Projections of the impacts of climate change on the water deficit and on the precipitation erosive indexes in Mantaro River Basin,Peru

Projections of climate change are essential to guide sustainable development plans in the tropical Andean countries such as Peru. This study assessed the projections of precipitation and potential evaporation, rain erosive potential, and precipitation concentration in the Mantaro River Basin, in the Peruvian Andes, which is important for agriculture and energy production in Peru. We assumed the Intergovernmental Panel on Climate Change (IPCC) A1B greenhouse gas emission scenario and simulated the global climate change by the HadCM3 global climate model. Due to the steepness of the mountain slopes and the narrowness of the river valley, this study uses the downscaling of the global model simulations by the regional Eta model down to 20-km resolution. The downscaling projections show decrease in the monthly precipitation with respect to the baseline period, especially during the rainy season, between February and April, until the end of the 21st century. Meanwhile, a progressive increase in the monthly evaporation from the baseline period is projected. The Modified Fournier Index (MFI) shows a statistically significant downward trend in the Mantaro River Basin, which suggests a possible reduction in the rain erosive potential. The Precipitation Concentration Index (PCI) shows a statistically significant increasing trend, which indicates increasingly more irregular temporal distribution of precipitation towards the end of the century. The results of this study allow us to conclude that there should be a gradual increase in water deficit and precipitation concentration. Both changes can be negative for agriculture, power generation, and water supply in the Mantaro River Basin in Peru.     

The higher grain production,the more social deprivation? A case study of Henan province in traditional agricultural areas of China

This paper examines the spatial-temporal dynamics of inequality from the perspective of social deprivation in the context of continuous growth of grain production using national census data from 2000 and 2010 for Henan province, China. Our analytical results show an overall level of social deprivation that is high and a widening social deprivation gap at the county level. The social deprivation shows great spatiotemporal heterogeneity, the higher deprived counties are mainly distributed in central and eastern Henan province, while counties with lower social deprivation are clustered in northwestern regions, formed a belt-shape spatial differential between the south (higher deprived counties clustered) and northwest (low deprived counties clustered) Henan in 2000, and changed toward a core-periphery semi annular spatial structure in 2010, the low deprived counties surrounded by high deprived counties. The social deprivation shows a “west low and east high” spatial pattern, similar to the grain production in Henan province. Socioeconomic development level was low in most counties in Yudong plain despite of keeping the continuous increase of grain production, meaning the higher grain output did not result in the more social development expected in Chinese traditional agricultural areas, and the regional disparity is expected to increase in the near future if development conditions are not changed, which could inspire more targeted rural governance options.     

Latitudinal and temporal shifts in the radial growth-climate response of Siberian larch in the Polar Urals

This paper presents a dendroclimatic analysis of Siberian larch trees sampled along a latitudinal 260-km transect located in the Polar Urals,Russia. Three standardised chronologies were built over a length of 230–293 years using 79 individual tree-ring chronologies collected in the southern,middle and northern parts of the Polar Urals.Bootstrapped correlation functions showed that the annual growth of the larches was mainly influenced by the air temperatures in June and July. The relative role of the temperatures increased from south to north. Daily air temperature data analysis revealed that the duration of the growing season in the northern part of the Polar Urals is 24 days less than that in the southern part. At the present time, air temperatures exceeded threshold of 8~℃, 5 days earlier than it did in the beginning of the 20 th century In response to the increase in the duration of the growing season and the changing winter conditions in the Polar Urals over the last 130 years, radial growth–temperature relationships in larches have weakened;this effect was strongly pronounced in the southern part of the Polar Urals.     

Global patterns in above-ground net primary production and precipitation-use efficiency in grasslands

The above-ground net primary production(ANPP) and the precipitation-use efficiency(PUE) regulate the carbon and water cycles in grassland ecosystems, but the relationships among the ANPP, PUE and precipitation are still controversial. We selected 717 grassland sites with ANPP and mean annual precipitation(MAP) data from 40 publications to characterize the relationships ANPP–MAP and PUE–MAP across different grassland types. The MAP and ANPP showed large variations across all grassland types, ranging from 69 to 2335 mm and 4.3 to 1706 g m~(-2), respectively. The global maximum PUE ranged from 0.19 to 1.49 g m~(-2) mm~(-1) with a unimodal pattern. Analysis using the sigmoid function explained the ANPP–MAP relationship best at the global scale. The gradient of the ANPP–MAP graph was small for arid and semi-arid sites(MAP 400 mm). This study improves our understanding of the relationship between ANPP and MAP across dry grassland ecosystems. It provides new perspectives on the prediction and modeling of variations in the ANPP for different grassland types along precipitation gradients.     

Tradeoff between the number of firefighting resources and the level of fire ignition prevention efforts in the Republic of Korea

This study explores the tradeoff relationship between the number of initial attack firefighting resources and the level of fire ignition prevention efforts mitigating the probability of human-made fires in the Republic of Korea, where most fires are caused by human activities. To examine this tradeoff relationship, we develop a hybrid model that combines a robust optimization model with a stochastic simulation model. The robust optimization minimizes the expected number of fires not receiving a pre-defined response, such as the number of firefighting resources that must arrive at the fire within half an hour, subject to budget constraints and uncertainty about the daily number and location of fires. The simulation model produces a set of fire scenarios in which a combination of number, location, ignition time, and intensity of fires occur. Results show that fire ignition prevention is as cost-effective as initial attack firefighting resources given the current budget in the Republic of Korea for reducing the expected number of fires not covered by the predefined response. The mixed policy of fire suppression and fire prevention may produce some gains in efficiency relative to the dominant policy of strong fire suppression strategies.     

Spatial downscaling of climate variables using three statistical methods in Central Iran

Spatial downscaling methods are widely used for the production of bioclimatic variables(e.g. temperature and precipitation) in studies related to species ecological niche and drainage basin management and planning. This study applied three different statistical methods, i.e. the moving window regression(MWR), nonparametric multiplicative regression(NPMR), and generalized linear model(GLM), to downscale the annual mean temperature(Bio1) and annual precipitation(Bio12) in central Iran from coarse scale(1 km × 1 km) to fine scale(250 m ×250 m). Elevation, aspect, distance from sea and normalized difference vegetation index(NDVI) were used as covariates to create downscaled bioclimatic variables. Model assessment was performed by comparing model outcomes with observational data from weather stations. Coefficients of determination(R2), bias, and root-mean-square error(RMSE) were used to evaluate models and covariates. The elevation could effectively justify the changes in bioclimatic factors related to temperature and precipitation. Allthree models could downscale the mean annual temperature data with similar R2, RMSE, and bias values. The MWR had the best performance and highest accuracy in downscaling annual precipitation(R2=0.70; RMSE=123.44). In general, the two nonparametric models, i.e. MWR and NPMR, can be reliably used for the downscaling of bioclimatic variables which have wide applications in species distribution modeling.     

Tourism resource assessment and spatial analysis of wine tourism development: a case study of the eastern foothills of China’s Helan Mountains

The reasonable development and utilization of mountainous regions closely relates to local economic development and ecological security. The wine production region in the eastern foothills of the Helan Mountains in Ningxia, Ningxia Hui Autonomous Region, with its excellent terroir, is emerging as one of China’s three major geographical attractions. Based on surveys of tourism resources and spatial analysis for this wine producing region, we propose a highly representative and practicable path for wine tourism development. Based on China’s national standard in Classification, Investigation and Evaluation of Tourism Resources (GB/T 18972-2003), which recommended the types and grades of tourism resources in one area, we conduct an analysis of resource characteristics and the current state of development. Using ArcGIS software, spatial autocorrelation analysis, average nearest neighbor analysis, as well as clustering and outlier analysis, we are able to derive the spatial distribution characteristics of tourism resources. Our survey showed that tourism resources in this area are relatively abundant and have good quality and clear combination advantages. Nonetheless, there are resources shortage for wine tourism and poor integration of wine production with the tourism industry. Regarding the spatial distribution of resources, we revealed the current states of and issues surrounding regions with concentrated resources, as well as characteristics of this clustering. Finally, we proposed a development path for wine tourism in this region based on the five dimensions of management mode, industrial path, product development, spatial optimization, and market development.     

Long-term variability of air temperature and precipitation conditions in the Polish Carpathians

Mountain regions are sensitive to climate changes, which make them good indicators of climate change. The aim of this study is to investigate the spatial and temporal variability of air temperature and precipitation in the Polish Carpathians. This study consists of climatological analyses for the historical period 1851-2010 and future projections for 2021-2100. The results confirm that there has been significant warming of the area and that this warming has been particularly pronounced over the last few decades and will continue in the oncoming years. Climate change is most evident in the foothills; however, these are the highest summits which have experienced the most intensive increases in temperature during the recent period. Precipitation does not demonstrate any substantial trend and has high year-to-year variability. The distribution of the annual temperature contour lines modelled for selected periods provides evidence of the upward shift of vertical climate zones in the Polish Carpathians, which reach approximately 350 meters, on average, what indicates further ecological consequences as ecosystems expand or become extinct and when there are changes in the hydrological cycle.     

Comparison of the spatio-temporal dynamics of vegetation between the Changbai Mountains of eastern Eurasia and the Appalachian Mountains of eastern North America

The Changbai Mountains and the Appalachian Mountains have similar spatial contexts. The elevation, latitude, and moisture gradients of both mountain ranges offer regional insight for investigating the vegetation dynamics in eastern Eurasia and eastern North America. We determined and compared the spatial patterns and temporal trends in the normalized difference vegetation index (NDVI) in the Changbai Mountains and the Appalachian Mountains using time series data from the Global Inventory Modeling and Mapping Studies 3rd generation dataset from 1982 to 2013. The spatial pattern of NDVI in the Changbai Mountains exhibited fragmentation, whereas NDVI in the Appalachian Mountains decreased from south to north. The vegetation dynamics in the Changbai Mountains had an insignificant trend at the regional scale, whereas the dynamics in the Appalachian Mountains had a significant increasing trend. NDVI increased in 55% of the area of the Changbai Mountains and in 95% of the area of the Appalachian Mountains. The peak NDVI occurred one month later in the Changbai Mountains than in the Appalachian Mountains. The results revealed a significant increase in NDVI in autumn in both mountain ranges. The climatic trend in the Changbai Mountains included warming and decreased precipitation, and whereas that in the Appalachian Mountains included significant warming and increased precipitation. Positive and negative correlations existed between NDVI and temperature and precipitation, respectively, in both mountain ranges. Particularly, the spring temperature and NDVI exhibited a significant positive correlation in both mountain ranges. The results of this study suggest that human actives caused the differences in the spatial patterns of NDVI and that various characteristics of climate change and intensity of human actives dominated the differences in the NDVI trends between the Changbai Mountains and the Appalachian Mountains. Additionally, the vegetation dynamics of both mountain ranges were not identical to those in previous broader-scale studies.     

Plant diversity and community structure of Brazilian <Emphasis Type="Italic">Páramos</Emphasis>

In Eastern South America, high altitude grasslands represent a mountain system that has a high number of endemic species. However, studies on the ecology of plant communities in these environments remain scarce. We aimed to evaluate the patterns of biodiversity and structure of plant communities from rocky outcrops in high altitude grasslands of three areas at the Caparaó National Park, southeastern Brazil, by sampling 300 randomly distributed plots. Then, we compared the floristic composition, relative abundance, and biological and vegetation spectra among areas. We classified species as endemic and non-endemic and verified the occurrence of endangered species. Species richness was evaluated by rarefaction analysis on the sampling units. The importance value and species abundance distribution (SAD) models were assessed. We also performed an indicator species analysis. We sampled 58 species belonging to 49 genera and 32 families. The number of species decreased with increasing altitude, with significant differences being observed among areas regarding richness, abundance, and cover. Of the total number of species, 10 are endemic to the Caparaó National Park and 17 are listed on the Brazilian Red List of endangered species. The dominant families on all peaks were Asteraceae and Poaceae. The SAD models showed lognormal and geometric distributions, corroborating the fact that 10 species that were common to all three areas were also the most dominant ones in the communities and showed the highest importance values, which ranged between 35% and 60%. Indicator species analysis revealed that 28 species (48.27%) were indicators. Of these, 42.85% had maximum specificity, meaning that they occurred only in one area. Thus, the number of species per life form ratio was similar among areas, yet vegetation spectra differed, especially for hemicryptophytes. The altimetric difference among the areas showed to be a very important driver in the community assembly, influencing the evaluated variables, however, other drivers as soil depth, slope and water could also influence the community structure on a smaller and local spatial scale.