Null models and spatial patterns of species richness in South American birds of prey

Abstract

In this paper, we used geostatistical approaches to describe bi‐dimensional spatial patterns in species richness of South American birds of prey (Falconiformes and Strigiformes). They indicated strong spatial patterns both across latitude and longitude, for the two groups. These patterns were then correlated with those expected by a bi‐dimensional null model constructed to take into account South America continental edges. As considerable departures from the null model were observed, there may be other ecological or evolutionary explanations for spatial patterns in species richness. Variation seems to be related to habitat heterogeneity across the continent, especially when considering differences between habitats in the central and south‐eastern portion of the continent and in the Andean region. This supports previous conclusions that habitat type and heterogeneity affect species richness and abundance at different spatial scales.

The Mid‐Domain Effect and Species Richness Patterns:What Have We Learned So Far?

“…In two dimensions, if polygons (representing geographic ranges) are randomly placed within a bounded area (for example, on the map of a continental area, for terrestrial species), a peak of polygon overlap (species richness) is produced near the center of the area (Ney-Nifle and Mangel 1999;Bokma et al 2001;Jetz andRahbek 2001, 2002;Diniz-Filho et al 2002;Hawkins and Diniz-Filho 2002;Laurie and Silander 2002). The polygons may be irregular and concave in shape, produced by algorithms (such as the "spreading dye" model of Jetz and Rahbek [2001]) that explicitly model the spread of a species geographic range in a gridded coordinate space according to a specified algorithm.…”

“…MDE model predictions depend crucially on the frequency distribution of range sizes (range size frequency distribution [RSFD]) from which "ranges" (line segments or polygon areas) are randomly sampled and randomly placed within the domain (Colwell and Hurtt 1994;Lees et al 1999;Colwell and Lees 2000a;Koleff and Gaston 2001;Diniz-Filho et al 2002;Laurie and Silander 2002;McCain 2003). Two otherwise identical MDE models with different RSFDs produce different patterns of richness when ranges are placed randomly on a domain (Colwell and Hurtt [1994] and Laurie and Silander [2002] provide theoretical examples, and Koleff and Gaston [2001] and McCain [2003] provide empirical ones).…”

“…McCain (2003) gives an empirical demonstration of the effect of confounding differences due to range placement with differences due to deviation of the theoretical RSFD from the empirical RSFD. Hawkins and Diniz-Filho (2002) and Diniz-Filho et al (2002) relied solely on the two-dimensional fully stochastic model, whereas Willig and Lyons (1998) and Laurie and Silander (2002) used the onedimensional fully stochastic model to assess the role of MDE in empirical richness patterns, suggesting that the fit to MDE was probably underestimated in these studies. See "RSFDs and Model Choice in Assessing MDE" in appendix C for additional comments and critique.…”

Identifying the spatial mixture distribution of bird diversity across urban and suburban areas in the metropolis: A case study in Taipei Basin of Taiwan

“…The conditional probability cumulative distribution function (ccdf) can be modeled using parametric approaches (e.g., a multivariate Gaussian distribution) (Goovaerts, 2001). Recent examples of using geostatistical methods to study bird distribution, species richness, and biodiversity include the works of Diniz-Filho, de Sant'Ana, de Souza, & Rangel (2002), Foster, Tweed, Camp, & Woodworth (2004), Jiguet & Julliard (2006), Walker et al, 2008, andLin et al (2008a).…”

Priority areas for anuran conservation using biogeographical data: a comparison of greedy, rarity, and simulated annealing algorithms to define reserve networks in Cerrado

“…granulosus) were excluded from our dataset (see Diniz-Filho et al, in press (a), for details). The occurrence of these species in South America was registered on a standardized map thereof (Azimuthal projection, scale 1:40,000,000) covered by a grid with 780 quadrats with sides of approximately 135 km (Bini et al, 2000;Diniz-Filho et al, 2002), based on extensive data in the literature as well as on records of the Museu Nacional (Universidade Federal do Rio de Janeiro). The cerrado biome in this grid was then delineated based on a map of Instituto Brasileiro de Geografia e Estatística (IBGE) and UNESCO (1981) (Fig.…”