辽东湾大凌河口湿地土壤微生物群落分析

土壤微生物对湿地生态系统的物质转化和能量流动具有重要作用,目前对天然湿地的微生物资源及群落结构缺少研究。应用PCR-DGGE技术研究辽东湾大凌河口湿地土壤中的微生物群落结构,并对其群落组成进行分析,结合冗余分析（RDA）方法考察环境因子对微生物群落结构的影响。共设定7个站位采集土壤样品,直接提取样品中微生物的总DNA,以巢式PCR扩增细菌16S rDNA-V3区片段,应用变性梯度凝胶电泳（DGGE）技术分离片段,研究河口区湿地土壤细菌的群落结构。结果表明：辽东湾大凌河口区土壤具有较为丰富的细菌种群,主要包含Proteobacteria、Actinobacteria和Bacteroidetes几大类门,且同一季节采集的样品在聚类分析图上聚类成簇。RDA分析表明,土壤的温度与盐度2个变量分别解释了6.5%、2.3%的土壤细菌群落结构变化,表明大凌河口区土壤的群落结构变化是多种环境因子共同作用的结果,其中温度的影响略大于盐度。     

Benthic invertebrate assemblages of Delaware Bay

During two consecutive summers, the first quantitative bay-wide survey (207 stations) of benthic invertebrates was conducted in Delaware Bay (USA). In 1972, 109 species were collected at 105 stations; and in 1973, 125 species were collected at 102 stations. A total of 169 different species were collected for both summers. The number of species and number of individuals increased with increasing salinity and increasing median grain size. These relationships were compared and were found similar to those in estuaries and bays throughout the world. Average density was 722 individuals m², which is low compared to other estuaries. The relationship of low secondary production to pollution, macroscopic algae, sediment transport, predation, and hydrography is discussed. Deposit feeders comparised the major feeding type. Local species composition was similar to that in Chesapeake Bay, and dominant species occurred in estuaries throughout the Mid-Atlantic Bight. The benthic invertebrates of Delaware Bay were related to the cosmopolitan mode of estuarine faunas. Faunal assemblages were identified by cluster analysis. The assemblages were associated with sediment type and salinity. It was concluded that Delaware Bay comprises a mosaic of animal assemblages, some of which have relatively sharp boundaries similar to classical level bottom type communities, whereas the boundaries of others are almost impossible to detect, and these represent species distributed along an environmental continum.     

The effect of species response form on species distribution model prediction and inference

Ecological theory and current evidence support the validity of various species response curves according to a variety of environmental gradients. Various methods have been developed for building species distribution models but it is not well known how these methods perform under various assumptions about the form of the underlying species response. It is also not well known how spatial correlation in species occurrence affects model performance. These effects were investigated by applying an environmental envelope method (BIOCLIM) and three regression-based methods: logistic regression (LR), generalized additive modelling (GAM), and classification and regression tree (CART) to simulated species occurrence data. Each simulated species was constructed as a sum of responses with varying weights. Three basic species response curves were assumed: Gaussian (bell-shaped), Beta (skew) and linear. The two non-linear responses conform to standard ecological niche theory. All three responses were applied in turn to three simulated environmental variables, each with varying degrees of spatial autocorrelation. GAM produced the most consistent model performance over all forms of simulated species response. BIOCLIM and CART were inclined to underrate the performance of variables with a linear response. BIOCLIM was less sensitive to data density. LR was susceptible to model misspecification. The use of a linear function in LR underestimated the performance of variables with non-linear species response and contributed to increased spatial autocorrelation in model residuals. Omission of important environmental variables with non-linear species response also contributed to increased spatial autocorrelation in model residuals. Adding a spatial autocovariate term to the LR model (autologistic model) reduced the spatial autocorrelation and improved model performance, but did not correct the misidentification of the dominant environmental determinant. This is to be expected since the autologistic approach was designed primarily for prediction and not for inference. Given that various forms of species response to environmental determinants arise commonly in nature: (1) higher order functions should always be tested when applying LR in modelling species distribution; (2) spatial autocorrelation in species distribution model residuals can indicate that environmental determinants with non-linear response are missing from the model; and (3) deficiencies in LR model performance due to model misspecification can be addressed by adding a spatial autocovariate to the model, but care should be taken when interpreting the coefficients of the model parameters.     

辽河口湿地生态系统健康诊断与评价

综合考虑生态系统健康标准及河口湿地的生态特征,借鉴压力-状态-响应(pressure-state-response,PSR)模型,从压力、环境状态以及生物响应3方面构建辽河口湿地生态系统健康评价指标体系,并引入突变级数法,对1996年和2000年辽河口湿地生态系统健康状况进行了评价和分析。结果表明,1996年辽河口湿地生态系统健康度为0.979 1,2000年则降至0.961 8,即由健康状态转为亚健康状态,其主要原因为水资源不足和石油类污染加剧。应加强对辽河口湿地区域石油开采的管理,并合理分配利用水资源,保障湿地生态用水,促进辽河口湿地的生态系统健康。     

Predicting Invasiveness of Plant Species Based on Biological Information

Abstract: Previous studies suggest that, within particular groups of plant species, biological attributes can be used to predict the potential invasiveness of species that are intentionally introduced for horticultural or agricultural purposes. We examined the broad question of whether commonly available biological information can predict the invasiveness of a wide range of intentionally and accidentally introduced species. We collected information from published floras on 165 pairs of plant species. In each pair, one species originated in Europe and successfully invaded New Brunswick, Canada, and the other was a congeneric species that has not invaded North America. Only three biological characters—lifeform, stem height, and flowering period—and European geographic range were known for all species. We conducted multiple logistic regression analyses using two-thirds (110) of the species pairs and tested the predictive ability of resulting models using the remaining 55 pairs. Although a significant logistic regression model was obtained using the biological attributes, the model could not predict invasiveness of the test species pairs. In contrast, a model using only European range successfully predicted invasiveness in 70% of the test species. The importance of geographic range suggests that prediction of invasiveness on a species-by-species basis is not likely to help stem the flow of accidentally introduced invasive species. Species that are inadvertently picked up and moved to a new location due to their wide distribution are the same species that are likely to succeed in a new environment due to their wide environmental tolerances.     

Life history strategy of a southern European population of brown shrimp (Crangon crangon L.): evidence for latitudinal changes in growth phenology and population dynamics

This study provides a comprehensive examination of the life cycle dynamics of the brown shrimp (Crangon crangon L.) in the Mondego estuary, Portugal, a habitat located near the southern edge of the range of this species in European waters. The phenology of all life stages was documented (from the occurrence of ovigerous females, developing embryos, planktonic larvae and benthic post-larvae), and migration patterns of larvae into and out of the estuary were examined. Temperature-dependent functions of egg and larval development were combined with data on field abundance to predict the timing and magnitude of occurrence of larvae and recruits. Compared to brown shrimp at higher latitudes, southern conspecifics grow slower, mature earlier and have smaller brood sizes, and larvae have a more protracted settlement period. The Mondego estuary, besides acting as nursery area, is a dynamic platform for C. crangon to use in different stages, sizes and seasons.     

Laboratory study of effects of temperature and salinity on survival and larval development of a population of Rhithropanopeus harrisii from the Mondego River estuary,Portugal

Rhithropanopeus harrisii (Gould) is an introduced species in the estuary of the Mondego River (Portugal): it was first recorded from the Iberian Peninsula in 1989. The larval development of this population was studied under laboratory conditions at different temperatures and salinities, and showed a larval development pattern very similar to that reported for American estuarine populations of this species. Larval development was negatively correlated with temperature. Time to megalopa varied between 7 and 35 d; the first crab (C₁) was reached after a maximum of 11 to 43 d. Larval development was optimum at 25°C and 15S. Larval survival was maximum at 10, 15 and 20S at all three temperatures studied (20, 25 and 30°C). The percentage of abnormal megalopae increased with increasing salinity to a maximum (100%) at 30S; incidence of abnormality was not affected by temperature.     

Comparison of larval fish assemblages in three large estuarine systems, KwaZulu-Natal, South Africa

 The structure of the larval fish assemblages in three large estuarine systems on the KwaZulu-Natal coast of South Africa was examined using a combination of univariate, distributional and multivariate techniques. The database was comprised of a full annual set of larval fish samples taken from each estuarine system: Durban Harbour, Richards Bay Harbour and St Lucia Estuary. The mean monthly densities of each species in each system were used in the species matrix, and the mean monthly values of salinity, temperature and turbidity were used in the environmental matrix. The mean species diversity and evenness index were significantly higher in Durban Harbour (H′ = 1.03, J′ = 0.65) than in the other two systems. The cumulative dominance curve showed that St Lucia Estuary has a high dominance of a few species, with Richards Bay Harbour intermediate and Durban Harbour being the most diverse. Classification and MDS (multiple-dimensional scaling) analyses of larval fish densities in all three systems grouped together into three main clusters on the basis of system. The species similarity matrix (inverse analysis) clustered into five groups at the 25% similarity level. The MDS analysis of the same matrix showed that the groups separated out according to the degree of estuarine association of a species and hence habitat type. The species most responsible for system groupings were: Glossogobius callidus, Gilchristella aestuaria, Stolephorus holodon, Croilia mossambica and Gobiid 12. The “best fitting” of the environmental variables to explain the larval fish community patterns in each system was turbidity on its own (weighted Spearman's rank correlation, ρ_w = 0.55). The relationship of larval densities to environmental conditions was shown to be species-specific with estuarine species (e.g. G. callidus and G. aestuaria), having a strong positive correlation with temperature and turbidity but negative correlations with salinity. In summary, much longer term studies with more sites within each system are needed to assess whether the larval fish assemblages are stable or at an equilibrium (both spatially and temporally) and whether these assemblages are indicative of the relative “health” and nursery function of the system. Received: 28 April 1999 / Accepted: 30 May 2000     

Improving inferences about private land conservation by accounting for incomplete reporting

Private lands provide key habitat for imperiled species and are core components of function protectected area networks; yet, their incorporation into national and regional conservation planning has been challenging. Identifying locations where private landowners are likely to participate in conservation initiatives can help avoid conflict and clarify trade-offs between ecological benefits and sociopolitical costs. Empirical, spatially explicit assessment of the factors associated with conservation on private land is an emerging tool for identifying future conservation opportunities. However, most data on private land conservation are voluntarily reported and incomplete, which complicates these assessments. We used a novel application of occupancy models to analyze the occurrence of conservation easements on private land. We compared multiple formulations of occupancy models with a logistic regression model to predict the locations of conservation easements based on a spatially explicit social–ecological systems framework. We combined a simulation experiment with a case study of easement data in Idaho and Montana (United States) to illustrate the utility of the occupancy framework for modeling conservation on private land. Occupancy models that explicitly accounted for variation in reporting produced estimates of predictors that were substantially less biased than estimates produced by logistic regression under all simulated conditions. Occupancy models produced estimates for the 6 predictors we evaluated in our case study that were larger in magnitude, but less certain than those produced by logistic regression. These results suggest that occupancy models result in qualitatively different inferences regarding the effects of predictors on conservation easement occurrence than logistic regression and highlight the importance of integrating variable and incomplete reporting of participation in empirical analysis of conservation initiatives. Failure to do so can lead to emphasizing the wrong social, institutional, and environmental factors that enable conservation and underestimating conservation opportunities in landscapes where social norms or institutional constraints inhibit reporting.     

Empirical realised niche models for British coastal plant species

Coastal environments host plant taxa adapted to a wide range of salinity conditions. Salinity, along with other abiotic variables, constrains the distribution of coastal plants in predictable ways, with relatively few taxa adapted to the most saline conditions. However, few attempts have been made to quantify these relationships to create niche models for coastal plants. Quantification of the effects of salinity, and other abiotic variables, on coastal plants is essential to predict the responses of coastal ecosystems to external drivers such as sea level rise. We constructed niche models for 132 coastal plant taxa in Great Britain based on eight abiotic variables. Paired measurements of vegetation composition and abiotic variables are rare in coastal habitats so four of the variables were defined using community mean values for Ellenberg indicators, i.e. scores assigned according to the typical alkalinity, fertility, moisture availability and salinity of sites where a species occurs. The remaining variables were the canopy height, annual precipitation, and maximum and minimum temperatures. Salinity and moisture indicator scores were significant terms in over 80 % of models, suggesting the distributions of most coastal species are at least partly determined by these variables. When the models were used to predict species occurrence against an independent dataset 64 % of models gave moderate to good predictions of species occurrence. This indicates that most models had successfully captured the key determinants of the niche. The models could potentially be applied to predict changes to habitats and species-dependent ecosystem services in response to rising sea levels.     

Occurrence of the Dinoflagellate Gymnodinium Catenatum (Graham) Along the Mediterranean Coast of Alexandria (Egypt)

A monitoring programme during 4 years (1993-1996) was established in four eutrophic marine basins along the Mediterranean coast of Alexandria (Egypt) to follow the occurrence of a newly recorded dinoflagellate Gymnodinium catenatum and ambient environmental conditions. the species achieved its massive occurrence in warm seasons at low salinity, density stratified water column and different nutrient concentrations. A simple statistical approach showed temperature and phosphate to effect its distribution. Apparently no cases of toxic effect have accompanied the occurrence of G. catenatum. the regular occurrence of the species during the 4 year survey mean the existence of its benthic resting cysts, which certainly have important implications for its distribution dynamics.     

Hydrodynamic and ecological assessment of nearshore restoration: A modeling study

Along the Pacific Northwest coast, much of the estuarine habitat has been lost over the last century to agricultural land use, residential and commercial development, and transportation corridors. As a result, many of the ecological processes and functions have been disrupted. To protect and improve these coastal habitats that are vital to aquatic species, many projects are currently underway to restore estuarine and coastal ecosystems through dike breaches, setbacks, and removals. Understanding site-specific information on physical processes is critical for improving the success of such restoration actions. In this study, a three-dimensional hydrodynamic model was developed to simulate estuarine processes in the Stillaguamish River estuary, where restoration of a 160-acre parcel through dike setback has been proposed. The model was calibrated to observed tide, current, and salinity data for existing conditions and applied to simulate the hydrodynamic responses to two restoration alternatives. Model results were then combined with biophysical data to predict habitat responses within the restoration footprint. Results showed that the proposed dike removal would result in desired tidal flushing and conditions that would support four habitat types on the restoration footprint. At the estuary scale, restoration would substantially increase the proportion of area flushed with freshwater (<5 ppt) at flood tide. Potential implications of predicted changes in salinity and flow dynamics are discussed relative to the distribution of tidal marsh habitat.     

Testing the Stochastic Dynamic Methodology (StDM) as a management tool in a shallow temperate estuary of south Europe (Mondego, Portugal)

A long-term monitoring program has been carried out since the early 1990s in the Mondego estuary, on Portugal's west coast, which is presently under heavy human pressure. In this shallow warm-temperate estuary, a significant macroalgal proliferation has been observed, which is a clear sign of nutrient enrichment. As a result of competition with algae, the extension of the seagrass meadows (mainly Zostera noltii) has been reduced. The present paper examined the applicability of a holistic Stochastic Dynamic Methodology (StDM) in predicting the tendencies of trophic key-components (macrophytes, macroalgae, benthic macroinvertebrate and wading birds) as a response to the changes in estuarine environmental conditions. The StDM is a sequential modelling process developed in order to predict the ecological status of changed ecosystems, from which management strategies can be designed. The data used in the dynamic model construction included true gradients of environmental changes and was sampled from January 1993 to September 1995 and from December 1998 to December 2005. The dynamic model developed was preceded by a conventional multivariate statistical procedure performed to discriminate the significant relationships between the selected ecological components. The model validation was based on independent data collected from January 1996 to January 1997 and from February 1999 to April 2000 for all the state variables considered. Overall, the simulation results are encouraging since they seem to demonstrate the StDM reliability in capturing the trophic dynamics of the studied estuary, by predicting the behavioural pattern for the most part of the components selected, with a focus on the Zostera noltii meadows recovery after the implementation of important management measures.     

Invasion, Disturbance, and Competition: Modeling the Fate of Coastal Plant Populations

Abstract:  Wetland habitats are besieged by biotic and abiotic disturbances such as invasive species, hurricanes, habitat fragmentation, and salinization. Predicting how these factors will alter local population dynamics and community structure is a monumental challenge. By examining ecologically similar congeners, such as Iris hexagona and I. pseudacorus (which reproduce clonally and sexually and tolerate a wide range of environmental conditions), one can identify life-history traits that are most influential to population growth and viability. We combined empirical data and stage-structured matrix models to investigate the demographic responses of native ( I. hexagona ) and invasive ( I. pseudacorus ) plant populations to hurricanes and salinity stress in freshwater and brackish wetlands. In our models I. hexagona and I. pseudacorus responded differently to salinity stress, and species coexistence was rare. In 82% of computer simulations of freshwater marsh, invasive iris populations excluded the native species within 50 years, whereas native populations excluded the invasive species in 99% of the simulations in brackish marsh. The occurrence of hurricanes allowed the species to coexist, and species persistence was determined by the length of time it took the ecosystem to recover. Rapid recovery (2 years) favored the invasive species, whereas gradual recovery (30 years) favored the native species. Little is known about the effects of hurricanes on competitive interactions between native and invasive plant species in marsh ecosystems. Our models contribute new insight into the relationship between environmental disturbance and invasion and demonstrate how influential abiotic factors such as climate change will be in determining interspecific interactions.     

Does biodiversity of estuarine phytoplankton depend on hydrology?

Phytoplankton growth in estuaries is controlled by factors such as flushing, salinity tolerance, light, nutrients and grazing. Here, we show that biodiversity of estuarine phytoplankton is related to flushing, and illustrate this for some European estuaries.The implications for the definition of reference conditions for quality elements in estuaries of different types are examined, leading to the conclusion that constraints on the number of estuarine and coastal types that may be defined for management purposes require that quality classes take into account natural variability within types, in order to be ecologically meaningful. We develop a screening model to predict the growth rate required for a phytoplankton species to be present under different flushing conditions and apply it to estuaries in the EU and US to show how changes in physical forcing may alter biodiversity. Additional results are presented on the consequences for eutrophication, showing that changes in residence time may interact with species-specific nutrient uptake rates to cause shifts in species composition, potentially leading to effects such as harmful algal blooms.We discuss applications for integrated coastal zone management, and propose an approach to normalization of estuarine phytoplankton composition as regards species numbers.     

Modeling and Predicting Species Occurrence Using Broad-Scale Environmental Variables: an Example with Butterflies of the Great Basin

Abstract: If occurrence of individual species can be modeled as a function of easily quantified environmental variables (e.g., derived from a geographic information system [GIS]) and the predictions of these models are demonstrably successful, then the scientific foundation for management planning will be strengthened. We used Bayesian logistic regression to develop predictive models for resident butterflies in the central Great Basin of western North America. Species inventory data and values for 14 environmental variables from 49 locations (segments of canyons) in the Toquima Range ( Nevada, U.S.A.) were used to build the models. Squares of the environmental variables were also used to accommodate possibly nonmonotonic responses. We obtained statistically significant models for 36 of 56 (64%) resident species of butterflies. The models explained 8–72% of the deviance in occurrence of those species. Each of the independent variables was significant in at least one model, and squared versions of five variables contributed to models. Elevation was included in more than half of the models. Models included one to four variables; only one variable was significant in about half the models. We conducted preliminary tests of two of our models by using an existing set of data on the occurrence of butterflies in the neighboring Toiyabe Range. We compared conventional logistic classification with posterior probability distributions derived from Bayesian modeling. For the latter, we restricted our predictions to locations with a high ( 70%) probability of predicted presence or absence. We will perform further tests after conducting inventories at new locations in the Toquima Range and nearby Shoshone Mountains, for which we have computed environmental variables by using remotely acquired topographic data, digital-terrain and microclimatic models, and GIS computation.     

Influence of environmental variables on the fish fauna of the deeper waters of a large Australian estuary

Fish were collected by gill nets from the deeper waters of the Entrance Channel, basins and rivers of the large Peel-Harvey estuarine system (south-western Australia) in the wet (June to November) and dry (December to May) periods between August 1979 and July 1981. Simple-regression analysis showed that the number of species, abundance and biomass of fish in the rivers rose with increases in the salinity and temperature of both the surface and bottom of the water column. No such significant correlations were found in the Entrance Channel andbasins (Peel Inlet and Harvey Estuary), where salinity changes were far less marked. The number of species at sites throughout the estuary was inversely correlated with distance from the estuary mouth. Multiple-regression equations showed that, compared with the other environmental variables tested, bottom salinity had a greater influence on the nunber of species and abundance both in the rivers and in the system as a whole. These results indicate that salinity has a greater effect on the fauna in the deeper waters than in the shallows (cf. Loneragan et al., 1986). The larger fish which characterise the deeper waters may thus be less tolerant to low salinities than the smaller fish typically found in the shallows. Both classification and ordination separated the faunal composition of the rivers from those of the Entrance Channel and basins. The fauna of the two narrow and deeper sites in the rivers separated into wet- and dry-period components. Differences between the faunal composition of the riverine regions and those of the Entrance Channel and basins have been related to the much more variable and lower minimum salinities in the rivers. Species characteristic of the rivers included Amniataba caudavittatus, which is estuarine sensu stricto in south-western Australia, the semianadromous Nematalosa vlaminghi and the highly euryhaline Mugil cephalus. The indicator species for the Entrance Channel and basins were all marine species (Cnidoglanis macrocephalus, Hyporhamphus melanochir, Gerres subfasciatus and Pomatomus saltator).     

胶州湾多毛类环节动物数量分布与环境因子的关系

根据1998~2002年胶州湾10个站各季度大型底栖动物调查结果,讨论了多毛类环节动物在各站出现种数、生物量、栖息密度与环境因子的关系.结果表明,海底底质是影响多毛类数量分布与变化的重要因子,沙质软泥有利于多毛类生长,而粗沙砾石底质多毛类分布较少;春季多毛类种数、生物量和栖息密度均较高;在一定条件下,盐度是多毛类的限制因子,当盐度升高时,其生物量和栖息密度呈增加趋势.图2表6参14     

Rookery Bay and Naples Bay circulation simulations: Applications to tides and fresh water inflow regulation

A three-dimensional, baroclinic numerical circulation model is applied to the combined Rookery Bay and Naples Bay estuary complex. We focus on two aspects of the model simulations: the tidal circulation, for which we have observations of sea level and currents at several stations spanning Rookery Bay, and the salinity variations, for which we have observations at one station. After establishing model veracity through quantitative comparisons with observations, we use the model to address salinity changes that could arise due to regulatory fresh water flow rate modifications. Two different sets of experiments are performed. The first considers the salinity changes in Rookery Bay by increasing the fresh water flow rates into Henderson Creek through the addition of either 1.4 m³/s or 2.8 m³/s to the ambient flow rates. The second considers the salinity changes in Naples Bay by decreasing the fresh water flow rates through the subtraction of 9.9 m³/s from the Golden Gate Canals’ ambient flow rates. All of these scenarios result in significant, quantifiable salinity changes within the Rookery Bay and Naples Bay estuary complexes, demonstrating the environmental management utility of using high resolution, three-dimensional, numerical circulation models, as applied herein, for assessing the water properties of complex, multi-connected estuarine systems.