A stochastic model for estimating sustainable limits to wildlife mortality in a changing world

Human-caused mortality of wildlife is a pervasive threat to biodiversity. Assessing the population-level impact of fisheries bycatch and other human-caused mortality of wildlife has typically relied upon deterministic methods. However, population declines are often accelerated by stochastic factors that are not accounted for in such conventional methods. Building on the widely applied potential biological removal (PBR) equation, we devised a new population modeling approach for estimating sustainable limits to human-caused mortality and applied it in a case study of bottlenose dolphins affected by capture in an Australian demersal otter trawl fishery. Our approach, termed sustainable anthropogenic mortality in stochastic environments (SAMSE), incorporates environmental and demographic stochasticity, including the dependency of offspring on their mothers. The SAMSE limit is the maximum number of individuals that can be removed without causing negative stochastic population growth. We calculated a PBR of 16.2 dolphins per year based on the best abundance estimate available. In contrast, the SAMSE model indicated that only 2.3–8.0 dolphins could be removed annually without causing a population decline in a stochastic environment. These results suggest that reported bycatch rates are unsustainable in the long term, unless reproductive rates are consistently higher than average. The difference between the deterministic PBR calculation and the SAMSE limits showed that deterministic approaches may underestimate the true impact of human-caused mortality of wildlife. This highlights the importance of integrating stochasticity when evaluating the impact of bycatch or other human-caused mortality on wildlife, such as hunting, lethal control measures, and wind turbine collisions. Although population viability analysis (PVA) has been used to evaluate the impact of human-caused mortality, SAMSE represents a novel PVA framework that incorporates stochasticity for estimating acceptable levels of human-caused mortality. It offers a broadly applicable, stochastic addition to the demographic toolbox to evaluate the impact of human-caused mortality on wildlife.     

高原生境不同水力停留时间下A2/O工艺活性污泥微生物代谢机制研究

在高原生境下构建不同水力停留时间(HRT)运行工况的A²/O系统,结合水质分析及对好氧池活性污泥的16S rRNA基因测序,对微生物优势菌属功能和代谢途径进行研究。结果表明:高原生境下HRT为26.25 h时A²/O工艺处理效果总体最好,微生物优势菌属代谢功能以有机物降解、反硝化脱氮和聚磷菌除磷为主,代谢途径以碳氮磷代谢为主;在高原生境下,应对外界环境变化的细菌双组分调节功能(ko02020)丰度较大,该代谢途径在适应环境变化中有显著作用,是高原生境下的优势代谢途径;微生物细胞中rpoE基因丰度偏大,为微生物适应高原环境提供了保障。HRT为26.25 h时微生物功能基因总丰度最大,可见26.25 h是高原生境下A²/O工艺最佳HRT运行工况。     

静脉产业类生态工业园区标准的研究

以静脉产业和静脉产业类生态工业园区的基本概念为基础,深入分析了我国建立静脉产业类生态工业园区标准的重要意义. 选取经济发展、资源循环与利用、污染控制和园区管理4个方面共20个指标,构成静脉产业类生态工业园区评价指标体系,旨在全面、准确地反映静脉产业类生态工业园区的建设水平. 经过综合分析,确定采用层次分析(AHP)法对评价指标体系进行权重计算. 根据权重分析结果可得出如下结论:静脉产业类生态工业园区的建设重点应为提高资源循环利用率和保障环境安全,污染控制以固体废物的安全处置为主. 最后,对该评价指标体系进行了可行性分析,该方法所设定的各项指标在经济上、技术上、可操作性上都是可行的. 依据该评价方法,制定了国家《静脉产业类生态工业园区标准》.      

纸基复合包装中铝塑分离的湿法工艺条件研究

纸基复合包装中的纸基部分通过水力碎浆分离后可直接用于生产再生纸. 其铝塑部分由1层0.02～0.03 mm厚的铝箔和2层0.03～0.08 mm厚的低密度聚乙烯膜层压复合而成,主要对铝塑的湿法分离进行研究.比较了甲酸、乙酸、盐酸3种剥离剂的分离效果; 用甲酸作为铝塑剥离剂时, 考察了剥离剂的浓度、反应温度、液固比及破碎尺寸对铝塑分离的影响; 根据铝塑分离时间、分离率、铝的损失率等指标,通过正交试验及方差分析优化铝塑分离的工艺条件. 结果表明,甲酸分离铝塑的最优条件: 剥离剂浓度为4 mol/L, 反应温度为60 ℃,液固比为60 L/kg, 破碎尺寸为5 cm×5 cm. 在该条件下, 铝塑的分离率达到100%.      

生活垃圾堆放场和填埋场矿化垃圾中磷的形态及其磷素活化

采用修正的Hedley磷素分级方法研究了生活垃圾堆放场和填埋场矿化垃圾中磷的形态分布,同时研究了鸡粪(含磷较高)和稻草(含磷较低)两种典型有机物料对矿化垃圾中不同形态磷的活化效应.结果表明,生活垃圾堆放场和填埋场矿化垃圾中,不同形态磷的含量表现出相似的趋势,仅树脂交换态磷和浓盐酸磷的含量存在明显差异;以氢氧化钠磷和磷灰石型磷构成的中度活性磷均为生活垃圾堆放场和填埋场矿化垃圾中磷的主要赋存形态,分别占各自总磷的78%和74.9%,表明矿化垃圾中磷素具有高效利用的潜能.鸡粪和稻草均能显著活化矿化垃圾中的磷,而且鸡粪的磷活化效果优于稻草;氢氧化钠磷、磷灰石型磷和浓盐酸磷是矿化垃圾中活化磷的主要来源.     

恒液位推流式改良SBR工艺处理生活污水

通过对恒液位推流式改良SBR工艺处理生活污水工程应用的研究,结果表明:恒液位推流式改良SBR工艺在降低工程成本和减少设备量的同时能较好的去除污水中的污染物,具有良好的脱氮除磷效果,COD去除率可达85%~93%;TP的去除率可达84%;TN的去除率可达82%。     

高温蒸汽灭菌处理技术处置医疗废物工艺设计

高温蒸汽灭菌处理技术是近几年开发的新型医疗废物处置技术,并在全国部分地区得到了应用和推广。以西北某市医疗废物处置工程中高温蒸汽灭菌处理技术的应用为例,通过对其工程原理、系统组成、工艺流程等的分析论证共同探讨其工程原理和性能特点,为今后在工程实际中的运用提供参考。     

Assessing the impact of biological control of Plutella xylostella through the application of Lotka–Volterra model

The Lotka–Volterra model was applied to the population densities of diamondback moth (DBM), Plutella xylostella (L.) and its exotic larval parasitoid Diadegma semiclausum (Hellen) data that was collected earlier by icipe's DBM biological control team. The collections were done for 15 months before the release and 36 months after release of the parasitoid in two areas; in Werugha, Coast Province of Kenya and Tharuni, Central Province of Kenya, respectively. For each area in pre- and post-release periods, we estimated Lotka–Volterra model parameters from the minimization of the loss function between the theoretical and experimental time-series datasets following the Nelder-Mead multidimensional method. The model estimated a reduction in the value of the steady state of DBM population from 4.86 to 2.17 in Werugha and from 6.11 to 3.76 and 3.45 (with and without exclusion of the time before D. semiclausum recovery) in Tharuni when transiting from the pre- and post-release periods, respectively. This change was a consequence of the newly introduced parasitoid, in the areas. The study presented a successful and detailed technique for non-linear model parameters restoration which was demonstrated by the correct mimicking of empirical datasets from the classical biological control with D. semiclausum, in different areas of Kenya. The applied model has measured the parasitoids impact on the DBM biological control through a quantitative estimate of the effectiveness of the newly introduced species D. semiclausum. These equations may therefore be used as tool for decision making in the implementation for such pests’ management system strategy.     

Role of competition in phytoplankton population for the occurrence and control of plankton bloom in the presence of environmental fluctuations

Termination of harmful algal blooms (HABs) and coexistence of phytoplankton–zooplankton populations are of great importance to human health, ecosystem, environment, tourism and fisheries. In this paper, we propose a three component model consisting of non-toxic phytoplankton (NTP), toxin producing phytoplankton (TPP) and zooplankton (Z). The growth of zooplankton species is assume to reduce due to toxic chemicals released by TPP population. We have extended the model proposed by Chattopadhyay et al. [Chattopadhyay, J., Sarkar, R.R., Pal, S., 2004. Mathematical modelling of harmful algal blooms supported by experimental findings. Ecol. Comp. 1, 225–235] by including competition terms between TPP and NTP. We observe the effect of competition factors both in the presence and absence of the environmental fluctuation. From our field as well as model analysis we observe that competition helps in the coexistence of the species, but if the effect of competition is very high on the TPP population, it results in planktonic bloom. It is shown that the coexistence equilibrium loses its stability when the competition coefficient crosses a critical value and resulting Hopf-bifurcation around the positive equilibrium depicting oscillations phenomena of the populations.     

The pattern of species turnover resulting from stochastic population dynamics: The model and field data

The model of random population dynamics in a sampling site returns geometric distribution of longevities of continuous presence (=persistence) and Poisson distribution of the presence–absence transitions. This discrete-time stochastic process describes the presence–absence pattern observed in the beetles surveyed 6 years on Mount Carmel, Israel. Homogeneous pools of species mostly on the Families rank, exhibit the predicted by the model patterns. Conformity to an ergodic hypothesis is the criterion of ecological homogeneity. This criterion assumes the equivalence of short-term behavior of entire pool and long-term behavior of any species from this pool. The pool of all 801 species of Order Coleoptera does not match the model. Thus a taxon of an arbitrary rank may not be considered a priory as a unit of ecological study. Determined from field data parameters of the model are biased and magnitude of the bias depends on longevity of the survey. Parameter of distribution depends also on species tolerance, which is the level adaptation of given species to given environment in given time interval. Random process of species turnover may be considered as a game of species to gain their presence against deteriorative fluctuations of environmental conditions.