The role of psychology in determining human–predator conflict across southern Kenya

Conflict between people and carnivores can lead to the widespread killing of predators in retaliation for livestock loss and is a major threat to predator populations. In Kenya, a large, rural, pastoralist population comes into regular conflict with predators, which persist across southern Kenya. We explored the social and psychological backdrop to livestock management practices in this area in a process designed to be easy to use and suitable for use across large areas for the study of conflict and transboundary implementation of wildlife conflict reduction measures, focusing on community involvement and needs. We carried out fully structured interviews of livestock managers with a survey tool that examined how social and psychological factors may influence livestock management behavior. We compared survey responses on 3 sites across the study area, resulting in 723 usable responses. Efficacy of individuals’ livestock management varied between and within communities. This variation was partially explained by normative and control beliefs regarding livestock management. Individual livestock managers’ self-reported management issues were often an accurate reflection of their practical management difficulties. Psychological norms, control beliefs, and attitudes differed among sites, and these differences partially explained patterns associated with conflict (i.e., variation in livestock management behavior). Thus, we conclude that a one-size-fits-all approach to improving livestock management and reducing human–predator conflict is not suitable.     

Evaluation of pay-for-release conservation incentives for unintentionally caught threatened species

In the developing world, the exploitation of threatened species jeopardizes their permanence in the wild. Because not all captures are intentional, for instance when capture methods have low selectivity, pressure on these species may be lessened by releasing living incidentally caught animals. However, it is often unrealistic to expect people to voluntarily do so because it means foregoing the benefits of resource extraction. Financial incentives for such animal release may foster conservation objectives. Reducing human–animal conflicts, protecting natural habitat, and conserving nests of threatened species are examples of conservation benefits that can be built on financial reward systems. However, incentives aiming to protect unintentionally captured threatened species are scarce. We considered pay for release, a type of ecosystem-service payment designed to foster the release of incidentally captured threatened species. We aimed to determine the best conditions to implement this scheme, its potential benefits (e.g., incentivizing the release of threatened species), and pitfalls and priority research needs (e.g., required conditions for pay for release to work) to show that its global applicability is possible. Given that approaches solely based on education and law enforcement may be ineffective under some circumstances, we argue that pay for release can protect incidentally captured endangered species if used under conditions conducive for its success. When local participants’ intrinsic motivation for conservation is weak, but the release of incidentally live-caught animals into their habitats is readily achievable, pay-for-release schemes could jump start urgently needed conservation efforts against indiscriminate animal harvesting.     

Compliance with ivory trade regulations in the United Kingdom among traders

Global demand for elephant ivory is contributing to illegal poaching and significant decline of African elephant (Loxondonta africana) populations. To help mitigate decline, countries with legal domestic ivory markets were recommended by the Convention on International Trade in Endangered Species of Wild Fauna and Flora to close domestic markets for commercial trade. However, implementing stricter regulations on wildlife trade does not necessarily mean compliance with rules will follow. Using an online questionnaire, we examined the relationship between self-reported compliance with ivory trade regulations among 115 ivory traders in the United Kingdom and 4 dimensions (control, deterrence, legitimacy, and social norms) hypothesized to influence compliance with conservation regulations. Although most traders supported regulations, a large number did not always check that they comply with them when trading objects containing ivory. The main factors influencing compliance with ivory trade regulations were traders’ ability to comply and their perceptions of the regulations and punishments to deter illegal trade. These findings demonstrate the utility of conservation criminology to improve wildlife trade regulations and identify opportunities to reduce illegal ivory entering the market in the United Kingdom. Compliance could be improved by clearer regulations that facilitate easier detection of illegal ivory products and stronger prosecution of violations.     

Evaluation of a Three‐Dimensional Hydrodynamic Model Applied to Chesapeake Bay Through Long‐Term Simulation of Transport Processes

A numerical model, the Curvilinear Hydrodynamics in 3‐Dimensions, Waterway Experiment Station version (CH3D‐WES), was applied to represent transport processes of the Chesapeake Bay. Grid resolution and spatial coverage, tied with realistic bathymetry, ensured dynamic responses along the channel and near the shoreline. The model was run with the forcing ranges from high frequency astronomical tides to lower frequency meteorological forcing, given by surface wind and heat flux, as well as hydrological forcing given by fresh water inflows both from upstream and distributed sources along the shoreline. To validate the model, a long‐term simulation over seven‐year time period between 1994 and 2000 was performed. The model results were compared with existing observation data including water level time series, which spans over a wide spectrum of time scales, and long‐term variations in salinity structures over varying parts of the Bay. The validated model is set to provide an appropriate transport mechanism to the water quality model through linkage, warranting that the model takes into account the complexity in time and spatial scales associated with the dynamic processes in the Chesapeake.     

Application of Neural Networks in Active Noise Reduction Systems

Active noise reduction systems based on a control unit in the form of a finite impulse response filter assume the linearity of every single component. Neural networks, which have so far been seldom used in this field, are a kind of a filter with the ability to project nonlinear characteristics of an active noise reduction system. This paper presents some simulation research studies of active noise reduction systems based on neural networks. Also presented are results of the operation of systems with different levels of complexity as well as the influence of different parameters of a neural network and of the system itself on those results.     

大气硝酸测量方法研究进展

大气中硝酸(HNO3)的生成是排放到空气中氮氧化物(NOx)的主要沉降途径,对降水酸化、二次细颗粒物中硝酸盐的形成以及在研究光化学污染和霾形成等大气复合污染过程之间的联系中具有重要作用.获得高时间分辨率、准确的大气HNO3测量数据对研究和认识大气中NOx的循环机理是十分必要和迫切的.大气中的HNO3浓度低且具有很强的吸...     

三种常用氨基甲酸酯类农药人工抗原合成方法的设计与优选

农药人工抗原的合成直接影响制备抗体的质量,是建立农药分子特异性强、灵敏度高的免疫分析方法的关键。本文综述了国内外对于氨基甲酸酯类广泛使用的3种农药甲萘威、克百威、涕灭威人工抗原合成过程中的农药分子半抗原的设计原则、合成方法,人工抗原的设计、优选及影响因素等方面的研究进展。     

安规实验室仪器期间核查基本方法研究

本文介绍期间核查的作用,要素,结果的判定,从而认识安规实验室仪器期间核查的基本方法与意义,对安规实验室仪器的期间核查的运用有进一步了解和帮助。     

The Impact of Asynchronicity on Event‐Flow Estimation in Basin‐Scale Hydrologic Model Calibration1

Abstract: The calibration of basin‐scale hydrologic models consists of adjusting parameters such that simulated values closely match observed values. However, due to inevitable inaccuracies in models and model inputs, simulated response hydrographs for multiyear calibrations will not be perfectly synchronized with observed response hydrographs at the daily time step. An analytically derived formula suggests that when timing errors are significant, traditional calibration approaches may generally underestimate the total event‐flow volume. An event‐adaptive time series is developed and incorporated into the Nash‐Sutcliffe Efficiency objective function to diagnose the potential impact of event‐flow synchronization errors. Test sites are the 50 km² Subwatershed I of the Little River Experimental Watershed (LREWswI) in southeastern Georgia, and the 610 km² Little Washita River Experimental Watershed (LWREW) in southwestern Oklahoma, with the Soil and Water Assessment Tool used as the hydrologic model. Results suggest that simulated surface runoff generation is 55% less for LREWswI when the daily time series is used compared with when the event‐adaptive technique is used. Event‐flow generation may also be underestimated for LWREW, but to a lesser extent than it may be for LREWswI, due to a larger portion of the event flow being lateral flow.     

Assessing Linkages in Stream Habitat,Geomorphic Condition,and Biological Integrity Using a Generalized Regression Neural Network

Watershed managers often use physical geomorphic and habitat assessments in making decisions about the biological integrity of a stream, and to reduce the cost and time for identifying stream stressors and developing mitigation strategies. Such analysis is difficult since the complex linkages between reach‐scale geomorphic and habitat conditions, and biological integrity are not fully understood. We evaluate the effectiveness of a generalized regression neural network (GRNN) to predict biological integrity using physical (i.e., geomorphic and habitat) stream‐reach assessment data. The method is first tested using geomorphic assessments to predict habitat condition for 1,292 stream reaches from the Vermont Agency of Natural Resources. The GRNN methodology outperforms linear regression (69% vs. 40% classified correctly) and improves slightly (70% correct) with additional data on channel evolution. Analysis of a subset of the reaches where physical assessments are used to predict biological integrity shows no significant linear correlation, however the GRNN predicted 48% of the fish health data and 23% of macroinvertebrate health. Although the GRNN is superior to linear regression, these results show linking physical and biological health remains challenging. Reasons for lack of agreement, including spatial and temporal scale differences, are discussed. We show the GRNN to be a data‐driven tool that can assist watershed managers with large quantities of complex, nonlinear data.