Hirofumi Hashimoto

Bio: Hirofumi Hashimoto is an academic researcher from California State University, Monterey Bay. The author has contributed to research in topics: Primary production & Geostationary orbit. The author has an hindex of 24, co-authored 48 publications receiving 6996 citations. Previous affiliations of Hirofumi Hashimoto include Ames Research Center & University of Montana.

Climate-Driven Increases in Global Terrestrial Net Primary Production from 1982 to 1999

Abstract: Recent climatic changes have enhanced plant growth in northern mid-latitudes and high latitudes. However, a comprehensive analysis of the impact of global climatic changes on vegetation productivity has not before been expressed in the context of variable limiting factors to plant growth. We present a global investigation of vegetation responses to climatic changes by analyzing 18 years (1982 to 1999) of both climatic data and satellite observations of vegetation activity. Our results indicate that global changes in climate have eased several critical climatic constraints to plant growth, such that net primary production increased 6% (3.4 petagrams of carbon over 18 years) globally. The largest increase was in tropical ecosystems. Amazon rain forests accounted for 42% of the global increase in net primary production, owing mainly to decreased cloud cover and the resulting increase in solar radiation.

A Continuous Satellite-Derived Measure of Global Terrestrial Primary Production

Abstract: Until recently, continuous monitoring of global vegetation productivity has not been possible because of technological limitations. This article introduces a new satellite-driven monitor of the global biosphere that regularly computes daily gross primary production (GPP) and annual net primary production (NPP) at 1-kilometer (km) resolution over 109,782,756 km 2 of vegetated land surface. We summarize the history of global NPP science, as well as the derivation of this calculation, and current data production activity. The first data on NPP from the EOS (Earth Observing System) MODIS (Moderate Resolution Imaging Spectroradiometer) sensor are presented with different types of validation. We offer examples of how this new type of data set can serve ecological science, land management, and environmental policy. To enhance the use of these data by nonspecialists, we are now producing monthly anomaly maps for GPP and annual NPP that compare the current value with an 18-year average value for each pixel, clearly identifying regions where vegetation growth is higher or lower than normal.

Large seasonal swings in leaf area of Amazon rainforests

Abstract: Despite early speculation to the contrary, all tropical forests studied to date display seasonal variations in the presence of new leaves, flowers, and fruits. Past studies were focused on the timing of phenological events and their cues but not on the accompanying changes in leaf area that regulate vegetation–atmosphere exchanges of energy, momentum, and mass. Here we report, from analysis of 5 years of recent satellite data, seasonal swings in green leaf area of ≈25% in a majority of the Amazon rainforests. This seasonal cycle is timed to the seasonality of solar radiation in a manner that is suggestive of anticipatory and opportunistic patterns of net leaf flushing during the early to mid part of the light-rich dry season and net leaf abscission during the cloudy wet season. These seasonal swings in leaf area may be critical to initiation of the transition from dry to wet season, seasonal carbon balance between photosynthetic gains and respiratory losses, and litterfall nutrient cycling in moist tropical forests.

Amazon forests did not green up during the 2005 drought

Abstract: [1] The sensitivity of Amazon rainforests to dry-season droughts is still poorly understood, with reports of enhanced tree mortality and forest fires on one hand, and excessive forest greening on the other. Here, we report that the previous results of large-scale greening of the Amazon, obtained from an earlier version of satellite-derived vegetation greenness data - Collection 4 (C4) Enhanced Vegetation Index (EVI), are irreproducible, with both this earlier version as well as the improved, current version (C5), owing to inclusion of atmosphere-corrupted data in those results. We find no evidence of large-scale greening of intact Amazon forests during the 2005 drought - approximately 11%–12% of these drought-stricken forests display greening, while, 28%–29% show browning or no-change, and for the rest, the data are not of sufficient quality to characterize any changes. These changes are also not unique - approximately similar changes are observed in non-drought years as well. Changes in surface solar irradiance are contrary to the speculation in the previously published report of enhanced sunlight availability during the 2005 drought. There was no co-relation between drought severity and greenness changes, which is contrary to the idea of drought-induced greening. Thus, we conclude that Amazon forests did not green-up during the 2005 drought.

Amazon forests did not green-up during the 2005 drought

Abstract: [1] The sensitivity of Amazon rainforests to dry-season droughts is still poorly understood, with reports of enhanced tree mortality and forest fires on one hand, and excessive forest greening on the other. Here, we report that the previous results of large-scale greening of the Amazon, obtained from an earlier version of satellite-derived vegetation greenness data - Collection 4 (C4) Enhanced Vegetation Index (EVI), are irreproducible, with both this earlier version as well as the improved, current version (C5), owing to inclusion of atmosphere-corrupted data in those results. We find no evidence of large-scale greening of intact Amazon forests during the 2005 drought - approximately 11%–12% of these drought-stricken forests display greening, while, 28%–29% show browning or no-change, and for the rest, the data are not of sufficient quality to characterize any changes. These changes are also not unique - approximately similar changes are observed in non-drought years as well. Changes in surface solar irradiance are contrary to the speculation in the previously published report of enhanced sunlight availability during the 2005 drought. There was no co-relation between drought severity and greenness changes, which is contrary to the idea of drought-induced greening. Thus, we conclude that Amazon forests did not green-up during the 2005 drought.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

Forests and Climate Change: Forcings, Feedbacks, and the Climate Benefits of Forests

Abstract: The world's forests influence climate through physical, chemical, and biological processes that affect planetary energetics, the hydrologic cycle, and atmospheric composition. These complex and nonlinear forest-atmosphere interactions can dampen or amplify anthropogenic climate change. Tropical, temperate, and boreal reforestation and afforestation attenuate global warming through carbon sequestration. Biogeophysical feedbacks can enhance or diminish this negative climate forcing. Tropical forests mitigate warming through evaporative cooling, but the low albedo of boreal forests is a positive climate forcing. The evaporative effect of temperate forests is unclear. The net climate forcing from these and other processes is not known. Forests are under tremendous pressure from global change. Interdisciplinary science that integrates knowledge of the many interacting climate services of forests with the impacts of global change is necessary to identify and understand as yet unexplored feedbacks in the Earth system and the potential of forests to mitigate climate change.

Europe-wide reduction in primary productivity caused by the heat and drought in 2003

Abstract: Future climate warming is expected to enhance plant growth in temperate ecosystems and to increase carbon sequestration. But although severe regional heatwaves may become more frequent in a changing climate their impact on terrestrial carbon cycling is unclear. Here we report measurements of ecosystem carbon dioxide fluxes, remotely sensed radiation absorbed by plants, and country-level crop yields taken during the European heatwave in 2003.We use a terrestrial biosphere simulation model to assess continental-scale changes in primary productivity during 2003, and their consequences for the net carbon balance. We estimate a 30 per cent reduction in gross primary productivity over Europe, which resulted in a strong anomalous net source of carbon dioxide (0.5 Pg Cyr21) to the atmosphere and reversed the effect of four years of net ecosystem carbon sequestration. Our results suggest that productivity reduction in eastern and western Europe can be explained by rainfall deficit and extreme summer heat, respectively. We also find that ecosystem respiration decreased together with gross primary productivity, rather than accelerating with the temperature rise. Model results, corroborated by historical records of crop yields, suggest that such a reduction in Europe's primary productivity is unprecedented during the last century. An increase in future drought events could turn temperate ecosystems into carbon sources, contributing to positive carbon-climate feedbacks already anticipated in the tropics and at high latitudes.

Support vector machines in remote sensing: A review

Abstract: A wide range of methods for analysis of airborne- and satellite-derived imagery continues to be proposed and assessed. In this paper, we review remote sensing implementations of support vector machines (SVMs), a promising machine learning methodology. This review is timely due to the exponentially increasing number of works published in recent years. SVMs are particularly appealing in the remote sensing field due to their ability to generalize well even with limited training samples, a common limitation for remote sensing applications. However, they also suffer from parameter assignment issues that can significantly affect obtained results. A summary of empirical results is provided for various applications of over one hundred published works (as of April, 2010). It is our hope that this survey will provide guidelines for future applications of SVMs and possible areas of algorithm enhancement.