63 research outputs found

    IMPACT OF CLIMATE CHANGE ON WILDLAND FIRE THREAT TO THE AMUR TIGER AND ITS HABITAT

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    Global biodiversity is increasingly threatened by combined pressures from human- and climate-related environmental change. Projected climate change indicates that these trends are likely to continue and may accelerate by the end of this century leading to large scale modification of species habitats. Such modification will be amplified by an increase in catastrophic natural events such as wildland fire - one of the dominant disturbance agents in boreal and temperate forests of the Russian Far East (RFE). In the RFE, large fire events lead to abrupt, extensive, and long-term conversion of forests to open landscapes, thus considerably impacting the habitat of the critically endangered Amur tiger (Panthera tigris altaica). A remotely sensed data-driven regional fire threat model (FTM) is developed to assess current and projected fire threat to the Amur tiger under scenarios of climate change. The FTM is parameterized to account for regional specifics of fire occurrence in the RFE and fire impacts on the Amur tigers, their main prey, and their habitat. Fire regimes are shown to be strongly influenced by anthropogenic use of fire and the monsoonal climate of the RFE, with large fire seasons observed during uncharacteristically dry years. Even with a large proportion of human ignition sources and periodic extreme events, fire currently poses a limited threat to the Amur tiger meta-population. The observed peaks in high fire threat conditions are localized in space and time and are likely to impact a small number of individual tigers. Under the wide range of the IPCC climate change scenarios, no considerable change in fire danger is expected by the mid-21st century. However, by the end of the 21st century under the A2 (regional self-reliance) scenario of the IPCC Special Report on Emissions, fire danger over the southern part of the RFE is predicted to increase by nearly 15%. An overlap of areas of likely increase in fire danger with areas of highest tiger habitat quality results in a 20% mean yearly increase in fire threat with a mean monthly increase of ~40% in August. The results have implications for conservation strategies aimed at securing long-term habitat availability

    Impacts of wildfire and landscape factors on organic soil properties in Arctic tussock tundra

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    Tundra ecosystems contain some of the largest stores of soil organic carbon among all biomes worldwide. Wildfire, the primary disturbance agent in Arctic tundra, is likely to impact soil properties in ways that enable carbon release and modify ecosystem functioning more broadly through impacts on organic soils, based on evidence from a recent extreme Anaktuvuk River Fire (ARF). However, comparatively little is known about the long-term impacts of typical tundra fires that are short-lived and transient. Here we quantitatively investigated how these transient tundra fires and other landscape factors affected organic soil properties, including soil organic layer (SOL) thickness, soil temperature, and soil moisture, in the tussock tundra. We examined extensive field observations collected from nearly 200 plots across a wide range of fire-impacted tundra regions in AK within the scope of NASA\u27s Arctic Boreal Vulnerability Experiment. We found an overall shallower SOL in our field regions (∼15 cm on average) compared to areas with no known fire record or the ARF (∼20 cm or thicker), suggesting that estimations based on evidence from the extreme ARF event could result in gross overestimation of soil organic carbon (SOC) stock and fire impacts across the tundra. Typical tundra fires could be too short-lived to result in substantial SOL consumption and yield less robust results of SOL and carbon storage. Yet, repeated fires may amount to a larger amount of SOC loss than one single severe burning. As expected, our study showed that wildfire could affect soil moisture and temperature in the tussock tundra over decades after the fire, with drier and warmer soils found to be associated with more frequent and severe burnings. Soil temperature was also associated with vegetation cover and air temperature

    The NASA NEESPI Data Portal: Products, Information, and Services

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    Studies have indicated that land cover and use changes in Northern Eurasia influence global climate system. However, the procedures are not fully understood and it is challenging to understand the interactions between the land changes in this region and the global climate. Having integrated data collections form multiple disciplines are important for studies of climate and environmental changes. Remote sensed and model data are particularly important die to sparse in situ measurements in many Eurasia regions especially in Siberia. The NASA GES DISC (Goddard Earth Sciences Data and Information Services Center) NEESPI data portal has generated infrastructure to provide satellite remote sensing and numerical model data for atmospheric, land surface, and cryosphere. Data searching, subsetting, and downloading functions are available. ONe useful tool is the Web-based online data analysis and visualization system, Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure), which allows scientists to assess easily the state and dynamics of terrestrial ecosystems in Northern Eurasia and their interactions with global climate system. Recently, we have created a metadata database prototype to expand the NASA NEESPI data portal for providing a venue for NEESPI scientists fo find the desired data easily and leveraging data sharing within NEESPI projects. The database provides product level information. The desired data can be found through navigation and free text search and narrowed down by filtering with a number of constraints. In addition, we have developed a Web Map Service (WMS) prototype to allow access data and images from difference data resources

    Remote sensing estimates of stand-replacement fires in Russia, 2002–2011

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    The presented study quantifies the proportion of stand-replacement fires in Russian forests through the integrated analysis of Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) data products. We employed 30 m Landsat Enhanced Thematic Mapper Plus derived tree canopy cover and decadal (2001–2012) forest cover loss (Hansen et al 2013 High-resolution global maps of 21st-century forest cover change Science 342 850–53) to identify forest extent and disturbance. These data were overlaid with 1 km MODIS active fire (earthdata.nasa.gov/data/near-real-time-data/firms) and 500 m regional burned area data (Loboda et al 2007 Regionally adaptable dNBR-based algorithm for burned area mapping from MODIS data Remote Sens. Environ. 109 429–42 and Loboda et al 2011 Mapping burned area in Alaska using MODIS data: a data limitations-driven modification to the regional burned area algorithm Int. J. Wildl. Fire 20 487–96) to differentiate stand-replacement disturbances due to fire versus other causes. Total stand replacement forest fire area within the Russian Federation from 2002 to 2011 was estimated to be 17.6 million ha (Mha). The smallest stand-replacement fire loss occurred in 2004 (0.4 Mha) and the largest annual loss in 2003 (3.3 Mha). Of total burned area within forests, 33.6% resulted in stand-replacement. Light conifer stands comprised 65% of all non-stand-replacement and 79% of all stand-replacement fire in Russia. Stand-replacement area for the study period is estimated to be two times higher than the reported logging area. Results of this analysis can be used with historical fire regime estimations to develop effective fire management policy, increase accuracy of carbon calculations, and improve fire behavior and climate change modeling efforts

    Quantifying burned area for North American forests: Implications for direct reduction of carbon stocks

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    A synthesis was carried out to analyze information available to quantify fire activity and burned area across North America, including a comparison of different data sources and an assessment of how variations in burned area estimate impact carbon emissions from fires. Data sets maintained by fire management agencies provide the longest record of burned area information. Canada and Alaska have the most well developed data sets consisting of the perimeters of large fires (\u3e200 ha) going back to 1959 and 1950, respectively. A similar data set back to 1980 exists for the Conterminous U.S., but contains data only from federal land management agencies. During the early half of the 20th century, average burned area across North America ranged between 10 and 20 × 106 ha yr−1, largely because of frequent surface fires in the southeastern U.S. Over the past two decades, an average of 5 × 106 ha yr−1 has burned. Moderate-resolution (500–1000 m) satellite burned area products information products appear to either underestimate burned area (GFED3 and MCD45A1) or significantly overestimate burned area (L3JRC and GLOBCARBON). Of all the satellite data products, the GFED3 data set provides the most consistent source of burned area when compared to fire management data. Because they do not suitably reflect actual fire activity, the L3JRC and GLOBCARBON burned area data sets are not suitable for use in carbon cycle studies in North America. The MCD45A1 data set appears to map a higher fraction of burned area in low biomass areas compared to the GFED3 data set

    Using the NASA NEESPI Portal Data to Study Land, Climate, and Socio-Economic Changes in Northern Eurasia

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    A large number of fires detected in July of 2003 - a nearly 200-time increase in fire detections compared to other years during 2001-2006. despite the summer monsoon suppression of large fire occurrence. Traditional vegetation indices (NDVI and EVI) included in operational fire danger assessment provide little information on the fuel state in this ecosystem pre- or post-fire. No considerable differences in surface temperature and soil moisture in July were observed between the catastrophic year of 2003 and the two subsequent years of low summer fire occurrence of 2004 and 2005. However, the temporal analysis indicates that dry spring conditions in 2003 (detected through low soil moisture measurements in April and May) may have led to a stressed vegetative state and created conditions conducive to catastrophic fire occurrence

    Synthesis, Crystal Structure Refinement, and Electrical Conductivity of Pb(8−x)Na2Smx(VO4)6O(x/2)

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    Solid solutions of Pb(8−x)Na2Smx(VO4)6O(x/2) were studied using X-ray diffraction analysis including Rietveld refinement and scanning electron microscopy and by measuring their electrical conductivity. Crystal structure of the solid solutions was refined and the solubility region 0 ≤ x ≤ 0.2 was determined for samarium substitution for lead under the scheme 2Pb2+ + ◻ → 2Sm3+ + O2-. The influence of degree of substitution on the electrical conductivity of solid solutions was established

    Modeling acute respiratory illness during the 2007 San Diego wildland fires using a coupled emissions-transport system and general additive modeling

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    Background A study of the impacts on respiratory health of the 2007 wildland fires in and around San Diego County, California is presented. This study helps to address the impact of fire emissions on human health by modeling the exposure potential of proximate populations to atmospheric particulate matter (PM) from vegetation fires. Currently, there is no standard methodology to model and forecast the potential respiratory health effects of PM plumes from wildland fires, and in part this is due to a lack of methodology for rigorously relating the two. The contribution in this research specifically targets that absence by modeling explicitly the emission, transmission, and distribution of PM following a wildland fire in both space and time. Methods Coupled empirical and deterministic models describing particulate matter (PM) emissions and atmospheric dispersion were linked to spatially explicit syndromic surveillance health data records collected through the San Diego Aberration Detection and Incident Characterization (SDADIC) system using a Generalized Additive Modeling (GAM) statistical approach. Two levels of geographic aggregation were modeled, a county-wide regional level and division of the county into six sub regions. Selected health syndromes within SDADIC from 16 emergency departments within San Diego County relevant for respiratory health were identified for inclusion in the model. Results The model captured the variability in emergency department visits due to several factors by including nine ancillary variables in addition to wildfire PM concentration. The model coefficients and nonlinear function plots indicate that at peak fire PM concentrations the odds of a person seeking emergency care is increased by approximately 50% compared to non-fire conditions (40% for the regional case, 70% for a geographically specific case). The sub-regional analyses show that demographic variables also influence respiratory health outcomes from smoke. Conclusions The model developed in this study allows a quantitative assessment and prediction of respiratory health outcomes as it relates to the location and timing of wildland fire emissions relevant for application to future wildfire scenarios. An important aspect of the resulting model is its generality thus allowing its ready use for geospatial assessments of respiratory health impacts under possible future wildfire conditions in the San Diego region. The coupled statistical and process-based modeling demonstrates an end-to-end methodology for generating reasonable estimates of wildland fire PM concentrations and health effects at resolutions compatible with syndromic surveillance data

    Urbanization and sustainability under transitional economies:a synthesis for Asian Russia

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    Spanning a vast territory of approximately 13 million km ^2 , Asian Russia was home to 38 million people in 2016. In an effort to synthesize data and knowledge regarding urbanization and sustainable development in Asian Russia in the context of socioeconomic transformation following the breakup of the Soviet Union in 1990, we quantified the spatiotemporal changes of urban dynamics using satellite imagery and explored the interrelationships between urbanization and sustainability. We then developed a sustainability index, complemented with structural equation modeling, for a comprehensive analysis of their dynamics. We chose six case cities, i.e., Yekaterinburg, Novosibirsk, Krasnoyarsk, Omsk, Irkutsk, and Khabarovsk, as representatives of large cities to investigate whether large cities are in sync with the region in terms of population dynamics, urbanization, and sustainability. Our major findings include the following. First, Asian Russia experienced enhanced economic growth despite the declining population. Furthermore, our case cities showed a general positive trend for population dynamics and urbanization as all except Irkutsk experienced population increases and all expanded their urban built-up areas, ranging from 13% to 16% from 1990 to 2014. Second, Asian Russia and its three federal districts have improved their sustainability and levels of economic development, environmental conditions, and social development. Although both regional sustainability and economic development experienced a serious dip in the 1990s, environmental conditions and social development continuously improved from 1990 to 2014, with social development particularly improving after 1995. Third, in terms of the relationships between urbanization and sustainability, economic development appeared as an important driver of urbanization, social development, and environmental degradation in Asian Russia, with economic development having a stronger influence on urbanization than on social development or environmental degradation

    Northern Eurasia Future Initiative (NEFI): facing the challenges and pathways of global change in the twenty-first century

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    During the past several decades, the Earth system has changed significantly, especially across Northern Eurasia. Changes in the socio-economic conditions of the larger countries in the region have also resulted in a variety of regional environmental changes that can have global consequences. The Northern Eurasia Future Initiative (NEFI) has been designed as an essential continuation of the Northern Eurasia Earth Science Partnership Initiative (NEESPI), which was launched in 2004. NEESPI sought to elucidate all aspects of ongoing environmental change, to inform societies and, thus, to better prepare societies for future developments. A key principle of NEFI is that these developments must now be secured through science-based strategies co-designed with regional decision-makers to lead their societies to prosperity in the face of environmental and institutional challenges. NEESPI scientific research, data, and models have created a solid knowledge base to support the NEFI program. This paper presents the NEFI research vision consensus based on that knowledge. It provides the reader with samples of recent accomplishments in regional studies and formulates new NEFI science questions. To address these questions, nine research foci are identified and their selections are briefly justified. These foci include warming of the Arctic; changing frequency, pattern, and intensity of extreme and inclement environmental conditions; retreat of the cryosphere; changes in terrestrial water cycles; changes in the biosphere; pressures on land use; changes in infrastructure; societal actions in response to environmental change; and quantification of Northern Eurasia’s role in the global Earth system. Powerful feedbacks between the Earth and human systems in Northern Eurasia (e.g., mega-fires, droughts, depletion of the cryosphere essential for water supply, retreat of sea ice) result from past and current human activities (e.g., large-scale water withdrawals, land use, and governance change) and potentially restrict or provide new opportunities for future human activities. Therefore, we propose that integrated assessment models are needed as the final stage of global change assessment. The overarching goal of this NEFI modeling effort will enable evaluation of economic decisions in response to changing environmental conditions and justification of mitigation and adaptation efforts
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