Estimating the vulnerability of fifteen tree species under changing climate in Northwest North America

In the Pacific northwestern (PNW) region of North America, climatic conditions have significantly warmed since a predominantly cool phase of the Pacific North American circulation patterns between 1950 and 1975. What are the implications of this shift in climate for the vulnerability of native tree species? To address this question, we combined mechanistic and statistical models to assess where a variety of native tree species might be more vulnerable within their recorded ranges and where they might potentially migrate. For long-lived species that are well adapted to compete, seasonal differences in photosynthesis and water use offer insights helpful in predicting their distributions. To evaluate the general response of conifers to climatic variation across the region, we previously applied a process-based model (3-PG), to simulate the growth and maximum leaf area index that Douglas-fir could attain within recognized forested areas. We then constructed automated decision tree models to define and map the ecological distributions of 15 tree species based on differences in how photosynthesis was constrained by drought, daytime temperatures, high evaporative demand, and the frequency of frost. For the baseline climate period (1950-1975), the decision tree models predicted presence and absence of each species at ∼23,000 observations with an average accuracy of 81%, with an average kappa statistic of 0.74. In this paper the same models were run annually for the period between 1976 and 2006 for each species, and the areas defined as remaining suitable or becoming vulnerable to disturbance were identified based on whether more or less than half of the years fell within the originally defined limits. Based on these criteria, 70% of the species recorded ranges remained suitable, with 30% deemed vulnerable. Results varied notably by species with western red cedar and western hemlock remaining highly adapted, with potential for range expansion in area of up to 50% relative to the baseline period. In contrast, ponderosa pine, lodgepole pine, grand, and noble fir were classified as vulnerable with potential net contractions in their ranges. The analysis was extended through the rest of the 21st century using climatic projections from the Canadian global circulation model with a high fossil fuel emission scenario (A2) and compared to other previously published species range predictions.     

Modelling the abundance of three key plant species in New Zealand hill-pasture using a decision tree approach

Decision tree models were developed to investigate and predict the relative abundance of three key pasture plants [ryegrass (Lolium perenne), browntop (Agrostis capillaris), and white clover (Trifolium repens)] with integration of a geographical information system (GIS) in a naturalised hill-pasture in the North Island, New Zealand, and were compared with regression models with respect to model fit and predictive accuracy. The results indicated that the decision tree models had a better model fit in terms of average squared error (ASE) and a higher percentage of adequately predicted cases in model validation than the corresponding regression models. These decision tree models clearly revealed the relative importance of environmental and management variables in influencing the abundance of these three species. Hill slope was the most significant environmental factor influencing the abundance of ryegrass while soil Olsen P and annual P fertilizer input were the most significant factors influencing the abundance of browntop, and white clover, respectively. Soil Olsen P of approximately 10 μg/g, or a slope of about 10.5° was critical points where the competition between ryegrass and browntop tended to come to an equilibrium. Integrating the decision tree models with a GIS in this study not only facilitated the model development and analyses, but also provided a useful decision support tool in pasture management such as in assisting precision fertilizer placement. The insights obtained from the decision tree models also have important implications for pasture management, for example, it is important to maintain a soil Olsen P higher than 10 μg/g in order to keep the dominance of ryegrass in the hill-pasture.     

State subsidies induce gray jays to accept greater danger: an ecologically rational response?

Models of strictly rational choice assume that decision-makers evaluate options on relevant dimensions, assign fixed values to options, and then make consistent choices based on these values. If so, recent experience would have no impact on preference. But, recent events change an animal’s state, and preference may change accordingly. We explore how state affects willingness to accept greater danger to obtain larger food rewards. We tested how a supplement in state (hoard size) impacts this willingness in gray jays (Perisoreus canadensis). When subsidized, most of the subjects increased their willingness to trade danger for food. Why would they become less cautious when their hoard was increased? Superficially, it might seem prudent to play it safer in response to a subsidy. But imagining fitness as a sigmoid function of state (hoard size) provides a tentative explanation for our counterintuitive finding. Above a threshold hoard size, a subsidy should weaken the willingness to accept extra danger. Incremental increases in state in the deceleratory phase yield smaller fitness gains, so it would pay to increase emphasis on safety after receiving a subsidy. But below this threshold, incremental increases in state in the acceleratory phase yield bigger fitness gains, and so it would pay to decrease emphasis on safety after receiving a subsidy. Most of our subjects’ choice behavior was, thus, plausibly consistent with the possibility that effective hoard size is considerably smaller than the total number of items stored. We speculate that this response may reflect an ecologically rational compensation for the inevitable loss of hoards via theft and rot.     

扑救森林火灾应遵守的安全规则

本文简要介绍了在林火扑救中扑火队员应遵守的安全规则。     

生命线工程网络抗震可靠性分析方法的比较研究

生命线工程网络抗震可靠性分析是进行生命线工程系统规划、设计、改造与优化的基础。因此 ,寻找一种高效的适应性强的系统可靠性分析方法对实际工程应用具有重要的意义。本文主要介绍两种高效的网络系统两终端连通可靠性分析方法———递推分解算法和有序二分决策图算法。首先 ,分别对两种算法的原理及实现过程进行了详细的论述和说明 ,并且用c语言编制了二分决策图算法的计算程序。然后 ,利用这两种方法及随机模拟算法对 2 0个以往研究中的经典算例和两个实际工程网络———河南省电力网和上海市浦西供水管网 ,进行了网络系统抗震连通可靠性分析。通过对实例分析结果的比较研究 ,得到了一些经验性的结论 ,以期为优化设计工程网络时选择系统可靠性的分析工具提供参考。研究表明 ,由于递推分解算法具有适应性强和能够求得问题近似解的优点 ,因此有良好的实际工程应用前景。     

鄱阳湖湿地植物生态系统结构及湖水位对其影响研究

通过对鄱阳湖水文过程和湖盆地形特点的分析,利用3S技术对鄱阳湖湿地进行了分类,研究了各种类型湿地植物生态系统的生境、主要植物群落结构和分布规律。结果表明,鄱阳湖湿地植物生态系统结构复杂,生物多样性极其丰富。湿地植物是以根茎为主要繁殖器官的克隆繁殖植物,以集群分布为主要特点。在宏观尺度上受地形高程、湖水位和洲滩出露时间制约,不同植物群落沿水分梯度分布;在景观尺度上受到土壤含水量、地下水埋深和土壤结构影响,形成水平镶嵌结构;微观尺度上还与微地形和土壤养分密切相关,部分区域表现为复合体结构。湿地植被对水分梯度的敏感性,导致湿地植物生态系统的易变性和脆弱性。近年来,鄱阳湖水位过低且持续时间长,使生态系统遭受一定损害。     

Multiple-resource modeling as a tool for conservation: Its applicability in Mexico

The current Mexican environmental law provides the legal basis for comprehensive land-use planning. Under the law, development of natural ecosystems must combine goals, policies, and practices towards the sustainable use of natural resources and the protection of biological diversity. Thus, ecosystem manipulation must be able to counter fragmentation of natural ecosystems and isolation of natural reserves, while providing for human needs. Assessment of the potential of natural ecosystems and management impacts are required. Multiple-resource simulation is an assessment and land-use planning tool that permits managers and decision makers to comply with the law, providing a flexible, user-oriented system that can meet the needs of managers, conservationists, and researchers. A multiple-resource model and an example of how it can be applied to meet planning needs is presented for discussion.     

Nutrient budgets: sustainability assessment of rainfed lowland rice-based systems in northeast Thailand

In northeast Thailand, the sustainability of rainfed lowland rice-based systems, the dominant land-use system (LUS) in the region, is a concern for the welfare of the population in this relatively poor region. Poor soil fertility and low inputs are seen as major causes of this lack of sustainability. In this context, the assessment of nutrient budgets is seen as a powerful tool for the assessment of critical components of the sustainability of this particular LUS. Biophysical, socioeconomic, and management-related data on the farming systems were collected for 30 farms in Ubon Ratchathani Province, northeast Thailand. A relational database system (RDBS) was developed to manage and analyze the data. The RDBS includes a calculation procedure for the semi-automatic generation of partial nutrient balances. Partial nutrient balances are good indicators for some critical components of sustainability, and important for decision support on soil fertility management when considered with the additional factors that are required for a full nutrient balance.For the rice-based systems of 30 farms, mean partial balances were 12 kg N ha⁻¹, 8 kg P ha⁻¹, and 7 kg K ha⁻¹ per year. Large variations in partial N, P, and K balances exist among different farms and, even more so, for different land utilization types (LUTs). The LUTs are distinct cropping system–management combinations that occur down to the subfield level. Many of the partial balances assessed were negative.Farmers manage nutrients for similar parcels of land in very different ways. This results in the observed large variation in partial nutrient balances, even for the same type of land use within the same farm. These results confirm the high inter-farm and intra-farm variability for partial balances of N, P, and K of several preliminary studies. Farmer interviews and field surveys revealed that different socioeconomic factors appear to be related with inter- and intra-farm variability in nutrient budgets. In addition, the socioeconomic component of the case study revealed that diversification of income sources, particularly off-farm employment, had a larger impact on household income than rice production. Furthermore, while many less well-off households had a greater reliance on rice production, many farms with high off-farm and non-rice farm income had a higher total production of rice.The nutrient balance approach, starting with partial nutrient balances, may become an important component of a dynamic and site-specific decision support tool (DST) for nutrient management, and a relational database of the form used in this study may become a key element.     

重庆市洪涝灾害的特点、成灾机制成灾背景调查与分析

洪涝灾害是重庆较为严重的一种自然灾害，本文分析重庆市洪涝灾害特征入手，在此基础上，对重庆市洪涝灾害的成灾机制做了阐述，并从影响洪涝灾害夏季降水的主要物理因素、地形地貌背景、地表径流与水系和人为活动等方面对重庆市洪涝灾害的成灾背景进行分析，阐明了各成灾因背景之间的相互联系。     

Use of genetic algorithms to select input variables in decision tree models for the prediction of benthic macroinvertebrates

Predicting freshwater organisms based on machine learning is becoming more and more reliable due to the availability of appropriate datasets, advanced modelling techniques and the continuously increasing capacity of computers. A database consisting of measurements collected at 360 sampling sites in non-navigable watercourses in Flanders was applied to predict the absence/presence of benthic macroinvertebrate taxa by means of decision trees. The measured variables were a combination of physical–chemical (temperature, pH, dissolved oxygen concentration, conductivity, total organic carbon, Kjeldahl nitrogen and total phosphorus), structural (granulometric analysis of the sediment, width, depth and flow velocity of the river) and two ecotoxicological variables. The predictive power of decision trees was assessed on the basis of the number of Correctly Classified Instances (CCI). A genetic algorithm was introduced to compare the predictive power of different sets of input variables for the decision trees. The number of input variables was reduced from 15 to 2–8 variables without affecting the predictive power of the decision trees significantly. Furthermore, reducing the number of input variables allowed to ease the identification of general data trends.