Mate sampling behaviour of black grouse females (Tetrao tetrix)

We studied female mate sampling behaviour in lekking black grouse (Tetrao tetrix). Females mainly visited males occupying territories in the centre of the lek with relatively large territories. They were also more likely to visit males that had high attendance. The same factors were also correlated with male mating success. A multiple regression model including these factors explained more of the variance in female visits per male (53%) than in mating success (33%). The pattern of female sampling conformed with a pool comparison (best-of-n) tactic. Such a tactic is expected if the costs of sampling are low. Females of high body mass visited more males than lighter females, however, which indicates that females may vary in their search tactics and suggests that there may be search costs. The existence of costs is further suggested by the fact that if the mate from a previous year was still present, females always mated with the same male in the following year. Though search costs were not measured directly, our findings suggest that some costs are negligible (e.g. energetic exhaustion or predation) whereas others (timing of mating) may be more important.     

The Botanist Effect Revisited: Plant Species Richness, County Area, and Human Population Size in the United States

Abstract:  The "botanist effect" is thought to be the reason for higher plant species richness in areas where botanists are disproportionately present as an artefactual consequence of a more thorough sampling. We examined whether this was the case for U.S. counties. We collated the number of species of vascular plants, human population size, and the area of U.S. counties. Controlling for spatial autocorrelation and county area, plant species richness increased with human population size and density in counties with and without universities and/or botanical gardens, with no significant differences in the relation between the two subsets. This is consistent with previous findings and further evidence of a broad-scale positive correlation between species richness and human population presence, which has important consequences for the experience of nature by inhabitants of densely populated regions. Combined with the many reports of a negative correlation between the two variables at a local scale, the positive relation between plant species richness in U.S. counties and human population presence stresses the need for the conservation of seminatural areas in urbanized ecosystems and for the containment of urban and suburban sprawl.     

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.     

Variance estimation in the EMAP strategy for sampling discrete ecological resources

The United States Environmental Protection Agency's Environmental Monitoring and Assessment Program (EMAP) is designed to describe status, trends and spatial pattern of indicators of condition of the nation's ecological resources. The proposed sampling design for EMAP is based on a triangular systematic grid and employs both variable probability and double sampling. The Horvitz-Thompson estimator provides the foundation of the design-based estimation strategy used in EMAP. However, special features of EMAP designed to accommodate the complexity of sampling environmental resources on a national scale require modifications of standard variance estimation procedures as well as development of new techniques. An overview of variance estimation methods proposed for application to EMAP's sampling strategy for discrete resources is presented.     

Estimating percentiles from composite environmental samples when all observations are nondetectable

Many environmental sampling problems involve some specified regulatory or contractual limit (RL). Often the interest is in estimating the percentile of the underlying contaminant concentration distribution corresponding to RL. The focus of this paper is on obtaining a point estimate and a lower confidence limit for that percentile when all observations are nondetectable, with the ith observation known to be less than some detection limit DLI, where DLi RL. Since composite samples are being considered, it is not unreasonable to assume an underlying normal distribution.     

Desirable design characteristics for long-term monitoring of ecological variables

Long-term environmental monitoring places a set of demands on a sampling strategy not present in a survey designed for a single time period. The inevitability that a sample will become out of date must be a dominant consideration in planning a long-term monitoring programme. The sampling strategy must be able to accommodate periodic frame update and sample restructuring in order to address changes in the composition of the universe and changes in the perception of issues leading to new questions and concerns. The sampling strategy must be capable of adapting to such changes while maintaining its identification as a probability sample and its capacity to detect trends that span the update occasions. These issues are examined with respect to sub-population estimation, post-stratification via conditioning, and sample enlargement and reduction. Design features that involve complex sample structure create potentially serious difficulties, whereas an equal probability design permits greater adaptability and flexibility. Structure should be employed sparingly and in awareness of its undesirable effects.     

Resampling from stochastic simulations

To model the uncertainty of an estimate of a global property, the estimation process is repeated on multiple simulated fields, with the same sampling strategy and estimation algorithm. As opposed to conventional bootstrap, this resampling scheme allows for spatially correlated data and the common situation of preferential and biased sampling. The practice of this technique is developed on a large data set where the reference sampling distributions are available. Comparison of the resampled distributions to that reference shows the probability intervals obtained by resampling to be reasonably accurate and conservative, provided the original and actual sample has been corrected for the major biases induced by preferential sampling.Andre G. Journel is a Professor of Petroleum Engineering at Stanford University with a joint appointment in the Department of Geological and Environmental Sciences. He is, also, Director of the Stanford Center for Reservoir Forecasting. Professor Journel has pioneered applications of geostatistical techniques in the mining/petroleum industry and extended his expertise to environmental applications and repository site characterization. Most notably, he developed the concept of non-parametric geostatistics and stochastic imaging with application to modeling uncertainty in reservoir/site characterization. Although the research described in this article has been supported by the United States Environmental Protection Agency under Cooperative Agreement CR819407, it has not been subjected to Agency review and therefore does not necessarily reflect the views of the Agency and no official endorsement should be inferred.     

Application of adaptive cluster sampling to low-density populations of freshwater mussels

Freshwater mussels appear to be promising candidates for adaptive cluster sampling because they are benthic macroinvertebrates that cluster spatially and are frequently found at low densities. We applied adaptive cluster sampling to estimate density of freshwater mussels at 24 sites along the Cacapon River, WV, where a preliminary timed search indicated that mussels were present at low density. Adaptive cluster sampling increased yield of individual mussels and detection of uncommon species; however, it did not improve precision of density estimates. Because finding uncommon species, collecting individuals of those species, and estimating their densities are important conservation activities, additional research is warranted on application of adaptive cluster sampling to freshwater mussels. However, at this time we do not recommend routine application of adaptive cluster sampling to freshwater mussel populations. The ultimate, and currently unanswered, question is how to tell when adaptive cluster sampling should be used, i.e., when is a population sufficiently rare and clustered for adaptive cluster sampling to be efficient and practical? A cost-effective procedure needs to be developed to identify biological populations for which adaptive cluster sampling is appropriate.     

水质在线监测中的若干问题

以环境水质自动监测子站的采样和配水系统为切入点，针对不同环节上极易出现的问题，分别提出具体的解决方案。