Land2014, 3(3), 1037-1058; doi:10.3390/land3031037 - published 22 August 2014 Show/Hide Abstract
Abstract: Currently, many studies on benefit sharing mechanisms (BSM) and the Reducing Emissions from Deforestation and Forest Degradation programme (REDD+) focus on poverty alleviation and livelihood development. However, relatively few studies incorporate an integrated livelihood framework. This study employs the sustainable livelihoods framework to assess the impact of BSM in Vietnam. The lessons learned could be used in creating social safeguards for REDD+. The communities in Central Vietnam involved in BSM were impacted by the programme on various dimensions. These dimensions, expressed in different types of capital, are interconnected and contribute to a person’s well-being. While the communities have restricted access to their natural forests, they benefited in terms of income diversification, knowledge improvement and network expansion. On the other hand, they faced food insecurity, they were more vulnerable to natural hazards, and their human, social and cultural capital faced risk of deterioration.
Land2014, 3(3), 1015-1036; doi:10.3390/land3031015 - published 22 August 2014 Show/Hide Abstract
Abstract: A stepwise multi regression-based statistics was employed for prioritizing the influence of several factors, anthropogenic and/or natural, on the ERA15 temperature increments. The 5 factors that are defined as predictors are: topography, aerosol index (TOMS-AI), tropospheric vertical velocity along with two anthropogenic factors, population density and land use changes (Land Use Change Index (LUCI) and Normalized Difference Vegetation Index (NDVI) trends). The seismic hazard assessment factor was also chosen as the “dummy variable” for validity. Special focus was given to the land use change factor, which was based on two different data sets; Human Impacts on Terrestrial Ecosystems(HITE) data of historical land use/land cover data and of NDVI trends during 1982 and 1991. The increment analysis updates of temperature, increments analysis update (IAU) (T), the predicted variable, was obtained from the ERA15 (1979–1993) reanalysis. The research consists of both spatial and vertical analyses, as well as the potential synergies of selected variables. The spatial geographic analysis is divided into three categories; (1) coarse region; (2) subregion analysis; and (c) a “small cell” of 4° × 4° analysis covering the global domain. It is shown that the following three factors, topography, TOMS-AI and NDVI, are statistically significant (at the p < 0.05 level) in the relationship with the IAU (T), which means that they are the most effective predictors of IAU (T), especially at the 700-hPa level during March–June. The 850-hPa level presents the weakest contribution to IAU (T), probably due to the contradicting influences of the various variables at this level. It was found that the land use effect, as expressed by the NDVI trends factor, shows a strong decrease with height and is one of the most influential near-surface factors over the East Mediterranean (EM), which explains up to 20% of the temperature increments in January at 700 hPa. Moreover, its influence is significant (p < 0.05) through all of the different stages of the multiple regression runs, a major finding not quantified earlier. The choice of monthly means was found to be not optimal, particularly for the tropospheric vertical velocity, due to the averaging of the synoptic systems within a month.
Land2014, 3(3), 981-1014; doi:10.3390/land3030981 - published 19 August 2014 Show/Hide Abstract
Abstract: Agricultural census data and fieldwork observations are used to analyze changes in land cover/use intensity across Rondônia and Mato Grosso states along the agricultural frontier in the Brazilian Amazon. Results show that the development of land use is strongly related to land distribution structure. While large farms have increased their share of annual and perennial crops, small and medium size farms have strongly contributed to the development of beef and milk market chains in both Rondônia and Mato Grosso. Land use intensification has occurred in the form of increased use of machinery, labor in agriculture and stocking rates of cattle herds. Regional and national demands have improved infrastructure and productivity. The data presented show that the distinct pathways of land use development are related to accessibility to markets and processing industry as well as to the agricultural colonization history of the region. The data analyzed do not provide any indication of frontier stagnation, i.e., the slowdown of agricultural expansion, in the Brazilian Amazon. Instead of frontier stagnation, the data analyzed indicate that intensification processes in consolidated areas as well as recent agricultural expansion into forest areas are able to explain the cycle of expansion and retraction of the agricultural frontier into the Amazon region. The evolution of land use is useful for scenario analysis of both land cover change and land use intensification and provides insights into the role of market development and policies on land use.
Abstract: Identifying patterns and drivers of regional land use changes is crucial for supporting land management and planning. Doing so for mountain ecosystems in East Asia, such as the So-yang River Basin in South Korea, has until now been a challenge because of extreme social and ecological complexities. Applying the techniques of geographic information systems (GIS) and statistical modeling via multinomial logistic regression (MNL), we attempted to examine various hypothesized drivers of land use changes, over the period 1980 to 2000. The hypothesized drivers included variables of topography, accessibility, spatial zoning policies and neighboring land use. Before the inferential statistic analyses, we identified the optimal neighborhood extents for each land use type. The two archetypical sub-periods, i.e., 1980–1990 with agricultural expansions and 1990–2000 with reforestation, have similar causal drivers, such as topographic factors, which are related to characteristics of mountainous areas, neighborhood land use, and spatial zoning policies, of land use changes. Since the statistical models robustly capture the mutual effects of biophysical heterogeneity, neighborhood characteristics and spatial zoning regulation on long-term land use changes, they are valuable for developing coupled models of social-ecological systems to simulate land use and dependent ecosystem services, and to support sustainable land management.
Abstract: A particular challenge for undertaking urbanization mapping of Beirut is the absence of a unified understanding of the city. Migration, informal settlements, a lack of urban planning, political corruption, as well as internal conflict have made this task even harder. The population in Lebanon is unevenly distributed among regions, where one third of the population resides in the Greater Beirut Area (GBA), whereas it occupies only 233 km2 (2% of Lebanon’s total area). The Greater Beirut Area is subject to pressures arising from population growth and economic expansion. This study aims to follow the evolution of urbanization from 1963 till 2005 by processing and interpreting topographical maps and satellite images acquired by different space platforms. Satellite imagery change analysis shows that average annual urban growth surpassed 1.8 km2∙yr−1. Actually, a variety of factors triggers urban growth in the GBA (i.e., transportation, public policies, economic activities and environmental variables). The logistic regression method has been applied to model future urban growth in the region of Greater Beirut. Consequently, an urban growth scenario map has been generated. To validate our results, we compared an urban map derived from RapidEye satellite acquired in 2010 to our model’s outcome of the same year. The output shows a satisfactory rate of success (~61%). This research aims to provide policy makers and urban planners in Lebanon an essential decision tool to support upcoming urban planning in this study area or in others major cities in Lebanon.
Abstract: In a modeling study we examine vulnerability of income from mobile (transhumant) pastoralism and sedentary pastoralism to reduced mean annual precipitation (MAP) and droughts. The study is based on empirical data of a 3410 km2 research region in southern, semi-arid Morocco. The land use decision model integrates a meta-model of the Environmental Policy Integrated Climate (EPIC) simulator to depict perennial and annual forage plant development. It also includes livestock dynamics and forward-looking decision making under uncertain weather. Mobile livestock in the model moves seasonally, sedentary livestock is restricted to pastures around settlements. For a reduction of MAP by 20%, our model shows for different experimental frequencies of droughts a significant decrease of total income from pastoralism by 8%–19% (p < 0.05). Looking separately at the two modes of pastoralism, pronounced income losses of 18%–44% (p < 0.05) show that sedentary pastoralism is much more vulnerable to dryer climate than mobile pastoralism, which is merely affected. Dedicating more pasture area and high quality fodder to mobile pastoralism significantly abates impacts from reduced MAP and droughts on total income by 11% (p < 0.05). Our results indicate that promotion of mobile pastoralism in semi-arid areas is a valuable option to increase resilience against climate change.