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295 results for “tropical dry forest”
Data from: Evolutionary constraints on tree size and aboveground biomass in tropical dry forests
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Flooding drives tropical dry forest tree community assembly in southeast Brazil
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Autogenic regulation and resilience in tropical dry forest
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Soil biogeochemistry across Central and South American tropical dry forests
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Data from: Changing ecological communities along an elevation gradient in seasonally dry tropical forest on Hispaniola (Sierra Martín García, Dominican Republic)
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A new, disjunct species of Bahiana (Euphorbiaceae-Acalyphoideae): Phytogeographic connections between the seasonally dry tropical forests of Peru and Brazil, and a review of spinescence in the family
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Phenological status of plants in the very tropical dry forests of Curaçao
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Successional and phenological effects on plant-floral visitor interaction networks of a tropical dry forest
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Data from: leaf functional diversity and environmental filtering in a tropical dry forest: comparison between two geological substrates
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Figure 5 in Three new Mexican species of the endemic Athysanini leafhopper genus Devolana DeLong (Hemiptera: Cicadellidae) from the tropical dry forest
Figure 5. Devolana tuxcacuensis Pinedo-Escatel and Aguilar-Pérez, sp. nov., site of habitat and collection. (a–c) Area covered by tropical dry forest at sampled site; (d) position and functionality of light trap used during the collections in the site (photo by GRJ).
Figure 3 in Three new Mexican species of the endemic Athysanini leafhopper genus Devolana DeLong (Hemiptera: Cicadellidae) from the tropical dry forest
Figure 3. Devolana tuxcacuensis Pinedo-Escatel and Aguilar-Pérez, sp. nov., holotype male genitalia: (a) pygofer, dorsal; (b) pygofer, lateral; (c) valve, ventral; (d) subgenital plate, ventral; (e) aedeagus, lateral; (f) apex of aedeagus, caudal; (g) aedeagus, ventral; (h) left style, dorsal; (i) connective, dorsal.
Data from: Genetic diversity of the rain tree (Albizia saman) in Colombian seasonally dry tropical forest for informing conservation and restoration interventions
<p><i>Albizia saman</i> is a multipurpose tree species of seasonally dry tropical forests (SDTFs) of Mesoamerica and northern South America typically cultivated in silvopastoral and other agroforestry systems around the world, a trend that is bound to increase in light of multimillion hectare commitments for forest and landscape restoration. The effective conservation and sustainable use of <i>A. saman</i> requires detailed knowledge of its genetic diversity across its native distribution range of which surprisingly little is known to date. We assessed the genetic diversity and structure of <i>A.saman</i> across twelve representative locations of SDTF in Colombia, and how they may have been shaped by past climatic changes and human influence. We found four different genetic groups which may be the result of differentiation due to isolation of populations in pre-glacial times. The current distribution and mixture of genetic groups across STDF fragments we observed might be the result of range expansion of SDTFs during the last glacial period followed by range contraction during the Holocene and human-influenced movement of germplasm associated with cattle ranching. Despite the fragmented state of the presumed natural <i>A. saman</i> stands we sampled we did not find any signs of inbreeding, suggesting that gene flow is not jeopardized in humanized landscapes. However, further research is needed to assess potential deleterious effects of fragmentation on progeny. Climate change is not expected to seriously threaten the <i>in situ</i> persistence of <i>A. saman</i> populations and might present opportunities for future range expansion. However, the sourcing of germplasm for tree planting activities needs to be aligned with the genetic affinity of reference populations across the distribution of Colombian SDTFs. We identify priority source populations for i<i>n situ</i> conservation based on their high genetic diversity, lack or limited signs of admixture and/or genetic uniqueness.</p>
Data from: Landscape genetics of leaf-toed geckos in the tropical dry forest of northern Mexico
Habitat fragmentation due to both natural and anthropogenic forces continues to threaten the evolution and maintenance of biological diversity. This is of particular concern in tropical regions that are experiencing elevated rates of habitat loss. Although less well-studied than tropical rain forests, tropical dry forests (TDF) contain an enormous diversity of species and continue to be threatened by anthropogenic activities including grazing and agriculture. However, little is known about the processes that shape genetic connectivity in species inhabiting TDF ecosystems. We adopt a landscape genetic approach to understanding functional connectivity for leaf-toed geckos (Phyllodactylus tuberculosus) at multiple sites near the northernmost limit of this ecosystem at Alamos, Sonora, Mexico. Traditional analyses of population genetics are combined with multivariate GIS-based landscape analyses to test hypotheses on the potential drivers of spatial genetic variation. Moderate levels of within-population diversity and substantial levels of population differentiation are revealed by FST and Dest. Analyses using STRUCTURE suggest the occurrence of from 2 to 9 genetic clusters depending on the model used. Landscape genetic analysis suggests that forest cover, stream connectivity, undisturbed habitat, slope, and minimum temperature of the coldest period explain more genetic variation than do simple Euclidean distances. Additional landscape genetic studies throughout TDF habitat are required to understand species-specific responses to landscape and climate change and to identify common drivers. We urge researchers interested in using multivariate distance methods to test for, and report, significant correlations among predictor matrices that can impact results, particularly when adopting least-cost path approaches. Further investigation into the use of information theoretic approaches for model selection is also warranted.
Data from: Modeling seasonal surface temperature variations in secondary tropical dry forests
Secondary tropical dry forests (TDFs) provide important ecosystem services such as carbon sequestration, biodiversity conservation, and nutrient cycle regulation. However, their biogeophysical processes at the canopy-atmosphere interface remain unknown, limiting our understanding of how this endangered ecosystem influences, and responds to the ongoing global warming. To facilitate future development of conservation policies, this study characterized the seasonal land surface temperature (LST) behavior of three successional stages (early, intermediate, and late) of a TDF, at the Santa Rosa National Park (SRNP), Costa Rica. A total of 38 Landsat-8 Thermal Infrared Sensor (TIRS) data and the Surface Reflectance (SR) product were utilized to model LST time series from July 2013 to July 2016 using a radiative transfer equation (RTE) algorithm. We further related the LST time series to seven vegetation indices which reflect different properties of TDFs, and soil moisture data obtained from a Wireless Sensor Network (WSN). Results showed that the LST in the dry season was 15–20 K higher than in the wet season at SRNP. We found that the early successional stages were about 6–8 K warmer than the intermediate successional stages and were 9–10 K warmer than the late successional stages in the middle of the dry season; meanwhile, a minimum LST difference (0–1 K) was observed at the end of the wet season. Leaf phenology and canopy architecture explained most LST variations in both dry and wet seasons. However, our analysis revealed that it is precipitation that ultimately determines the LST variations through both biogeochemical (leaf phenology) and biogeophysical processes (evapotranspiration) of the plants. Results of this study could help physiological modeling studies in secondary TDFs.
Functional organization of woody plant assemblages along precipitation and human disturbance gradients in a seasonally dry tropical forest
<p>Chronic anthropogenic disturbances (CAD) and rainfall are important drivers of plant community assembly, but little is known about the role played by inter and intraspecific trait variation as communities respond to these pervasive forces. Here we examined the hypothesis that lower precipitation and higher CAD reduce both intra and interspecific trait variation in Caatinga dry forests. We sampled woody plants across 15 plots along precipitation and CAD gradients and measured resource-use traits. Effects of precipitation and CAD on RaoQ functional diversity were decomposed into species turnover and intraspecific variability. We used "T-statistics" to assess the trait sorting from the regional pool to local communities (i.e. external filtering), and within-community forces leading to low trait overlap (i.e. internal filtering) at individual- and species-level. Intraspecific variability explained at least one third of the total trait variation and 46% of variation in multitrait diversity across communities. Increasing disturbance reduced multitrait diversity, while precipitation affected some particular traits, such as wood density. Overall, precipitation determined species sorting across communities, while disturbance relaxed internal filters, leading to higher trait overlap within communities due to higher intraspecific variability.<b> </b>Our results suggest that<b> </b>the woody Caatinga flora contains a substantial amount of both inter and intraspecific trait variation. This variation is not randomly distributed within and across communities, but varies according to rainfall conditions and disturbance intensity. These findings reinforce the emerging idea that human-disturbances can reorganize plant communities at multiple scales and highlight trait variability as a key biological asset for the resilience of dry forests.</p>
Data from: Can terrestrial laser scanners (TLSs) and hemispherical photographs predict tropical dry forest succession with liana abundance?
Tropical dry forests (TDFs) are ecosystems with long drought periods, a mean temperature of 25 °C, a mean annual precipitation that ranges from 900 to 2000 mm, and that possess a high abundance of deciduous species (trees and lianas). What remains of the original extent of TDFs in the Americas remains highly fragmented and at different levels of ecological succession. It is estimated that one of the main fingerprints left by global environmental and climate change in tropical environments is an increase in liana coverage. Lianas are non-structural elements of the forest canopy that eventually kill their host trees. In this paper we evaluate the use of a terrestrial laser scanner (TLS) in combination with hemispherical photographs (HPs) to characterize changes in forest structure as a function of ecological succession and liana abundance. We deployed a TLS and HP system in 28 plots throughout secondary forests of different ages and with different levels of liana abundance. Using a canonical correlation analysis (CCA), we addressed how the VEGNET, a terrestrial laser scanner, and HPs could predict TDF structure. Likewise, using univariate analyses of correlations, we show how the liana abundance could affect the prediction of the forest structure. Our results suggest that TLSs and HPs can predict the differences in the forest structure at different successional stages but that these differences disappear as liana abundance increases. Therefore, in well known ecosystems such as the tropical dry forest of Costa Rica, these biases of prediction could be considered as structural effects of liana presence. This research contributes to the understanding of the potential effects of lianas in secondary dry forests and highlights the role of TLSs combined with HPs in monitoring structural changes in secondary TDFs.
Data from: Scale-dependent variation in nitrogen cycling and soil fungal communities along gradients of forest composition and age in regenerating tropical dry forests
Rates of ecosystem nitrogen (N) cycling may be mediated by the presence of ectomycorrhizal fungi, which compete directly with free‐living microbes for N. In the regenerating tropical dry forests of Central America, the distribution of ectomycorrhizal trees is affected by succession and soil parent material, both of which may exert independent influence over soil N fluxes. In order to quantify these interacting controls, we used a scale‐explicit sampling strategy to examine soil N cycling at scales ranging from the microsite to ecosystem level. We measured fungal community composition, total and inorganic N pools, gross proteolytic rate, net N mineralization and microbial extracellular enzyme activity at multiple locations within 18 permanent plots that span dramatic gradients of soil N concentration, stand age and forest composition. The ratio of inorganic to organic N cycling was correlated with variation in fungal community structure, consistent with a strong influence of ectomycorrhiza on ecosystem‐scale N cycling. However, on average, > 61% of the variation in soil biogeochemistry occurred within plots, and the effects of forest composition were mediated by this local‐scale heterogeneity in total soil N concentrations. These cross‐scale interactions demonstrate the importance of a spatially explicit approach towards an understanding of controls on element cycling.
Data from: Canopy height variation and environmental heterogeneity in the tropical dry forests of coastal Oaxaca, Mexico
Despite its importance for carbon storage and other ecosystem functions, the variation of vegetation canopy height is not yet well understood. We examined the relationship between this community attribute and environmental heterogeneity in a tropical dry forest of southern Mexico. We sampled vegetation in 15 sites along a 100-km coastal stretch of Oaxaca State, and measured the heights of all woody plants (excluding lianas). The majority of the ca. 4000 individuals recorded concentrated in the 4–8 m height range. We defined three plant sets to describe overall community canopy height at each site: a set including all plants, a set made up by the tallest plants representing 10 percent of all individuals, and a set comprising the 10 tallest plants. For each site we computed maximum height and the mean and median heights of the three sets. Significant collinearity was observed between the seven resulting height variables, but null distributions constructed through bootstrap revealed their different behaviors as functions of species richness and density of individuals. Through linear modeling and a model selection procedure, we identified 21 models that best described the variation of canopy height variables. These models pointed out to soil (measured as PC1 of a principal component analysis performed on 10 soil variables), water stress, and elevation as the main drivers of canopy height variation in the region. In the event of increasing water stress resulting from global climate change, the studied tropical dry forests could become shorter and thus decrease their carbon storage potential.
Data from: Unraveling the mechanisms underlying pulse dynamics of soil respiration in tropical dry forests
Tropical dry forests are already undergoing changes in the quantity and timing of rainfall, but there is great uncertainty over how these shifts will affect belowground carbon (C) cycling. While it has long been known that dry soils quickly release carbon dioxide (CO2) upon rewetting, the mechanisms underlying the so-called 'Birch effect' are still debated. Here, we quantified soil respiration pulses and their biotic predictors in response to simulated precipitation events in a regenerating tropical dry forest in Costa Rica. We also simulated the observed rewetting CO2 pulses with two soil carbon models: a conventional model assuming first-order decay rates of soil organic matter, and an enzyme- catalyzed model with Michaelis–Menten kinetics. We found that rewetting of dry soils produced an immediate and dramatic pulse of CO2, accompanied by rapid immobilization of nitrogen into the microbial biomass. However, the magnitude of the rewetting CO2 pulse was highly variable at fine spatial scales, and was well correlated with the size of the dissolved organic C pool prior to rewetting. Both the enzyme-catalyzed and conventional models were able to reproduce the Birch effect when respiration was coupled directly to microbial C uptake, although models differed in their ability to yield realistic estimates of SOC and microbial biomass pool sizes and dynamics. Our results suggest that changes in the timing and intensity of rainfall events in tropical dry forests will exert strong influence on ecosystem C balance by affecting the dynamics of microbial biomass growth.
Extinction-immigration dynamics lag behind environmental filtering in shaping the composition of tropical dry forests within a changing landscape
The impact of rapid habitat loss and fragmentation on biodiversity is a major issue. However, we still lack an integrative understanding of how these changes influence biodiversity dynamics over time. In this study, we investigate the effects of these changes in terms of both niche-based and neutral dynamics. We hypothesize that habitat loss has delayed effects on neutral immigration-extinction dynamics, while edge effects and environmental heterogeneity in habitat patches have rapid effects on niche-based dynamics. We analyzed taxonomic and functional composition of 100 tree communities in a tropical dry forest landscape of New-Caledonia subject to habitat loss and fragmentation. We designed an original, process-based simulation framework, and performed Approximate Bayesian Computation to infer the influence of niche-based and neutral processes. Then, we performed partial regressions to evaluate the relationships between inferred parameter values of communities and landscape metrics (distance to edge, patch area, and habitat amount around communities), derived from either recent or past (65 yrs ago) aerial photographs, while controlling for the effect of soil and topography. We found that landscape structure influences both environmental filtering and immigration. Immigration rate was positively related to past habitat amount surrounding communities. In contrast, environmental filtering was mostly affected by present landscape structure and mainly influenced by edge vicinity and topography. Our results highlight that landscape changes have contrasting spatio-temporal influences on niche-based and neutral assembly dynamics. First, landscape-level habitat loss and community isolation reduce immigration and increase demographic stochasticity, resulting in slow decline of local species diversity and extinction debt. Second, recent edge creation affects environmental filtering, incurring rapid changes in community composition by favoring species with edge-adapted strategies. Our study brings new insights about temporal impacts of landscape changes on biodiversity dynamics. We stress that landscape history critically influences these dynamics and should be taken into account in conservation policies.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.