Estimating aboveground biomass using Pléiades satellite image in a karst watershed of Guizhou Province,Southwestern China

Biomass in karst terrain has rarely been measured because the steep mountainous limestone terrain has limited the ability to sample woody plants.Satellite observation, especially at high spatial resolution, is an important surrogate for the quantification of the biomass of karst forests and shrublands. In this study, an artificial neural network(ANN) model was built using Pléiades satellite imagery and field biomass measurements to estimate the aboveground biomass(AGB) in the Houzhai River Watershed, which is a typical plateau karst basin in Central Guizhou Province, Southwestern China. A back-propagation ANN model was also developed.Seven vegetation indices, two spectral bands of Pléiades imagery, one geomorphological parameter,and land use/land cover were selected as model inputs. AGB was chosen as an output. The AGB estimated by the allometric functions in 78 quadrats was utilized as training data(54 quadrats, 70%),validation data(12 quadrats, 15%), and testing data(12 quadrats, 15%). Data-model comparison showed that the ANN model performed well with an absolute root mean square error of 11.85 t/ha, which was 9.88%of the average AGB. Based on the newly developed ANN model, an AGB map of the Houzhai River Watershed was produced. The average predicted AGB of the secondary evergreen and deciduous broadleaved mixed forest, which is the dominant forest type in the watershed, was 120.57 t/ha. The average AGBs of the large distributed shrubland,tussock, and farmland were 38.27, 9.76, and 11.69 t/ha, respectively. The spatial distribution pattern ofthe AGB estimated by the new ANN model in the karst basin was consistent with that of the field investigation. The model can be used to estimate the regional AGB of karst landscapes that are distributed widely over the Yun-Gui Plateau.     

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.     

Assessment of prospective hazards resulting from the 2017 earthquake at the world heritage site Jiuzhaigou Valley,Sichuan, China

On August 8, 2017, a Ms = 7.0 magnitude earthquake occurred in the Jiuzhaigou Valley, in Sichuan Province, China(N: 33.20°, E: 103.82°). Jiuzhaigou Valley is an area recognized and listed as a world heritage site by UNESCO in 1992. Data analysis and field survey were conducted on the landslide, collapse, and debris flow gully, to assess the coseismic geological hazards generated by the earthquake using an unmanned aerial vehicle(UAV), remote-sensing imaging, laser range finders, geological radars, and cameras. The results highlighted the occurrence of 13 landslides, 70 collapses, and 25 potential debris flow gullies following the earthquake. The hazards were classified on the basis of their size and the potential property loss attributable to them. Consequently, 14 large-scale hazards, 30 medium-sized hazards, and 64 small hazards accounting for 13%, 28%, and 59% of the total hazards, respectively, were identified. Based on the variation tendency of the geological hazards that ensued in areas affected by the Kanto earthquake(Japan), Chi-chi earthquake(Taiwan China), and Wenchuan earthquake(Sichuan China), the study predicts that, depending on the rain intensity cycle, the duration of geological hazard activities in the Jiuzhaigou Valley may last over ten years and will gradually decrease for the following five to ten yearsbefore returning to pre-earthquake levels. Thus,necessary monitoring and early warning systems must be implemented to ensure the safety of residents,workers and tourists during the construction of engineering projects and reopening of scenic sites to the public.     

Impacts of tourism development on the physical environment of Mussoorie,a hill station in the lower Himalayan range of India

Tourism in mountainous regions is a significant source of revenue generation. However, it has also been associated with many adverse environmental consequences. This study aims at assessing the negative impacts of the incessant upsurge in tourism development on the physical environment of Mussoorie, a well-known mountain tourist destination in India. The impact indicators for the region were identified and assessed by qualitative and quantitative analysis of field observations. The observations indicated the aggravation of traffic congestion, atmospheric pollution, undisposed solid waste, water scarcity and infrastructure unavailability as the prevalent issues, especially during the peak tourist months. The extent of the consequential damage to the environment was evaluated by conducting an assessment of tourism-induced human disturbance on the natural landscape of the town. Slope, slope aspect, vegetation cover, road network and drainage network were incorporated as the determining landscape attributes to prepare thematic maps of landscape quality (perceivable intrinsic properties) and landscape fragility (vulnerability to anthropogenic disturbances) using GIS technique. An absorption capacity map was finally prepared to characterize the study area into regions of different conservation needs. The results identified the need for planning appropriate preservation strategies for different tourist places in the town. The study can be used by the policy makers for implementing the regulatory measures against potential disturbances due to mass-tourism.     

Differentiated payments for environmental services schemes: Amethodology proposal

Payment schemes for environmental services face serious budget constraints in Mexico. Payments are equally distributed among forest owners, and the governmental agencies that make payments to beneficiaries do not evaluate the amount of environmental services produced by forested areas. This lack of evaluation could lead to economic and environmental deficiencies that restrict the possible benefits of such programmes. In general, these programmes do not achieve their conservation objectives, and local beneficiaries are not involved in the design or application of these programmes. Similarly, the Payments for Hydrological Environmental Services (PHES) programme of the State of Mexico, Mexico, makes equal payments to beneficiaries of forested areas considering tree density. The objective of the present work was to create a methodology for determining differentiated payments schemes for hydrological environmental services, prioritising areas that contribute the most to groundwater recharge and promote the participation of society. In the Nevado de Toluca Natural Protected Area, the environmental criteria of forest type, tree density and aquifer overexploitation as well as social participation were considered in a multi-criteria analysis implemented in a Geographic Information System. A methodology was developed to determine differentiated payments based on specific forest characteristics that influence the potential capacity of forests to recharge groundwater reserves in addition to the level of social participation. In particular, social participation is key as it could ensure the viability of PHES programmes as conservation alternatives in forested areas with high groundwater recharge potential.     

Using multispectral landsat and sentinel-2 satellite data to investigate vegetation change at Mount St. Helens since the great volcanic eruption in 1980

Long-term analyses of vegetation succession after catastrophic events are of high interest for an improved understanding of succession dynamics. However, in many studies such analyses were restricted to plot-based measurements. Contrarily, spatially continuous observations of succession dynamics over extended areas and time-periods are sparse. Here, we applied a change vector analysis (CVA) to investigate vegetation succession dynamics at Mount St. Helens after the great volcanic eruption in 1980 using Landsat. We additionally applied a supervised random forest classification using Sentinel-2 data to map the currently prevailing vegetation types. Change vector analysis was performed with the normalized difference vegetation index (NDVI) and the urban index (UI) for three subsequent decades after the eruption as well as for the whole observation time between 1984 and 2016. The influence of topography on the current vegetation distribution was examined by comparing altitude, slope angles and aspect values of vegetation classes derived by the random forest classification. Wilcox- Rank-Sum test was applied to test for significant differences between topographic properties of the vegetation classes inside and outside of the areas affected by the eruption. For the full time period, a total area of 516 km² was identified as re-vegetated, whereas the area and magnitude of re-growing vegetation decreased during the three decades and migrated closer to the volcanic crater. Vegetation losses were mainly observed in regions unaffected by the eruption and related mostly to timber harvesting. The vegetation type classification reached a high overall accuracy of approximately 90%. 36 years after the eruption, coniferous and deciduous trees have established at formerly devastated areas dominating with a proportion of 66%, whereas shrubs are more abundant in riparian zones. Sparse vegetation dominates at regions very close to the crater. Elevation was found to have a great influence on the reestablishment and distribution of the vegetation classes within the devastated areas showing in almost all cases significant differences in altitude distribution. Slope was less important for the different classes - only representing significantly higher values for meadows, whereas aspect seems to have no notable influence on the reestablishment of vegetation at Mount St. Helens. We conclude that major vegetation succession dynamics after catastrophic events can be assessed and characterized over large areas from freely available remote sensing data and hence contribute to an improved understanding of succession dynamics.     

Stabilization versus decomposition in alpine ecosystems of the Northwestern Caucasus: The results of a tea bag burial experiment

Mountainous areas exhibit highly variable decomposition rates as a result of strong local differences in climate and vegetation type. This paper describes the effect of these factors on two major determinants of the local carbon cycle: litter decomposition and carbon stabilization. In order to adequately reflect local heterogeneity, we have sampled 12 typical plant communities of the Russian Caucasus. In order to minimize confounding effects and encourage comparative studies, we have adapted the widely used tea bag index (TBI) that is typically used in areas with low decomposition. By incubating standardized tea litter for a year, we investigated whether (1) initial litter decomposition rate (k) is negatively correlated with litter stabilization (S) and (2) whether k or S exhibit correlations with altitude and other environmental conditions. Our results show that S and k are not correlated. Altitude, pH, and water content significantly influenced the stabilization factor S, while soil-freezing had no influence. In contrast, none of these factors predicted the decomposition rate k. Based on our data, we argue that collection of decomposition rates alone, as is now common practice, is not sufficient to understand carbon input to soils and can potentially lead to misleading results. Our data on community-specific decomposition and stabilization rates further constrain estimates of litter accumulation in subalpine communities and the potential effects of climate change.     

Spatio-temporal Variation of Soil Respiration and Its Driving Factors in Semi-arid Regions of North China

Soil respiration (SR) is the second-largest flux in ecosystem carbon cycling. Due to the large spatio-temporal variability of environmental factors, SR varied among different vegetation types, thereby impeding accurate estimation of CO₂ emissions via SR. However, studies on spatio-temporal variation of SR are still scarce for semi-arid regions of North China. In this study, we conducted 12-month SR measurements in six land-use types, including two secondary forests (Populus tomentosa (PT) and Robinia pseudoacacia (RP)), three artificial plantations (Armeniaca sibirica (AS), Punica granatum (PG) and Ziziphus jujuba (ZJ)) and one natural grassland (GR), to quantify spatio-temporal variation of SR and distinguish its controlling factors. Results indicated that SR exhibited distinct seasonal patterns for the six sites. Soil respiration peaked in August 2012 and bottomed in April 2013. The temporal coefficient of variation (CV) of SR for the six sites ranged from 76.98% to 94.08%, while the spatial CV of SR ranged from 20.28% to 72.97% across the 12-month measurement. Soil temperature and soil moisture were the major controlling factors of temporal variation of SR in the six sites, while spatial variation in SR was mainly caused by the differences in soil total nitrogen (STN), soil organic carbon (SOC), net photosynthesis rate, and fine root biomass. Our results show that the annual average SR and Q₁₀ (temperature sensitivity of soil respiration) values tended to decrease from secondary forests and grassland to plantations, indicating that the conversion of natural ecosystems to man-made ecosystems may reduce CO₂ emissions and SR temperature sensitivity. Due to the high spatio-temporal variation of SR in our study area, care should be taken when converting secondary forests and grassland to plantations from the point view of accurately quantifying CO₂ emissions via SR at regional scales.     

Effect of Aspect on Climate Variation in Mountain Ranges of Shennongjia Massif,Central China

The aim of this study was to better understand the mechanisms of regional climate variation in mountain ranges with contrasting aspects as mediated by changes in global climate. It may help predict trends of vegetation variations in native ecosystems in natural reserves. As measures of climate response, temperature and precipitation data from the north, east, and south-facing mountain ranges of Shennongjia Massif in the coldest and hottest months(January and July), different seasons(spring, summer, autumn, and winter) and each year were analyzed from a long-term dataset(1960 to 2003) to tested variations characteristics, temporal and spatial quantitative relationships of climates. The results showed that the average seasonal temperatures and precipitation in the north, east, and south aspects of the mountain ranges changed at different rates. The average seasonal temperatures change rate ranges in the north, east, and south-facing mountain ranges were from –0.0210℃/yr to 0.0143℃/yr, –0.0166℃/yr to 0.0311℃/yr, and –0.0290 ℃/yr to 0.0084℃/yr, respectively, and seasonal precipitation variation magnitude were from –1.4940 mm/yr to 0.6217 mm/yr, –1.6833 mm/yr to 2.6182 mm/yr, and –0.8567 mm/yr to 1.4077 mm/yr, respectively. The climates variation trend among the three mountain ranges were different in magnitude and direction, showing a complicated change of the climates in mountain ranges and some inconsistency with general trends in global climate change. The climate variations were significantly different and positively correlated cross mountain ranges, revealing that aspects significantly affected on climate variations and these variations resulted from a larger air circulation system, which were sensitive to global climate change. We conclude that location and terrain of aspect are the main factors affecting differences in climate variation among the mountain ranges with contrasting aspects.     

Evolution Characteristics of Government-Industry-University-Research Cooperative Innovation Network for China’s Agriculture and Influencing Factors: Illustrated According to Agricultural Patent Case

Under the special background of China, the cooperative innovation between different government-industry-university-research institutes plays an increasingly important role in the agricultural field. However, the existing literature has paid little attention to it. Considering the cooperation patents, published in the agriculture field stemming from the Full-text Database of China Patents as the study object, the spatial and institutional attribute of the authors as the data source, and by combining the social network and spatial econometrics analysis, this paper analyzes the structure evolution characteristics of cooperative innovation networks of agricultural government-industry-university-research institute in the city level of China in 1985–2014, based on the triple helix theory, with the influence factors discussed. This shows that, 1) since 1985, China's agricultural innovation level has been substantially increased, but the development degree of the cooperative innovation network is low, and the patent cooperation mainly relies on authors in the same unit; 2) enterprises play a leading role in the agricultural cooperative innovation. The effect of the government and hybrid organizations driven by the government is not obvious; 3) the cooperative innovation in the province and city dominates, and a multi-pole pattern has been formed. The cooperative innovation network structure evolves from a single helix empty core and double helix multi core to a double helix hierarchical network; 4) the city's science, education funding and personnel investment are key factors determining the agricultural cooperative innovation, while the agricultural development of the city presents slight negative impacts on it. The spatial mismatch of supply and demand is present in the technical cooperative innovation of China's agriculture. Therefore, the science enhancement and education investment to big agricultural provinces should be promptly implemented.