Effects of Weighting Schemes on the Identification of Wildlife Corridors Generated with Least‐Cost Methods

The importance of movement corridors for maintaining connectivity within metapopulations of wild animals is a cornerstone of conservation. One common approach for determining corridor locations is least‐cost corridor (LCC) modeling, which uses algorithms within a geographic information system to search for routes with the lowest cumulative resistance between target locations on a landscape. However, the presentation of multiple LCCs that connect multiple locations generally assumes all corridors contribute equally to connectivity, regardless of the likelihood that animals will use them. Thus, LCCs may overemphasize seldom‐used longer routes and underemphasize more frequently used shorter routes. We hypothesize that, depending on conservation objectives and available biological information, weighting individual corridors on the basis of species‐specific movement, dispersal, or gene flow data may better identify effective corridors. We tested whether locations of key connectivity areas, defined as the highest 75th and 90th percentile cumulative weighted value of approximately 155,000 corridors, shift under different weighting scenarios. In addition, we quantified the amount and location of private land that intersect key connectivity areas under each weighting scheme. Some areas that appeared well connected when analyzed with unweighted corridors exhibited much less connectivity compared with weighting schemes that discount corridors with large effective distances. Furthermore, the amount and location of key connectivity areas that intersected private land varied among weighting schemes. We believe biological assumptions and conservation objectives should be explicitly incorporated to weight corridors when assessing landscape connectivity. These results are highly relevant to conservation planning because on the basis of recent interest by government agencies and nongovernmental organizations in maintaining and enhancing wildlife corridors, connectivity will likely be an important criterion for prioritization of land purchases and swaps. Efectos de los Esquemas de Ponderación sobre la Identificación de Corredores para Vida Silvestre Generados con Métodos Menos Costosos     

Ecological correlates of duckling adoption among white-winged scoters Melanitta fusca: strategy, epiphenomenon, or combination?

Young waterfowl can frequently join foster females shortly after hatch, resulting in post-hatch brood amalgamation. Much uncertainty remains about physiological or ecological factors that motivate adoption including potential costs and benefits to fostered offspring as well as to females that either lose or accept young. Several hypotheses have been put forth to explain adoption. In this paper, we examine the salvage strategy (SSH) and accidental-mixing (AMH) hypotheses. According to the SSH, females abandon or lose their young due to substantial energetic constraints from incubation and brood rearing. The AMH posits that adoption results from local ecological conditions on breeding areas (i.e., adverse weather conditions, high brood densities) which act to separate offspring and mothers. We used multistate modeling to estimate relationships between probabilities of adoption by white-winged scoter (Melanitta fusca) ducklings from natal to foster females and a set of hypothesized ecological covariates. Results showed that most adoption occurred within 6 days of hatch; additionally, likelihood of adoption was positively related to inclement weather and negatively related to hatch date, size, and condition of natal females, and duckling condition. We conclude that adoption in this population is consistent with both the salvage strategy and accidental-mixing hypotheses. Ultimately, we suggest that adoption in our study population was foremost an outcome of intense gull predation but also of local environmental conditions.     

Modeling the Effect of Climate Change on the Distribution of Oak and Pine Species of Mexico

Abstract:  We examined the vulnerability of 34 species of oaks ( Quercus ) and pines ( Pinus ) to the effects of global climate change in Mexico. We regionalized the HadCM2 model of climate change with local climatic data (mean annual temperature and rainfall) and downscaled the model with the inverse distance-weighted method. Databases of herbaria specimens, genetic algorithms (GARP), and digital covers of biophysical variables that affect oaks and pines were used to project geographic distributions of the species under a severe and conservative scenario of climate change for the year 2050. Starting with the current average temperature of 20.2 °C and average precipitation of 793 mm, under the severe warming scenario mean temperature and precipitation changed to 22.7 °C and 660 mm, respectively, in 2050. For the conservative warming scenario, these variables shifted to 21.8 °C and 721 mm. Responses to the different scenarios of climate change were predicted to be species-specific and related to each species climate affinity. The current geographic distribution of oaks and pines decreased 7–48% and 0.2–64%, respectively. The more vulnerable pines were Pinus rudis , P. chihuahuana , P. oocarpa , and P. culminicola , and the most vulnerable oaks were Quercus crispipilis , Q. peduncularis , Q. acutifolia , and Q. sideroxyla . In addition to habitat conservation, we think sensitive pine and oak species should be looked at more closely to define ex situ strategies (i.e., seed preservation in germplasm banks) for their long-term conservation. Modeling climatic-change scenarios is important to the development of conservation strategies.     

Assessing the effects of pseudo-absences on predictive distribution model performance

Modelling species distributions with presence data from atlases, museum collections and databases is challenging. In this paper, we compare seven procedures to generate pseudo-absence data, which in turn are used to generate GLM-logistic regressed models when reliable absence data are not available. We use pseudo-absences selected randomly or by means of presence-only methods (ENFA and MDE) to model the distribution of a threatened endemic Iberian moth species (Graellsia isabelae). The results show that the pseudo-absence selection method greatly influences the percentage of explained variability, the scores of the accuracy measures and, most importantly, the degree of constraint in the distribution estimated. As we extract pseudo-absences from environmental regions further from the optimum established by presence data, the models generated obtain better accuracy scores, and over-prediction increases. When variables other than environmental ones influence the distribution of the species (i.e., non-equilibrium state) and precise information on absences is non-existent, the random selection of pseudo-absences or their selection from environmental localities similar to those of species presence data generates the most constrained predictive distribution maps, because pseudo-absences can be located within environmentally suitable areas. This study shows that if we do not have reliable absence data, the method of pseudo-absence selection strongly conditions the obtained model, generating different model predictions in the gradient between potential and realized distributions.     

洞庭湖区农业环境与湖垸农业可持续发展模式

围湖垦殖形成了洞庭湖区湖垸农业形式,湖垸农业的形成加速了湖区人口的增长,人口的压力也促进了围垦。不断的围湖垦殖使耕地面积迅速增加。由于湖泊面积减少,湖垸农业处于外洪内涝的环境中。归纳了洞庭湖区的农业环境问题：洪涝灾害发生频率加大;水面减少,生物多样性降低;环境污染严重,湿地生态功能衰退;土壤退化和潜育化严重;血吸虫病死灰复燃等。结合已有经验,提出了湖垸农业可持续发展模式：认真实施生态保护工程,减少泥沙淤积;调整湖垸农业结构,建立可持续发展生态农业模式：避灾、减灾模式、水生经济植物模式、工业原料作物模式、林农复合经营模式、湖洲草地草食畜禽模式、麻基（油菜）渔塘农业模式等。     

深圳市高层建筑地震安全指数判定系统

以深圳市高层建筑为研究实例,介绍了香港大学的城市灾害损失评估及应急反应管理系统,并采用此系统内置的建筑易损性分析模块,结合泛珠三角地区灾害危险性概率模式,场地特征及高层建筑实地调查分析结果,从建筑安全性角度对深圳市的标志性建筑进行危险性分析,进而对深圳市应对突发性灾难事件的管理建设提出建议。作为应用实例,模拟一定概率条件下的灾难事件发生时的建筑物损坏情况,归纳出高层建筑的损坏模式,总结深圳市高层建筑的安全性隐患,提出目前防灾减灾急需实施的相应步骤:建议在一元化的城市灾害预警和应急指挥体系下,整合各个灾种防灾减灾管理部门的资源,以科学分析软件为灾情模拟和决策预案制定的工具,使危机处理的理念由领导决策型转向科学分析型,加强城市应对面对突发事件的能力,保障经济与社会的持续稳定发展。     

Modeling individual and population dynamics in a consumer–resource system: Behavior under food limitation and crowding and the effect on population cycling in Daphnia

In population modeling, a considerable level of complexity is often required to provide trustworthy results, comparable with field observations. By assuring sufficient detail at the individual level while preserving the potential to explore the consequences at higher levels, individual-based modeling may thus provide a useful tool to investigate dynamics at different levels of organization. Still, population dynamics resulting from such models are often at odds with observations from the field. This may be partly caused by a lack of focus on the individual dynamics under conditions of food stress and starvation. I developed a physiologically structured, individual-based simulation model to investigate life history of Daphnia and its effect on population dynamics in response to the productivity of the system. In verifying model behavior with available literature data on life history and physiology, I paid special attention to the dynamics of food intake and the verification of individual level results under conditions of food limitation and starvation. I show that the maximum filtering rates under low food levels used in the current model are much closer to measured filtering rates than the ones used in other models. Being consistent with results on physiology and life history from experiments at a wide range of food availability (including starvation), the model generates low amplitude or high amplitude population density cycles depending on the productivity of the system, as observed in field and experimental populations of Daphnia and with the minimum population densities being one to two orders of magnitude lower in the high amplitude than in the low amplitude cycles. To generate results which are not only qualitatively but also quantitatively comparable to experimental and field observations, however, a crowding effect on the filtering response has to be incorporated in the model.     

On the use of growth rate parameters for projecting population sizes: Application to aphids

This paper extends the application of the cumulative size based mechanistic model, which has previously been shown to describe diverse aphid population size data well. The mechanistic model is reviewed with a focus on the explanatory role of the birth and death rate formulation. An analysis of two data sets, one on the mustard aphid and the other on the pecan aphid, indicates that multiple linear regression equations based on the estimated birth and death rate parameters alone account for nearly all (R² > 0.95) of the variability in two key population attributes, namely the peak count and the cumulative density. This indicates that population size variables may be projected directly from the growth rate parameters using linear equations. Such linear relationships based on the birth and death rate parameters are shown to hold also for certain generalized mechanistic models for which the analytical solution is not available. The birth and death rate coefficients, therefore, constitute a new succinct set of variables that could be included in the predictive modeling of aphid populations, as well as other insect and animal populations with local collapse which follow similar growth dynamics.     

Closed population estimation models and their extensions in Program MARK

Program MARK provides > 65 data types in a common configuration for the estimation of population parameters from mark-encounter data. Encounter information from live captures, live resightings, and dead recoveries can be incorporated to estimate demographic parameters. Available estimates include survival (S or ϕ), rate of population change (λ), transition rates between strata (Ψ), emigration and immigration rates, and population size (N). Although N is the parameter most often desired by biologists, N is one of the most difficult parameters to estimate precisely without bias for a geographically and demographically closed population. The set of closed population estimation models available in Program MARK incorporate time (t) and behavioral (b) variation, and individual heterogeneity (h) in the estimation of capture and recapture probabilities in a likelihood framework. The full range of models from M ₀ (null model with all capture and recapture probabilities equal) to M _tbh are possible, including the ability to include temporal, group, and individual covariates to model capture and recapture probabilities. Both the full likelihood formulation of Otis et al. (1978) and the conditional model formulation of Huggins (1989, 1991) and Alho (1990) are provided in Program MARK, and all of these models are incorporated into the robust design (Kendall et al. 1995, 1997; Kendall and Nichols 1995) and robust-design multistrata (Hestbeck et al. 1991, Brownie et al. 1993) data types. Model selection is performed with AICc (Burnham and Anderson 2002) and model averaging (Burnham and Anderson 2002) is available in Program MARK to provide estimates of N with standard error that reflect model selection uncertainty.