Hierarchical spatial modeling for estimation of population size

Estimation of population size has traditionally been viewed from a finite population sampling perspective. Typically, the objective is to obtain an estimate of the total population count of individuals within some region. Often, some stratification scheme is used to estimate counts on subregions, whereby the total count is obtained by aggregation with weights, say, proportional to the areas of the subregions. We offer an alternative to the finite population sampling approach for estimating population size. The method does not require that the subregions on which counts are available form a complete partition of the region of interest. In fact, we envision counts coming from areal units that are small relative to the entire study region and that the total area sampled is a very small proportion of the total study area. In extrapolating to the entire region, we might benefit from assuming that there is spatial structure to the counts. We implement this by modeling the intensity surface as a realization from a spatially correlated random process. In the case of multiple population or species counts, we use the linear model of coregionalization to specify a multivariate process which provides associated intensity surfaces hence association between counts within and across areal units. We illustrate the method of population size estimation with simulated data and with tree counts from a Southwestern pinyon-juniper woodland data set.     

Exploring the influence of lake water chemistry on chlorophyll a: A multivariate statistical model analysis

A multivariate statistical approach integrating the absolute principal components score (APCS) and multivariate linear regression (APCS-MLR), along with structural equation modeling (SEM), was used to model the influence of water chemistry variables on chlorophyll a (Chl a) in Lake Qilu, a severely polluted lake in southwestern China. Water quality was surveyed monthly from 2000 to 2005. APCS-MLR was used to identify key water chemistry variables, mine data for SEM, and predict Chl a. Seven principal components (PCs) were determined as eigenvalues >1, which explained 68.67% of the original variance. Four PCs were selected to predict Chl a using APCS-MLR. The results showed a good fit between the observed data and modeled values, with R² = 0.80. For SEM, Chl a and eight variables were used: NH₄-N (ammonia-nitrogen), total phosphorus (TP), Secchi disc depth (SD), cyanide (CN), arsenic (As), cadmium (Cd), fluoride (F), and temperature (T). A conceptual model was established to describe the relationships among the water chemistry variables and Chl a. Four latent variables were also introduced: physical factors, nutrients, toxic substances, and phytoplankton. In general, the SEM demonstrated good agreement between the sample covariance matrix of observed variables and the model-implied covariance matrix. Among the water chemistry factors, T and TP had the greatest positive influence on Chl a, whereas SD had the largest negative influence. These results will help researchers and decision-makers to better understand the influence of water chemistry on phytoplankton and to manage eutrophication adaptively in Lake Qilu.     

多元逐步回归对苯胺类化合物结构与毒性模型研究

采用Chemoffice6．0中MOPAC-AMl量子化学法计算了24种苯胺类化合物的6种量子化学结构参数．其中取17个化合物作为样本集对-lgEC50进行多元逐步回归分析．得到最佳方程．经自由度校正的回归系数R=0．985。应用所建立的QSAR模型验证了苯胺类化合物的EC50值．并通过“Jackknife”中的逐一抽取法进行模型检验,得出该模型具有很好的稳定性．平均残差仅为0．05个对数单位．小于文献值。经过7个预测样本对该模型进行验证．结果表明．该模型具有很好的预测能力。同时分析了苯胺类化合物的毒性机理。     

Environmental Objectives,Cost Efficiency,and Multivariate Stochastic Control

This paper is concerned with the cost efficiency in achieving the Swedish national air quality objectives under uncertainty. To realize an ecologically sustainable society, the parliament has approved a set of interim and long-term pollution reduction targets. However, there are considerable quantification uncertainties on the effectiveness of the proposed pollution reduction measures. In this paper, we develop a multivariate stochastic control framework to deal with the cost efficiency problem with multiple pollutants. Based on the cost and technological data collected by several national authorities, we explore the implications of alternative probabilistic constraints. It is found that a composite probabilistic constraint induces considerably lower abatement cost than separable probabilistic restrictions. The trend is reinforced by the presence of positive correlations between reductions in the multiple pollutants.

Hierarchical spatial point process analysis for a plant community with high biodiversity

A complex multivariate spatial point pattern of a plant community with high biodiversity is modelled using a hierarchical multivariate point process model. In the model, interactions between plants with different post-fire regeneration strategies are of key interest. We consider initially a maximum likelihood approach to inference where problems arise due to unknown interaction radii for the plants. We next demonstrate that a Bayesian approach provides a flexible framework for incorporating prior information concerning the interaction radii. From an ecological perspective, we are able both to confirm existing knowledge on species’ interactions and to generate new biological questions and hypotheses on species’ interactions.

Vegetation zonation and management in the Damietta estuary of the River Nile

The zonation of the vegetation along the saline and freshwater marshes of the Damietta estuary of the Nile River was studied from near the river mouth to 20 km upstream. Downstream, the estuarine water is almost stagnant and highly saline with high concentrations of nutrients. This makes the habitat unsuitable for euhydrophytes. Upstream, the vegetation consists mostly of freshwater macrophytes. 75 sampling plots were established in representative stands of the upshore and upstream vegetation zones. Classification and ordination of the data revealed seven vegetation types, indicated A—G. The dominant species of the saline marshes werePhragmites australis, Tamarix nilotica andArthrocnemum macrostachyum (A),Zygophyllum aegyptium andPolygonum equisetiforme (B),Cynodon dactylon andSuaeda vera (C). In the freshwater marshes the dominants were:Ludwigia stolonifera, Persicaria lapathifolia (D),Typha domingensis (E),Eichhornia crassipes (F) andCeratophyllum demersum (G). The first axis of the ordination axis obtained with Detrended Correspondence Analysis can be associated with the upstream gradient. It separates the salt marsh vegetation groups from those of the freshwater marshes. Plant species richness increased upshore along both saline and freshwater marshes. The concentration of dominance increased upstream. Some aspects of proper management of estuarine vegetation are mentioned.     

Spatial Patterns of Macrobenthic Communities in Shallow-Water Tidal Embayments and Their Association with Environmental Factors

This study examines the distribution, composition, and structure of benthic communities in nine shallow-water semienclosed embayments on Cape Cod, southeastern Massachusetts. The spatial patterns were used to associate benthic characteristics with local environmental factors. Field data from multiple years were collected to measure macrofaunal abundance, community composition, and environmental characteristics. Multivariate statistics were used to analyze the spatial variations of species composition and the abundance of benthic macrofauna. Canonical ordination, specifically redundancy analysis, was used to determine the relative importance of the environmental factors (nutrients and habitat factors) being studied. The analyses demonstrate that the benthic communities in the shallow tidal embayments are clearly clustered in association with the local environments. Species composition and community structure of the benthic macrofauna are significantly correlated with water column parameters, especially with phytoplankton biomass, total nitrogen, and dissolved oxygen.     

Dissolved heavy metal concentrations of the Kralkızı, Dicle and Batman dam reservoirs in the Tigris River basin,Turkey

Water samples were collected at monthly intervals during 1 year of monitoring from Kralk?z?, Dicle and Batman dam reservoirs in the Tigris River basin to assess the concentrations of dissolved heavy metals and to determine their spatial and seasonal variations. The results indicated that dissolved heavy metal concentrations in the reservoirs were very low, reflecting the natural background levels. The lowest total metal concentrations in the three dam reservoirs were detected at sampling sites close to the dam wall. However, the highest total concentrations were observed at sites, which are located at the entrance of the streams to the reservoirs. Fe, Cr and Ni were the most abundant elements in the reservoirs, whereas Cd and As were the less abundant. The mean concentrations of dissolved metals in the dam reservoirs never exceeded the maximum permitted concentrations established by EC (European Community), WHO and USEPA drinking water quality guidelines. All heavy metals showed significant seasonal variations. As, Cd, Cr, Cu, Fe, Ni and Pb displayed higher values in the dry season, while higher values for Zn in the wet season. Cluster analysis grouped all ten sampling sites into three clusters. Clusters 1 and 2, and cluster 3 corresponded to relatively low polluted and moderate polluted regions, respectively. PCA/FA demonstrated the dissolved metals in the dam reservoirs controlled by natural sources.     

Managing Abandoned Farmland: The Need to Link Biological and Sociological Aspects

The lack of a particular use associated with abandoned farmland provides real opportunities with respect to the various land-use pressures occurring in productive territories. These environments remain generally poorly known and, because of this, require in-depth studies on the feasibility of management options, on biological as well as social grounds. This study, based on research on the biophysical potential and the perceptions by the owners of abandoned farmlands, analyzes the feasibility of silvicultural management options to improve forestry potential. Using a questionnaire, we surveyed abandoned farmland owners on different aspects of the status of their abandoned farmland in order to determine their willingness toward the management of these private lands. The land owners were also asked to express their interests and their constraints toward various types of interventions, with an emphasis on silvicultural work. The data were analyzed using multivariate methods to establish relationships between the questionnaire data and the characteristics of the land owners (socioeconomic profile and value system toward the environment). The results show that, in general, abandoned farmland is an unwanted space, is generally little used, is poorly known, and has little importance in the plans of its owners. We have found three types of owner profiles; the owners with a farmer’s profile are those who are the most interested in managing their abandoned farmland, whether for agriculture or silviculture. The desire to improve abandoned farmland seems less important to owners with an ecocentric profile (high awareness of the environment) and to older owners. Finally, by associating the type of abandoned farmland owned and the characteristics of the owners, it is possible to propose different management options that reconcile the wishes of the owners as well as the biophysical potential of their abandoned farmland.     

Discriminating zooplankton assemblages through multivariate methods: A case for a tropical polluted harbour and Bar-built estuary

A comparative study (June-July 2001) on zooplankton community structure amid polluted conditions in a stagnant harbour and relatively unaffected tidal estuary near Visakhapatnam, on the east coast of India, revealed a marked disparity in species composition and abundance. While the harbour supported a rich population of calanoids (46.4%), the estuary sustained mostly cyclopoids (55.2%). Univariate and multivariate techniques (species diversity, clustering, non-metric multi-dimensional scaling and one-way ANOSIM) revealed the existence of two differing zooplankton assemblages and associated water quality (similarity 50.6%). While the estuary is typified by high amounts of dissolved silica (67.4 ± 17.7 μmol l^-1) linked with monsoon influx, the harbour waters revealed abnormal levels of phosphate (40.9 ± 9.2 μmol l^-1) and nitrate (15.3 ± 5.41 μmol l^{- 1}) suggestive of intense eutrophication, caused by the discharge of fertilizer-factory waste and domestic sewage. On the basis of routines (e.g. BVSTEP, SIMPER) implemented in Plymouth Routines in Multivariate Ecological Research, it was possible to demonstrate that while species such as Oithona rigida, Oithona brevicornis, crustacean nauplii, gastropod veligers, Acartia spinicauda, and Acartia centrura played a key role in discriminating the zooplankton assemblage in the estuary, Acrocalanus spp. (mainly Acrocalanus gracilis) played a keyed role in harbour waters. Canonical Correspondence Analysis revealed species-environment relationships; for example, while the distribution of Oithona spp. and its associates in the estuary corresponded intimately with high silicate, temperature, and low salinity, it was high salinity, phosphate, and nitrate in the harbour channel that supported a different assemblage of copepods dominated by calanoids.