Using Modeling to Improve Monitoring of Structured Populations: Are We Collecting the Right Data?

Abstract:  Population monitoring is central to most demographic studies and conservation efforts, but it may not always be directed at the most appropriate life stage. We used stochastic simulation modeling to evaluate the effectiveness of a monitoring program for a well-studied population of Eastern Imperial Eagles ( Aquila heliaca ) in Kazakhstan. Specifically, we asked whether the most appropriate data were being collected to understand system state and population dynamics. Our models were parameterized with data collected over the course of 25 years of study of this population. We used the models to conduct simulation experiments to evaluate relationships between monitored or potentially monitored parameters and the demographic variables of interest—population size ( N ) and population growth (λ). Static analyses showed that traditional territory-based monitoring was a poor indicator of eagle population size and growth and that monitoring survivorship would provide more information about these parameters. Nevertheless, these same traditionally monitored territory-based parameters had greater power to detect long-term changes in population size than did survivorship or population structure. Regardless of the taxa considered, threats can have immediate impacts on population size and growth or longer-term impacts on population dynamics. Prudently designed monitoring programs for any species will detect the demographic effects of both types of threats.     

鼓翅皱膝蝗生态学特性研究

在甘肃省夏河县对鼓翅皱膝蝗的种群结构、数量变动、空间格局及动脉进行了系统研究。鼓翅皱膝蝗1a发生1代，以卵在土中越冬，翌年5月中旬开始孵化出土，6月上旬达到出土高峰，此期蝗虫种群仅由1龄和2龄蝗蝻组成，其中1龄蝗蝻占81.8％，2龄蝗蝻占18.2％，成虫于7月上旬开始羽化，8月上旬达到羽化高峰，此期的成虫数量达61.3％，而蝗蝻仅占38.7％，蝗蝻期约为72d，成虫寿命54d左右，每雌平均产卵32.6粒。鼓翅皱膝蝗在草地上属聚集分布，蝗蝻发生期种群的空间动态主要表现出扩散趋势，但初孵化出土时有短暂的聚集行为。取食量随龄期增大而增大，每头鼓翅皱膝蝗取食牧草量蝗蝻期平均为1.5g，成早期约为5.8g，成早期的食量是蝗蝻期的3.7倍。表3参12     

天津城市化发展趋向与水资源可持续利用

分析了新时期天津城市化发展趋向，从城市人口增长、城市工业结构、城市化进程等诸方面，探讨了城市化进程与水资源利用之间的关系，提出了适应城市化发展的水资源可持续利用战略。     

On the latent state estimation of nonlinear population dynamics using Bayesian and non-Bayesian state-space models

Nonlinear state-space models have been increasingly applied to study population dynamics and data assimilation in environmental sciences. State-space models can account for process error and measurement error simultaneously to correct for the bias in the estimates of system state and model parameters. However, few studies have compared the performance of different nonlinear state-space models for reconstructing the state of population dynamics from noisy time series. This study compared the performance of the extended Kalman filter (EKF), unscented Kalman filter (UKF) and Bayesian nonlinear state-space models (BNSSM) through simulations. Synthetic population time series were generated using the theta logistic model with known parameters, and normally distributed process and measurement errors were introduced using the Monte Carlo simulations. At higher levels of nonlinearity, the UKF and BNSSM had lower root mean square error (RMSE) than the EKF. The BNSSM performed reliably across all levels of nonlinearity, whereas increased levels of nonlinearity resulted in higher RMSE of the EKF. The Metropolis–Hastings algorithm within the Gibbs algorithm was used to fit the theta logistic model to synthetic time series to estimate model parameters. The estimated posterior distribution of the parameter θ indicated that the 95% credible intervals included the true values of θ (=0.5 and 1.5), but did not include 1.0 and 0.0. Future studies need to incorporate the adaptive Metropolis algorithm to estimate unknown model parameters for broad applications of Bayesian nonlinear state-space models in ecological studies.     

The Novel and Endemic Pathogen Hypotheses: Competing Explanations for the Origin of Emerging Infectious Diseases of Wildlife

Abstract:  Chytridiomycosis, caused by the fungal pathogen Batrachochytrium dendrobatidis , is an emerging infectious disease implicated in declines of amphibian populations around the globe. An emerging infectious disease is one that has recently been discovered; has recently increased in incidence, geography, or host range; or is newly evolved. For any given outbreak of an emerging disease, it is therefore possible to state two hypotheses regarding its origin. The novel pathogen hypothesis states that the disease has recently spread into new geographic areas, whereas the endemic pathogen hypothesis suggests that it has been present in the environment but recently has increased in host range or pathogenicity. Distinguishing between these hypotheses is important, because the conservation measures needed to slow or stop the spread of a novel pathogen are likely to differ from those needed to prevent outbreaks of an endemic pathogen. Population genetics may help discriminate among the possible origins of an emerging disease. Current evidence suggests chytridiomycosis may be a novel pathogen being spread worldwide by carriers; until we know how much genetic variation to expect in an endemic strain, however, we cannot yet conclude that B. dendrobatidis is a novel pathogen.     

Designatable Units for Status Assessment of Endangered Species

Abstract:  Species status assessment and the conservation of biological diversity may require defining units below the species level to portray probabilities of extinction accurately and to help set priorities for conservation efforts. What those units should be has been debated in the scientific literature largely in terms of evolutionarily significant units (ESUs), but this discourse has had little impact on government policy with regard to status assessment. As with species concepts, the variously proposed ESU concepts have not been resolvable into a single approach. The need for a practicable procedure to identify infraspecific entities for status assignment is the motivation behind employing designatable units (DUs). In aid of a policy to prevent elements of biodiversity from becoming extinct or extirpated, DUs are determined during the process of resolving a species' conservation status according to broadly applicable guidelines. The procedure asks whether putative DUs are distinguishable based on a reliably established taxonomy or a well-corroborated phylogeny, compelling evidence of genetic distinction, range disjunction, and/or biogeographic distinction as long as extinction probabilities also differ. The language of the DU approach avoids wording that implies value judgments concerning evolutionary importance or significance. Because species conservation status assessment is not science but, rather, the use of science to further policy, DUs contribute to a precautionary approach to listing whereby status may be assessed even though knowledge of systematic relationships below the species level may be lacking or unresolved. The pragmatic approach of using DUs has been adopted by the Committee on the Status of Endangered Wildlife in Canada for status assessment of species under the Canadian Species at Risk Act.     

Using the bootstrap with two-phase adaptive stratified samples from multiple populations at multiple locations

Recently the two-phase adaptive stratified sampling design proposed by Francis (1984) has been extended by Manly et al. (2002) for situations where several biological populations are sampled simultaneously, and where this is done at several different geographical locations in order to estimate population totals or means. The method uses the results from a first phase sample to decide how best to allocate a second phase sample to locations and strata, in order to maximise a criterion (based on estimated coefficients of variation) that measures the accuracy of estimation for population totals, for all variables at all locations. One potential problem with this method is bias in the estimators of the population totals and means. In this paper bootstrapping is considered as a means of overcoming these biases. It is shown using model populations of Pacific walrus and shellfish, based on real data, that bootstrapping is a useful tool for removing about half of the bias. This is also confirmed from some simulations using artificial data.     

农村经济活动对云南野生稻居群的影响

云南野生稻包括普通野生稻(O.rufipogon Griff)、疣粒野生稻(O.meyeriana Baill)和药用野生稻(O.officinalis Wall),是属于全国仅存的几处宝贵基因资源库之一。野生稻具有许多优良特性及其相应的基因,在栽培稻育种和生物技术利用等方面具有巨大的潜力。文章在对云南野生稻居群长期调查或考察的基础上,分析了云南野生稻居群濒危的现状,认为热区经济开发、游牧、木材消耗、采集草药、外来种入侵和环境污染等农村经济活动是致濒的主要因素。阐明了选择合理的保护方法、加大普法和执法力度、完善保护体制与运行机制、调整种植结构是当前云南野生稻居群保护管理与经济协调发展的四项重点措施。     

海洋纤毛虫实验生态学研究Ⅳ:不同人工海水培养液及温度对扇形游仆虫种群增长的影响

为了揭示出海洋纤毛虫在人工海水中及不同温度下的种群动力学，利用实验生态学方法，就4种培养液及2种（17℃和23℃）温度对海洋纤毛虫扇形游仆虫（Euplotes vannus Mailer，1786）种群增长的影响进行了初步探讨．结果显示：①该种纤毛虫原生动物在4种人工海水培养液中的种群增长率大小顺序为：牛肉浸膏培养液〉米粒培养液〉酵母粉培养液〉蛋白胨培养液；②种群密度大小顺序依次为：米粒培养液〉牛肉浸膏培养液〉酵母粉培养液〉蛋白胨培养液；③指数增长期及稳定期在米粒培养液中均长于牛肉浸膏培养液；④随着培养温度的升高，种群增长率增大，指数增长期及稳定期缩短；⑤温度系数（Q10）的大小顺序为：蛋白胨培养液〉牛肉浸膏培养液〉米粒培养液〉酵母粉培养液．结果表明，米粒人工海水培养液不仅适合于保种培养，而且适合于种群的扩大培养，而牛肉浸膏培养液更适合于种群的快速扩大培养，其他两种培养液则只适合于保种培养．图2表4参13