Conservation initiatives overwhelmingly focus on terrestrial biodiversity, and little is known about the freshwater cobenefits of terrestrial conservation actions. We sampled more than 1500 terrestrial and freshwater species in the Amazon and simulated conservation for species from both realms. Prioritizations based on terrestrial species yielded on average just 22% of the freshwater benefits achieved through freshwater-focused conservation. However, by using integrated cross-realm planning, freshwater benefits could be increased by up to 600% for a 1% reduction in terrestrial benefits. Where freshwater biodiversity data are unavailable but aquatic connectivity is accounted for, freshwater benefits could still be doubled for negligible losses of terrestrial coverage. Conservation actions are urgently needed to improve the status of freshwater species globally. Our results suggest that such gains can be achieved without compromising terrestrial conservation goals.

ABSTRACT. Tropical forests continue to be plagued by the dual sustainability challenges of deforestation and rural poverty. We seek to understand why many of the farmers living in the Brazilian Amazon, home to the world's largest tropical agricultural-forest frontier, persist in agricultural activities associated with low incomes and high environmental damage. To answer this question, we assess the factors that shape the development and distribution of agricultural activities and farmer well-being in these frontiers. Our study utilizes a uniquely comprehensive social-ecological dataset from two regions in the eastern Brazilian Amazon and employs a novel conceptual framework that highlights the interdependencies between household attributes, agricultural activities, and well-being. We find that livestock production, which yields the lowest per hectare incomes, remains the most prevalent land use in remote areas, but many examples of high income fruit, horticulture, and staple crop production exist on small properties, particularly in peri-urban areas. The transition to more profitable land uses is limited by lagging supply chain infrastructure, social preferences, and the fact that income associated with land use activities is not a primary source of perceived life quality. Instead subjective well-being is more heavily influenced by the nonmonetary attributes of a rural lifestyle (safety, tranquility, community relations, etc.). We conclude that transitions away from low-income land uses in agricultural-forest frontiers of the Brazilian Amazon need not abandon a land-focused vision of development, but will require policies and programs that identify and discriminate households based on a broader set of household assets, cultural attributes, and aspirations than are traditionally applied. At a broader scale, access to distant markets for high value crops must be improved via investments in processing, storage, and marketing infrastructure.

Carbon (C) emissions from forest fires in the Amazon during extreme droughts may correspond to more than half of the global emissions resulting from land cover changes. Despite their relevant contribution, forest fire-related C emissions are not directly accounted for within national-level inventories or carbon budgets. A fundamental condition for quantifying these emissions is to have a reliable estimation of the extent and location of land cover types affected by fires. Here, we evaluated the relative performance of four burned area products (TREES, MCD64A1 c6, GABAM, and Fire_cci v5.0), contrasting their estimates of total burned area, and their influence on the fire-related C emissions in the Amazon biome for the year 2015. In addition, we distinguished the burned areas occurring in forests from non-forest areas. The four products presented great divergence in the total burned area and, consequently, total related C emissions. Globally, the TREES product detected the largest amount of burned area (35,559 km2), and consequently it presented the largest estimate of committed carbon emission (45 Tg), followed by MCD64A1, with only 3% less burned area detected, GABAM (28,193 km2) and Fire_cci (14,924 km2). The use of Fire_cci may result in an underestimation of 29.54 ± 3.36 Tg of C emissions in relation to the TREES product. The same pattern was found for non-forest areas. Considering only forest burned areas, GABAM was the product that detected the largest area (8994 km2), followed by TREES (7985 km2), MCD64A1 (7181 km2) and Fire_cci (1745 km2). Regionally, Fire_cci detected 98% less burned area in Acre state in southwest Amazonia than TREES, and approximately 160 times less burned area in forests than GABAM. Thus, we show that global products used interchangeably on a regional scale could significantly underestimate the impacts caused by fire and, consequently, their related carbon emissions.

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Agricultural fires are a double-edged sword that allow for cost-efficient land management in the tropics but also cause accidental fires and emissions of carbon and pollutants. To control fires in Amazon, it is currently unclear whether policy-makers should prioritize commandand-control or incentive-based instruments such as REDD+. Aiming to generate knowledge about the relative merits of the two policy approaches, this paper presents a spatially-explicit agent-based model that simulates the causal effects of four policy instruments on intended and unintended fires. All instruments proved effective in overturning the predominance of highly profitable but risky fire-use and decreasing accidental fires, but none were free from imperfections. The performance of command-and-control proved highly sensitive to the spatial and social reach of enforcement. Side-effects of incentive-based instruments included a disproportionate increase in controlled fires and a reduced acceptance of conservation subsidies, caused by the prohibition of reckless fires, and also indirect deforestation. The instruments that were most effective in reducing deforestation were not the most effective in reducing fires and vice-versa, which suggests that the two goals cannot be achieved with a single policy intervention.