How to balance land demand conflicts to guarantee sustainable land development.

Severe arable land loss and ecological problems raise attention to protect/develop land for food and ecology demand. Spatial conflict appears in front of multidemand for urbanization, food, and ecology. Our study took China as an example and explicitly outlined spatial preference of urbanization, food, and ecology. From the aspect of land amount, there are enough lands to support multidemand with a surplus of agriculture land of 45.5 × 106 ha. However, spatial conflict widely appears among the multidemands. We tested the impacts of different priorities on urban pattern, crop yield, and ecology and found the priority of food > ecology > urbanization gave the best outcome. Our results verified the importance of including priority of land multidemand to avoid confusion and increase efficiency in the implementation of land policies.

Brazil's sugarcane embitters the EU-Mercosur trade talks.

The Brazilian government's decision to open the Amazon biome to sugarcane expansion reignited EU concerns regarding the sustainability of Brazil's sugar sector, hindering the ratification of the EU-Mercosur trade agreement. Meanwhile, in the EU, certain conventional biofuels face stricter controls, whilst uncertainty surrounding the commercialisation of more sustainable advanced-biofuels renders bioethanol as a short- to medium-term fix. This paper examines Brazil's land-use changes and associated greenhouse gas emissions arising from an EU driven ethanol import policy and projections for other 13 biocommodities. Results suggest that Brazil's sugarcane could satisfy growing ethanol demand and comply with EU environmental criteria, since almost all sugarcane expansion is expected to occur on long-established pasturelands in the South and Midwest. However, expansion of sugarcane is also driven by competition for viable lands with other relevant commodities, mainly soy and beef. As a result, deforestation trends in the Amazon and Cerrado biomes linked to soy and beef production could jeopardize Brazil's contribution to the Paris agreement with an additional 1 ± 0.3 billion CO2eq tonnes above its First NDC target by 2030. Trade talks with a narrow focus on a single commodity could thus risk unsustainable outcomes, calling for systemic sustainability benchmarks, should the deal be ratified.

Deforestation reduces rainfall and agricultural revenues in the Brazilian Amazon.

It has been suggested that rainfall in the Amazon decreases if forest loss exceeds some threshold, but the specific value of this threshold remains uncertain. Here, we investigate the relationship between historical deforestation and rainfall at different geographical scales across the Southern Brazilian Amazon (SBA). We also assess impacts of deforestation policy scenarios on the region's agriculture. Forest loss of up to 55-60% within 28 km grid cells enhances rainfall, but further deforestation reduces rainfall precipitously. This threshold is lower at larger scales (45-50% at 56 km and 25-30% at 112 km grid cells), while rainfall decreases linearly within 224 km grid cells. Widespread deforestation results in a hydrological and economic negative-sum game, because lower rainfall and agricultural productivity at larger scales outdo local gains. Under a weak governance scenario, SBA may lose 56% of its forests by 2050. Reducing deforestation prevents agricultural losses in SBA up to US$ 1 billion annually.

Modelling Highly Biodiverse Areas in Brazil.

Traditional conservation techniques for mapping highly biodiverse areas assume there to be satisfactory knowledge about the geographic distribution of biodiversity. There are, however, large gaps in biological sampling and hence knowledge shortfalls. This problem is even more pronounced in the tropics. Indeed, the use of only a few taxonomic groups or environmental surrogates for modelling biodiversity is not viable in mega-diverse countries, such as Brazil. To overcome these limitations, we developed a comprehensive spatial model that includes phylogenetic information and other several biodiversity dimensions aimed at mapping areas with high relevance for biodiversity conservation. Our model applies a genetic algorithm tool for identifying the smallest possible region within a unique biota that contains the most number of species and phylogenetic diversity, as well as the highest endemicity and phylogenetic endemism. The model successfully pinpoints small highly biodiverse areas alongside regions with knowledge shortfalls where further sampling should be conducted. Our results suggest that conservation strategies should consider several taxonomic groups, the multiple dimensions of biodiversity, and associated sampling uncertainties.

Modelling highly biodiverse areas in Brazil

Traditional conservation techniques for mapping highly biodiverse areas assume there to be satisfactory knowledge about the geographic distribution of biodiversity. There are, however, large gaps in biological sampling and hence knowledge shortfalls. This problem is even more pronounced in the tropics. Indeed, the use of only a few taxonomic groups or environmental surrogates for modelling biodiversity is not viable in mega-diverse countries, such as Brazil. To overcome these limitations, we developed a comprehensive spatial model that includes phylogenetic information and other several biodiversity dimensions aimed at mapping areas with high relevance for biodiversity conservation. Our model applies a genetic algorithm tool for identifying the smallest possible region within a unique biota that contains the most number of species and phylogenetic diversity, as well as the highest endemicity and phylogenetic endemism. The model successfully pinpoints small highly biodiverse areas alongside regions with knowledge shortfalls where further sampling should be conducted. Our results suggest that conservation strategies should consider several taxonomic groups, the multiple dimensions of biodiversity, and associated sampling uncertainties.

Modelling highly biodiverse areas in Brazil

Traditional conservation techniques for mapping highly biodiverse areas assume there to be satisfactory knowledge about the geographic distribution of biodiversity. There are, however, large gaps in biological sampling and hence knowledge shortfalls. This problem is even more pronounced in the tropics. Indeed, the use of only a few taxonomic groups or environmental surrogates for modelling biodiversity is not viable in mega-diverse countries, such as Brazil. To overcome these limitations, we developed a comprehensive spatial model that includes phylogenetic information and other several biodiversity dimensions aimed at mapping areas with high relevance for biodiversity conservation. Our model applies a genetic algorithm tool for identifying the smallest possible region within a unique biota that contains the most number of species and phylogenetic diversity, as well as the highest endemicity and phylogenetic endemism. The model successfully pinpoints small highly biodiverse areas alongside regions with knowledge shortfalls where further sampling should be conducted. Our results suggest that conservation strategies should consider several taxonomic groups, the multiple dimensions of biodiversity, and associated sampling uncertainties.

Publisher Correction: Biodiversity conservation gaps in the Brazilian protected areas.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

Biodiversity conservation gaps in the Brazilian protected areas.

Although Brazil is a megadiverse country and thus a conservation priority, no study has yet quantified conservation gaps in the Brazilian protected areas (PAs) using extensive empirical data. Here, we evaluate the degree of biodiversity protection and knowledge within all the Brazilian PAs through a gap analysis of vertebrate, arthropod and angiosperm occurrences and phylogenetic data. Our results show that the knowledge on biodiversity in most Brazilian PAs remain scant as 71% of PAs have less than 0.01 species records per km2. Almost 55% of Brazilian species and about 40% of evolutionary lineages are not found in PAs, while most species have less than 30% of their geographic distribution within PAs. Moreover, the current PA network fails to protect the majority of endemic species. Most importantly, these results are similar for all taxonomic groups analysed here. The methods and results of our countrywide assessment are suggested to help design further inventories in order to map and secure the key biodiversity of the Brazilian PAs. In addition, our study illustrates the most common biodiversity knowledge shortfalls in the tropics.

Biodiversity conservation gaps in the Brazilian protected areas

Although Brazil is a megadiverse country and thus a conservation priority, no study has yet quantified conservation gaps in the Brazilian protected areas (PAs) using extensive empirical data. Here, we evaluate the degree of biodiversity protection and knowledge within all the Brazilian PAs through a gap analysis of vertebrate, arthropod and angiosperm occurrences and phylogenetic data. Our results show that the knowledge on biodiversity in most Brazilian PAs remain scant as 71% of PAs have less than 0.01 species records per km(2). Almost 55% of Brazilian species and about 40% of evolutionary lineages are not found in PAs, while most species have less than 30% of their geographic distribution within PAs. Moreover, the current PA network fails to protect the majority of endemic species. Most importantly, these results are similar for all taxonomic groups analysed here. The methods and results of our countrywide assessment are suggested to help design further inventories in order to map and secure the key biodiversity of the Brazilian PAs. In addition, our study illustrates the most common biodiversity knowledge shortfalls in the tropics.

Simulating fire regimes in the Amazon in response to climate change and deforestation.

Fires in tropical forests release globally significant amounts of carbon to the atmosphere and may increase in importance as a result of climate change. Despite the striking impacts of fire on tropical ecosystems, the paucity of robust spatial models of forest fire still hampers our ability to simulate tropical forest fire regimes today and in the future. Here we present a probabilistic model of human-induced fire occurrence for the Amazon that integrates the effects of a series of anthropogenic factors with climatic conditions described by vapor pressure deficit. The model was calibrated using NOAA-12 night satellite hot pixels for 2003 and validated for the years 2002, 2004, and 2005. Assessment of the fire risk map yielded fitness values > 85% for all months from 2002 to 2005. Simulated fires exhibited high overlap with NOAA-12 hot pixels regarding both spatial and temporal distributions, showing a spatial fit of 50% within a radius of 11 km and a maximum yearly frequency deviation of 15%. We applied this model to simulate fire regimes in the Amazon until 2050 using IPCC's A2 scenario climate data from the Hadley Centre model and a business-as-usual (BAU) scenario of deforestation and road expansion from SimAmazonia. Results show that the combination of these scenarios may double forest fire occurrence outside protected areas (PAs) in years of extreme drought, expanding the risk of fire even to the northwestern Amazon by midcentury. In particular, forest fires may increase substantially across southern and southwestern Amazon, especially along the highways slated for paving and in agricultural zones. Committed emissions from Amazon forest fires and deforestation under a scenario of global warming and uncurbed deforestation may amount to 21 +/- 4 Pg of carbon by 2050. BAU deforestation may increase fires occurrence outside PAs by 19% over the next four decades, while climate change alone may account for a 12% increase. In turn, the combination of climate change and deforestation would boost fire occurrence outside PAs by half during this period. Our modeling results, therefore, confirm the synergy between the two Ds of REDD (Reducing Emissions from Deforestation and Forest Degradation in Developing Countries).

Modelling conservation in the Amazon basin.

Expansion of the cattle and soy industries in the Amazon basin has increased deforestation rates and will soon push all-weather highways into the region's core. In the face of this growing pressure, a comprehensive conservation strategy for the Amazon basin should protect its watersheds, the full range of species and ecosystem diversity, and the stability of regional climates. Here we report that protected areas in the Amazon basin--the central feature of prevailing conservation approaches--are an important but insufficient component of this strategy, based on policy-sensitive simulations of future deforestation. By 2050, current trends in agricultural expansion will eliminate a total of 40% of Amazon forests, including at least two-thirds of the forest cover of six major watersheds and 12 ecoregions, releasing 32 +/- 8 Pg of carbon to the atmosphere. One-quarter of the 382 mammalian species examined will lose more than 40% of the forest within their Amazon ranges. Although an expanded and enforced network of protected areas could avoid as much as one-third of this projected forest loss, conservation on private lands is also essential. Expanding market pressures for sound land management and prevention of forest clearing on lands unsuitable for agriculture are critical ingredients of a strategy for comprehensive conservation.

Cenários de desmatamento para a Amazônia / Deforestation scenarios for Amazonia

A AMAZÕNIA está entrando em uma era de rápidas mudanças impulsionadas pela previsão de asfaltamento de rodovias que estimularão a expansão da fronteira agrícola e de exploração madeireira. O declínio do custo de transporte tem importantes implicações para a biodiversidade, emissão de gases que contribuem para o efeito estufa e prosperidade da sociedade da Amazônia a longo prazo. Para analisar esse contexto, foi desenvolvido um modelo de simulação de desmatamento na bacia Amazônica, sensível a diferentes cenários de políticas públicas frente à expansão da infra-estrutura de transporte pela região. Resultados do modelo indicam que, dentro de um cenário pessimista, o desmatamento projetado pode eliminar, até meados deste século, 40 por cento dos atuais 5,4 milhões de km² de florestas da Amazônia, liberando o equivalente a 32 Pg (10(9) toneladas) de carbono para atmosfera. A modelagem de cenários alternativos aponta que a expansão de uma rede de áreas protegidas, efetivamente implementadas, poderia reduzir em até 1/3 as perdas florestais projetadas. Contudo, outras medidas de conservação são ainda necessárias para se manter a integridade funcional das paisagens e bacias hidrográficas amazônicas. Atuais experimentos em conservação florestal em propriedades privadas, mercados de serviços ambientais e zoneamento agro-ecológico devem ser refinados e multiplicados a fim de se buscar uma conservação extensiva.

The distribution of Biomphalaria spp. in different habitats in relation to physical, biological, water contact and cognitive factors in a rural area in Minas Gerais, Brazil

A total of 256 sites in 11 habitats were surveyed for Biomphalaria in Melquiades rural area (State of Minas Gerais) in August and November 1999 and in March 2000. Of the 1,780 Biomphalaria collected, 1,721 (96.7 percent) were B. glabrata and 59 (3.3 percent) B. straminea. Snails were found in all habitats except in wells, with the largest mean numbers in tanks, seepage ponds and canals, and the smallest numbers in springs, rice fields and fishponds. People's knowledge of the occurrence of Biomphalaria at the collection sites and the presence of Biomphalaria ova were strongly correlated with the occurrence of snails, and distance between houses and collection sites, as well as water velocity were inversely correlated with Biomphalaria occurrence (p < 0.001). The strongest predictor o f Biomphalaria occurrence was the presence of tilapia fish in fishponds. Fourteen Biomphalaria (0.8 percent of all snails) found at 6 sites were infected with Schistosoma mansoni. Suggestions are made for the utilization of local people's knowledge in snail surveys and further studies are recommended on the possible use of tilapia for biological control of Biomphalaria in fishponds, as well as modeling of S. mansoni transmission and reinfection