Abstract:Mapping cropland areas is of great interest in diverse fields, from crop monitoring to climate change and food security. Recognizing the value of a reliable and harmonized crop mask that entirely covers the African continent, the objectives of this study were to (i) consolidate the best existing land cover/land use datasets, (ii) adapt the Land Cover Classification System (LCCS) for harmonization, (iii) assess the final product, and (iv) compare the final product with two existing datasets. Ten datasets were compared and combined through an expert-based approach in order to create the derived map of cropland areas at 250 m covering the whole of Africa. The resulting cropland mask was compared with two recent cropland extent maps at 1 km: one derived from MODIS and one derived from five existing products. The accuracy of the three products was assessed against a validation sample of 3,591 pixels of 1km regularly distributed over Africa and interpreted using high resolution images, which were collected using the Geo-Wiki tool. The comparison of the resulting crop mask with existing products shows that it has a greater agreement with the expert validation dataset, in particular for places where the cropland represents more than 30% of the area of the validation pixel.

Annual forest loss in the Brazilian Amazon had in 2012 declined to less than 5,000 sqkm, from over 27,000 in 2004. Mounting empirical evidence suggests that changes in Brazilian law enforcement strategy and the related governance system may account for a large share of the overall success in curbing deforestation rates. At the same time, Brazil is experimenting with alternative approaches to compensate farmers for conservation actions through economic incentives, such as payments for environmental services, at various administrative levels. We develop a spatially explicit simulation model for deforestation decisions in response to policy incentives and disincentives. The model builds on elements of optimal enforcement theory and introduces the notion of imperfect payment contract enforcement in the context of avoided deforestation. We implement the simulations using official deforestation statistics and data collected from field-based forest law enforcement operations in the Amazon region. We show that a large-scale integration of payments with the existing regulatory enforcement strategy involves a tradeoff between the cost-effectiveness of forest conservation and landholder incomes. Introducing payments as a complementary policy measure increases policy implementation cost, reduces income losses for those hit hardest by law enforcement, and can provide additional income to some land users. The magnitude of the tradeoff varies in space, depending on deforestation patterns, conservation opportunity and enforcement costs. Enforcement effectiveness becomes a key determinant of efficiency in the overall policy mix.

Multitemporal optical remote sensing constitutes a useful, cost efficient method for crop status monitoring over large areas. Modelers interested in yield monitoring can rely on past and recent observations of crop reflectance to estimate aboveground biomass and infer the likely yield. Therefore, in a framework constrained by information availability, remote sensing data to yield conversion parameters are to be estimated. Statistical models are suitable for this purpose, given their ability to deal with statistical errors. This paper explores the performance in yield estimation of various remote sensing indicators based on varying degrees of bio-physical insight, in interaction with statistical methods (linear regressions) that rely on different hypotheses. Performances in estimating the temporal and spatial variability of yield, and implications of data scarcity in both dimensions are investigated. Jackknifed results (leave one year out) are presented for the case of wheat yield regional estimation in Tunisia using the SPOT-VEGETATION instrument. Best performances, up to 0.8 of R 2 , are achieved using the most physiologically sound remote sensing indicator, in conjunction with statistical specifications allowing for parsimonious spatial adjustment of the parameters. OPEN ACCESSRemote Sens. 2013, 5 540

A standard protocol to evaluate the effects of biostimulants on plant physiology is still lacking. The proton pumps present in the vacuolar and plasma membranes are the primary agents responsible for the regulation of the electrochemical gradient that energizes the nutrient uptake system and acid growth mechanism of plant cells. In this study, two of these enzymes were characterized as biochemical markers of biostimulant activity. A simple and fast protocol based on the degree of root acidification using a pH sensitive dye and the Micro-Tom tomato as a plant model is proposed as an efficient methodology to prove the efficacy of biostimulants that are claimed to improve nutrient acquisition and root growth. The results agree with the data from more conventional, expensive and time-consuming proton pump assays. A direct correlation was found between plasmalemma proton-adenosine triphosphatase (H + -ATPase) activation and the amount of rhizosphere acidification observed in the bromocresol gel. Moreover, roots of the diageotropica (dgt) Micro-Tom plants, defective in auxin responses, barely acidify bromocresol purple gel even in the presence of indole-3-acetic acid (IAA, 1 μM). The biostimulant TEA (vermicompost water extract, 25 %) enhances proton extrusion by 40 % in wild type (WT) plants, but no effect was induced in dgt plants. These results reinforce the notion that the class of biostimulant known as humic substances stimulates plant proton pumps and promotes root growth by exerting an auxin-like bioactivity and establish the usefulness of an economically and technically feasible assay to certify this kind of biostimulant.

O presente trabalho teve por objetivo avaliar os efeitos da aplicação de extrato húmico solúvel em água (EHSA), biofertilizante Hortbio® (HORT) e a combinação dos dois produtos sobre o crescimento vegetativo, indicador fisiológico (medida do teor de clorofila) e a capacidade de absorção de nutrientes em mudas de guanandi (Callophyllum brasiliense). A adição isolada ou em conjunto de EHSA e HORT não alterou a altura das mudas, o número de folhas, a matéria seca foliar e radicular e a área radicular e foliar durante a fase inicial de crescimento em viveiro. Entretanto, os teores de clorofila e N total aumentaram significativamente nas mudas que receberam os tratamentos HORT e EHSA+HORT. Além disso, a adição de HORT resultou em maiores teores de S, Zn, B, Mg, Mn e Cu nas plantas, enquanto a aplicação do ESHA aumentou os teores de K, Mg, S e B. Os teores de P e Ca não tiveram seus teores alterados pela aplicação dos tratamentos, mas a adição do EHSA e ESHA+HORT reduziram significativamente a absorção de Cu, Fe, Mn e Zn.Effects of water-soluble humic extract and biofertilizer on development of Callophyllum brasiliense seedlingsThe objective of this work was to evaluate the effects of water-soluble humic extract (EHSA), Hortbio® biofertilizer (HORT) and both compounds combination (EHSA+HORT) on vegetative growth, nutrient absorption and chlorophyll levels in guanandi (Callophyllum brasiliense) seedlings. Isolated and combined additions of EHSA and HORT did not affect seedlings height, number of leaves, leaf and root dry matter and leaf area during early stages of seedling growth. However, HORT and EHSA+HORT treatments increased chlorophyll levels and total N content. Addition of HORT resulted in S, Zn, Mg, Mn and Cu increases in the seedlings leaves, while ESHA application increased K, Mg, S and B. P and Ca levels were not altered by the treatments, however, addition of EHSA and EHSA+HORT reduced significantly the absorption of Cu, Fe, Mn and Zn.Index terms: Forestry production; Guanandi; Vegetative growth

Abstract:Monitoring the start of the crop season in Sahel provides decision makers with valuable information for an early assessment of potential production and food security threats. Presently, the most common method for the estimation of sowing dates in West African countries consists of applying given thresholds on rainfall estimations. However, the coarse spatial resolution and the possible inaccuracy of these estimations are limiting factors. In this context, the remote sensing approach, which consists of deriving green-up onset dates from satellite remote sensing data, appears as an interesting alternative. It builds upon a novel statistic model that translates vegetation onset detections derived from MODIS time series into sowing probabilities at the village level. Results for Niger show that this approach outperforms the standard method adopted in the region based on rainfall thresholds.

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