Morphology and modern sedimentary deposits of the macrotidal Marapanim Estuary (Amazon,Brazil)

The northern Brazilian coast, east of the Amazon River is characterized by several macrotidal estuarine systems that harbor large mangrove areas with approximately 7600 km². The Marapanim Estuary is influenced by macrotidal regime with moderate waves influence. Morphologic units were investigated by using remote sensing images (i.e., Landsat-7 ETM+, RADARSAT- 1 Wide and SRTM) integrated with bathymetric data. The modern sedimentary deposits were analyzed from 67 cores collected by Vibracore and Rammkersonde systems. Analysis of morphology and surface sedimentary deposits of the Marapanim River reveal they are strongly influenced by the interaction of tidal, wave and fluvial currents. Based on these processes it was possible to recognize three distinct longitudinal facies zonation that revels the geological filling of a macrotidal estuary. The estuary mouth contain fine to medium marine sands strongly influenced by waves and tides, responsible for macrotidal sandy beaches and estuarine channel development, which are characterized by wave-ripple bedding and longitudinal cross-bedding sands. The estuary funnel is mainly influenced by tides that form wide tidal mudflats, colonized by mangroves, along the estuarine margin, with parallel laminations, lenticular bedding, root fragments and organic matter lenses. The upstream estuary contains coarse sand to gravel of fluvial origin. Massive mud with organic matter lenses, marks and roots fragments occur in the floodplain accumulates during seasonal flooding providing a slowly aggrading in the alluvial plain. This morphologic and depositional pattern show easily a tripartite zonation of a macrotidal estuary, that are in the final stage of filling.     

基于数值预报和随机森林算法的强对流天气分类预报技术

随机森林算法是当前得到较为广泛应用的机器学习方法之一,有着很高的预测精度,训练结果稳定,泛化能力强,解决多分类问题有明显优势。本文将随机森林算法应用于强对流的潜势预测和分类,分短时强降水、雷暴大风、冰雹和无强对流四种类别,基于2005—2016年NCEP 1°×1°再分析资料计算的对流指数和物理量,开展强对流天气的分类训练、0～12 h预报和检验,经2015—2016年独立测试样本检验表明,针对强对流发生站点的点对点检验,整体误判率为21. 9%,85次强对流过程基本无漏报,模型尤其适用于较大范围强对流天气。随机森林算法筛选的因子物理意义较为明确,和主观预报经验基本相符,模型准确率高,可用于日常业务。     

Forty-year multi-scale land cover change and political ecology data reveal a dynamic and regenerative process of forests in Peruvian Indigenous Territories

This article explores deforestation and reforestation dynamics over 415,749 hectares of 25 titled Indigenous Community Lands (ICLs) in the Peruvian Amazon over forty years at three scales: total area, regions, and communities. We focus on ICLs as the territorial unit of analysis, as they are increasingly discussed regarding their importance for conservation. Additionally indigenous communities (ICs) are a too-marginalized group in the Amazon that merit more attention. Analyses of this kind are often short-term and use only large-scale Earth Observation methodologies. We use a multi-method approach linking remote sensing with ground verification, and qualitative historical political ecology work with ICs. We find that overall accumulated deforestation was low at 5%, but that when reforestation is considered, net deforestation was only 3.5%. At the community level deforestation and afforestation dynamics are complex, except for one period that indicates a macro state driver in the region. Results suggest inadequate accounting for forest regeneration in deforestation analyses and challenge the notion that presenting stakeholders with accumulated forest loss values is helpful in tropical areas where forests and people are dynamic. Furthermore, our work with communities highlights that categorizing them and their lands as pro-environment or not in general terms is unhelpful for determining fund flows to ICLs for environmental or development purposes.     

基于FY-4A卫星和随机森林算法的西藏山南市雷电短临预报方法

针对青藏高原地区雷电短临预报缺乏雷达资料的问题,采用FY-4A卫星多通道数据、欧洲中心第5代再分析资料(ERA5)中的对流指数、闪电定位仪资料等多源监测数据,根据雷电的发生、发展机理,提出了18个关键预报因子,利用随机森林算法建立了适用于西藏山南地区的雷电短临预报模型。统计分析各预报因子在有无雷电天气样本中的概率密度分布与随机森林模型得到的特征重要度指标,结果表明提出的预报因子物理意义明确,建立的模型可信度较高。利用随机森林算法分别对未来10 min、20 min、30 min建立雷电预报模型,并与光流外推预报方法进行对比检验,结果表明：随机森林模型预报效果命中率(POD)、临界成功指数(CSI)均高于光流法,空报率(FAR)也相对较低;未来20 min的随机森林预报模型CSI评分最高,整体预报效果最佳。     

海南岛天然橡胶林台风灾害风险评价

台风灾害是海南橡胶种植中影响最为严重和主要的灾害,为对其风险进行定量评估,本研究以海南岛天然橡胶林为研究对象,基于灾害风险评估理论,融合橡胶台风灾害、社会经济和气象数据,建立橡胶台风灾害危险性、暴露性和脆弱性评价模型,利用加权综合评价法开展天然橡胶林台风灾害风险评价。结果表明：海南橡胶种植高风险区位于沿海台风发生频繁市县,其中琼海、文昌、海口为海南岛橡胶灾害风险最高的地区,其次陵水、万宁、琼中、屯昌、东方等地区灾害风险也较高。风险最低地区位于中部五指山、保亭、乐东、三亚等地区,评价结果与实际灾害发生以及种植情况相符。评价结果表明,台风灾害危险性是风险的主导因子,但非单一决定因子,种植技术、品种改良等措施对脆弱性降低起到了较好的促进作用。评价结果可为橡胶林避灾防灾及种植布局提供依据。     

Distinguishing the Regional Atmospheric Controls on Precipitation Isotopic Variability in the Central-Southeast Portion of Brazil

Precipitation isotope ratios (O and H) record the history of water phase transitions and fractionation processes during moisture transport and rainfall formation. Here, we evaluated the isotopic composition of precipitation over the central-southeastern region of Brazil at different timescales. Monthly isotopic compositions were associated with classical effects (rainfall amount, seasonality, and continentality), demonstrating the importance of vapor recirculation processes and different regional atmospheric systems (South American Convergence Zone-SACZ and Cold Fronts-CF). While moisture recycling and regional atmospheric processes may also be observed on a daily timescale, classical effects such as the amount effect were not strongly correlated (δ¹⁸O-precipitation rate r ≤ –0.37). Daily variability revealed specific climatic features, such as δ¹⁸O depleted values (~ –6‰ to –8‰) during the wet season were associated with strong convective activity and large moisture availability. Daily isotopic analysis revealed the role of different moisture sources and transport effects. Isotope ratios combined with d-excess explain how atmospheric recirculation processes interact with convective activity during rainfall formation processes. Our findings provide a new understanding of rainfall sampling timescales and highlight the importance of water isotopes to decipher key hydrometeorological processes in a complex spatial and temporal context in central-southeastern Brazil.     

Pretend Participation: Procedural Injustices in the Madeira Hydroelectric Complex

Energy infrastructure projects have long been associated with a lack of participation by impacted, local populations—this history is evident in the case of hydropower projects in the Global South. Ever since the World Commission on Dams’ Report (WCD 2000), there has been substantive evidence, and numerous recommendations, that have called on governments, financial agencies and construction companies to increase community engagement and participation in dam construction and in their governance thereafter. Further, community groups, activists, and scholars have long articulated the need for participatory governance in energy projects. In this analysis, we evaluate participation in institutionalized mechanisms provided by dam builders—such as public meetings and negotiations—in Brazil’s Madeira hydroelectric complex. We evaluate how perceptions of positive and negative impacts, among other factors, predict engagement, estimating a series of logit models based on a social survey of 673 households carried out in 2019/20. Perceptions of negative and positive impacts of the dams before construction are related to participation in the meetings promoted by dam builders. Yet our results also imply that participation was rare, fleeting, and insufficient and points to the need to ensure community engagement and governance to ensure energy justice in future dam projects in Brazil and elsewhere.     

Reevaluating suitability estimates based on dynamics of cropland expansion in the Brazilian Amazon

Agricultural suitability maps are a key input for land use zoning and projections of cropland expansion. Suitability assessments typically consider edaphic conditions, climate, crop characteristics, and sometimes incorporate accessibility to transportation and market infrastructure. However, correct weighting among these disparate factors is challenging, given rapid development of new crop varieties, irrigation, and road networks, as well as changing global demand for agricultural commodities. Here, we compared three independent assessments of cropland suitability to spatial and temporal dynamics of agricultural expansion in the Brazilian state of Mato Grosso during 2001–2012. We found that areas of recent cropland expansion identified using satellite data were generally designated as low to moderate suitability for rainfed crop production. Our analysis highlighted the abrupt nature of suitability boundaries, rather than smooth gradients of agricultural potential, with little additional cropland expansion beyond the extent of the flattest areas (0–2% slope). Satellite-based estimates of the interannual variability in the use of existing crop areas also provided an alternate means to assess suitability. On average, cropland areas in the Cerrado biome had higher utilization (84%) than croplands in the Amazon region of northern Mato Grosso (74%). Areas of more recent expansion had lower utilization than croplands established before 2002, providing empirical evidence for lower suitability or alternative management strategies (e.g., pasture–soya rotations) for lands undergoing more recent land use transitions. This unplanted reserve constitutes a large area of potentially available cropland (PAC) without further expansion, within the management limits imposed for pest management and fallow cycles. Using two key constraints on future cropland expansion, slope and restrictions on further deforestation of Amazon or Cerrado vegetation, we found little available flat land for further legal expansion of crop production in Mato Grosso. Dynamics of cropland expansion from more than a decade of satellite observations indicated narrow ranges of suitability criteria, restricting PAC under current policy conditions, and emphasizing the advantages of field-scale information to assess suitability and utilization.     

西双版纳热带次生林林窗辐射特征初步研究

利用西双版纳不同季节热带次生林林窗、林内及旷地不同波长太阳辐射的实测资料,比较分析了热带次生林窗不同波长辐射特征。分析得出：热带次生林窗中央与北侧林冠下的不同波长太阳辐射量值在中午前后迅速达到最大后又急速下降的现象明显;林窗内不同波长太阳辐射日总量值均大于林内,小于旷地;林窗中央和北侧林冠下相比较。一般是北侧林冠下的各辐射要素总量值高于林窗中央;林窗区域的总辐射日总量在干热季最高,雨季和雨季后期次之,雾凉季时最小;林窗中央和北侧林冠下的红外辐射及可见光在总辐射中所占份额随季节的变化而不同,充分显示了林窗辐射环境的异质性;与旷地和林内相比,林窗内各测点的红外辐射在总辐射中所占份额高于旷地却低于林内,而可见光占总辐射的比值情况正好相反。     

A simple model to estimate monthly forest evapotranspiration in Japan from monthly temperature

The estimation of evapotranspiration (E) in forested areas is required for various practical purposes (e.g. evaluation of drought risks) in Japan. This study developed a model that estimates monthly forest E in Japan with the input of monthly temperature (T). The model is based on the assumptions that E equals the equilibrium evaporation rate (E_eq) and that E_eq is approximated by a function of T. The model formulates E as E (mm month⁻¹) = 3·48 T ( °C) + 32·3. The accuracy of the model was examined using monthly E data derived using short‐term water balance (WB) and micrometeorological (M) methods for 15 forest sites in Japan. The model estimated monthly E more accurately than did the Thornthwaite and Hamon equations according to regression analysis of the estimated E and E derived using the WB and M methods. Although the model tended to overestimate monthly E, the overestimation could be reduced by considering the effect of precipitation on E. As T data are commonly available all over Japan, the model would be a useful tool to estimate forest E in Japan. Copyright © 2010 John Wiley & Sons, Ltd.