Estimation of land use during the Holocene is crucial to understand impacts of human activity on climate change in preindustrial period. Until now it is still a key issue to reconstruct amount and spatial distribution of prehistoric land use due to lack of data. Most reconstructions are simply extrapolations of population, cleared land amount per person and land suitability for agriculture. In this study, a new quantitative prehistoric land use model (PLUM) is developed based on semi-quantitative predictive models of archeological sites.

Steppe, an important belt to protect North China from dust storms, is vulnerable and has been degraded in recent decades because of climatic change and heavy grazing. In order to improve steppe management, this study presents a framework for the monitoring of grazing intensity in Xilingol steppe of middle Inner Mongolia, northern China, by integrating the CENTURY ecosystem model-based simulation and remotely sensed MODIS data-based inversion.

Based on the same data source of Landsat TM/ETM+ in 1990s, 2000s and 2010s, all urban built-up areas in China are mapped mainly by human interpretation. Mapping results were checked and refined by the same analyst with the same set of criteria. The results show during the last 20 years urban areas in China have increased exponentially more than 2 times. The greatest area of urbanization changed from Northeastern provinces in 1990s to the Southeast coast of China in Jiangsu, Guangdong, Shandong, and Zhejiang in 2010s. Urban areas are mostly converted from croplands in China.

SummaryThe relationship between woody fuel consumption and fireline intensity was assessed using data collected at controlled fires and wildfires in south-western Western Australia, central Victoria and south-eastern New South Wales. The combined dataset consisted of fires in a range of dry eucalypt forests. Fire behaviour varied from slow, self-extinguishing prescribed burns to intense, fast—moving fires burning under conditions of extreme fire danger. Fireline intensity ranged from 50 kW m⁻ˡ to

Water resources are influenced by various factors such as weather, topography, geology, and environment. Therefore, there are many difficulties in evaluating and analyzing water resources for the future under climate change. In this paper, we consider climate, land cover and water demand as the most critical factors affecting change in future water resources. We subsequently introduce the procedures and methods employed to quantitatively evaluate the influence of each factor on the change in future water resources.

Surface albedo determines radiative forcing and is a key parameter for driving Earth’s climate. Better characterization of surface albedo for individual land cover types can reduce the uncertainty in estimating changes to Earth’s radiation balance due to land cover change. This paper presents new albedo look-up maps (LUM) using a multi-scale hierarchical approach based on MODIS BRDF/albedo products and Landsat imagery. Ten years (2001-2011) of MODIS BRDF/albedo products were used to generate global albedo climatology.

Recent observations show that human-induced climate change (CC) and land transformation (LT) are threatening wildlife globally. Thus, there is a need to assess the sensitivity of wildlife on large spatial scales and evaluate whether national parks (NPs), a key conservation tools used to protect species, will meet their mandate under future CC and LT conditions. Here, we assess the sensitivity of 277 mammals at African scale to CC at 10[prime] resolution, using static LT assumptions in a 'first-cut' estimate, in the absence of credible future LT trends.

Rapid development of shrimp farming may lead to unrecognized and undesirable changes of land cover/land use patterns in coastal areas. Of special concern is the loss of mangrove forest in coastal areas such as Quang Ninh, Vietnam, which is adjacent to the World Heritage-listed Ha Long Bay. Understanding the status and changes of land cover/land use for coastal shrimp farms and mangrove forests can support environmental protection and decision-making for sustainable development in coastal areas.

BACKGROUND: Climate-smart agriculture (CSA) addresses the challenge of meeting the growing demand for food, fibre and fuel, despite the changing climate and fewer opportunities for agricultural expansion on additional lands. CSA focuses on contributing to economic development, poverty reduction and food security; maintaining and enhancing the productivity and resilience of natural and agricultural ecosystem functions, thus building natural capital; and reducing trade-offs involved in meeting these goals.

BACKGROUND: Ethiopia encompasses an extraordinary number of ecological zones and plant diversity. However, the diversity of plants is highly threatened due to lack of institutional capacity, population pressure, land degradation and deforestation. An adequate documentation of these plants also has not been conducted. The farmers in Ethiopia face serious and growing food insecurity caused by drought, land degradation and climate change. Thus, rural communities are dependent on underutilized wild edible plants to meet their food and nutritional needs.

Most anthropogenic activities impacted on water quality and quantity, and further impacted on ecosystem services (ESs) in watershed are related to land use and climate changes those may cause losses of ecosystem functions. Effective information regarding ESs and their optimal priority conservation planning responded to land use and climate changes provide useful support for diverse stakeholders in ESs planning, management and policies.