Length Of Dry Season Research Articles

Living in Sangiran: A spatial reconstruction of hominin environment in Java at 1 Ma

This study focuses on analysing and testing the relationship between Homo erectus behaviour and environmental dynamics in Sangiran, Java, at the time around 1 Ma. Here, palaeoenvironmental conditions encountered by Homo erectus in Java at 1 Ma were reconstructed using multiple methods. High resolution palaeotopography and coastlines, palaeoclimatic, as well as palaeovegetation maps are produced in this study for the eastern part of Java, where the majority of hominin fossils was found. After correcting for tectonic elevation changes and eustatic sea-level changes, which sum up to a marine regression of −41.8 m, the palaeotopography map shows a significant extension of land surface in the northern and eastern parts of the palaeoisland. As a palaeoclimatic indicator drought categories are used here, derived from the proportion between the number of dry and wet months according to monthly mean precipitation. Drought, i.e. the length of dry season, is the main driver of lowland vegetation distribution. Palaeotopography and paleoclimatic estimates were combined to develop a palaeovegetation map based on the topographic and climatic restrictions of modern vegetation units. In eastern Java, lowland monsoonal forests dominated the landscape at 1 Ma. These results provide for the first time a spatial sense of how topography and hydrology, rainfall patterns and vegetation units could have been distributed in the palaeolandscape of Sangiran Homo erectus.

Amazon savannization and climate change are projected to increase dry season length and temperature extremes over Brazil

Land use change and atmospheric composition, two drivers of climate change, can interact to affect both local and remote climate regimes. Previous works have considered the effects of greenhouse gas buildup in the atmosphere and the effects of Amazon deforestation in atmospheric general circulation models. In this study, we investigate the impacts of the Brazilian Amazon savannization and global warming in a fully coupled ocean-land-sea ice-atmosphere model simulation. We find that both savannization and global warming individually lengthen the dry season and reduce annual rainfall over large tracts of South America. The combined effects of land use change and global warming resulted in a mean annual rainfall reduction of 44% and a dry season length increase of 69%, when averaged over the Amazon basin, relative to the control run. Modulation of inland moisture transport due to savannization shows the largest signal to explain the rainfall reduction and increase in dry season length over the Amazon and Central-West. The combined effects of savannization and global warming resulted in maximum daily temperature anomalies, reaching values of up to 14 °C above the current climatic conditions over the Amazon. Also, as a consequence of both climate drivers, both soil moisture and surface runoff decrease over most of the country, suggesting cascading negative future impacts on both agriculture production and hydroelectricity generation.

Dry-season length affects the annual ecosystem carbon balance of a temperate semi-arid shrubland

Semi-arid ecosystems have been shown to dominate over tropical forests in determining the trend and interannual variability of land carbon (C) sink. However, the magnitude and variability of ecosystem C balance remain largely uncertain for temperate semi-arid shrublands at the decadal scale. Using eddy-covariance and micro-meteorological measurements, we quantified the interannual variation in net ecosystem production (NEP) and its components, gross primary production (GPP) and ecosystem respiration (Reco, i.e., the sum of autotrophic and heterotrophic respiration), in a semi-arid shrubland of the Mu Us Desert, northern China during 2012–2022. This shrubland was an overall weak C sink over the 11 years (NEP = 12 ± 46 g C m−2 yr−1, mean ± SD). Annual NEP ranged from −66 to 77 g C m−2 yr−1, with the ecosystem frequently switching between being an annual C sink and a C source. GPP was twice as sensitive as Reco to prolonged dry seasons, leading to a close negative relationship between annual NEP and dry-season length (R2 = 0.80, P < 0.01). Annual GPP (R2 = 0.51, P = 0.01) and NEP (R2 = 0.58, P < 0.01) were positively correlated with annual rainfall. Negative annual NEP (the ecosystem being a C source) tended to occur when the dry season exceeded 50 d yr−1 or rainfall dropped below 280 mm yr−1. Increases in dry-season length strengthened the effects of low soil moisture relative to high vapor pressure deficit in constraining NEP. Both GPP and NEP were more closely correlated with C uptake amplitude (annual maximum daily values) than with C uptake period. These findings indicate that dry-season extension under climate change may reduce the long-term C sequestration in semi-arid shrublands. Plant species adapted to prolonged dry seasons should be used in ecosystem restoration in the studied area to enhance ecosystem functions.

Future Projections of Low‐Level Atmospheric Circulation Patterns Over South Tropical South America: Impacts on Precipitation and Amazon Dry Season Length

AbstractThe last few decades have shown evidence of a lengthening dry season in southern Amazonia, which is associated with a delay in the onset of the South American Monsoon System (SAMS). Using a pattern recognition framework of atmospheric circulation patterns (CPs), previous studies have identified specific atmospheric situations related to the onset of the SAMS. Here, we analyze the future changes in the CPs that largely define the main hydro‐climatological states of Tropical South America. We evaluated the CP changes that occurred between two periods: historical (1970–2000) and future (2040–2070), using six General Circulation Models (GCMs) from the Coupled Model Intercomparison Project Phase 6. Future GCM projections show significant spatio‐temporal changes in the CPs associated with the dry season in southern Amazonia during the mid‐21st century. These changes are related to both a late onset of the SAMS and an early demise of the SAMS. Particularly, the CP methodology allowed for a better understanding of the behavior of the southern Amazon dry season under future conditions, showing an increase in the frequency of the CPs typically observed during the dry season. The occurrence of dry days in the Amazon basin during the austral winter of the mid‐21st century increases by 19.4% on average, with respect to the historical period. This methodology also identified a future increase in the frequency of dry CPs, both at the beginning of the dry‐to‐wet transition period (8%) and at the end of the wet‐to‐dry transition season (11%).

Contrasting effects of intensified dry-season drought and extended dry-season length on soil greenhouse gas emissions in a subtropical forest

Over two-thirds of the Earth's land surface is subjected to seasonal precipitation changes along with climate warming, including the subtropical forests that represent one of the Earth's most important carbon sink and source. However, few experiments have been conducted to understand the response of soil greenhouse gas (GHGs) emissions from these forests to seasonal changes in precipitation. Herein, we conducted a field experiment in a subtropical forest of southern China including two precipitation seasonality treatments: an intensified dry-season (Oct–Mar) drought and wetter wet-season (Jun–Sep) treatment (ID) and an extended dry-season (Apr–May) length and wetter wet-season treatment (ED); for both ID and ED, the annual precipitation amount was kept the same as under ambient control (AC). Compared to AC, the decreased annual CO2 emissions for ID were mainly due to decreased WFPS in Oct–Mar of 2013–2014 and increased WFPS during Jun–Sep of 2013; the increased annual CH4 uptake for ID was predominantly attributed to decreased WFPS in Oct–Mar of 2013–2014; the decreased annual N2O emissions for ID were mainly due to decreased WFPS in Oct–Mar of 2013; the increased annual N2O emissions for ID in 2014 were mainly attributed to increased WFPS in Jun–Sep (p < 0.05). Relative to AC, the increased annual CO2 and N2O emissions from ED were predominantly attributed to decreased WFPS in Apr–May and increased WFPS in Jun–Sep during 2013–2014, respectively (p < 0.05). The average annual CO2-equivalent CH4 and N2O emissions increased under ED but decreased under ID compared to AC (p < 0.05). Although our two precipitation manipulation scenarios simulated seasonal drought impacts without changing annual precipitation amount, ED and ID had distinct impacts on soil GHGs emissions, which have important implications for modeling the subtropical forests GHG emissions and managing the forests to mitigate climate change.

Fire carbon emissions over Equatorial Asia reduced by shortened dry seasons

Fire carbon emissions over Equatorial Asia (EQAS) play a critical role in the global carbon cycle. Most regional fire emissions (89.0%) occur in the dry season, but how changes in the dry-season length affect the fire emissions remains poorly understood. Here we show that, the length of the EQAS dry season has decreased significantly during 1979–2021, and the delayed dry season onset (5.4 ± 1.6 (± one standard error) days decade−1) due to increased precipitation (36.4 ± 9.1 mm decade−1) in the early dry season is the main reason. The dry season length is strongly correlated with the length of the fire season. Increased precipitation during the early dry season led to a significant reduction (May: −0.7 ± 0.4 Tg C decade−1; August: −12.9 ± 6.7 Tg C decade−1) in fire carbon emissions during the early and peak fire season. Climate models from the Coupled Model Intercomparison Project Phase 6 project a continued decline in future dry season length in EQAS under medium and high-emission scenarios, implying further reductions in fire carbon emissions.

Wet season rainfall characteristics and temporal changes for Cape Town, South Africa, 1841–2018

Abstract. Wet seasons may be characterized by the frequency of wet–dry days, duration of wet–dry spells and season length. These properties are investigated for Cape Town using rainfall data from four weather stations in the Cape Town metropolitan area located at the South African Astronomical Observatory (SAAO), Maitland, Kirstenbosch and Cape Town International airport. The primary focus is on the long SAAO daily rainfall record dating back to 1841, with the specific aim to statistically assess attributes of the wet season (April to October) and its temporal variability over the period 1841–2018. The decade 1950–1959 had significantly high frequencies of wet days, but there was a subsequent significant decline in wet days at the SAAO (−1 d per decade) and Maitland (−1.1 d per decade) during the period 1950–2018. A significant decline in wet days also occurred at the SAAO between 1880 and 1940 (−3.3 d per decade, p=0.005). Dry spells longer than 5 d have become more prevalent since the beginning of the 20th century. A rain-based definition for the onset and termination of the wet season is presented using 5 d running sums and pentad means; these were applied to each year containing adequate daily data, so as to track changes during the wet season. We identify a recent decadal decline in mean wet season length (−1.4 d per decade) since ca. 1940, particularly between 1941–1994 (−4.2 d per decade), such that wet seasons since 2000 have only averaged 182 d in length while the long-term (1841–2018) average is 188 d. This decline is attributed to an increased incidence of late onsets (after 15 April) and early terminations (earlier than 18 October) of the wet season, or a combination of both, particularly since the year 2000. Interannual variability in wet season characteristics is associated with solar (sunspot) cycles and fluctuations in the Southern Oscillation Index and Southern Annular Mode.

Rising ecosystem water demand exacerbates the lengthening of tropical dry seasons

Precipitation-based assessments show a lengthening of tropical dry seasons under climate change, without considering simultaneous changes in ecosystem water demand. Here, we compare changes in tropical dry season length and timing when dry season is defined as the period when precipitation is less than: its climatological average, potential evapotranspiration, or actual evapotranspiration. While all definitions show more widespread tropical drying than wetting for 1983-2016, we find the largest fraction (48.7%) of tropical land probably experiencing longer dry seasons when dry season is defined as the period when precipitation cannot meet the need of actual evapotranspiration. Southern Amazonia (due to delayed end) and central Africa (due to earlier onset and delayed end) are hotspots of dry season lengthening, with greater certainty when accounting for water demand changes. Therefore, it is necessary to account for changing water demand when characterizing changes in tropical dry periods and ecosystem water deficits.

Climate Change Affects Reproductive Phenology in Lianas of Australia’s Wet Tropics

Lianas are increasing in abundance in many tropical forests. This increase can alter forest structure and decrease both carbon storage and tree diversityviaantagonistic relationships between lianas and their host trees. Climate change is postulated as an underlying driver of increasing liana abundances,viaincreases in dry-season length, forest-disturbance events, and atmospheric CO2concentrations; all factors thought to favour lianas. However, the impact of climate change on liana reproductive phenology, an underlying determinant of liana abundance, has been little studied, particularly outside of Neotropical forests. Over a 15-year period (2000–2014), we examined the phenological patterns of a liana community in intact rainforests of the Wet Tropics bioregion of Australia; a World Heritage Area and hotspot of floral diversity. Specifically, we assessed (1) flowering and fruiting patterns of liana species; (2) potential climate drivers of flowering and fruiting activity; and (3) the influence of El Niño-related climatic disturbances on liana phenology. We found that flowering and fruiting of the studied liana species increased over time. Liana reproduction, moreover, rose in apparent response to higher temperatures and reduced rainfall. Finally, we found flowering and fruiting of the liana species increased following El Niño events. These results suggest that liana reproduction and abundance are likely to increase under predicted future climate regimes, with potentially important impacts on the survival, growth, and reproduction of resident trees and thus the overall health of Australian tropical rainforests.

Profiling User Needs for Weather and Climate Information in Fostering Drought Risk Preparedness in Central-Southern Nigeria

Weather and climate information trigger early action and facilitate better disaster preparedness. Decision-driven and people-centered weather and climate information are pivotal for the effective uptake. The challenge of early responses in preparing for drought hazard is growing in the dry savannah of tropical sub-Saharan African countries. This paper analyzed user needs for weather and climate information in fostering drought risk preparedness in Central-Southern Nigeria. Stratified, snowball, and simple random samplings were used to obtain a sample of 397 respondents across the agro-ecological zones of Edo State. Structured questionnaire was used to collect farm-level household data across communities. Eight focus group discussions and 11 key informants' interviews were conducted, targeting contact farmers and other agricultural stakeholders in selected key economic sectors of Edo State, Central-Southern Nigeria. Results show that non-users of weather and climate information are more than users in the savannah area. Heckman probit results explained that male gender, farmers' experience, income, and persistent incidence of erratic rainfall have more propensity to facilitate use of WCI in taking critical decisions while group membership or associations and distance of meteorological station prevent stakeholders from developing interest in using WCI for drought preparedness and response. Multi-criteria decision-making indicated that rainfall amount, onset and cessation rainfall dates, and rainfall distributions are the most useful WCI needed by end users in their decision response plan in agriculture; rainfall intensity, rainfall cessation date, rainfall distributions, and length of dry season are ranked as the most useful WCI for water resource management while heat intensity, rainstorms, and drought alerts were ranked as most appropriate for users in the disaster risk reduction in fostering resilience toward anticipated future drought hazard. Subseasonal-to-seasonal (S2S) and medium (4–10 days) timescales information are the most highly rated to facilitate resource planning for efficient utilization and management in all the economic sectors. The users' most preferred delivery method of receiving WCI are mobile telephone, radio, agricultural extension officers, farmers' groups, and contact farmers/specialist for efficiency and convenient criteria in enhancing users' decision capacity to uptake WCI. There is a need for a policy drive to build synergy that will make WCI forecasting systems include impact-based forecast estimates and response advisory across a wide range of natural hazards. A seamless collaborative effort in bringing scientific outputs and users' needs together will increase the utility of WCI through systematic efforts. NiMet should improve on its engagement with the stakeholders, the agricultural extension and planning office, water management authorities, and disaster risk reduction and emergency response personnel as partner institutions. These policy actions would provide a robust collaborative framework for co-producing useable WCI based on user needs in managing decision points against extreme events and mainstream preparedness into existing decision-making apparatus of rural communities in Central-Southern Nigeria.

Pronounced loss of Amazon rainforest resilience since the early 2000s

The resilience of the Amazon rainforest to climate and land-use change is crucial for biodiversity, regional climate and the global carbon cycle. Deforestation and climate change, via increasing dry-season length and drought frequency, may already have pushed the Amazon close to a critical threshold of rainforest dieback. Here, we quantify changes of Amazon resilience by applying established indicators (for example, measuring lag-1 autocorrelation) to remotely sensed vegetation data with a focus on vegetation optical depth (1991–2016). We find that more than three-quarters of the Amazon rainforest has been losing resilience since the early 2000s, consistent with the approach to a critical transition. Resilience is being lost faster in regions with less rainfall and in parts of the rainforest that are closer to human activity. We provide direct empirical evidence that the Amazon rainforest is losing resilience, risking dieback with profound implications for biodiversity, carbon storage and climate change at a global scale.

Changes in obliquity drive tree cover shifts in eastern tropical South America

Despite its great ecological importance, the main factors governing tree cover in tropical savannas as well as savanna-forest boundaries are still largely unknown. Here we address this issue by investigating marine sediment records of long-chain n-alkane stable carbon (δ13Cwax) and hydrogen (δDwax) isotopes from a core collected off eastern tropical South America spanning the last ca. 45 thousand years. While δ13Cwax is a proxy for the main photosynthetic pathway of terrestrial vegetation, tracking the relative proportion of C3 (mainly trees) versus C4 (mainly grasses) plants, δDwax is a proxy for continental precipitation, tracking the intensity of rainfall. The investigated core was collected off the mouth of the São Francisco River drainage basin, a tropical savanna-dominated region with dry austral autumn, winter and spring. On top of millennial-scale changes, driven by anomalies in the amount of precipitation associated with Heinrich Stadials, we identify a marked obliquity control over the expansion and contraction of tree and grass cover. During periods of maximum (minimum) obliquity, trees (grasses) reached maximum coverage. We suggest that maximum (minimum) obliquity decreased (increased) the length of the dry season allowing (hampering) the expansion of tree-dominated vegetation. Periods of maximum obliquity induced an anomalous heating (cooling) of the summer (winter) hemisphere that in combination with a delayed response of the climate system slightly increased autumn precipitation over the São Francisco River drainage basin, through a shift of the Intertropical Convergence Zone towards or further into the anomalously heated hemisphere. We found that atmospheric CO2 concentration has only a secondary effect on tree cover. Our results underline the importance of the dry season length as a governing factor in the long-term control of tree cover in tropical landscapes.

Liana community attributes in one of the northernmost neotropical rainforests

Background: Lianas are an important woody component of tropical rain forests. We described and compared the composition, structure, and diversity of the liana community in one of the northernmost neotropical rain forests.&#x0D; Question: How much does this liana community differ in attributes with global patterns documented in other tropical and subtropical rain forests?&#x0D; Study site and dates: Los Tuxtlas Tropical Biology Station, Veracruz, Mexico. 2015-2018.&#x0D; Methods: We censused all lianas ≥ 1 cm in diameter in a 1-ha plot and determined dominant families and species, diametric distribution, and diversity of order q .&#x0D; Results: We recorded 396 liana stems, 42 species, and 20 families. Basal area was 6619.2 cm2. Order 1 and 2 diversity was 21.9 and 13.4, respectively. Apocynaceae, Bignoniaceae, Celastraceae, and Malpighiaceae accounted for about 60 % of abundance and basal area, and 45.2 % of species richness. The 10 most abundant species included more than 60 % of stems and basal area.&#x0D; Conclusions: Species richness, abundance, and basal area were low compared with other tropical and subtropical sites worldwide. It was noteworthy the coincidence of some dominant species and families across the Neotropics and the absence of Fabaceae among the most important families. Latitudinal location and some key climatic factors such annual average rainfall and dry season length may explain, in part, our findings.

Deep learning models for improved reliability of tree aboveground biomass prediction in the tropical evergreen broadleaf forests

Aboveground biomass (AGB) and carbon uptake of a forest are key ecological indicators for various technical and scientific applications and sustainable forest management. Deep Learning (DL) methods have been considered as alternative to regression techniques to increase the reliability of tree AGB prediction. The objectives were to develop DL models to predict AGB in the tropical evergreen broadleaf forests and compare DL models with traditional regression equations for their reliability in AGB prediction. A total of 968 individual trees were destructively sampled from fourteen 1-ha and twenty-six 0.2-ha plots distributed across five ecoregions of Viet Nam to get a dataset of tree predictors of diameter at breast height (DBH), tree height (H), wood density (WD) and the response variable of AGB along with forest stand factors of basal area (BA) and density (N); ecological and environmental variables such as ecoregion, slope, altitude, soil type, averaged annual temperature (T), averaged annual rainfall (P) and averaged dry season length. The DL models were developed using different combinations of variables selected by factor analysis for mixed data and compared with traditional regression equations by using cross-validation. Trees AGB in tropical rainforest predicted by DL models had significantly higher reliability than the conventional regression equations when both had the same input variables. Of the 16 developed DL models with 1 to 9 predictors, the model with 9 predictors (DBH, H, Ecoregion, Altitude, P, T, Soil type, N and WD) was the best DL model which reduced root mean square percent error (RMSPE) and mean absolute percent error (MAPE) by up to 7.7% and 6.1%, respectively, compared to traditional allometric equations. The DL models created in this study should be applied for measured tree data following factors of the forest stand, ecology, and environment in sampled plots to predict the tree AGB and total AGB, carbon on a large scale with variation in the value of these factors. Thus, we recommend that the DL models apply for the Measurement, Reporting, and Verification (MRV) system of the Reducing Emissions from Deforestation and forest Degradation (REDD+) program at a large regional level, national or territorial level scale.

GIS-Based Assessment of Suitability Area of Rainwater Harvesting in Daro Labu District, Oromia, Ethiopia

Rainwater harvesting is the process of intercepting, conveying and storing rainfall for future use as an alternative source of water in the drought prone areas of Ethiopia especially eastern Oromia. The aim of the research was to assess and mapping suitability area of water harvesting site in Daro Labu District. There are various methodologies and criteria to identify suitable sites and techniques for rainwater harvesting (RWH). Determining the best method or guidelines for site selection, however, is difficult. GIS is the recent technology of spatiotemporal data used to assess the factor of influences for rainfall and runoff depth estimation for identification of potential area of RWH for crop production and mapping of the potential site. The influence factors for consideration of the assessment was climate data, soil texture and depth, land use and land cover (LULC) type, slope difference were used. The total area of the catchment was about 156064.72 ha. The SCS–CN for rainfall used to runoff depth estimation compute runoff and volume from the land surface depend on the level of antecedent moisture condition (AMC.) The length of wet and dry season of the study area were known with antecedent moisture condition (AMC) of II, I III by having the values of 82, 67 and 91 respectively. The annual of 20 years average rainfall was 925.2 mm with maximum and minimum of 1134 mm and 737.3 mm respectively with average annual runoff depth of estimate was 185.3 mm. From the estimated annual runoff the volume of water harvested was about 2.89 × 10⁸ m³. The suitability map of the study area shows extremely potential, highly potential, potential and not potential accounts by coverage areas about (12,797.3 ha) 8.2%, (25,906.7 ha) 16.6%, (98,302.8 ha) 63.5%, and (19,040 ha) 7.5% respectively. The runoff in the study area was affected by geomorphological factors, particularly, land use change, topography, soil texture and depth, drainage density, and population density affects the runoff rate and volume significantly.

Tree growth responses to climate variation in upland and seasonally flooded forests and woodlands of the Cerrado-Pantanal transition of Brazil

Tropical forest trees are sensitive to climate variations, especially during anomalously warm and dry years that occur during El Niño. However, species growth responses are poorly understood. We measured annual stem growth of 27 different tree species from upland and seasonally flooded forests and woodlands in the Cuiaba Basin and Northern Pantanal of Mato Grosso, Brazil. Stem growth increment was measured using plastic, spring-loaded dendrometer bands installed on 344 trees. Measurements were made between 2015 and 2019, which encompassed the 2015–16 El Niño that was one of the warmest and driest on record. Relative stem growth rates (RGR) at both sites increased with higher rainfall and declined with an increase in maximum temperature, but the RGR of trees in the Cuiaba Basin also declined as the length of the dry season increased. RGR, and the response of RGR to climate variation, varied substantially across species. Some species only exhibited a significant RGR response to variations in rainfall, maximum temperature, or dry season length, other species responded to more than one climate variable, and a subset were insensitive to the variation in all three climate variables studied. Rainfall appeared to be a stronger control on RGR in the predominately upland Cuiaba Basin (87% of species exhibited a significant RGR response to rainfall in the Cuiaba Basin vs. 39% in the Pantanal) while temperature was a stronger control on RGR in the seasonally flooded Pantanal (67% of species exhibited a significant RGR response to temperature in the Pantanal vs. 53% in the Cuiaba Basin). While our study period was short, and measurements were done on a small subset of available species, our data indicate that variations in climate affect the growth of tropical forest and woodland tree species differently. These species-specific responses have the potential to alter community diversity and productivity as climate change ensues.

Characterization of Dry-Season Phenology in Tropical Forests by Reconstructing Cloud-Free Landsat Time Series

Fine-resolution satellite imagery is needed for characterizing dry-season phenology in tropical forests since many tropical forests are very spatially heterogeneous due to their diverse species and environmental background. However, fine-resolution satellite imagery, such as Landsat, has a 16-day revisit cycle that makes it hard to obtain a high-quality vegetation index time series due to persistent clouds in tropical regions. To solve this challenge, this study explored the feasibility of employing a series of advanced technologies for reconstructing a high-quality Landsat time series from 2005 to 2009 for detecting dry-season phenology in tropical forests; Puerto Rico was selected as a testbed. We combined bidirectional reflectance distribution function (BRDF) correction, cloud and shadow screening, and contaminated pixel interpolation to process the raw Landsat time series and developed a thresholding method to extract 15 phenology metrics. The cloud-masked and gap-filled reconstructed images were tested with simulated clouds. In addition, the derived phenology metrics for grassland and forest in the tropical dry forest zone of Puerto Rico were evaluated with ground observations from PhenoCam data and field plots. Results show that clouds and cloud shadows are more accurately detected than the Landsat cloud quality assessment (QA) band, and that data gaps resulting from those clouds and shadows can be accurately reconstructed (R2 = 0.89). In the tropical dry forest zone, the detected phenology dates (such as greenup, browndown, and dry-season length) generally agree with the PhenoCam observations (R2 = 0.69), and Landsat-based phenology is better than MODIS-based phenology for modeling aboveground biomass and leaf area index collected in field plots (plot size is roughly equivalent to a 3 × 3 Landsat pixels). This study suggests that the Landsat time series can be used to characterize the dry-season phenology of tropical forests after careful processing, which will help to improve our understanding of vegetation–climate interactions at fine scales in tropical forests.

Long-term (35 Years) Rainy and Dry Season Characterization in Semiarid Northeastern Brazil

Abstract Uncertainties in the timing and quality of rainy season are a threat for food and water security, and also in terms of fire vulnerability. Then, understanding features associated to rainfall allows a climate characterization useful for climate and fire risk management. We used rainfall data series (1983-2018) from 15 meteorological stations to characterize the greatest conservation area of Brazilian-unique seasonally dry tropical forest Caatinga (northeastern Brazil). Accumulated anomalies in daily series were used to determine onset and end of rainy seasons. We also determined seasonal and annual rainfall (quality) and rain rate, and performed a dry season sub-classification. Results showed greater variability for end dates as compared to onset dates for rainy season. Droughts in the region are becoming more severe. We found a significant decreasing tendency of 7 mm/year on annual rainfall, of 0.3 mm/day per decade on rain rate, and an increase of 12 days per decade on consecutive dry days. Dry season length presented a 14-year periodicity and is related with previous but uncorrelated from posterior rainy season length. The complexity of the rainfall patterns is evidenced by the weak correlation we found between the amount of rainfall and the rainy season length.

On the role of aerosol radiative effect in the wet season onset timing over the Congo rainforest during boreal autumn

Abstract. The boreal summer dry season length is reported to have been increasing in the last 3 decades over the Congo rainforest, which is the second-largest rainforest in the world. In some years, the wet season in boreal autumn starts early, while in others it arrives late. The mechanism behind such a change in the wet season onset date has not been investigated yet. Using multi-satellite data sets, we discover that the variation in aerosols in the dry season plays a major role in determining the subsequent wet season onset. Dry season aerosol optical depth (AOD) influences the strength of the southern African easterly jet (AEJ-S) and, thus, the onset of the wet season. Higher AOD associated with a higher dust mass flux reduces the net downward shortwave radiation and decreases the surface temperature over the Congo rainforest region, leading to a stronger meridional temperature gradient between the rainforest and the Kalahari Desert as early as in June. The latter, in turn, strengthens the AEJ-S, sets in an early and a stronger easterly flow, and leads to a stronger equatorward convergence and an early onset of the wet season in late August to early September. The mean AOD in the dry season over the region is strongly correlated (r=0.7) with the timing of the subsequent wet season onset. Conversely, in low AOD years, the onset of the wet season over the Congo basin is delayed to mid-October.

The El Niño – Southern Oscillation dramatically influences the probability of reproduction and reproductive rate of a tropical forest bird

Although climate change has been implicated in population declines of tropical forest birds, there is a critical lack of data on the mechanisms underlying these declines. Attempts to link climatic factors to variation in adult survival, fecundity or nest success have been largely inconclusive. Recent community‐scale analyses have suggested that tropical birds may be less likely to breed under adverse conditions, but long‐term data on individual reproduction are needed to test this hypothesis. Here we leverage 12 years of data on a lowland forest bird, the greater ani Crotophaga major, to investigate how demographic parameters vary with phase of the El Niño – Southern Oscillation (ENSO), a major driver of climatic conditions in tropical wet forest. The likelihood of breeding and annual reproductive rate both decreased dramatically in El Niño‐like years, with only 37.5% of adults attempting breeding in 2015 (a strong El Niño year). For birds that did breed, however, clutch size and daily nest predation rate were unaffected by climate. Of the local climate variables investigated, dry season length and the frequency of high temperatures were most closely associated with reproductive failure. These results indicate that El Niño conditions alter the demography of greater anis by reducing the likelihood of reproduction, a response that may be more widespread than currently recognized. We suggest that reduced reproduction under adverse conditions represents an important and understudied aspect of the life histories of tropical forest birds.