This paper examines the interactions between state-led land reform, agrarian structures, and deforestation in the Brazilian Amazon. Land reform tends to promote land redistribution through ...regularization of smallholder land invasions of large-scale landholdings, and by redistribution of public lands to smallholders in existing colonization frontiers. The implications of state-led land reform on deforestation are heterogeneous. I argue that impacts of agrarian reform are strongly related to the pre-existing social and economic configuration of the frontiers where it takes place. While it leads to lower rates of deforestation in landscapes dominated by smallholders with diversified land use, its impact on forest conversion is higher in landscapes where extensive land use, mainly prompted by large-scale cattle ranching, tends to dominate. I provide an assessment for the whole Brazilian Amazon, and examine two research sites in the state of Pará, namely Uruará and Redenção. The study is based on informant interviews, secondary information, agricultural census data, and remote sensing data.
Assessing how climate change will affect hydrological ecosystem services (HES) provision is necessary for long-term planning and requires local comprehensive climate information. In this study, we ...used SWAT to evaluate the impacts on four HES, natural hazard protection, erosion control regulation and water supply and flow regulation for the Laguna del Sauce catchment in Uruguay. We used downscaled CMIP-5 global climate models for Representative Concentration Pathways (RCP) 2.6, 4.5 and 8.5 projections. We calibrated and validated our SWAT model for the periods 2005–2009 and 2010–2013 based on remote sensed ET data. Monthly NSE and R2 values for calibration and validation were 0.74, 0.64 and 0.79, 0.84, respectively. Our results suggest that climate change will likely negatively affect the water resources of the Laguna del Sauce catchment, especially in the RCP 8.5 scenario. In all RCP scenarios, the catchment is likely to experience a wetting trend, higher temperatures, seasonality shifts and an increase in extreme precipitation events, particularly in frequency and magnitude. This will likely affect water quality provision through runoff and sediment yield inputs, reducing the erosion control HES and likely aggravating eutrophication. Although the amount of water will increase, changes to the hydrological cycle might jeopardize the stability of freshwater supplies and HES on which many people in the south-eastern region of Uruguay depend. Despite streamflow monitoring capacities need to be enhanced to reduce the uncertainty of model results, our findings provide valuable insights for water resources planning in the study area. Hence, water management and monitoring capacities need to be enhanced to reduce the potential negative climate change impacts on HES. The methodological approach presented here, based on satellite ET data can be replicated and adapted to any other place in the world since we employed open-access software and remote sensing data for all the phases of hydrological modelling and HES provision assessment.
New plantations can either cause deforestation by replacing natural forests or avoid this by using previously cleared areas. The extent of these two situations is contested in tropical biodiversity ...hotspots where objective data are limited. Here, we explore delays between deforestation and the establishment of industrial tree plantations on Borneo using satellite imagery. Between 1973 and 2015 an estimated 18.7 Mha of Borneo's old-growth forest were cleared (14.4 Mha and 4.2 Mha in Indonesian and Malaysian Borneo). Industrial plantations expanded by 9.1 Mha (7.8 Mha oil-palm; 1.3 Mha pulpwood). Approximately 7.0 Mha of the total plantation area in 2015 (9.2 Mha) were old-growth forest in 1973, of which 4.5-4.8 Mha (24-26% of Borneo-wide deforestation) were planted within five years of forest clearance (3.7-3.9 Mha oil-palm; 0.8-0.9 Mha pulpwood). This rapid within-five-year conversion has been greater in Malaysia than in Indonesia (57-60% versus 15-16%). In Indonesia, a higher proportion of oil-palm plantations was developed on already cleared degraded lands (a legacy of recurrent forest fires). However, rapid conversion of Indonesian forests to industrial plantations has increased steeply since 2005. We conclude that plantation industries have been the principle driver of deforestation in Malaysian Borneo over the last four decades. In contrast, their role in deforestation in Indonesian Borneo was less marked, but has been growing recently. We note caveats in interpreting these results and highlight the need for greater accountability in plantation development.
This paper analyzes the influence that both policies and markets have on driving forest conversion to agricultural land use focusing on the Bolivian case. It assesses the effects that two models of ...economic development have had on prompting agricultural expansion, and hence deforestation in lowland Bolivia. The first model, of economic diversification and import substitution, initiated in the early 1950s, stimulated the occupation of forestlands for agricultural expansion through colonization, and incentives to developing a medium and large-scale agriculture. The second model of development, initiated in the mid-1980s, prompted by structural adjustment policies, led to an intense process of agrarian change in the lowlands, mainly by connecting the agricultural frontier to the international market of commodities, particularly soybeans. The move from an import substitution industrialization model to another based on economic liberalization, even though it had positive implications on stimulating agricultural growth, has led to accelerate the pace of deforestation in lowland Bolivia, which has a larger contribution of medium and large-scale agriculture. This paper moves forward the debate about deforestation in Bolivia by making explicit connections between some analytical assessments on land-use/cover change and empirical evidences about forest removal in a five-decades period.
The links between plantation expansion and deforestation in Borneo are debated. We used satellite imagery to map annual loss of old‐growth forests, expansion of industrial plantations (oil palm and ...pulpwood), and their overlap in Borneo from 2001 to 2017. In 17 years, forest area declined by 14% (6.04 Mha), including 3.06 Mha of forest ultimately converted into industrial plantations. Plantations expanded by 170% (6.20 Mha: 88% oil palm; 12% pulpwood). Most forests converted to plantations were cleared and planted in the same year (92%; 2.83 Mha). Annual forest loss generally increased before peaking in 2016 (0.61 Mha) and declining sharply in 2017 (0.25 Mha). After peaks in 2009 and 2012, plantation expansion and associated forest conversion have been declining in Indonesia and Malaysia. Annual plantation expansion is positively correlated with annual forest loss in both countries. The correlation vanishes when we consider plantation expansion versus forests that are cleared but not converted to plantations. The price of crude palm oil is positively correlated with plantation expansion in the following year in Indonesian (not Malaysian) Borneo. Low palm oil prices, wet conditions, and improved fire prevention all likely contributed to reduced 2017 deforestation. Oversight of company conduct requires transparent concession ownership.
Annual deforestation rates in the Brazilian Amazon fell by 77% between 2004 and 2011, yet have stabilized since 2009 at 5,000–7,000 km ². We provide the first submunicipality assessment, to our ...knowledge, of actor-specific contributions to the deforestation slowdown by linking agricultural census and remote-sensing data on deforestation and forest degradation. Almost half (36,158 km ²) of the deforestation between 2004 and 2011 occurred in areas dominated by larger properties (>500 ha), whereas only 12% (9,720 km ²) occurred in areas dominated by smallholder properties (<100 ha). In addition, forests in areas dominated by smallholders tend to be less fragmented and less degraded. However, although annual deforestation rates fell during this period by 68–85% for all actors, the contribution of the largest landholders (>2,500 ha) to annual deforestation decreased over time (63% decrease between 2005 and 2011), whereas that of smallholders went up by a similar amount (69%) during the same period. In addition, the deforestation share attributable to remote areas increased by 88% between 2009 and 2011. These observations are consistent across the Brazilian Amazon, regardless of geographical differences in actor dominance or socioenvironmental context. Our findings suggest that deforestation policies to date, which have been particularly focused on command and control measures on larger properties in deforestation hotspots, may be increasingly limited in their effectiveness and fail to address all actors equally. Further reductions in deforestation are likely to be increasingly costly and require actor-tailored approaches, including better monitoring to detect small-scale deforestation and a shift toward more incentive-based conservation policies.
Significance The Brazilian Amazon is at a critical juncture after the recent stabilization of deforestation rates. Identifying opportunities for continued deforestation reductions requires an understanding of the contribution of different actors to overall deforestation. We provide the first such assessment, to our knowledge, that reports on two headline findings. First, between 2004 and 2011, areas dominated by properties larger than 500 ha accounted for 48% of the deforestation compared with only 12% for smallholders (<100 ha). Second, the deforestation share attributed to the largest properties (≥2,500 ha) declined by 63% from a peak in 2005, whereas that of smallholders increased by 69%. Further reductions in deforestation are likely to require a shift toward more incentive-based policies that are tailored toward different actors.
Streams of the Pampasic plain in Southeastern South America are ecosystems affected by both water pollution and habitat alteration mainly due to agricultural activity. Water quality is influenced by ...the quality of habitats and both depend on land use and watershed morphology. The objective of this study was to determine the relationship between the variables of four factors: (1) the morphology of the watershed, (2) land use in the watershed, (3) river habitat, and (4) water quality of wadeable streams in Uruguay, as well as to determine the most representative variables to quantify such factors. We studied 28 watersheds grouped into three ecoregions and four principal activities, which generated seven zones with three to five streams each. Correlations between the variables of each factor allowed reducing the total number of variables from 57 to 32 to perform principal component analyses (PCA) by factor, reducing the number of variables to 18 for a general PCA. The first component was associated with water quality and elevation. The second was associated with the stream and watershed size, the third with habitat quality, and the fourth to the use of neighboring soils and objects in the channel. Our results indicate that agricultural intensity and elevation are the main factors associated with the habitat and water quality of these lowland streams. These factors must be especially considered in the development of water quality monitoring programs.
Laguna del Sauce, one of the main drinking water sources in Uruguay, is an eutrophic shallow lake with high temporal variation of inorganic turbidity caused by extreme wind events. During low ...turbidity periods, high phytoplankton biomass can be reached, frequently associated to cyanobacteria blooms, which can cause interferences in the water supply. In this study, we assessed the environmental drivers of cyanobacteria dominance, composition, and nitrogen-fixation behavior. For this, we analyzed the spatial and temporal phytoplankton composition, physical and chemical variables performing weekly samplings during two summers: 2015–2016 and 2016–2017. When inorganic turbidity was high (above 30 NTU), phytoplankton biomass was controlled, below this threshold, temperature, secchi depth and nutrients played key factors controlling cyanobacteria biomass and composition. Blooms of N
2
-fixing cyanobacteria (
Dolichospermum crassum
,
Aphanizomenon gracile
, and
Cuspidothrix issatschenkoi
) were promoted by low N:P ratios (average 11.5) and wide TN range (286–1300 µg l
−1
). Non-heterocystous cyanobacteria blooms occurred above TN 1000–1200 µg l
−1
. The N
2
-fixing behavior (heterocytes:vegetative cell ratio) depended on TN, it was highest at low TN (< 700 µg l
−1
) but null above ca. 1000 µg l
−1
. While low inorganic turbidity allowed cyanobacteria blooms in Laguna del Sauce, its composition and N
2
-fixation behavior depended on the TN and TP levels.
The computer numerical control (CNC) machine has recently taken a fundamental role in the manufacturing industry, which is essential for the economic development of many countries. Current high ...quality production standards, along with the requirement for maximum economic benefits, demand the use of tool condition monitoring (TCM) systems able to monitor and diagnose cutting tool wear. Current TCM methodologies mainly rely on vibration signals, cutting force signals, and acoustic emission (AE) signals, which have the common drawback of requiring the installation of sensors near the working area, a factor that limits their application in practical terms. Moreover, as machining processes require the optimal tuning of cutting parameters, novel methodologies must be able to perform the diagnosis under a variety of cutting parameters. This paper proposes a novel non-invasive method capable of automatically diagnosing cutting tool wear in CNC machines under the variation of cutting speed and feed rate cutting parameters. The proposal relies on the sensor information fusion of spindle-motor stray flux and current signals by means of statistical and non-statistical time-domain parameters, which are then reduced by means of a linear discriminant analysis (LDA); a feed-forward neural network is then used to automatically classify the level of wear on the cutting tool. The proposal is validated with a Fanuc Oi mate Computer Numeric Control (CNC) turning machine for three different cutting tool wear levels and different cutting speed and feed rate values.
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