Dataset Information

The role of climate and environmental variables in structuring bird assemblages in the Seasonally Dry Tropical Forests (SDTFs).

ABSTRACT: Understanding the processes that influence species diversity is still a challenge in ecological studies. However, there are two main theories to discuss this topic, the niche theory and the neutral theory. Our objective was to understand the importance of environmental and spatial processes in structuring bird communities within the hydrological seasons in dry forest areas in northeastern Brazil. The study was conducted in two National Parks, the Serra da Capivara and Serra das Confusões National Parks, where 36 areas were sampled in different seasons (dry, dry/rainy transition, rainy, rainy/dry transition), in 2012 and 2013. We found with our results that bird species richness is higher in the rainy season and lower during the dry season, indicating a strong influence of seasonality, a pattern also found for environmental heterogeneity. Richness was explained by local environmental factors, while species composition was explained by environmental and spatial factors. The environmental factors were more important in explaining variations in composition. Climate change predictions have currently pointed out frequent drought events and a rise in global temperature by 2050, which would lead to changes in species behavior and to increasing desertification in some regions, including the Caatinga. In addition, the high deforestation rates and the low level of representativeness of the Caatinga in the conservation units negatively affects bird communities. This scenario has demonstrated how climatic factors affect individuals, and, therefore, should be the starting point for conservation initiatives to be developed in xeric environments.

SUBMITTER: Goncalves GSR

PROVIDER: S-EPMC5404791 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Publications

The role of climate and environmental variables in structuring bird assemblages in the Seasonally Dry Tropical Forests (SDTFs).

Gonçalves Gabriela Silva Ribeiro GSR Cerqueira Pablo Vieira PV Brasil Leandro Schlemmer LS Santos Marcos Pérsio Dantas MPD

PloS one 20170425 4

Understanding the processes that influence species diversity is still a challenge in ecological studies. However, there are two main theories to discuss this topic, the niche theory and the neutral theory. Our objective was to understand the importance of environmental and spatial processes in structuring bird communities within the hydrological seasons in dry forest areas in northeastern Brazil. The study was conducted in two National Parks, the Serra da Capivara and Serra das Confusões Nationa ...[more]

PMID: 28441412

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Project description:Seasonally dry tropical plant formations (SDTF) are likely to exhibit phylogenetic clustering owing to niche conservatism driven by a strong environmental filter (water stress), but heterogeneous edaphic environments and life histories may result in heterogeneity in degree of phylogenetic clustering. We investigated phylogenetic patterns across ecological gradients related to water availability (edaphic environment and climate) in the Caatinga, a SDTF in Brazil. Caatinga is characterized by semiarid climate and three distinct edaphic environments - sedimentary, crystalline, and inselberg -representing a decreasing gradient in soil water availability. We used two measures of phylogenetic diversity: Net Relatedness Index based on the entire phylogeny among species present in a site, reflecting long-term diversification; and Nearest Taxon Index based on the tips of the phylogeny, reflecting more recent diversification. We also evaluated woody species in contrast to herbaceous species. The main climatic variable influencing phylogenetic pattern was precipitation in the driest quarter, particularly for herbaceous species, suggesting that environmental filtering related to minimal periods of precipitation is an important driver of Caatinga biodiversity, as one might expect for a SDTF. Woody species tended to show phylogenetic clustering whereas herbaceous species tended towards phylogenetic overdispersion. We also found phylogenetic clustering in two edaphic environments (sedimentary and crystalline) in contrast to phylogenetic overdispersion in the third (inselberg). We conclude that while niche conservatism is evident in phylogenetic clustering in the Caatinga, this is not a universal pattern likely due to heterogeneity in the degree of realized environmental filtering across edaphic environments. Thus, SDTF, in spite of a strong shared environmental filter, are potentially heterogeneous in phylogenetic structuring. Our results support the need for scientifically informed conservation strategies in the Caatinga and other SDTF regions that have not previously been prioritized for conservation in order to take into account this heterogeneity.

Project description:BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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 in silico. 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.

Project description:Several studies have shown that rainfall seasonality, soil heterogeneity, and increased nitrogen (N) deposition may have important effects on tropical forest function. However, the effects of these environmental controls on soil microbial communities in seasonally dry tropical forests are poorly understood. In a seasonally dry tropical forest in the Yucatan Peninsula (Mexico), we investigated the influence of soil heterogeneity (which results in two different soil types, black and red soils), rainfall seasonality (in two successive seasons, wet and dry), and 3 years of repeated N enrichment on soil chemical and microbiological properties, including bacterial gene content and community structure. The soil properties varied with the soil type and the sampling season but did not respond to N enrichment. Greater organic matter content in the black soils was associated with higher microbial biomass, enzyme activities, and abundances of genes related to nitrification (amoA) and denitrification (nirK and nirS) than were observed in the red soils. Rainfall seasonality was also associated with changes in soil microbial biomass and activity levels and N gene abundances. Actinobacteria, Proteobacteria, Firmicutes, and Acidobacteria were the most abundant phyla. Differences in bacterial community composition were associated with soil type and season and were primarily detected at higher taxonomic resolution, where specific taxa drive the separation of communities between soils. We observed that soil heterogeneity and rainfall seasonality were the main correlates of soil bacterial community structure and function in this tropical forest, likely acting through their effects on soil attributes, especially those related to soil organic matter and moisture content.IMPORTANCE Understanding the response of soil microbial communities to environmental factors is important for predicting the contribution of forest ecosystems to global environmental change. Seasonally dry tropical forests are characterized by receiving less than 1,800 mm of rain per year in alternating wet and dry seasons and by high heterogeneity in plant diversity and soil chemistry. For these reasons, N deposition may affect their soils differently than those in humid tropical forests. This study documents the influence of rainfall seasonality, soil heterogeneity, and N deposition on soil chemical and microbiological properties in a seasonally dry tropical forest. Our findings suggest that soil heterogeneity and rainfall seasonality are likely the main factors controlling soil bacterial community structure and function in this tropical forest. Nitrogen enrichment was likely too low to induce significant short-term effects on soil properties, because this tropical forest is not N limited.

Project description:BackgroundReliable information about the spatial distribution of aboveground biomass (AGB) in tropical forests is fundamental for climate change mitigation and for maintaining carbon stocks. Recent AGB maps at continental and national scales have shown large uncertainties, particularly in tropical areas with high AGB values. Errors in AGB maps are linked to the quality of plot data used to calibrate remote sensing products, and the ability of radar data to map high AGB forest. Here we suggest an approach to improve the accuracy of AGB maps and test this approach with a case study of the tropical forests of the Yucatan peninsula, where the accuracy of AGB mapping is lower than other forest types in Mexico. To reduce the errors in field data, National Forest Inventory (NFI) plots were corrected to consider small trees. Temporal differences between NFI plots and imagery acquisition were addressed by considering biomass changes over time. To overcome issues related to saturation of radar backscatter, we incorporate radar texture metrics and climate data to improve the accuracy of AGB maps. Finally, we increased the number of sampling plots using biomass estimates derived from LiDAR data to assess if increasing sample size could improve the accuracy of AGB estimates.ResultsCorrecting NFI plot data for both small trees and temporal differences between field and remotely sensed measurements reduced the relative error of biomass estimates by 12.2%. Using a machine learning algorithm, Random Forest, with corrected field plot data, backscatter and surface texture from the L-band synthetic aperture radar (PALSAR) installed on the on the Advanced Land Observing Satellite-1 (ALOS), and climatic water deficit data improved the accuracy of the maps obtained in this study as compared to previous studies (R2?=?0.44 vs R2?=?0.32). However, using sample plots derived from LiDAR data to increase sample size did not improve accuracy of AGB maps (R2?=?0.26).ConclusionsThis study reveals that the suggested approach has the potential to improve AGB maps of tropical dry forests and shows predictors of AGB that should be considered in future studies. Our results highlight the importance of using ecological knowledge to correct errors associated with both the plot-level biomass estimates and the mismatch between field and remotely sensed data.

Dataset Information

The role of climate and environmental variables in structuring bird assemblages in the Seasonally Dry Tropical Forests (SDTFs).

Publications

The role of climate and environmental variables in structuring bird assemblages in the Seasonally Dry Tropical Forests (SDTFs).

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