Population structure and community characteristics of Acer catalpifolium Rehd北大核心CSCD

Acer catalpifolium Rehd., a critically endangered tree species with an extremely limited range of distribution, is one of the 120 plant species with extremely small populations, as approved by the state forestry administration of the People's Republic of China and requires urgent rescue action. In order to comprehensively understand the population status and the future developmental trend of A. catalpifolium, the plant communities were investigated from 5 sites, including Caishenmiao (CSM), Banruosi (BRS), Zhangshancun (ZSC), Fuhusi (FHS), and Baoguosi (BGS). The population structure of A. catalpifolium as well as the species composition and community characteristics of its habitat were investigated. The results showed that A. catalpifolium is mainly distributed in the evergreen broad-leaved and deciduous broad-leaved mixed forests, in different community layers, namely, the tree layer, shrub layer, and herb layer, and is accompanied by 52, 74, and 52 plant species, respectively. Analyses of the distribution of population abundance revealed that BRS had the largest distribution of A. catalpifolium, accounting for 26.04% of the total population, followed by FHS, ZSC, BGS, and CSM, in that order. Analyses of the community characteristics revealed that the species diversity indices in FHS, BRS, BGS, and CSM were greater than that in ZSC. Analyses of the population age structure of A. catalpifolium revealed the gap in the distribution of the levels of seedlings and young trees. There were serious obstacles to the regeneration of the natural population. We concluded that the obstacle to the regeneration of the population of A. catalpifolium might be caused by the high competitive pressure from the dominant species and the micro-environment in the forest. Understanding the community characteristics and the population structure of A. catalpifolium could provide a theoretical foundation for its reintroduction and recovery. © 2018 Science Press. All rights reserved.     

Modeling the population dynamics of cotton bollworm Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae) over a wide area in northern China

The cotton bollworm Helicoverpa armigera (Lepidoptera: Noctuidae) is one of the most serious crop pests in northern China, calling for accurate prediction of pest outbreaks and strategies for pest control. A computer model is developed to simulate the population dynamics of H. armigera over a wide area in northern China. The area considered covers 12 provinces where serious outbreaks of H. armigera have been observed. In this model, pest development is driven by local ambient temperature, and adults migrate long distances between regions and select preferred hosts for oviposition within a region. Six types of host including cotton, wheat, corn, peanut, soybean and a single category composed of all other minor hosts are considered in this model. Survival rates of eggs and larvae are based on life-table data, and simulated as a function of host type, host phenology and temperature. The incidence of diapause depends on temperature and photoperiod experienced during the larval stage. Survival rate of non-diapause pupae is a nonlinear function of rainfall, and overwinter survival rate is a nonlinear function of temperature. Insecticide is applied when population density exceeds the economic threshold on a host crop within a region. Comparisons of model output with light-trap data indicate that our model reflects the pest population dynamics over a wide area, and could potentially be used for testing novel pest control strategies in northern China.     

Influence of low and decreasing food levels on Daphnia-algal interactions: Numerical experiments with a new dynamic energy budget model

Based on numerical experiments with a new physiologically structured population model we demonstrate that predator physiology under low food and under starving conditions can have substantial implications for population dynamics in predator-prey interactions. We focused on Daphnia-algae interactions as model system and developed a new dynamic energy budget (DEB) model for individual daphnids. This model integrates the κ-rule approach common to net assimilation models into a net-production model, but uses a fixed allocation of net-productive energy in juveniles. The new DEB-model agrees well with the results of life history experiments with Daphnia. Compared to a pure κ-rule model the new allocation scheme leads to significant earlier maturation at low food levels and thus is in better agreement with the data. Incorporation of the new DEB-model into a physiologically structured population model using a box-car elevator technique revealed that the dynamics of Daphnia-algae interactions are highly sensitive to the assumptions on the energy allocation of juveniles under low food conditions. Additionally we show that also other energy allocation rules of our DEB-model concerning decreasing food levels and starving conditions at the individual level have strong implications for Daphnia-algae interactions at the population level. With increasing carrying capacity of algae a stable equilibrium with coexistence of Daphnia occurs and algae shifts to limit cycles. The amplitudes of the limit cycles increase with increasing percentage of sustainable weight loss. If a κ-rule energy allocation is applied to juveniles, the stable equilibrium occurs for a much narrower range of algal carrying capacities, the algal concentration at equilibrium is about 2 times larger, and the range of algae carrying capacities at which daphnids become extinct extends to higher carrying capacities than in the new DEB-model. Because predator-prey dynamics are very sensitive to predator physiology under low food and starving conditions, empirical constraints of predator physiology under these conditions are essential when comparing model results with observations in laboratory experiments or in the field.     

Will progress in science and technology avert or accelerate global collapse? A critical analysis and policy recommendations

Industrial society will move towards collapse if its total environmental impact (I), expressed either in terms of energy and materials use or in terms of pollution, increases with time, i.e., dI/dt > 0. The traditional interpretation of the I = PAT equation reflects the optimistic belief that technological innovation, particularly improvements in eco-efficiency, will significantly reduce the technology (T) factor, and thereby result in a corresponding decline in impact (I). Unfortunately, this interpretation of the I = PAT equation ignores the effects of technological change on the other two factors: population (P) and per capita affluence (A). A more heuristic formulation of this equation is I = P(T)·A(T)·T in which the dependence of P and A on T is apparent. From historical evidence, it is clear that technological revolutions (tool-making, agricultural, and industrial) have been the primary driving forces behind successive population explosions, and that modern communication and transportation technologies have been employed to transform a large proportion of the world’s inhabitants into consumers of material- and energy-intensive products and services. In addition, factor analysis from neoclassical growth theory and the rebound effect provide evidence that science and technology have played a key role in contributing to rising living standards. While technological change has thus contributed to significant increases in both P and A, it has at the same time brought about considerable eco-efficiency improvements. Unfortunately, reductions in the T-factor have generally not been sufficiently rapid to compensate for the simultaneous increases in both P and A. As a result, total impact, in terms of energy production, mineral extraction, land-use and CO₂ emissions, has in most cases increased with time, indicating that industrial society is nevertheless moving towards collapse. The belief that continued and even accelerated scientific research and technological innovation will automatically result in sustainability and avert collapse is at best mistaken. Innovations in science and technology will be necessary but alone will be insufficient for sustainability. Consequently, what is most needed are specific policies designed to decrease total impact, such as (a) halting population growth via effective population stabilization plans and better access to birth control methods, (b) reducing total matter-energy throughput and pollution by removing perverse subsidies, imposing regulations that limit waste discharges and the depletion of non-renewable resources, and implementing ecological tax reform, and (c) moving towards a steady-state economy in which per-capita affluence is stabilized at lower levels by replacing wasteful conspicuous material consumption with social alternatives known to enhance subjective well-being. While science and technology must play an important role in the implementation of these policies, none will be enacted without a fundamental change in society’s dominant values of growth and exploitation. Thus, value change is the most important prerequisite for avoiding global collapse.

Population viability of the Siberian Tiger in a changing landscape: Going, going and gone?

The Amur tiger (Panthera tigris altaica) is a flagship species of the boreal forest ecosystem in northeastern China and Russia Far East. During the past century, the tiger population has declined sharply from more than 3000 to fewer than 600 individuals, and its habitat has become much smaller and greatly fragmented. Poaching, habitat degradation, habitat loss, and habitat fragmentation have been widely recognized as the primary causes for the observed population decline. Using a population viability analysis tool (RAMAS/GIS), we simulated the effects of poaching, habitat degradation, habitat loss, and habitat fragmentation on the population dynamics and extinction risk of the Amur tiger, and then explored the relative effectiveness of three conservation strategies involving improving habitat quality and establishing movement corridors in China and Russia. A series of controlled simulation experiments were performed based on the current spatial distribution of habitat and field-observed vital rates. Our results showed that the Amur tiger population could be viable for the next 100 years if the current habitat area and quality were well-maintained, with poaching strictly prohibited of the tigers and their main prey species. Poaching and habitat degradation (mainly prey scarcity) had the largest negative impacts on the tiger population persistence. While the effect of habitat loss was also substantial, habitat fragmentation per se had less influence on the long-term fate of the tiger population. However, to sustain the subpopulations in both Russia and China would take much greater conservation efforts. The viability of the Chinese population of tigers would rely heavily on its connectivity with the largest patch on the other side of the border. Improving the habitat quality of small patches only or increasing habitat connectivity through movement corridors alone would not be enough to guarantee the long-term population persistence of the Amur tiger in both Russia and China. The only conservation strategy that allowed for long-term persistence of tigers in both countries required both the improvement of habitat quality and the establishment of a transnational reserve network. Our study provides new insights into the metapopulation dynamics and persistence of the Amur tiger, which should be useful in landscape and conservation planning for protecting the biggest cat species in the world.     

Using simulation to explore the functional relationships of terrestrial carnivore population indices

Population indices based on visits to detection stations commonly are used to monitor wildlife populations. Inferences about populations are based on 1 of 2 measures: (1) change in the proportion of stations visited at least once or (2) change in the cumulative number of visits by unique individuals. The functional relationships between index responses and population density is poorly understood and can lead to misinterpretation of index data when an incorrect functional relationship (e.g. linear) is assumed. We created a flexible simulation environment to study the response of detection-based population indices under a wide variety of conditions meant to reflect species life history and study design. Proportional indices exhibited non-linear saturating responses to changes in population density while cumulative indices responded linearly. Shapes of responses were functions of home range sizes, individual detection probabilities, and spatial arrangement of animals and sampling stations. Non-linear relationships of proportional indices lead to under-estimation of mean population density when data are aggregated from multiple detection stations deployed in a heterogeneous landscape. Cumulative indices have significant statistical advantages over proportional indices including smaller sample sizes required to detect density change, linearity, consistent index responses across a wide range of densities, and ability to aggregate data to meet minimum sample size requirements. Our simulation provides a flexible tool for the interpretation of station-based population indices.     

Forecasting population trend from the scaling pattern of occupancy

Forecasting the temporal trend of a focal species, its range expansion or retraction, provides crucial information regarding population viability. To this end, we require the accumulation of temporal records which is evidently time consuming. Progress in spatial data capturing has enabled rapid and accurate assessment of species distribution across large scales. Therefore, it would be appealing to infer the temporal trends of populations from the spatial structure of their distributions. Based on a combination of models from the fields of range dynamics, occupancy scaling and spatial autocorrelation, here I present a model for forecasting the population trend solely from its spatial distribution. Numerical tests using cellular automata confirm a positive correlation, as inferred from the model, between the temporal change in species range sizes and the exponent of the power-law scaling pattern of occupancy. The model is thus recommended for rapid estimation of species range dynamics from a single snapshot of its current distribution. Further applications in biodiversity conservation could provide a swift risk assessment, especially, for endangered and invasive species.     

A provider-based water planning and management model--WaterSim 4.0--for the Phoenix Metropolitan Area

Uncertainty in future water supplies for the Phoenix Metropolitan Area (Phoenix) are exacerbated by the near certainty of increased, future water demands; water demand may increase eightfold or more by 2030 for some communities. We developed a provider-based water management and planning model for Phoenix termed WaterSim 4.0. The model combines a FORTRAN library with Microsoft C# to simulate the spatial and temporal dynamics of current and projected future water supply and demand as influenced by population demographics, climatic uncertainty, and groundwater availability. This paper describes model development and rationale. Water providers receive surface water, groundwater, or both depending on their portfolio. Runoff from two riverine systems supplies surface water to Phoenix while three alluvial layers that underlie the area provide groundwater. Water demand was estimated using two approaches. One approach used residential density, population projections, water duties, and acreage. A second approach used per capita water consumption and separate population growth estimates. Simulated estimates of initial groundwater for each provider were obtained as outputs from the Arizona Department of Water Resources (ADWR) Salt River Valley groundwater flow model (GFM). We compared simulated estimates of water storage with empirical estimates for modeled reservoirs as a test of model performance. In simulations we modified runoff by 80%-110% of the historical estimates, in 5% intervals, to examine provider-specific responses to altered surface water availability for 33 large water providers over a 25-year period (2010-2035). Two metrics were used to differentiate their response: (1) we examined groundwater reliance (GWR; that proportion of a providers' portfolio dependent upon groundwater) from the runoff sensitivity analysis, and (2) we used 100% of the historical runoff simulations to examine the cumulative groundwater withdrawals for each provider. Four groups of water providers were identified, and discussed. Water portfolios most reliant on Colorado River water may be most sensitive to potential reductions in surface water supplies. Groundwater depletions were greatest for communities who were either 100% dependent upon groundwater (urban periphery), or nearly so, coupled with high water demand projections. On-going model development includes linking WaterSim 4.0 to the GFM in order to more precisely model provider-specific estimates of groundwater, and provider-based policy options that will enable "what-if" scenarios to examine policy trade-offs and long-term sustainability of water portfolios.     

秦山岛周边海域大型底栖动物群落健康状况评价

2015年8月,对秦山岛周边的10个站位进行大型底栖动物定量调查。采用生物多样性指数法和丰度生物量比较法对大型底栖动物群落健康状况进行评价。结果显示,共鉴定大型底栖动物7大类31种,其中软体动物、环节动物各10种,节肢动物5种,脊索动物和棘皮动物各2种,纽虫类和腔肠动物各1种;密度优势类群为软体动物,占总密度的35.00%,生物量优势类群为脊索动物,占总生物量的49.35%;优势种分别为红狼牙虾虎鱼(Odontamblyopus rubicundus)、棘刺锚参(Protankyra bidentata)、内卷原盒螺(Eocylichna involuta)和微角齿口螺(Odostomia subangulata)。大型底栖动物密度为站位St.6最大,为115 ind./m²,St.2最小,为20 ind./m²,平均值为70 ind./m²;生物量St.3最大,为197.25 g/m²,St.9最小,为2.56 g/m²,平均值为54.04 g/m²。秦山岛受污染压力、人为活动干扰和生境限制能因素影响,多样性偏低,优势种为耐污的软体动物、脊索动物和棘皮动物,但其主要为K对策种类,大型底栖动物群落受到了轻度干扰,但群落结构仍较为稳定。     

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.