmental correlations and opposing residual correlations between
 dimensions, which suggest that single-scale and single-dimension analyses
 are not entirely appropriate for quantifying habitat-biodiversity
 relationships. After accounting for shared habitat relationships, we found
 positive within-site residual correlations between taxonomic,
 phylogenetic, and functional diversity, suggesting that habitat change
 over time influenced all biodiversity dimensions relatively similarly.
 However, negative between-site residual correlation among biodiversity
 dimensions may indicate trade-offs in achieving maximum biodiversity
 across multiple biodiversity dimensions at any given location. Although
 habitat management can to a limited degree improve biodiversity relatively
 across all metrics, other environmental effects may ensure that not all
 facets of biodiversity can be maximized at once. If maximizing a specific
 biodiversity dimension is the goal, then care should be taken to consider
 these within-site residual correlations.
description: Bird surveys: We conducted 500 m fixed radius
 avian point count surveys during the breeding seasons (mid-April to
 late-June) of 2016 and 2017, on publicly accessible secondary and tertiary
 roads across Nebraska, USA. Sites were grouped into ‘routes’ consisting of
 7-19 point count locations such that all sites in each route could be
 visited within one morning. Additional routes were created in 2017 to
 include several of Nebraska’s Biologically Unique Landscapes, which are
 managed for declining rare species and unique natural communities. During
 surveys, trained observers recorded every bird seen or heard within a
 three-minute period (i.e., a visit), which occurred between 15 minutes
 before sunrise and 10 A.M: the time at which avian vocalizations are
 greatest and most consistent across species (Hutto et al., 1986). We did
 not perform surveys during inclement weather, including fog, drizzle,
 prolonged rain, and wind with speeds &gt;20 kmh. 
 Land cover: Survey sites were selected based
 on generalized random tessellation stratified sampling, which randomly
 distributed sampling sites across 6 a priori-selected land cover types
 (based on a 30m resolution land cover product developed by the Rainwater
 Basin Joint Venture: Bishop et al., 2011) to spatially balance our
 sampling by mimicking the spatial variation across habitat gradients in
 Nebraska (Stevens Jr & Olsen, 2004). Using the Rainwater Basin
 Joint Venture land cover product, we calculated the proportions of each
 land cover variable within 0.5 km, 1km, 2km, 5km, 10km, 15km, and 20km
 radius spatial scales surrounding our sampling locations.
 Functional traits: We built a functional
 dendrogram based on 23 functional traits: four reproductive traits, ten
 diet traits, one binary activity trait, one body size trait, and seven
 foraging strategy traits (Petchey et al., 2007). Trait information was
 compiled from “The Birds of North America” series from the American
 Ornithologists’ Society (Rodewald, 2015), the “Elton Traits 1.0” species
 foraging characteristics database for extant birds (Wilman et al., 2014),
 and the <i>CRC Handbook of Avian Body Masses</i> (Dunning Jr,
 2007).
description: Location
 data (i.e., GPS coordinates) was not used in the analysis and thus was not
 included in the uploaded datasets to protect the privacy of the
 surrounding residents.  Files
 included: Bird surveys:
 1. PC2016-2017_Full_detection.csv 2.
 README-PC2016-2017_Full_detection.txt Land
 cover: 1. PC_landcover.csv
 2. README-PC_landcover.txt Functional
 traits: 1.
 PC_FullTraits_2016_2017.csv 2.
 README-PC_FullTraits_2016_2017.txt