Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Replication Data for: Assessing ecosystem services in neotropical dry forests : A systematic review

ABSTRACT There is an increasing consensus on the importance of understanding ecosystem service (ES) provision in order to facilitate decision making and the sustainable management of Neotropical dry forests (NTDFs), yet research on the ESs provided by NTDFs is limited. We identified the main existing gaps and trends in the quantification of provisioning, regulating and supporting ESs in NTDFs. Systematic web-based searches showed that research has been increasing in recent decades in NTDFs, supporting greater ES knowledge and assessment. Carbon storage and biodiversity are the main subjects under study, while ESs relating to water and soil lack investigation. The most common approaches for assessing ES were fauna and plant inventories, carbon dynamics and ecological processes

Tree diameter growth for three successional stages of Tropical Dry Forest in Minas Gerais, Brazil

he tropical dry forests of Brazil are classified as the most threatened and disturbed ecosystems in the country. We estimate the diameter growth in three successional stages in the Mata Seca State Park, in Minas Gerais, Brazil, through annual measurement of all individuals with more than 5 cm of diameter at breast height in 18 permanent plots (6 plots for each succession stage) in the early, intermediate, and late successional stages, over a period of 5 years (2006-2011). With this information the annual diameter increments for each individual were calculated to determine the diameter increments per stage, plot, and diameter class. The results show the following annual increments for each stage of succession: early (5.02 mm/year), intermediate (2.55 mm/year), and late (1.91 mm/year). We found high similarity in incremental growth between the plots in the intermediate and late stages. The greatest increments in the early stage was in  the 15-20 cm diameter class, in the intermediate stage in the 30-35 cm class, and in the late stage in the 45-50 cm class. The dominant species with the highest increments were Myracrodruon urundeuva (9.33 mm/year) and Mimosa hostilis (10.35 mm/year). Species with lower increments were mostly those of the late stage. The high diameter increment in the early stage and the differences we observed between stages were associated with species composition and biophysical factors that regulate the growth and structure of each forest

Changes in forest structure and composition in a successional tropical dry forest

We describe changes in forest structure and floristic composition of three successional stages for Mata Seca State Park, in Minas Gerais, Brazil, through the measurement of all trees greater than 5 cm of diameter at breast height (DBH) of 18 permanent plots (6 per stage) for early, intermediate, and late successional stages of a tropical dry forest during a 5-year period. Using this information, we calculated the Importance Value Index (IVI), Holdridge Complexity Index, Jaccard Similarity Coefficient, and Shannon Diversity Index for each stage of succession. The floristic composition and structure of the successional stages expressed by the Holdridge Complexity Index, showed that complexity increases gradually as we advance through the successional stages, while the Shannon Diversity Index indicated that species diversity was higher in the intermediate stage of succession. The Jaccard Similarity Coefficients showed that the intermediate and late successional stages had high similarity, whereas the early successional stage had low similarity with these two successional stages. Mortality rates were higher in the early stage, especially in stems with smaller diameters (5-10cm). This information contributes to the dissemination of important knowledge for the conservation of the tropical dry forests of Brazil, which are the most threatened ecosystems in this country and, at the same time, the least studied

Dynamics of Carbon Accumulation in Tropical Dry Forests under Climate Change Extremes

We analyze here how much carbon is being accumulated annually by secondary tropical dry forests (TDFs) and how structure, composition, time since abandonment, and climate can influence the dynamics of forest carbon accumulation. The study was carried out in Santa Rosa National Park in Guanacaste province, Costa Rica and Mata Seca State Park in Minas Gerais, Brazil. Total carbon storage and carbon accumulation were obtained for both sites from the sum of the aboveground carbon and belowground carbon gain plus the annual litterfall. Carbon accumulation of these TDFs varied from 2.6 Mg C ha−1 y−1 to 6.3 Mg C ha−1 y−1, depending on the age of the forest stands. Time since abandonment and number of stems per plot were the best predictors for carbon storage, annual carbon gains, and losses. Mortality rates and carbon losses were also associated with seasonal climate variability. We found significant correlations between tree mortality, carbon losses and mean seasonal temperature, mean seasonal precipitation, potential evapotranspiration, and the Oceanic Niño Index. Carbon dynamics in tropical dry forests are driven by time since abandonment and forest structure; however, rising temperature and El Niño Southern Oscillation (ENSO) events can have a significant impact on tree mortality and carbon losses. Depending on their location and land-use history, some dry forests are more impacted by climatic extremes than others, and differences between secondary stages are expected. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.Inter-American Institute for Global Change ResearchOpen access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Phyllostomid bat occurence in successional stages of neotropical dry forests

Tropical dry forests (TDFs) are highly endangered tropical ecosystems being replaced by a complex mosaic of patches of different successional stages, agricultural fields and pasturelands. In this context, it is urgent to understand how taxa playing critical ecosystem roles respond to habitat modification. Because Phyllostomid bats provide important ecosystem services (e.g. facilitate gene flow among plant populations and promote forest regeneration), in this study we aimed to identify potential patterns on their response to TDF transformation in sites representing four different successional stages (initial, early, intermediate and late) in three Neotropical regions: México, Venezuela and Brazil. We evaluated bat occurrence at the species, ensemble (abundance) and assemblage level (species richness and composition, guild composition). We also evaluated how bat occurrence was modulated by the marked seasonality of TDFs. In general, we found high seasonal and regional specificities in phyllostomid occurrence, driven by specificities at species and guild levels. For example, highest frugivore abundance occurred in the early stage of the moistest TDF, while highest nectarivore abundance occurred in the same stage of the driest TDF. The high regional specificity of phyllostomid responses could arise from: (1) the distinctive environmental conditions of each region, (2) the specific behavior and ecological requirements of the regional bat species, (3) the composition, structure and phenological patterns of plant assemblages in the different stages, and (4) the regional landscape composition and configuration. We conclude that, in tropical seasonal environments, it is imperative to perform long-term studies considering seasonal variations in environmental conditions and plant phenology, as well as the role of landscape attributes. This approach will allow us to identify potential patterns in bat responses to habitat modification, which constitute an invaluable tool for not only bat biodiversity conservation but also for the conservation of the key ecological processes they provide