25 research outputs found

    Impacts of land use, restoration, and climate change on tropical peat carbon stocks in the 21st century: Implications for climate mitigation

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    The climate mitigation potential of tropical peatlands has gained increased attention as Southeast Asian peatlands are being deforested, drained and burned at very high rates, causing globally significant carbon dioxide (CO2) emissions to the atmosphere. We used a process-based dynamic tropical peatland model to explore peat carbon (C) dynamics of several management scenarios within the context of simulated twenty-first century climate change. Simulations of all scenarios with land use, including restoration, indicated net C losses over the twenty-first century ranging from 10 to 100 % of pre-disturbance values. Fire can be the dominant C-loss pathway, particularly in the drier climate scenario we tested. Simulated 100 years of oil palm (Elaeis guineensis) cultivation with an initial prescribed burn resulted in 2400–3000 Mg CO2 ha−1 total emissions. Simulated restoration following one 25-year oil palm rotation reduced total emissions to 440–1200 Mg CO2 ha−1, depending on climate. These results suggest that even under a very optimistic scenario of hydrological and forest restoration and the wettest climate regime, only about one third of the peat C lost to the atmosphere from 25 years of oil palm cultivation can be recovered in the following 75 years if the site is restored. Emissions from a simulated land degradation scenario were most sensitive to climate, with total emissions ranging from 230 to 10,600 Mg CO2 ha−1 over 100 years for the wettest and driest dry season scenarios, respectively. The large difference was driven by increased fire probability. Therefore, peat fire suppression is an effective management tool to maintain tropical peatland C stocks in the near term and should be a high priority for climate mitigation efforts. In total, we estimate emissions from current cleared peatlands and peatlands converted to oil palm in Southeast Asia to be 8.7 Gt CO2 over 100 years with a moderate twenty-first century climate. These emissions could be minimized by effective fire suppression and hydrological restoration

    Intercomparison of phenological transition dates derived from the PhenoCam Dataset V1.0 and MODIS satellite remote sensing

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    Phenology is a valuable diagnostic of ecosystem health, and has applications to environmental monitoring and management. Here, we conduct an intercomparison analysis using phenological transition dates derived from near-surface PhenoCam imagery and MODIS satellite remote sensing. We used approximately 600 site-years of data, from 128 camera sites covering a wide range of vegetation types and climate zones. During both “greenness rising” and “greenness falling” transition phases, we found generally good agreement between PhenoCam and MODIS transition dates for agricultural, deciduous forest, and grassland sites, provided that the vegetation in the camera field of view was representative of the broader landscape. The correlation between PhenoCam and MODIS transition dates was poor for evergreen forest sites. We discuss potential reasons (including sub-pixel spatial heterogeneity, flexibility of the transition date extraction method, vegetation index sensitivity in evergreen systems, and PhenoCam geolocation uncertainty) for varying agreement between time series of vegetation indices derived from PhenoCam and MODIS imagery. This analysis increases our confidence in the ability of satellite remote sensing to accurately characterize seasonal dynamics in a range of ecosystems, and provides a basis for interpreting those dynamics in the context of tangible phenological changes occurring on the ground

    Focus on the impact of climate change on wetland ecosystem and carbon dynamics

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    The renewed growth in atmospheric methane (CH4)since 2007 after a decade of stabilization has drawn much attention to its causes and future trends. Wetlands are the single largest source of atmospheric CH4. Understanding wetland ecosystems and carbon dynamics is critical to the estimation of global CH4 and carbon budgets. After approximately 7 years of CH4 related research following the renewed growth in atmospheric CH4, Environmental Research Letters launched a special issue of research letters on wetland ecosystems and carbon dynamics in 2014. This special issue highlights recent developments in terrestrial ecosystem models and field measurements of carbon fluxes across different types of wetland ecosystems. The 14 research letters emphasize the importance of wetland ecosystems in the global CO2 and CH4 budget

    The use and re-use of unsustainable groundwater for irrigation: A global budget

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    Depletion of groundwater aquifers across the globe has become a significant concern, as groundwater is an important and often unsustainable source of irrigation water. Simultaneously, the field of water resource management has seen a lively debate over the concepts and metrics used to assess the downstream re-use of agricultural runoff, with most studies focusing on surface water balances. Here, we bring these two lines of research together, recognizing that depletion of aquifers leads to large amounts of groundwater entering surface water storages and flows by way of agricultural runoff. While it is clear that groundwater users will be impacted by reductions in groundwater availability, there is a major gap in our understanding of potential impacts downstream of groundwater pumping locations. We find that the volume of unsustainable groundwater that is re-used for irrigation following runoff from agricultural systems is nearly as large as the volume initially extracted from reservoirs for irrigation. Basins in which the volume of irrigation water re-used is equal to or greater than the volume of water initially used (which is possible due to multiple re-use of the same water) contain 33 million hectares of irrigated land and are home to 1.3 billion people. Some studies have called for increasing irrigation efficiency as a solution to water shortages. We find that with 100% irrigation efficiency, global demand for unsustainable groundwater is reduced by 52%, but not eliminated. In many basins, increased irrigation efficiency leads to significantly decreased river low flows; increasing irrigation efficiency to 70% globally decreases total surface water supplies by backsim600 km3 yr−1. These findings illustrate that estimates of aquifer depletion alone underestimate the importance of unsustainable groundwater to sustaining surface water systems and irrigated agriculture

    Evaluating multiple causes of persistent low microwave backscatter from Amazon forests after the 2005 drought

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    Amazonia has experienced large-scale regional droughts that affect forest productivity and biomass stocks. Space-borne remote sensing provides basin-wide data on impacts of meteorological anomalies, an important complement to relatively limited ground observations across the Amazon’s vast and remote humid tropical forests. Morning overpass QuikScat Ku-band microwave backscatter from the forest canopy was anomalously low during the 2005 drought, relative to the full instrument record of 1999–2009, and low morning backscatter persisted for 2006–2009, after which the instrument failed. The persistent low backscatter has been suggested to be indicative of increased forest vulnerability to future drought. To better ascribe the cause of the low post-drought backscatter, we analyzed multiyear, gridded remote sensing data sets of precipitation, land surface temperature, forest cover and forest cover loss, and microwave backscatter over the 2005 drought region in the southwestern Amazon Basin (4°-12°S, 66°-76°W) and in adjacent 8°x10° regions to the north and east. We found moderate to weak correlations with the spatial distribution of persistent low backscatter for variables related to three groups of forest impacts: the 2005 drought itself, loss of forest cover, and warmer and drier dry seasons in the post-drought vs. the pre-drought years. However, these variables explained only about one quarter of the variability in depressed backscatter across the southwestern drought region. Our findings indicate that drought impact is a complex phenomenon and that better understanding can only come from more extensive ground data and/or analysis of frequent, spatially-comprehensive, high-resolution data or imagery before and after droughts

    Changes in the soil organic carbon balance on China’s cropland during the last two decades of the 20th century

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    Agro-ecosystems play an important role in regulating global changes caused by greenhouse gas emissions. Restoration of soil organic carbon (SOC) in agricultural soils can not only improve soil quality but also influence climate change and agronomic productivity. With about half of its land area under agricultural use, China exhibits vast potential for carbon (C) sequestration that needs to be researched. Chinese cropland has experienced SOC change over the past century. The study of SOC dynamics under different bioclimatic conditions and cropping systems can help us to better understand this historical change, current status, the impacts of bioclimatic conditions on SOC and future trends. We used a simulation based on historical statistical data to analyze the C balance of Chinese croplands during the 1980s and 1990s, taking into account soil, climate and agricultural management. Nationwide, 77.6% of the national arable land is considered to be in good condition. Appropriate farm management practices should be adopted to improve the poor C balance of the remaining 22.4% of cropland to promote C sequestration

    Assessing Short‐Term Impacts of Management Practices on N2O Emissions From Diverse Mediterranean Agricultural Ecosystems Using a Biogeochemical Model

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    Croplands are important sources of nitrous oxide (N2O) emissions. The lack of both long‐term field measurements and reliable methods for extrapolating these measurements has resulted in a large uncertainty in quantifying and mitigating N2O emissions from croplands. This is especially relevant in regions where cropping systems and farming management practices (FMPs) are diverse. In this study, a process‐based biogeochemical model, DeNitrification‐DeComposition (DNDC), was tested against N2O measurements from five cropping systems (alfalfa, wheat, lettuce, vineyards, and almond orchards) representing diverse environmental conditions and FMPs. The model tests indicated that DNDC was capable of predicting seasonal and annual total N2O emissions from these cropping systems, and the model\u27s performance was better than the Intergovernmental Panel on Climate Change emission factor approach. DNDC also captured the impacts on N2O emissions of nitrogen fertilization for wheat and lettuce, of stand age for alfalfa, as well as the spatial variability of N2O fluxes in vineyards and orchards. DNDC overestimated N2O fluxes following some heavy rainfall events. To reduce the biases of simulating N2O fluxes following heavy rainfall, studies should focus on clarifying mechanisms controlling impacts of environmental factors on denitrification. DNDC was then applied to assess the impacts on N2O emissions of FMPs, including tillage, fertilization, irrigation, and management of cover crops. The practices that can mitigate N2O emissions include reduced or no tillage, reduced N application rates, low‐volume irrigation, and cultivation of nonleguminous cover crops. This study demonstrates the necessity and potential of utilizing process‐based models to quantify N2O emissions from regions with highly diverse cropping systems

    Achieving sustainable irrigation water withdrawals: global impacts on food security and land use

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    Unsustainable water use challenges the capacity of water resources to ensure food security and continued growth of the economy. Adaptation policies targeting future water security can easily overlook its interaction with other sustainability metrics and unanticipated local responses to the larger-scale policy interventions. Using a global partial equilibrium grid-resolving model SIMPLE-G, and coupling it with the global Water Balance Model, we simulate the consequences of reducing unsustainable irrigation for food security, land use change, and terrestrial carbon. A variety of future (2050) scenarios are considered that interact irrigation productivity with two policy interventions— inter-basin water transfers and international commodity market integration. We find that pursuing sustainable irrigation may erode other development and environmental goals due to higher food prices and cropland expansion. This results in over 800 000 more undernourished people and 0.87 GtC additional emissions. Faster total factor productivity growth in irrigated sectors will encourage more aggressive irrigation water use in the basins where irrigation vulnerability is expected to be reduced by inter-basin water transfer. By allowing for a systematic comparison of these alternative adaptations to future irrigation vulnerability, the global gridded modeling approach offers unique insights into the multiscale nature of the water scarcity challenge

    Invisible water, visible impact: How unsustainable groundwater use challenges sustainability of Indian agriculture under climate change

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    India is one of the world’s largest food producers, making the sustainability of its agricultural system of global significance. Groundwater irrigation underpins India’s agriculture, currently boosting crop production by enough to feed 170 million people. Groundwater overexploitation has led to drastic declines in groundwater levels, threatening to push this vital resource out of reach for millions of small-scale farmers who are the backbone of India’s food security. Historically, losing access to groundwater has decreased agricultural production and increased poverty. We take a multidisciplinary approach to assess climate change challenges facing India’s agricultural system, and to assess the effectiveness of large-scale water infrastructure projects designed to meet these challenges. We find that even in areas that experience climate change induced precipitation increases, expansion of irrigated agriculture will require increasing amounts of unsustainable groundwater. The large proposed national river linking project has limited capacity to alleviate groundwater stress. Thus, without intervention, poverty and food insecurity in rural India is likely to worsen

    Ancient Amazonian populations left lasting impacts on forest structure

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    Amazonia contains a vast expanse of contiguous tropical forest and is influential in global carbon and hydrological cycles. Whether ancient Amazonia was highly disturbed or modestly impacted, and how ancient disturbances have shaped current forest ecosystem processes, is still under debate. Amazonian Dark Earths (ADEs), which are anthropic soil types with enriched nutrient levels, are one of the primary lines of evidence for ancient human presence and landscape modifications in settings that mostly lack stone structures and which are today covered by vegetation. We assessed the potential of using moderate spatial resolution optical satellite imagery to predict ADEs across the Amazon Basin. Maximum entropy modeling was used to develop a predictive model using locations of ADEs across the basin and satellite‐derived remotely sensed indices. Amazonian Dark Earth sites were predicted to be primarily along the main rivers and in eastern Amazonia. Amazonian Dark Earth sites, when compared with randomly selected forested sites located within 50 km of ADE sites, were less green canopies (lower normalized difference vegetation index) and had lower canopy water content. This difference was accentuated in two drought years, 2005 and 2010. This is contrary to our expectation that ADE sites would have nutrient‐rich soils that support trees with greener canopies and forests on ADE soils being more resilient to drought. Biomass and tree height were lower on ADE sites in comparison with randomly selected adjacent sites. Our results suggested that ADE‐related ancient human impact on the forest is measurable across the entirety of the 6 million km2 of Amazon Basin using remotely sensed data
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