Forest phenoclusters for Argentina based on vegetation phenology and climate.

Forest biodiversity conservation and species distribution modeling greatly benefit from broad-scale forest maps depicting tree species or forest types rather than just presence and absence of forest, or coarse classifications. Ideally, such maps would stem from satellite image classification based on abundant field data for both model training and accuracy assessments, but such field data do not exist in many parts of the globe. However, different forest types and tree species differ in their vegetation phenology, offering an opportunity to map and characterize forests based on the seasonal dynamic of vegetation indices and auxiliary data. Our goal was to map and characterize forests based on both land surface phenology and climate patterns, defined here as forest phenoclusters. We applied our methodology in Argentina (2.8 million km2 ), which has a wide variety of forests, from rainforests to cold-temperate forests. We calculated phenology measures after fitting a harmonic curve of the enhanced vegetation index (EVI) time series derived from 30-m Sentinel 2 and Landsat 8 data from 2018-2019. For climate, we calculated land surface temperature (LST) from Band 10 of the thermal infrared sensor (TIRS) of Landsat 8, and precipitation from Worldclim (BIO12). We performed stratified X-means cluster classifications followed by hierarchical clustering. The resulting clusters separated well into 54 forest phenoclusters with unique combinations of vegetation phenology and climate characteristics. The EVI 90th percentile was more important than our climate and other phenology measures in providing separability among different forest phenoclusters. Our results highlight the potential of combining remotely sensed phenology measures and climate data to improve broad-scale forest mapping for different management and conservation goals, capturing functional rather than structural or compositional characteristics between and within tree species. Our approach results in classifications that go beyond simple forest-nonforest in areas where the lack of detailed ecological field data precludes tree species-level classifications, yet conservation needs are high. Our map of forest phenoclusters is a valuable tool for the assessment of natural resources, and the management of the environment at scales relevant for conservation actions.

Agricultural expansion and the ecological marginalization of forest-dependent people.

Agricultural expansion into subtropical and tropical forests causes major environmental damage, but its wider social impacts often remain hidden. Forest-dependent smallholders are particularly strongly impacted, as they crucially rely on forest resources, are typically poor, and often lack institutional support. Our goal was to assess forest-smallholder dynamics in relation to expanding commodity agriculture. Using high-resolution satellite images across the entire South American Gran Chaco, a global deforestation hotspot, we digitize individual forest-smallholder homesteads (n = 23,954) and track their dynamics between 1985 and 2015. Using a Bayesian model, we estimate 28,125 homesteads in 1985 and show that forest smallholders occupy much larger forest areas (>45% of all Chaco forests) than commonly appreciated and increasingly come into conflict with expanding commodity agriculture (18% of homesteads disappeared; n = 5,053). Importantly, we demonstrate an increasing ecological marginalization of forest smallholders, including a substantial forest resource base loss in all Chaco countries and an increasing confinement to drier regions (Argentina and Bolivia) and less accessible regions (Bolivia). Our transferable and scalable methodology puts forest smallholders on the map and can help to uncover the land-use conflicts at play in many deforestation frontiers across the globe. Such knowledge is essential to inform policies aimed at sustainable land use and supply chains.

How do habitat amount and habitat fragmentation drive time-delayed responses of biodiversity to land-use change?

Land-use change is a root cause of the extinction crisis, but links between habitat change and biodiversity loss are not fully understood. While there is evidence that habitat loss is an important extinction driver, the relevance of habitat fragmentation remains debated. Moreover, while time delays of biodiversity responses to habitat transformation are well-documented, time-delayed effects have been ignored in the habitat loss versus fragmentation debate. Here, using a hierarchical Bayesian multi-species occupancy framework, we systematically tested for time-delayed responses of bird and mammal communities to habitat loss and to habitat fragmentation. We focused on the Argentine Chaco, where deforestation has been widespread recently. We used an extensive field dataset on birds and mammals, along with a time series of annual woodland maps from 1985 to 2016 covering recent and historical habitat transformations. Contemporary habitat amount explained bird and mammal occupancy better than past habitat amount. However, occupancy was affected more by the past rather than recent fragmentation, indicating a time-delayed response to fragmentation. Considering past landscape patterns is therefore crucial for understanding current biodiversity patterns. Not accounting for land-use history ignores the possibility of extinction debt and can thus obscure impacts of fragmentation, potentially explaining contrasting findings of habitat loss versus fragmentation studies.

Combined effects of agrochemical contamination and forest loss on anuran diversity in agroecosystems of east-central Argentina.

Agricultural expansion and intensification has led globally to a rapid landscape structure change and high agrochemical use resulting in habitat loss and degraded environmental quality. Co-occurrence of landscape change and agrochemical contamination threatens biodiversity and might have interactive effects especially for organisms with complex life-cycles such as amphibians. We evaluated effects of landscape structure and agrochemical contamination at different spatial scales on anurans in Entre Rios, Argentina. We selected 35 independent stream headwaters along an agricultural expansion and intensification gradient. We conducted anuran call surveys from spring 2012 to summer 2013 and obtained detection-non detection data to estimate mean richness and focal species occupancy. We quantified forest area and riparian forest width at two spatial scales (sub-basin and local reach scale). We measured nutrients and pesticides in water and sediment. We evaluated anuran response to landscape and contamination variables using GLMs for richness and single season single-species occupancy models for focal species. Anuran diversity increased with forest area and riparian forest width, and decreased at sites with herbicide and nutrient contamination, particularly glyphosate; 2,4-D and nitrates. Also, most focal frog species responded mainly to basin forest and 2,4-D. Negative effects of agrochemical contamination on anuran diversity was mitigated in areas with larger basin forest cover. Agricultural management should ensure the reduction of herbicide and fertilizer use, the sparing of adequate forested habitat within drainage areas, and preservation of riparian forests around anuran breeding habitat to reduce and mitigate the negative effects of agrochemical contamination on anurans diversity in agroecosystems.

Carbon emissions from agricultural expansion and intensification in the Chaco.

Carbon emissions from land-use changes in tropical dry forest systems are poorly understood, although they are likely globally significant. The South American Chaco has recently emerged as a hot spot of agricultural expansion and intensification, as cattle ranching and soybean cultivation expand into forests, and as soybean cultivation replaces grazing lands. Still, our knowledge of the rates and spatial patterns of these land-use changes and how they affected carbon emissions remains partial. We used the Landsat satellite image archive to reconstruct land-use change over the past 30 years and applied a carbon bookkeeping model to quantify how these changes affected carbon budgets. Between 1985 and 2013, more than 142 000 km2 of the Chaco's forests, equaling 20% of all forest, was replaced by croplands (38.9%) or grazing lands (61.1%). Of those grazing lands that existed in 1985, about 40% were subsequently converted to cropland. These land-use changes resulted in substantial carbon emissions, totaling 824 Tg C between 1985 and 2013, and 46.2 Tg C for 2013 alone. The majority of these emissions came from forest-to-grazing-land conversions (68%), but post-deforestation land-use change triggered an additional 52.6 Tg C. Although tropical dry forests are less carbon-dense than moist tropical forests, carbon emissions from land-use change in the Chaco were similar in magnitude to those from other major tropical deforestation frontiers. Our study thus highlights the urgent need for an improved monitoring of the often overlooked tropical dry forests and savannas, and more broadly speaking the value of the Landsat image archive for quantifying carbon fluxes from land change.

Human and biophysical drivers of fires in Semiarid Chaco mountains of Central Argentina.

Fires are a recurrent disturbance in Semiarid Chaco mountains of central Argentina. The interaction of multiple factors generates variable patterns of fire occurrence in space and time. Understanding the dominant fire drivers at different spatial scales is a fundamental goal to minimize the negative impacts of fires. Our aim was to identify the biophysical and human drivers of fires in the Semiarid Chaco mountains of Central Argentina and their individual effects on fire activity, in order to determine the thresholds and/or ranges of the drivers at which fire occurrence is favored or disfavored. We used fire frequency as the response variable and a set of 28 potential predictor variables, which included climatic, human, topographic, biological and hydrological factors. Data were analyzed using Boosted Regression Trees, using data from near 10,500 sampling points. Our model identified the fire drivers accurately (75.6% of deviance explained). Although humans are responsible for most ignitions, climatic variables, such as annual precipitation, annual potential evapotranspiration and temperature seasonality were the most important determiners of fire frequency, followed by human (population density and distance to waste disposals) and biological (NDVI) predictors. In general, fire activity was higher at intermediate levels of precipitation and primary productivity and in the proximity of urban solid waste disposals. Fires were also more prone to occur in areas with greater variability in temperature and productivity. Boosted Regression Trees proved to be a useful and accurate tool to determine fire controls and the ranges at which drivers favor fire activity. Our approach provides a valuable insight into the ecology of fires in our study area and in other landscapes with similar characteristics, and the results will be helpful to develop management policies and predict changes in fire activity in response to different climate changes and development scenarios.

Housing is positively associated with invasive exotic plant species richness in New England, USA.

Understanding the factors related to invasive exotic species distributions at broad spatial scales has important theoretical and management implications, because biological invasions are detrimental to many ecosystem functions and processes. Housing development facilitates invasions by disturbing land cover, introducing nonnative landscaping plants, and facilitating dispersal of propagules along roads. To evaluate relationships between housing and the distribution of invasive exotic plants, we asked (1) how strongly is housing associated with the spatial distribution of invasive exotic plants compared to other anthropogenic and environmental factors; (2) what type of housing pattern is related to the richness of invasive exotic plants; and (3) do invasive plants represent ecological traits associated with specific housing patterns? Using two types of regression analysis (best subset analysis and hierarchical partitioning analysis), we found that invasive exotic plant richness was equally or more strongly related to housing variables than to other human (e.g., mean income and roads) and environmental (e.g., topography and forest cover) variables at the county level across New England. Richness of invasive exotic plants was positively related to area of wildland-urban interface (WUI), low-density residential areas, change in number of housing units between 1940 and 2000, mean income, plant productivity (NDVI), and altitudinal range and rainfall; it was negatively related to forest area and connectivity. Plant life history traits were not strongly related to housing patterns. We expect the number of invasive exotic plants to increase as a result of future housing growth and suggest that housing development be considered a primary factor in plans to manage and monitor invasive exotic plant species.

Prevalence and factors associated with the presence of non alcoholic fatty liver disease in an apparently healthy adult population in primary care units.

BACKGROUND: Fatty liver disease is characterized by the accumulation of fat vacuoles inside of the hepatocytes. Non alcoholic fatty liver is associated with obesity, type 2 diabetes, dyslipemia, the intake of certain drugs and with the so-called metabolic syndrome. However, there is little information on the clinical relevance of this disorder as a healthcare problem in the general population, since the studies published generally include a limited number of patients and the diagnosis is established on the basis of clear biochemical alterations and liver biopsy. METHODS/DESIGN: The aim of the study is the prevalence of non-alcoholic fatty liver disease in a general adult population by hepatic ultrasonography.A population-based, descriptive, transversal, multicentre study. Eighteen primary care centres of the north of Barcelona and the Maresme Areas of Healthcare Management attending an urban and semi-urban population of 360.000 inhabitants.A randomized sample of 786 subjects of 15 years or older were selected from the population and assigned to the participating centres according to the Primary Care Information System (SIAP): This population is practically the same as the general population of the area. The following determinations will be carried out in all the participants: hepatic ultrasonography to detect fatty liver, a questionnaire concerning liver diseases, alcohol intake, smoking and drug use, physical examination including abdominal perimeter and body mass index and biochemical analysis including liver function tests and parameters related to the metabolic syndrome and the HAIR score. Ultrasonographic diagnosis of fatty liver will be made according to established criteria (American Gastroenterology Association) and diagnosis of metabolic syndrome according to the criteria of the European Group for the Study of Insulin Resistance. DISCUSSION: This study will attempt to determine the prevalence of non alcoholic fatty liver disease, as well as, the factors most frequently associated with the presence of this disease to thereby achieve the most appropriate treatment and avoid the evolution of the disease.