Wildcat population density in NE Portugal: A regional stronghold for a nationally threatened felid

Population density data on depleted and endangered wildlife species are essential to assure their effective management and, ultimately, conservation. The European wildcat is an elusive and threatened species inhabiting the Iberian Peninsula, with fragmented populations and living in low densities. We fitted spatial capture–recapture models on camera-trap data, to provide the first estimate of wildcat density for Portugal and assess the most influential drivers determining it. The study was implemented in Montesinho Natural Park (NE Portugal), where we identified nine individuals, over a total effort of 3,477 trap-nights. The mean density estimate was 0.032 ± 0.012 wildcat/km², and density tended to increase with distance to humanized areas, often linked to lower human disturbance and domestic cat presence, with forest and herbaceous vegetation cover and with European rabbit abundance. Although, this density estimate is within the range of values estimated for protected areas elsewhere in the Iberian Peninsula, our estimates are low at the European level. When put in context, our results highlight that European wildcats may be living in low population densities across the Iberian Mediterranean biogeographic region. No phenotypic domestic or hybrid cats were detected, suggesting potentially low admixture rates between the two species, although genetic sampling would be required to corroborate this assertion. We provide evidence that Montesinho Natural Park may be a suitable area to host a healthy wildcat population, and thus be an important protected area in this species' conservation context.     

Modelling HIV immune response and validation with clinical data

A system of ordinary differential equations is formulated to describe the pathogenesis of HIV infection, wherein certain features that have been shown to be important by recent experimental research are incorporated in the model. These include the role of CD4+memory cells that serve as a major reservoir of latently infected cells, a critical role for T-helper cells in the generation of CD8 memory cells capable of efficient recall response, and stimulation by antigens other than HIV. A stability analysis illustrates the capability of this model in admitting multiple locally asymptotically stable (locally a.s.) off-treatment equilibria. We show that this more biologically detailed model can exhibit the phenomenon of transient viremia experienced by some patients on therapy with viral load levels suppressed below the detection limit. We also show that the loss of CD4+T-cell help in the generation of CD8+memory cells leads to larger peak values for the viral load during transient viremia. Censored clinical data is used to obtain parameter estimates. We demonstrate that using a reduced set of 16 free parameters, obtained by fixing some parameters at their population averages, the model provides reasonable fits to the patient data and, moreover, that it exhibits good predictive capability. We further show that parameter values obtained for most clinical patients do not admit multiple locally a.s off-treatment equilibria. This suggests that treatment to move from a high viral load equilibrium state to an equilibrium state with a lower (or zero) viral load is not possible for these patients.     

Coffee production in southern Saudi Arabian highlands: Current status and water conservation

Work aimed at assessing status and introducing water conservation regimes for coffee production in southern Saudi Arabian highlands. Data on farm locations, altitudes, areas, practices, irrigation, tree density, and annual coffee production were analyzed. Field experiment using chlorophyll fluorescence and different irrigation regimes was conducted to examine effects of reducing irrigation frequency on photosynthesis. Results indicated that Coffea arabica L. is commonly grown at altitudes of 1300–1400 m. Plants grown at 4–6 Trees m^?2 using 100 kg ha^?1 mineral fertilizer produce an average of 3 t ha^?1. High frequency 2-day-intervals irrigation regime practiced by farmers during the dry season presents ecological challenge to limited local artesian water resources. Changes in chlorophyll fluorescence under 14-day-intervals irrigation regime initiated water stress that markedly inhibited Photosystem II efficiency and quantum yield and increased non-photochemical energy dissipation. Applying a 7-day-intervals irrigation regime induced less inhibitory effects on Photosystem II. Results also indicated that shifting from 2-day-intervals irrigation regime to 7-day-intervals regime improves coffee agroecology and directs coffee production towards sustainability.     

An actuated dissipative spring-mass walking model: Predicting human-like ground reaction forces and the effects of model parameters

Simple models are widely used to understand the mechanics of human walking. The optimization-based minimal biped model and spring-loaded-inverted-pendulum (SLIP) model are two popular models that can achieve human-like walking patterns. However, ground reaction forces (GRF) from these two models still deviate from experimental data. In this paper, we proposed an actuated dissipative spring-mass model by integrating these two models to realize more human-like GRF patterns. We first explored the function of stiffness, damping, and weights of both energy cost and force cost in the objective function and found that these parameters have distinctly different influences on the optimized gait and GRF profiles. The stiffness and objective weight affect the number and size of peaks in the vertical GRF and stance time. The damping changes the relative size of the peaks but has little influence on stance time. Based on these observations, these parameters were manually tuned at three different speeds to approach experimentally measured vertical GRF and the highest correlation coefficient can reach 0.983. These results indicate that the stiffness, damping, and proper objective functions are all important factors in achieving human-like motion for this simple walking model. These findings can facilitate the understanding of human walking dynamics and may be applied in future biped models.     

重庆市生态风险预警等级划分及演化趋势模拟

生态风险预警等级评估和演化趋势模拟，可为生态风险管理提供可靠的辅助决策。以重庆市为研究对象，基于驱动力-压力-状态-影响-响应模型，构建重庆市生态风险预警指标体系，采用正态云模型和集对分析法，定量分析重庆市生态风险时空分异特征和演化趋势。研究结果表明：（1）2013-2019年，重庆市生态风险值呈"上升-下降"的波动趋势，综合生态风险隶属于重警等级，生态风险综合值从0.295下降到0.278，生态环境逐年好转；（2）重庆市生态风险有下降、不变、先上升后降低、先降低后上升以及一直升高5种演化趋势，分别占比39%、16%、5%、21%、24%；（3）重庆市生态风险转移分为两个方向，2013-2016年生态风险空间分异性增大，中警、轻警和无警风险等级不断向东北、东南和西部四周分散转移；2016-2019年生态风险分布格局变化较小，重警风险区在东部聚集；（4）演化趋势模拟结果表明，未来重庆市生态风险降低的区县有13个，占比34%，生态环境有向好发展的趋势；生态风险上升的区县有25个，占比66%，生态环境会有所恶化，但是恶化程度较低。将生态风险等级划分与预警演化趋势相结合，能为城市生态风险管理提供科学依据。     

Influences of temporal independence of data on modelling species distributions

Modelling species distributions has been widely used to understand present and future potential distributions of species, and can provide adaptation and mitigation information as references for conservation and management under climate change. However, various methods of data splitting to develop and validate functions of the models do not get enough attention, which may mislead the interpretation of predicted results. We used the Taiwanese endemic birds to test the influences of temporal independence of datasets on model performance and prediction. Training and testing data were considered to be independent if they were collected during different survey periods (1993–2004 and 2009–2010). The results indicated no significant differences of six model performance measures (AUC, kappa, TSS, accuracy, sensitivity, and specificity) among the combinations of training and testing datasets. Both species- and grid cell-based assessments differed significantly between predictions by the annual and pooled training data. We also found an average of 85.8% similarity for species presences and absences in different survey periods. The remaining dissimilarity was mostly caused by species observed in the late survey period but not in the early one. The method of data splitting, yielding training and testing data, is critical for resulting model species distributions. Even if similar model performance exists, different methods can lead to different species distributional maps. More attention needs to be given to this issue, especially when amplifying these models to project species distributions in a changing world.