Evaluating and expanding the European Union's protected-area network toward potential post-2020 coverage targets

The Convention on Biological Diversity's (CBD) strategic plan will expire in 2020, but biodiversity loss is ongoing. Scientists call for more ambitious targets in the next agreement. The nature-needs-half movement, for example, has advocated conserving half of Earth to solve the biodiversity crisis, which has been translated to protecting 50% of each ecoregion. We evaluated current protection levels of ecoregions in the territory of one of the CBD's signatories, the European Union (EU). We also explored the possible enlargement of the Natura 2000 network to implement 30% or 50% ecoregion coverage in the EU member states’ protected area (PA) network. Based on the most recent land-use data, we examined whether ecoregions have enough natural area left to reach such high coverage targets. We used a spatially explicit mixed integer programing model to estimate the least-cost expansion of the PA network based on 3 scenarios that put different emphasis on total conservation cost, ecological representation of ecosystems, or emphasize an equal share of the burden among member states. To realize 30% and 50% ecoregion coverage, the EU would need to add 6.6% and 24.2%, respectively, of its terrestrial area to its PA network. For all 3 scenarios, the EU would need to designate most recommended new PAs in seminatural forests and other semi- or natural ecosystems. Because 15 ecoregions did not have enough natural area left to implement the ecoregion-coverage targets, some member states would also need to establish new PAs on productive land, allocating the largest share to arable land. Thirty percent ecoregion coverage was met by protecting remaining natural areas in all ecoregions except 3, where productive land would also need to be included. Our results support discussions of higher ecoregions protection targets for post-2020 biodiversity frameworks.     

Audience effect alters male but not female mating preferences

Males often face strong mating competition by neighboring males in their social environment. A recent study by Plath et al. (Anim Behav 75:21–29, 2008a) has demonstrated that the visual presence of a male competitor (i.e., an audience male) affects the expression of male mating preferences in a poeciliid fish (Poecilia mexicana) with a weaker expression of mating preferences when an audience male observed the focal male. This may be a tactic to reduce sperm competition, since surrounding males likely share intrinsic preferences for female traits or copy mate choice decisions. Here, we examined the hypothesis that a same-sex audience would affect female mate preferences less than male mating preferences. Our hypothesis was based on the assumptions that (1) competition for mates in a fashion that would be comparable in strength to sperm competition or overt male–male aggression is absent among Poecilia females, and (2) P. mexicana females typically form female-biased shoals, such that almost any female mate choice in nature occurs in front of a female audience. Poecilia females (P. mexicana, surface and cave form, and the closely related gynogenetic Poecilia formosa) were given a choice between a large and a small male, and the tests were repeated while a conspecific, a heterospecific, or no audience female (control) was presented. Females spent more time in the neutral zone and, thus, less time near the males during the second part of a trial when an audience was presented, but—consistent with predictions—females showed only slightly weaker expression of mate preferences during the second part of the tests. This decline was not specific to the treatment involving an audience and was significantly weaker than the effect seen in the male sex.     

Animal social networks: an introduction

Network analysis has a long history in the mathematical and social sciences and the aim of this introduction is to provide a brief overview of the potential that it holds for the study of animal behaviour. One of the most attractive features of the network paradigm is that it provides a single conceptual framework with which we can study the social organisation of animals at all levels (individual, dyad, group, population) and for all types of interaction (aggressive, cooperative, sexual etc.). Graphical tools allow a visual inspection of networks which often helps inspire ideas for testable hypotheses. Network analysis itself provides a multitude of novel statistical tools that can be used to characterise social patterns in animal populations. Among the important insights that networks have facilitated is that indirect social connections matter. Interactions between individuals generate a social environment at the population level which in turn selects for behavioural strategies at the individual level. A social network is often a perfect means by which to represent heterogeneous relationships in a population. Probing the biological drivers for these heterogeneities, often as a function of time, forms the basis of many of the current uses of network analysis in the behavioural sciences. This special issue on social networks brings together a diverse group of practitioners whose study systems range from social insects over reptiles to birds, cetaceans, ungulates and primates in order to illustrate the wide-ranging applications of network analysis. This contribution is part of the special issue “Social Networks: new perspectives” (Guest Editors: J. Krause, D. Lusseau and R. James).     

基于物联网林区火险监警系统方案的探讨

利用传感技术、卫星定位、地理信息、人工智能等物联网相关技术,设计适用于城市森林、自然保护区、旅游景区等环境防火监测系统,系统可对监测区域环境因素尤其火情信息实现区域覆盖、全天候、数字化监测,构建起数字化森林物联网络,可为森林防火提供实时、准确、科学的依据。     

基于数据融合的风机风量值无线监测技术研究

为了解决主要通风机在测风量过程中在线实时监测等问题,建立了以无线传输技术为基础的三层传输系统框架,并将改进的数据融合算法引入到风量值数据处理当中,通过选取阙值区间利用二次曲线函数来消除阙值点处相互支持的模糊性,取得最优融合传感器组,并对实测数据进行抗干扰实验分析。实验结果表明,无线传输方式有利于风量数据的在线实时监测;改进的数据融合算法能及时有效地消除传感器的测量偏差、提高风量数据的测量精确度。研究结果对煤矿主要通风机风量在线远程监测具一定的理论价值和实用意义。     

基于灰色模型和模糊神经网络的综合水质预测模型研究

水质状态变化趋势预测研究对水资源管理和维护具有重要的现实意义。提出了一种将灰色模型和模糊神经网络相结合的水质预测模型。首先基于改进的灰色模型预测出水体中各理化因子在未来一段时间内的指标变化,然后采用T-S模糊神经网络对各单因子的预测值进行数据融合,构建水质变化综合趋势预测模型,预测出下一时间段的水质整体状态指标。实验表明,这种方式用来预测湖泊水质变化趋势具有可行性;与BP网络模型相比,基于T-S模糊神经网络系统的模型具有预测精度高、模型系统稳定等优越性。     

'All hazards approach' to disaster management: the role of information and knowledge management, Boyd's OODA Loop, and network-centricity

The ever-increasing complexity of disasters demands utilisation of knowledge that exists outside domains traditionally drawn upon in disaster management. To be operationally useful, such knowledge must he extracted, combined with information generated by the disaster itself, and transformed into actionable knowledge. The process, though, is hampered by existing, business-oriented approaches to knowledge management, by technical issues related to access to relevant, multi-domain information/knowledge, and by executive decision-making processes based predominantly on historical knowledge. Consequently, as shown by many recent incidents, the management of large-scale (mega) disasters is often inefficient and exceedingly costly. This paper demonstrates that the integration of modified information and knowledge management into the concepts of network-centric operations and network-enabled capabilities, and the employment of Boyd's OODA (Observe, Orient, Decide, and Act) Loop-based decision-making in unpredictable and dynamically changing environments, may address some of these problems.     

岩石变形破裂过程中电荷感应信号的检测

设计了采用非接触方式、高放大倍数、高效率的电荷传感器,并给出了电荷传感器的设计原理和技术指标。利用研制的电荷传感器对岩石变形破裂过程中产生的电荷感应信号进行了检测试验。结果表明,岩石在变形破裂过程中会产生电荷感应信号,并能够被研制的电荷传感器检测到;电荷感应信号是瞬时脉冲的;随着加载应力水平的增加,电荷感应信号强度增强,在峰值应力前,电荷感应信号强度达到最大值;在破裂面接收到的电荷感应信号较强,主破裂面接收到的信号最强,因而电荷的产生和岩石的破裂有很大的关系。作为正在探索的检测岩石破坏过程的手段之一,电荷感应方法应是一种很具潜力的方法,值得深入研究。     

Review and comparison of methods to study the contribution of variables in artificial neural network models

Convinced by the predictive quality of artificial neural network (ANN) models in ecology, we have turned our interests to their explanatory capacities. Seven methods which can give the relative contribution and/or the contribution profile of the input factors were compared: (i) the ‘PaD’ (for Partial Derivatives) method consists in a calculation of the partial derivatives of the output according to the input variables; (ii) the ‘Weights’ method is a computation using the connection weights; (iii) the ‘Perturb’ method corresponds to a perturbation of the input variables; (iv) the ‘Profile’ method is a successive variation of one input variable while the others are kept constant at a fixed value; (v) the ‘classical stepwise’ method is an observation of the change in the error value when an adding (forward) or an elimination (backward) step of the input variables is operated; (vi) ‘Improved stepwise a’ uses the same principle as the classical stepwise, but the elimination of the input occurs when the network is trained, the connection weights corresponding to the input variable studied is also eliminated; (vii) ‘Improved stepwise b’ involves the network being trained and fixed step by step, one input variable at its mean value to note the consequences on the error. The data tested in this study concerns the prediction of the density of brown trout spawning redds using habitat characteristics. The PaD method was found to be the most useful as it gave the most complete results, followed by the Profile method that gave the contribution profile of the input variables. The Perturb method allowed a good classification of the input parameters as well as the Weights method that has been simplified but these two methods lack stability. Next came the two improved stepwise methods (a and b) that both gave exactly the same result but the contributions were not sufficiently expressed. Finally, the classical stepwise methods gave the poorest results.     

有机化合物厌氧生物降解性的测定和预测

测定有机物厌氧生物降解性的方法包括非特性参数和特性参数测定法。本文着重介绍有机物厌氧生物降解性的筛选测定法，以基团贡献法为基础，不外加其它理化参数的有机物结构与生物降解性关系的预测已经由简单的线性模型发展至专家系统和人工神经网络模型，并显示出极好的应用前景。