Testing for Network and Spatial Autocorrelation

Testing for dependence has been a well-established component of spatial statistical analyses for decades. In particular, several popular test statistics have desirable properties for testing for the presence of spatial autocorrelation in continuous variables. In this paper we propose two contributions to the literature on tests for autocorrelation. First, we propose a new test for autocorrelation in categorical variables. While some methods currently exist for assessing spatial autocorrelation in categorical variables, the most popular method is unwieldy, somewhat ad hoc, and fails to provide grounds for a single omnibus test. Second, we discuss the importance of testing for autocorrelation in data sampled from the nodes of a network, motivated by social network applications. We demonstrate that our proposed statistic for categorical variables can both be used in the spatial and network setting

Biophysical suitability, economic pressure and land-cover change: a global probabilistic approach and insights for REDD+

There has been a concerted effort by the international scientific community to understand the multiple causes and patterns of land-cover change to support sustainable land management. Here, we examined biophysical suitability, and a novel integrated index of “Economic Pressure on Land” (EPL) to explain land cover in the year 2000, and estimated the likelihood of future land-cover change through 2050, including protected area effectiveness. Biophysical suitability and EPL explained almost half of the global pattern of land cover (R 2 = 0.45), increasing to almost two-thirds in areas where a long-term equilibrium is likely to have been reached (e.g. R 2 = 0.64 in Europe). We identify a high likelihood of future land-cover change in vast areas with relatively lower current and past deforestation (e.g. the Congo Basin). Further, we simulated emissions arising from a “business as usual” and two reducing emissions from deforestation and forest degradation (REDD) scenarios by incorporating data on biomass carbon. As our model incorporates all biome types, it highlights a crucial aspect of the ongoing REDD + debate: if restricted to forests, “cross-biome leakage” would severely reduce REDD + effectiveness for climate change mitigation. If forests were protected from deforestation yet without measures to tackle the drivers of land-cover change, REDD + would only reduce 30 % of total emissions from land-cover change. Fifty-five percent of emissions reductions from forests would be compensated by increased emissions in other biomes. These results suggest that, although REDD + remains a very promising mitigation tool, implementation of complementary measures to reduce land demand is necessary to prevent this leakage

Combining remote sensing and household level data for regional scale analysis of land cover change in the Brazilian Amazon

Land cover change in the Brazilian Amazon depends on the spatial variability of political, socioeconomic and biophysical factors, as well as on the land use history and its actors. A regional scale analysis was made in Rondônia State to identify possible differences in land cover change connected to spatial policies of land occupation, size and year of establishment of properties, accessibility measures and soil fertility. The analysis was made based on remote sensing data and household level data gathered with a questionnaire. Both types of analyses indicate that the highest level of total deforestation is found inside agrarian projects, especially in those established more than 20 years ago. Even though deforestation rates are similar inside and outside official settlements, inside agrarian projects forest depletion can exceed 50% at the property level within 10–14 years after establishment. The data indicate that both small-scale and medium to large-scale farmers contribute to deforestation processes in Rondônia State encouraged by spatial policies of land occupation, which provide better accessibility to forest fringes where soil fertility and forest resources are important determinants of location choic

Evaluating the spatial uncertainty of future land abandonment in a mountain valley (Vicdessos, Pyrenees-France) : insights form model parameterization and experiments

International audienceEuropean mountains are particularly sensitive to climatic disruptions and land use changes. The latter leads to high rates of natural reforestation over the last 50 years. Faced with the challenge of predicting possible impacts on ecosystem services, LUCC models offer new opportunities for land managers to adapt or mitigate their strategies. Assessing the spatial uncertainty of future LUCC is crucial for the defintion of sustainable land use strategies. However, the sources of uncertainty may differ, including the input parameters, the model itself, and the wide range of possible futures. The aim of this paper is to propose a method to assess the probability of occurrence of future LUCC that combines the inherent uncertainty of model parameterization and the ensemble uncertainty of the future based scenarios. For this purpose, we used the Land Change Modeler tool to simulate future LUCC on a study site located in the Pyrenees Mountains (France) and 2 scenarios illustratins 2 land use strategies. The model was parameterized with the same driving factors used for its calibration. The defintion of static vs. dynamic and quantitative vs. qualitative (discretized) driving factors, and their combination resulted in 4 parameterizations. The combination of model outcomes produced maps of spatial uncertainty of future LUCC. This work involves literature to future-based LUCC studies. It goes beyond the uncertainty of simulation models by integrating the unceertainty of the future to provide maps to help decision makers and land managers

Projecting Land-Use Change and Its Consequences for Biodiversity in Northern Thailand

Rapid deforestation has occurred in northern Thailand over the last few decades and it is expected to continue. The government has implemented conservation policies aimed at maintaining forest cover of 50% or more and promoting agribusiness, forestry, and tourism development in the region. The goal of this paper was to analyze the likely effects of various directions of development on the region. Specific objectives were (1) to forecast land-use change and land-use patterns across the region based on three scenarios, (2) to analyze the consequences for biodiversity, and (3) to identify areas most susceptible to future deforestation and high biodiversity loss. The study combined a dynamic land-use change model (Dyna-CLUE) with a model for biodiversity assessment (GLOBIO3). The Dyna-CLUE model was used to determine the spatial patterns of land-use change for the three scenarios. The methodology developed for the Global Biodiversity Assessment Model framework (GLOBIO 3) was used to estimate biodiversity intactness expressed as the remaining relative mean species abundance (MSA) of the original species relative to their abundance in the primary vegetation. The results revealed that forest cover in 2050 would mainly persist in the west and upper north of the region, which is rugged and not easily accessible. In contrast, the highest deforestation was expected to occur in the lower north. MSA values decreased from 0.52 in 2002 to 0.45, 0.46, and 0.48, respectively, for the three scenarios in 2050. In addition, the estimated area with a high threat to biodiversity (an MSA decrease >0.5) derived from the simulated land-use maps in 2050 was approximately 2.8% of the region for the trend scenario. In contrast, the high-threat areas covered 1.6 and 0.3% of the region for the integrated-management and conservation-oriented scenarios, respectively. Based on the model outcomes, conservation measures were recommended to minimize the impacts of deforestation on biodiversity. The model results indicated that only establishing a fixed percentage of forest was not efficient in conserving biodiversity. Measures aimed at the conservation of locations with high biodiversity values, limited fragmentation, and careful consideration of road expansion in pristine forest areas may be more efficient to achieve biodiversity conservation. © 2010 Springer Science+Business Media, LLC

Land use/land cover change dynamics and drivers in a low-grade marginal coffee growing region of Veracruz, Mexico

In the state of Veracruz, Mexico, lowland and marginal coffee growing regions have been particularly vulnerable since the 1989 coffee crisis. Government programs have promoted production diversification as a strategy to improve local incomes and conserve environmentally beneficial shade-tree coffee agroforests. We present results on land use/land cover dynamics in the municipality of Zozocolco de Hidalgo from 1973 to 2006. The municipality is recognized for its indigenous population and poverty, and currently, diversification efforts are being implemented. Our study combines remote sensing and GIS analyses, binary logistic regression and econometric modeling, as well as socioeconomic surveys to evaluate land use/land cover change (LULCC) dynamics and explore potential environmental and socioeconomic drivers. Results show that tree cover and coffee agroforests had largely been conserved during the first decade after the coffee crisis. But, recent trends indicate loss of tree cover in coffee agroforests and their conversion mostly to pasture. Land use/land cover drivers are largely explained by spatially explicit environmental variables such as slope and elevation. Relevant socioeconomic variables such as distance to markets and land use profitability were not significantly related to land use changes in Zozocolco. Surveys revealed that many households had converted coffee agroforests to pasture or agriculture in the past decade and others intended on renting or selling their agroforest plots, mostly for conversion to pasture. Diversification programs may not be sufficient to stem deforestation in lowland and marginal coffee growing regions. Moreover, information about locally varying socioeconomic and cultural contexts needs to be strongly considered in order to formulate effective strategies