"Our species' pervasive presence on the planet is the combined result of two powerful forces: earth's rich natural endowments and humanity's ability to manipulate nature. From our ability to control fire to our expertise in breeding palatable plants, from our capacity to ship fertilizer across the Atlantic to our skill in selectively tinkering with plant genomes, DeFries describes the ingenious manipulations of nature that have enabled humankind to nourish and flourish. Throughout history humans have been able to ratchet up populations, survive the hatchets that threaten the species, and pivot to a new strategy for survival"--
Landscape-level conservation that maintains biodiversity and livelihoods for local people requires long-term collaborations across local communities, scientists, practitioners and decision-makers. The Network for Conserving Central India (NCCI) provides a platform for such collaborations in a globally important tiger conservation region within a complex social-ecological system. Using the NCCI as an example, our study identifies indicators to track progress in collaborative landscape-level networks across four dimensions: the composition of the network; collaborative scientific output; dissemination of research outputs through social, electronic and print media; and participation in policy and decision-making bodies. The NCCI is primarily comprised of members of the scientific community, Non-Governmental Organizations (NGOs) and various levels of government. Since 2013, the NCCI members conducted research that predominantly addressed human-wildlife conflicts and human livelihood needs around protected areas (PAs), with less attention to forest ecology and climate. NGOs within the NCCI work closely with local communities and provide avenues for local engagement. Co-production of policies is an essential but challenging goal due to established hierarchies and top-down institutional structures. Our analyses highlight the NCCI's role as a knowledge platform and bridge among researchers, NGOs, and government, with significant opportunities for boundary work in the Science, Policy and Practice Interface (SPPI). A challenging and unfulfilled goal is the engagement of local communities to co-produce approaches that balance conservation, local livelihoods, and development. We suggest that other landscape-level networks in social-ecological systems can modify these dimensions as pertinent to their respective circumstances to track progress towards co-produced management to address livelihood and conservation needs.
In north India, agricultural burning adversely affects local and regional air quality during the post-monsoon season (October to November), when the prevailing meteorology is favorable for smog and haze formation. Quantifying the contribution of smoke to air pollution in this region, however, is challenging. While the Moderate Resolution Imaging Spectroradiometer (MODIS), aboard NASA's Terra and Aqua satellites, provides a nearly 20-year record of global fire activity, the sensor cannot adequately capture small, short-lasting agricultural fires due to its moderate spatial resolution (500 m–1 km) and limited overpasses (twice daily for each satellite), as well as the hazy conditions that typically obscure the north India land surface at this time of year. Moreover, current global fire emissions inventories based on MODIS observations can differ by up to an order of magnitude in this region. Here we incorporate household survey data to bridge gaps in MODIS observations and improve estimates of fire emissions over the states of Punjab, Haryana, Uttar Pradesh, and Bihar during the 2003–2018 post-monsoon burning seasons. We develop a novel method that adjusts MODIS Fire Radiative Power (FRP) for: (1) small fires detected by the Visible Infrared Imaging Radiometer Suite (VIIRS) at 375-m spatial resolution, (2) cloud/haze gaps in satellite observations, (3) partial-field burning practices, and (4) the diurnal cycle of fire activity. Adjusting FRP for the fire diurnal cycle yields the largest boost to emissions due to the short lifetime of the fires (~1/2 h) and the brief windows of satellite detection. Using adjusted FRP, we estimate on average 10.4 ± 3 Tg dry matter (DM) burned each year, yielding emissions of 65 ± 18 Gg organic carbon (OC), 5.6 ± 1.6 Gg black carbon (BC), 791 ± 225 Gg CO, and 14.9 ± 4.2 Tg CO2. On average, our OC + BC emissions are 3.4 times (min: 0.6, max: 6.6) the estimates from five widely used global fire emissions inventories. Our estimate for Punjab, which contributes more than two-thirds of emissions in the region, is consistent with our bottom-up validation, which uses burn rates from the household survey and government crop production statistics in 2016 and 2017. We spatially disaggregate the state-level emissions to construct a gridded inventory at daily, 0.25 ° × 0.25 ° resolution over north India from 2003 to 2018. The inventory, SAGE-IGP (Survey Constraints on FRP-based Agricultural Fire Emissions in the Indo-Gangetic Plain), improves modeling assessments of air quality impacts from agricultural burning, thus supporting effective policy development.
Humanity faces the grand challenge of feeding a growing, more affluent population in the coming decades while reducing the environmental burden of agriculture. Approaches that integrate food security and environmental goals offer promise for achieving a more sustainable global food system, yet little work has been done to link potential solutions with agricultural policies. Taking the case of cereal production in India, we use a process-based crop water model and government data on food production and nutrient content to assess the implications of various crop-shifting scenarios on consumptive water demand and nutrient production. We find that historical growth in wheat production during the rabi (non-monsoon) season has been the main driver of the country's increased consumptive irrigation water demand and that rice is the least water-efficient cereal for the production of key nutrients, especially for iron, zinc, and fiber. By replacing rice areas in each district with the alternative cereal (maize, finger millet, pearl millet, or sorghum) with the lowest irrigation (blue) water footprint (WFP), we show that it is possible to reduce irrigation water demand by 33% and improve the production of protein (+1%), iron (+27%), and zinc (+13%) with only a modest reduction in calories. Replacing rice areas with the lowest total (rainfall + irrigation) WFP alternative cereal or the cereal with the highest nutritional yield (metric tons of protein per hectare or kilograms of iron per hectare) yielded similar benefits. By adopting a similar multidimensional framework, India and other nations can identify food security solutions that can achieve multiple sustainability goals simultaneously.
From 2006 to 2010, deforestation in the Amazon frontier state of Mato Grosso decreased to 30% of its historical average (1996–2005) whereas agricultural production reached an all-time high. This study combines satellite data with government deforestation and production statistics to assess land-use transitions and potential market and policy drivers associated with these trends. In the forested region of the state, increased soy production from 2001 to 2005 was entirely due to cropland expansion into previously cleared pasture areas (74%) or forests (26%). From 2006 to 2010, 78% of production increases were due to expansion (22% to yield increases), with 91% on previously cleared land. Cropland expansion fell from 10 to 2% of deforestation between the two periods, with pasture expansion accounting for most remaining deforestation. Declining deforestation coincided with a collapse of commodity markets and implementation of policy measures to reduce deforestation. Soybean profitability has since increased to pre-2006 levels whereas deforestation continued to decline, suggesting that antideforestation measures may have influenced the agricultural sector. We found little evidence of direct leakage of soy expansion into cerrado in Mato Grosso during the late 2000s, although indirect land-use changes and leakage to more distant regions are possible. This study provides evidence that reduced deforestation and increased agricultural production can occur simultaneously in tropical forest frontiers, provided that land is available and policies promote the efficient use of already-cleared lands (intensification) while restricting deforestation. It remains uncertain whether government- and industry-led policies can contain deforestation if future market conditions favor another boom in agricultural expansion.
Groundwater depletion is becoming a global threat to food security, yet the ultimate impacts of depletion on agricultural production and the efficacy of available adaptation strategies remain poorly quantified. We use high-resolution satellite and census data from India, the world's largest consumer of groundwater, to quantify the impacts of groundwater depletion on cropping intensity, a crucial driver of agricultural production. Our results suggest that, given current depletion trends, cropping intensity may decrease by 20% nationwide and by 68% in groundwater-depleted regions. Even if surface irrigation delivery is increased as a supply-side adaptation strategy, which is being widely promoted by the Indian government, cropping intensity will decrease, become more vulnerable to interannual rainfall variability, and become more spatially uneven. We find that groundwater and canal irrigation are not substitutable and that additional adaptation strategies will be necessary to maintain current levels of production in the face of groundwater depletion.
Groundwater depletion is becoming a global threat to food security, yet the ultimate impacts of depletion on agricultural production and the efficacy of available adaptation strategies remain poorly quantified. We use high-resolution satellite and census data from India, the world's largest consumer of groundwater, to quantify the impacts of groundwater depletion on cropping intensity, a crucial driver of agricultural production. Our results suggest that, given current depletion trends, cropping intensity may decrease by 20% nationwide and by 68% in groundwater-depleted regions. Even if surface irrigation delivery is increased as a supply-side adaptation strategy, which is being widely promoted by the Indian government, cropping intensity will decrease, become more vulnerable to interannual rainfall variability, and become more spatially uneven. We find that groundwater and canal irrigation are not substitutable and that additional adaptation strategies will be necessary to maintain current levels of production in the face of groundwater depletion.
The Brazilian government annually assesses the extent of deforestation in the Legal Amazon for a variety of scientific and policy applications. Currently, the assessment requires the processing and storing of large volumes of Landsat satellite data. The potential for efficient, accurate, and less data-intensive assessment of annual deforestation using data from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) at 250-m resolution is evaluated. Landsat-derived deforestation estimates are compared to MODIS-derived estimates for six Landsat scenes with five change-detection algorithms and a variety of input data—Surface Reflectance (MOD09), Vegetation Indices (MOD13), fraction images derived from a linear mixing model, Vegetation Cover Conversion (MOD44A), and percent tree cover from the Vegetation Continuous Fields (MOD44B) product. Several algorithms generated consistently low commission errors (positive predictive value near 90 and identified more than 80% of deforestation polygons larger than 3 ha. All methods accurately identified polygons larger than 20 ha. However, no method consistently detected a high percent of Landsat-derived deforestation area across all six scenes. Field validation in central Mato Grosso confirmed that all MODIS-derived deforestation clusters larger than three 250-m pixels were true deforestation. Application of this field-validated method to the state of Mato Grosso for 2001–04 highlighted a change in deforestation dynamics; the number of large clusters (>10 MODIS pixels) that were detected doubled, from 750 between August 2001 and August 2002 to over 1500 between August 2003 and August 2004. These analyses demonstrate that MODIS data are appropriate for rapid identification of the location of deforestation areas and trends in deforestation dynamics with greatly reduced storage and processing requirements compared to Landsat-derived assessments. However, the MODIS-based analyses evaluated in this study are not a replacement for high-resolution analyses that estimate the ...
