Dataset Information

Climate-induced distribution dynamics of Plebeia flavocincta, a stingless bee from Brazilian tropical dry forests.

ABSTRACT: Aim:The objective of this study is to estimate the current potential geographic distribution of Plebeia flavocincta and to evaluate the influence of climate on the dynamics of suitable habitat availability in the past and in the future. Location:Northeast region of Brazil and dry forest areas. Methods:The habitat suitability modeling was based on two algorithms, two global circulation models, and six different scenarios. We used this tool to estimate the areas of occurrence in the past (Last Interglacial and Last Glacial Maximum), in the present, and in the future (years 2050 and 2070). Results:According to the models, P. flavocincta had great dynamics in the availability of suitable habitats with periods of retraction and expansion of these areas in the past. Our results suggest that this taxon may benefit in terms of climate suitability gain in Northeast Brazil in the future. In addition, we identified high-altitude areas and the eastern coast as climatically stable. Conclusion:The information provided can be used by decision makers to support actions toward protecting and sustainably managing this taxon. Protection measures for this taxon are particularly important because this insect contributes to the local flora and, although our results indicate that the climate may favor this taxon, other factors can negatively affect it, such as high levels of habitat loss due to anthropogenic activities.

SUBMITTER: Maia UM

PROVIDER: S-EPMC7520209 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Publications

Climate-induced distribution dynamics of <i>Plebeia flavocincta</i>, a stingless bee from Brazilian tropical dry forests.

Maia Ulysses Madureira UM Miranda Leonardo de Sousa LS Carvalho Airton Torres AT Imperatriz-Fonseca Vera Lucia VL de Oliveira Guilherme Corrêa GC Giannini Tereza Cristina TC

Ecology and evolution 20200820 18

<h4>Aim</h4>The objective of this study is to estimate the current potential geographic distribution of <i>Plebeia flavocincta</i> and to evaluate the influence of climate on the dynamics of suitable habitat availability in the past and in the future.<h4>Location</h4>Northeast region of Brazil and dry forest areas.<h4>Methods</h4>The habitat suitability modeling was based on two algorithms, two global circulation models, and six different scenarios. We used this tool to estimate the areas of occ ...[more]

PMID: 33005369

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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

Climate-induced distribution dynamics of Plebeia flavocincta, a stingless bee from Brazilian tropical dry forests.

Publications

Climate-induced distribution dynamics of <i>Plebeia flavocincta</i>, a stingless bee from Brazilian tropical dry forests.

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