Forgotten forests - issues and prospects in biome mapping using Seasonally Dry Tropical Forests as a case study

<p>Abstract</p> <p>Background</p> <p>South America is one of the most species diverse continents in the world. Within South America diversity is not distributed evenly at both local and continental scales and this has led to the recognition of various areas with unique species assemblages. Several schemes currently exist which divide the continental-level diversity into large species assemblages referred to as biomes. Here we review five currently available biome maps for South America, including the WWF Ecoregions, the Americas basemap, the Land Cover Map of South America, Morrone's Biogeographic regions of Latin America, and the Ecological Systems Map. The comparison is performed through a case study on the Seasonally Dry Tropical Forest (SDTF) biome using herbarium data of habitat specialist species.</p> <p>Results</p> <p>Current biome maps of South America perform poorly in depicting SDTF distribution. The poor performance of the maps can be attributed to two main factors: (1) poor spatial resolution, and (2) poor biome delimitation. Poor spatial resolution strongly limits the use of some of the maps in GIS applications, especially for areas with heterogeneous landscape such as the Andes. Whilst the Land Cover Map did not suffer from poor spatial resolution, it showed poor delimitation of biomes. The results highlight that delimiting structurally heterogeneous vegetation is difficult based on remote sensed data alone. A new refined working map of South American SDTF biome is proposed, derived using the Biome Distribution Modelling (BDM) approach where georeferenced herbarium data is used in conjunction with bioclimatic data.</p> <p>Conclusions</p> <p>Georeferenced specimen data play potentially an important role in biome mapping. Our study shows that herbarium data could be used as a way of ground-truthing biome maps <it>in silico</it>. The results also illustrate that herbarium data can be used to model vegetation maps through predictive modelling. The BDM approach is a promising new method in biome mapping, and could be particularly useful for mapping poorly known, fragmented, or degraded vegetation. We wish to highlight that biome delimitation is not an exact science, and that transparency is needed on how biomes are used as study units in macroevolutionary and ecological research.</p

The strengths and weaknesses of species distribution models in biome delimitation

This is the final published version, also available from Frontiers via the DOI in this record.Aim: The aim was to test whether species distribution models (SDMs) can reproduce major macroecological patterns in a species-rich, tropical region and provide recommendations for using SDMs in areas with sparse biotic inventory data. Location: North-east Brazil, including Minas Gerais. Time period: Present. Major taxa studied: Flowering plants. Methods: Species composition estimates derived from stacked SDMs (s-SDMs) were compared with data from 1,506 inventories of 933 woody plant species from north-east Brazil. Both datasets were used in hierarchical clustering analyses to delimit floristic units that correspond to biomes. The ability of s-SDMs to predict the identity, functional composition and floristic composition of biomes was compared across geographical and environmental space. Results: The s-SDMs and inventory data both resolved four major biomes that largely corresponded in terms of their distribution, floristics and function. The s-SDMs proved excellent at identifying broad-scale biomes and their function, but misassigned many individual sites in complex savanna–forest mosaics. Main conclusions: Our results show that s-SDMs have a unique role to play in describing macroecological patterns in areas lacking inventory data and for poorly known taxa. s-SDMs accurately predict floristic and functional macroecological patterns but struggle in areas where non-climatic factors, such as fire or soil, play key roles in governing distributions.Natural Environment Research Council (NERC)Coordenação de Aperfeiçoamento de Pessoal de Nível SuperiorConselho Nacional de Desenvolvimento Científico e TecnológicoRoyal Societ

Phylogeny and dating of Aframomum (Zingiberaceae)

International audienceA phylogeny of the African genus Aframomum (Zingiberaceae) is presented based on nuclear ribosomal DNA ITS and plastid trnL-trnF DNA sequences. parsimony and Bayesian analyses were performed on both independent and combined data sets, which were obtained by adding new sequences to already published data. Aframomum, whose sister clade is quite likely to be the genus Renealmia, is shown to be monophyletic in the trees from the analyses of the combined data sets and ITS, but the relationships within the genus are not well supported apart from the clades with accessions from the same species (Aframomum limbatum, A. longiligulatum and A. verrucosum). Dating of the crown node of Aframomum using either Non-Prametric Rate Smoothing or a Bayesian approach using BEAST revealed that it diversified during the late Oligocene to Miocene (8.4 +/-0.1-31.4+/-2.9 Mya), which is older than that suggested by previous authors who postulated that the genus may have speciated during the Pleistocene

Environmental and geographical biases in plant specimen data from the Colombian Andes

Specimen records are a major source of species information for biodiversity research. However, specimen records currently available may be geographically or environmentally biased. Detailed knowledge of biases is useful for understanding and accounting for errors they introduce into analyses of biodiversity patterns. Here we study geographical and environmental biases in online records representing the flora of the Colombian Andes and explore their effect on sample completeness at different spatial scales. We found a strong geographical and environmental sampling bias. Plant records were concentrated close to cities where herbaria and researchers are located. The highlands > 2000 m are better sampled, whereas mid- and lowlands remain poorly sampled (i.e. montane and lowland forest). Sampling completeness (SC) median across the Colombian Andes i

Performance of different DNA extraction methods with historic plant herbarium specimens; results of the three best performing methods are in bold under each category.

1<p>CTAB (cetyltrimethylammonium bromide lysis) with PVP and β-mercaptoethanol.</p>2<p>See File S1 for details of extraction protocol used.</p>3<p>A260/A280 ratios 1.7–2.0 were considered pure.</p

Effect of extraction method on DNA yield and purity.

<p>Effect of extraction method on DNA yield and purity.</p

DataSheet3_Functional and ecological diversification of underground organs in Solanum.csv

The evolution of geophytes in response to different environmental stressors is poorly understood largely due to the great morphological variation in underground plant organs, which includes species with rhizomatous structures or underground storage organs (USOs). Here we compare the evolution and ecological niche patterns of different geophytic organs in Solanum L., classified based on a functional definition and using a clade-based approach with an expert-verified specimen occurrence dataset. Results from PERMANOVA and Phylogenetic ANOVAs indicate that geophytic species occupy drier areas, with rhizomatous species found in the hottest areas whereas species with USOs are restricted to cooler areas in the montane tropics. In addition, rhizomatous species appear to be adapted to fire-driven disturbance, in contrast to species with USOs that appear to be adapted to prolonged climatic disturbance such as unfavorable growing conditions due to drought and cold. We also show that the evolution of rhizome-like structures leads to changes in the relationship between range size and niche breadth. Ancestral state reconstruction shows that in Solanum rhizomatous species are evolutionarily more labile compared to species with USOs. Our results suggest that underground organs enable plants to shift their niches towards distinct extreme environmental conditions and have different evolutionary constraints.</p