Bioregions of Eastern Brazil, Based on Vascular Plant Occurrence Data

Reginato, Marcelo; Michelangeli, Fabián A.

doi:10.1007/978-3-030-31167-4_18

Cited by 7 publications

(3 citation statements)

References 67 publications

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“…The biogeographical segregation of inselbergs supports recent studies showing floristic differences between inselbergs found in the Atlantic Forest versus those in the Caatinga biome (de Paula et al, 2018;Barbosa-Silva et al, 2022). It is also coherent with more comprehensive regionalizations, such as those presented by Reginato & Michelangeli (2020). In fact, there is a long-standing perception among scientists that geomorphological differences between inselbergs in northeast and southeast Brazil (Ab′Sáber, 1967) might drive compositional variation of their rupicolous flora.…”

Section: Lithobiomes In Eastern South Americasupporting

confidence: 84%

“…We emphasize that, wherever possible, field surveys should include sampling of all plant life forms, enabling future studies to understand overall patterns of compositional similarity between lithobiomes and other vegetation types. Since the six lithobiomes seem to extrapolate recently defined bioregions for eastern Brazil (Reginato & Michelangeli, 2020), looking at rocky ecosystems as a distinct unit could bring new insights regarding rock outcrops as island‐like ecosystems (Itescu, 2019). Of specific concern to studies in conservation biogeography would be to test how the proportion of species listed as “restricted” to a given lithobiome in our analyses compares to the proportion that are strictly endemic to each lithobiome, that is, not found in the surrounding matrix and/or in other rock outcrop types.…”

Section: Discussionmentioning

confidence: 99%

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On the rocks: Biogeography and floristic identity of rocky ecosystems in eastern South America

Azevedo,

Zappi,

de Oliveira

et al. 2024

J of Sytematics Evolution

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The geodiversity of rocky ecosystems includes diverse plant communities with specific names, but their continental‐scale floristic identity and the knowledge on the role of macroclimate remain patchy. Here, we assessed the identity of plant communities in eastern Brazil across multiple types of rocky landscapes and evaluated the relative importance of climatic variables in constraining floristic differentiation. We provided lists of diagnostic species and an assessment of the conservation status of the identified floristic groups. We compiled a data set of 151 sites (4498 species) from rocky ecosystems, including campos rupestres, campos de altitude, granitic‐gneiss lowland inselbergs, and limestone outcrops. We used unsupervised clustering analysis followed by ANOSIM to assess floristic groups among sites. We performed a random forest variable selection to test whether the identified floristic groups occupy distinct climatic spaces. Six groups (lithobiomes) segregated floristically according to lithology and climate. Alongside campos de altitude and limestone outcrops, inselbergs were divided according to the biome in which they occur (Atlantic Forest or Caatinga), and campos rupestres were largely segregated according to their lithological matrix (ironstone or quartzitic). Plant communities of Caatinga inselbergs were more similar to limestone outcrops, while Atlantic Forest inselbergs communities resembled campos de altitude. The composition of plant communities on outcrops seems to be largely constrained by lithology, but climatic factors are also meaningful for sites with similar lithology. The current network of protected areas does not cover these unique ecosystems and their floristic heterogeneity, with Caatinga inselbergs and limestone outcrops being the least protected.

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Section: Lithobiomes In Eastern South Americasupporting

confidence: 84%

Section: Discussionmentioning

confidence: 99%

On the rocks: Biogeography and floristic identity of rocky ecosystems in eastern South America

Azevedo,

Zappi,

de Oliveira

et al. 2024

J of Sytematics Evolution

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“…Models trained with larger presence datasets tend to perform better due to improved sampling of environmental tolerances of species and reduced sampling bias (Araújo & Guisan, 2006; Stockwell & Peterson, 2002). Occurrence data are rapidly being digitized and disseminated online (Reginato & Michelangeli, 2020; Zurell, Franklin, et al, 2020; Petersen et al, 2021), but the records are available for a small percentage of existing specimens, which may themselves represent a fraction of global plant diversity (Marsico et al, 2020). Additionally, collections are often reduced to plants that are easy to acquire due to their accessible locations (Elith & Leathwick, 2009; Kadmon et al, 2004) whereas factors such as difficulty of handling and preserving cacti specimens (Baker et al, 1985; Fosberg, 1932) or narrow endemism and rarity (Ferrier & Guisan, 2006; Papeş & Gaubert, 2007) may limit collecting efforts.…”

Section: Discussionmentioning

confidence: 99%

How does spatial extent and environmental limits affect the accuracy of species richness estimates from ecological niche models? A case study with North American Pinaceae and Cactaceae

Nizamani

Papeş

Wang

et al. 2023

Ecology and Evolution

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Measuring species richness at varying spatial extents can be challenging, especially at large extents where exhaustive species surveys are difficult or impossible. Our work aimed at determining the reliability of species richness estimates from stacked ecological niche models at different spatial extents for taxonomic groups with vastly different environmental dependencies and interactions. To accomplish this, we generated ecological niche models for the species of Cactaceae and Pinaceae that occur within 180 published floras from North America north of Mexico. We overlaid or stacked the resulting species' potential distribution estimates over the bounding boxes representing each of the 180 floras to generate predictions of species richness.In general, our stacked models of Cactaceae and Pinaceae were poor predictors of species richness. The relationships between observed and predicted values improved noticeably with the size of spatial extents. However, the stacked models tended to overpredict the richness of Cactaceae and over-and underpredict the richness of Pinaceae. Cactaceae stacked models showed higher sensitivity and lower specificity than those for Pinaceae. We conclude that stacked ecological niche models may be somewhat poor predictors of species richness at smaller spatial extents and should be used with caution for this purpose. Perhaps more importantly, abilities to compensate for their limitations or apply corrections to their reliability may vary with taxonomic groups.

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