Study on the Global Carbon Assimilation System Based on Multisource Remote Sensing Data

The Paris agreement signed in April, 2016 aims to balance global anthropogenic carbon emissions and terrestrial carbon sinks by the middle of the 21^st century. To fulfill this goal, it is necessary to calculate carbon fluxes of different regions reliably. The global carbon assimilation system is an effective technique for achieving this goal. The Ministry of Science and Technology of China supports the project entitled as study on the global carbon assimilation system based on multisource remote sensing data through the national key research and development programs for global change and adaptation during the thirteen-five period. This project will develop synergic inversion techniques for retrieving key parameters of biological and atmospheric cycles and for assimilating multisource remote sensing and ground based data. Then, the high resolution global carbon assimilation system coupled with an ecological model will be constructed. This system is able to assimilate jointly multisource observation data and to optimize key model parameters, photosynthesis and respiration carbon fluxes of global terrestrial ecosystems, and anthropogenic carbon emission fluxes of key regions. This system will be used to study quantitatively the spatial and temporal patterns of carbon fluxes of global terrestrial ecosystems and anthropogenic carbon emission fluxes of key regions and to identify the mechanisms driving the global terrestrial carbon sinks and sources. The outputs of this study will be helpful for the fulfillment of the key research and development programs for global change and adaptation and provide valuable data and technical support for the decision-making in China.     

Review on Montane Forest Eco-hydrology in Arid Area

Since the forest eco-hydrology of arid area shows a well sensitivity of the global climate change, the relationship between forest and water and the hydrological function has attracted the attention of academic communites and management departments. This paper expounds the research progress in arid mountain forest eco-hydrology, and analyses the formation and stable mechanism of forest patch pattern, the relationship between forest and water yield and the response of forest eco-hydrology to climate change from three aspects: Forest spatial pattern, hydrological process and its response to climate change. In addition, combined with the current research progress, the research emphases in the future are put forward: Strengthening the research on the coupling of vegetation pattern and hydrological process; solving the scale problem by using remote sensing technique and model; enhancing the understanding towards the hydrological function of forest; determining the suitable forest scale which can balance the relationship of ecology and hydrological effect.     

Reefs at the edge: coral community structure around Rapa,southernmost French Polynesia

Rapa (27°36′ S, 144°20′ W) is a small (~40 km²) volcanic island isolated in the Southern Austral Archipelago, where direct anthropogenic stressors are extremely limited. Here, we present the results of the first quantitative survey of coral community structure across habitats and depths around the island. Despite its geographical isolation in the depauperate South Central Pacific, its small size and unfavourable environmental conditions (competition with macroalgae, low sea surface temperatures, reduced reef accretion), the diversity of scleractinian corals at Rapa is particularly high (112 species from 32 genera, including 37 species of Acropora) in comparison to other French Polynesian islands and subtropical Pacific locations. Our results indicate that the abundance (>100 colonies per 10 m² recorded at nine of the 17 sampling stations) and cover (>40% at four stations) of corals are relatively high for a marginal reef location. Strong spatial heterogeneity was found, with high variation in diversity, abundance, cover and community composition among stations. Variation in community composition was related to habitat types, with distinct assemblages among fringing reefs within bays, reef formations at bay entrances, and those on the submerged platform surrounding the island. On the platform, a depth gradient was detected, with generic richness, abundance and cover generally greater at deeper stations (18–20 m depth) compared with medium‐depth (10–12 m) and shallow (1–3 m) stations. A gradient was also recorded along bays, with increasing coral diversity and abundance from the bay heads to the bay entrances. The coral community at Rapa was characterized by the presence of several taxa not found in other French Polynesian archipelagos and the rarity of others that are common and abundant in the Society and the Tuamotu islands. Another distinctive feature of reef communities at Rapa is the high cover and dominance of macroalgae, particularly in the shallower parts of the surrounding platform, which probably explains the lower densities of coral colonies recorded there. These characteristics of the diversity and biogeographical composition of coral assemblages at Rapa provide considerable ecological grounds for its conservation.     

不同饵料种类、投喂方式及环境条件对凡纳滨对虾相对摄食量的影响

为提高对虾养殖过程中的饵料利用率并减少养殖废水的排放,作者以凡纳滨对虾(Litopenaeus vannamei)为实验对象,研究了不同饵料种类、投喂方式、体质量、充气量、光照强度、水温及盐度对其相对摄食量的影响。结果表明:配合饲料组对虾的相对摄食量显著高于冰鲜虾肉组;连续单颗投喂时对虾的相对摄食量较高;相对摄食量随对对虾体重升高而显著(P0.01)下降,而且不同规格的对虾在竞争条件下平均相对摄食量会降低;充气量6 L/min组对虾的相对摄食量明显高于另外两组;弱光环境下对虾的相对摄食量较高;水温和盐度对相对摄食量的影响极显著(P0.01),在32℃时对虾获得最大相对摄食量,在盐度为5时相对摄食量最小,高盐度下组间差异不显著(P0.05)。因此,在实际生产中应采取少量多次的投饵策略,并根据环境条件的变化合理的调整投饵量。     

Estimating attendance from cellular network data

An automatic estimate of the number of attendees to events happening in the city can provide valuable information to geographic information systems and geo-located applications. We present a methodology to estimate the number of events’ attendees from cellular network data. In this work, we used anonymized Call Detail Records (CDRs) comprising data on where and when users access the cellular network. Our approach is based on two key ideas: (1) we identify the network cells associated with the event location. (2) We verify the attendance of each user, as a measure of whether (s)he generates CDRs during the event, but not during other times. We evaluate our approach to estimate the number of attendees to a number of events ranging from football matches in stadiums to concerts and festivals in open squares. Comparing our results with the best groundtruth data available, our estimates provide a median error of less than 15% of the actual number of attendees.     

Interactive discovery of sequential patterns in time series of wind data

Wind speed and direction vary over space and time due to the interactions between different pressures and temperature gradients within the atmospheric layers. Near the earth’s surface, these interactions are modulated by topography and artificial structures. Hence, characterizing wind behaviour over large areas and long periods is a complex but essential task for various energy-related applications. In this study, we present a novel approach to discover wind patterns by integrating sequential pattern mining and interactive visualization techniques. The approach relies on the use of the Linear time Closed pattern Miner sequence algorithm in conjunction with a time sliding window that allows the discovery of all sequential patterns present in the data. These patterns are then visualized using integrated 2D and 3D coordinated multiple views and visually explored to gain insight into the characteristics of the wind from a spatial, temporal and attribute (type of wind pattern) point of view. This proposed approach is used to analyse 10 years of hourly wind speed and direction data for 29 weather stations in the Netherlands. The results show that there are 15 main sequential patterns in the data. The spatial task shows that weather stations located in the same region do not necessarily experience similar wind pattern. For within the selected time interval, similar wind patterns can be observed in different stations and in the same station at different times of occurrence. The attribute task discovered that the repetitive occurrences of chosen pattern indicate as regular wind behaviour at different weather stations that persisted continuously over time. The results of these tasks show that the proposed interactive discovery facilitates the understanding of wind dynamics in space and time.     

Dasymetric Spatiotemporal Interpolation

This research applies the principles of dasymetric mapping to spatiotemporal interpolation by extending the spatial concepts of zone and area to their temporal analogs of interval and duration, respectively. An example application of dasymetric spatiotemporal interpolation using crime event data is presented. Results indicate that dasymetric spatiotemporal interpolation significantly improves the accuracy of estimates over areal or duration weighting. In addition, even when dasymetric interpolation in either the spatial or temporal dimension is relatively weak, combining dasymetric estimation in both space and time dimensions simultaneously has the potential to amplify the accuracy of the overall dasymetric estimation.     

Local Spatiotemporal Modeling of House Prices: A Mixed Model Approach

The real estate market has long provided an active application area for spatial–temporal modeling and analysis and it is well known that house prices tend to be not only spatially but also temporally correlated. In the spatial dimension, nearby properties tend to have similar values because they share similar characteristics, but house prices tend to vary over space due to differences in these characteristics. In the temporal dimension, current house prices tend to be based on property values from previous years and in the spatial–temporal dimension, the properties on which current prices are based tend to be in close spatial proximity. To date, however, most research on house prices has adopted either a spatial perspective or a temporal one; relatively little effort has been devoted to situations where both spatial and temporal effects coexist. Using ten years of house price data in Fife, Scotland (2003–2012), this research applies a mixed model approach, semiparametric geographically weighted regression (GWR), to explore, model, and analyze the spatiotemporal variations in the relationships between house prices and associated determinants. The study demonstrates that the mixed modeling technique provides better results than standard approaches to predicting house prices by accounting for spatiotemporal relationships at both global and local scales.     

A STATISTICAL FRAMEWORK FOR TREE‐RING RECONSTRUCTION OF HIGH‐MAGNITUDE MASS MOVEMENTS: CASE STUDY OF SNOW AVALANCHES IN EASTERN CANADA

This paper investigates the application of the peaks‐over‐threshold method in combination with fitting of the generalized Pareto distribution for estimating the frequency of high‐magnitude geomorphic events, on the basis of tree‐ring data. In particular, attention is focused on extreme value distribution of tree‐ring responses and in the minimum threshold or index number required to assure the past occurrence of high‐magnitude events. The objective is to set a threshold, adapted to the sample distribution, which will make the distinction between high‐magnitude years and remaining years, where the response of sampled trees is too weak to be attributed to a high‐magnitude geomorphic event. The statistical framework proposed is based on the statistics of extremes. Through the use of simple, strong and effective mathematics, this model should strengthen the position of dendrogeomorphology in the evaluation and management of natural hazards.