Using occupancy models to determine mammalian responses to landscape changes

Determining impacts of anthropogenic landscape changes on wildlife populations is difficult.Besides the challengesDetermining impacts of anthropogenic landscape changes on wildlife populations is difficult.Besides the challenges of designing field studies to document conditions before and after landscape changes occur,assessment of popula-of designing field studies to document conditions before and after landscape changes occur,assessment of popula-tion responses(e.g.changes in population density)often provide poor inference because of sampling limitations.tion responses(e.g.changes in population density)often provide poor inference because of sampling limitations.Estimation of occupancy,however,only requires data on detection or non-detection of a species and might provideEstimation of occupancy,however,only requires data on detection or non-detection of a species and might provide better inference.To demonstrate the utility of occupancy models,we used data from an American black bear(Ursusbetter inference.To demonstrate the utility of occupancy models,we used data from an American black bear(Ursus americanus Pallas)population in North Carolina,USA to test our research hypothesis that documented declines inamericanus Pallas)population in North Carolina,USA to test our research hypothesis that documented declines in site occupancy of black bears would be greater near a new four-lane highway.We used multi-season occupancysite occupancy of black bears would be greater near a new four-lane highway.We used multi-season occupancy models to estimate site occupancy based on bear visitation to survey sites before and after completion of the newmodels to estimate site occupancy based on bear visitation to survey sites before and after completion of the new highway and as a function of distance to the highway.Site occupancy declined from 0.81 to 0.35 between the twohighway and as a function of distance to the highway.Site occupancy declined from 0.81 to 0.35 between the two study phases,but was not a function of distance to the highway.Therefore,the impact of the new highway onstudy phases,but was not a function of distance to the highway.Therefore,the impact of the new highway on occupancy extended to the entire study area.Our case study demonstrates that occupancy models can provideoccupancy extended to the entire study area.Our case study demonstrates that occupancy models can provide powerful inference regarding the potential impacts of landscape changes on species occupancy.As urban areas andpowerful inference regarding the potential impacts of landscape changes on species occupancy.As urban areas and transportation infrastructure are rapidly expanding in developing regions of the world,the need to determine howtransportation infrastructure are rapidly expanding in developing regions of the world,the need to determine how these changes affect mammal populations and how they might be mitigated increases accordingly.Because fieldthese changes affect mammal populations and how they might be mitigated increases accordingly.Because field sampling for occupancy models only requires detection data,surveys can be conducted for extensive geographicsampling for occupancy models only requires detection data,surveys can be conducted for extensive geographic areas,thus making these surveys particularly applicable to studies of large mammals.areas,thus making these surveys particularly applicable to studies of large mammals.

Development of Job Burden-capital Model of Occupational Stress： An Exploratory Study

这研究在职业应力上为全面评价作为工作负担首都模型建议一个新框架。1618 件有效样品被自我评估的问询表在书面允许以后在湖南省从电子生产服务工业招募。结构的方程模型分析被采用由收集的数据验证模型。最后的适合模型有令人满意的恰当的美德(CMIN/DF=5.78， AGFI=0.937， NNFI=0.960， IFI=0.968， RMSEA=0.054 ) 。两个都，测量，模型和结构的模型有可接受的路径装载。工作负担和资本也能直接影响职业结果或间接地通过个性影响他们。多组结构的方程模型分析显示模型的一般适用性到如此的人口的基本特征。工作负担首都模型在职业应力上为更深入的学习开创新地平线。

Modelling method of inter-building movement for campus-scale occupancy simulation:A case study

As an important factor in the investigation of building energy consumption,occupant behavior(OB)has been widely studied on the building level.However so far,studies of OB modelling on the district scale remain limited.Indeed,district-scale OB modelling has been facing the challenges from the scarcity of district-scale data,modelling methods,as well as simulation application.This study initiates the extrapolation of occupancy modelling methodology from building level to district scale through proposing modelling methods of inter-building movements.The proposed modelling methods utilize multiple distribution fittings and Bayesian network to upscale the event description methods from inter-zone movement events at the building level to inter-building movement events at the district level.This study provides a framework on the application of the proposed modelling methods for a university campus in the suburbs of Shanghai,taking advantages of data sensing,monitoring and survey techniques.With the collected campus-scale occupancy data,this paper defines five patterns of inter-building movement.One pattern represents the dominated inter-building movement events for one kind of students in their daily campus life.Based on the quantitative descriptions for various inter-building movement events,this study performs the stochastic simulation for the campus district,using Markov chain models.The simulation results are then validated with the campus-scale occupancy measurement data.Furthermore,the impact of inter-building movement modelling methods on building energy demand is evaluated for the library building,taking the deterministic occupancy schedules suggested by current building design standard as a baseline.

Modelling method for air-conditioning usage behavior in multi-occupant office space based on group decision-making strategy

Occupant behavior largely influence the energy use within buildings.In the multi-occupant office,occupant behavior is affected by individual preference as well as the interaction among occupants,and yet no suitable model is available to precisely reflect the behavior characteristics.This paper proposed and introduced a method for innovative multi-occupant air-conditioning(AC)usage behavior modelling in a multi-occupant office,which used intuitionistic fuzzy preference relationship to describe individual behavior intention and a hierarchical structure to reflect the social relationship among multiple occupants through subjective evaluation method.The group decision-making process combined the individual behavior intention and the weights of occupants using the analytic hierarchy process.Then,the AC usage behavior of a multi-occupant office was simulated by integrating the multi-occupant model into designer’s simulation toolkit(DeST)building performance simulation software.The results of conducted analysis of a single office with multi-occupant showed that the proposed multi-occupant modelling method could quantitatively characterize the group relationships and AC usage behavior patterns.The absolute errors for the total AC operation time and frequency of the start-up periods of AC between the simulation and measurement results were only 2.7%and 2.0%,respectively.Thus,the proposed multi-occupant modelling method could realize a relatively accurate simulation of the multi-occupant behavior.

Review on occupancy detection and prediction in building simulation

Energy simulation results for buildings have significantly deviated from actual consumption because of the uncertainty and randomness of occupant behavior.Such differences are mainly caused by the inaccurate estimation of occupancy in buildings.Therefore,the error between reality and prediction could be largely reduced by improving the accuracy level of occupancy prediction.Although various studies on occupancy have been conducted,there are still many differences in the approaches to detection,prediction,and validation.Reports published within this domain are reviewed in this article to discover the advantages and limitations of previous studies,and gaps in the research are identified for future investigation.Six methods of monitoring and their combinations are analyzed to provide effective guidance in choosing and applying a method.The advantages of deterministic schedules,stochastic schedules,and machine-learning methods for occupancy prediction are summarized and discussed to improve prediction accuracy in future work.Moreover,three applications of occupancy models—improving building simulation software,facilitating building operation control,and managing building energy use—are examined.This review provides theoretical guidance for building design and makes contributions to building energy conservation and thermal comfort through the implementation of intelligent control strategies based on occupancy monitoring and prediction.

Amphibian richness along modified riparian areas of central Mexico:conservation priorities

Background:Land‑use change frequently affects faunistic populations and communities.To achieve successful conservation strategies,we need suitable information about species distribution and the causes of extinction risk.Many amphibian species depend on riparian vegetation to complete their life cycles.About 41%of amphibian species are globally threatened,and accurate estimations of population size,species richness and the identification of critical habitats are urgently needed worldwide.To evaluate the magnitude of changes in species richness and demography,estimations that include detection probability are necessary.In this study,we employed multi‑species occupancy models to estimate detection probability and the effect of land cover type(i.e.,cropland,artificial pasture,secondary and mature forest)in a 500‑m radius on the occupancy probability and richness of diurnal amphibians in 60 riparian zones in the state of Michoacán in central Mexico.Furthermore,we evaluated the potential of the endemic salamander Ambystoma ordinarium as a flagship species for the conservation of other native amphibian species.Results:We registered a total of 20 amphibian species in the diurnal assemblage,of which 10 species are considered at risk of extinction.We found that cropland was the most important land‑use type for explaining amphibian distribu‑tion in riparian zones,with negative effects on most amphibian species.We found no differences in species richness between zones with and without A.ordinarium.In riparian zones occupied by A.ordinarium,however,we found a higher number of species at risk of extinction.Conclusions:Our findings showed negative effects of croplands on the distribution of most amphibian species.The riparian zones are important for the maintenance of native diurnal amphibian communities and A.ordinarium can act as a flagship species for the conservation of threatened amphibian species.