Spatio-temporal dissolved oxygen dynamics in the Orbetello lagoon by fuzzy pattern recognition

This paper models the dissolved oxygen (DO) dynamics in the Orbetello lagoon as a function of the physico-chemical and ecological system variables, including the submerged vegetation, nutrients, and hydrodynamics. It should be viewed as the concluding sequel to a previous paper describing the dynamics of the lagoon ecosystem [Giusti, E., Marsili-Libelli, S., 2006. An integrated model for the Orbetello lagoon ecosystem, Ecol. Model. 196, 379–394] by introducing the missing DO dynamics. The model considers the oxygen demand originating from the decay of carbonaceous and nitrogenous compounds, as well as photosynthesis and natural reaeration by winds and currents as the oxygen producing processes. With a fixed-parameter set the model could accurately reproduce each single circadian DO cycle, but in the long run it failed to extend this fit and could not accommodate the large DO fluctuations induced by the seasonal variability. In order to enhance the model flexibility, a fuzzy pattern recognition algorithm was designed to classify the circadian DO patterns into four typical behaviours, related to the season, and estimate the corresponding parameters, with the overall model output being a fuzzy combination of these sets. The paper discusses several methods to patch the parameter sets and compares their performance in tracking long-term DO variations. A final assessment of the model validity is obtained by incorporating the whole DO dynamics (model, fuzzy pattern recognition and parameter combination) into the general lagoon model and producing a consistently correct series of DO daily distributions over a yearly cycle. Thus the paper contains both a practical and a methodological aspect. The practical one is the linking of all the lagoon dynamics to the dissolved oxygen kinetics in order to clarify to what extent macroalgae and macrophytes influence the oxygen balance. The methodological aspect consists of extending the validity of short-term models to long time-horizons through a patching technique supported by fuzzy pattern recognition.     

A preliminary model of nutrient cycling in sediments of a Mediterranean lagoon

A model of nitrogen and phosphorus cycles in the sediment of a lagoon has been developed. This model was applied to the Thau lagoon (southern France). Sediment was sliced in three layers to reproduce the oxygen profile, which is simulated within the model. Following an equilibrium hypothesis, the model was calibrated against field data. State variables and fluxes were estimated in the sediment and across the sediment-water interface. A Monte Carlo sensitivity analysis was performed to determine the most sensitive parameters and sediment state variables. A dynamic simulation with varying oxygen concentrations then showed the influence of anoxia on the phosphorus and nitrogen fluxes between water and sediment.     

Sediments distribution of trace metals in a coastal lagoon (Southern Sardinia,Mediterranean Sea): assessment of contamination and ecological risk

Coastal lagoons are subject to several sources of contaminations. To shade light on the contamination level of the Santa Gilla lagoon (Tyrrhenian Sea) we investigated the spatial distribution of Cr, Ni, Pb, Zn and Hg in sediments and their correlation with grain size and organic matter contents. Moreover, sediment contamination levels and the ecological risk associated with metal concentration were assessed using different abiotic indicators. The lagoon is characterised by low levels of contamination, with exceptions for Pb and Hg, whose distribution reflects the position of an old chlor-alkali plant and that of an airport. These results indicate that the restoration put in place 30 years ago have not reached the expected target and that the presence of the airport deserves further attention. In the outer section of the lagoon, where clam fishery occurs, we observed low levels of contamination suggesting that such artisanal fishery could somehow help mobilising metals. We conclude that the area exposed to Hg pollution, though tentatively restored, still suffers of a potential risk of ecosystem deterioration. We pinpoint that further investigations on the mobility, bioavailability and toxicity of metals are needed to finally address the actual impairment of the Santa Gilla lagoon.     

Modelling the responses of the Lagoon of Venice ecosystem to variations in physical forcings

A Finite Element Ecological Model for the Lagoon of Venice (VELFEEM) has been used to test the responses of the Lagoon of Venice ecosystem to variations in physical conditions.The model is obtained by coupling a finite element hydrodynamic model, that computes the velocity fields of water, an energetic model to compute the water temperature fields, and an ecological model that simulates the dynamic of phytoplankton, zooplankton, nutrients (ammonia, nitrate and phosphate) organic detritus (organic nitrogen, organic phosphorous and CBOD) and dissolved oxygen.The transport model is a two-dimensional barotropic finite element model which allows for a better resolution of the lagoon morphology.The ecological model has been developed by starting from the ecological module EUTRO of WASP (Water Analysis Simulation System released by US EPA), and by adapting it to the peculiarity of the Lagoon of Venice.A reference condition has been identified by running a 1-year simulation under climatologic condition. Then, the sensitivity to physical forcing (tide and wind) and to the input of macronutrients has been investigated, by comparing model predictions of spatial and temporal evolution of major state variables and of an aggregate index of Water Quality Trophic Index (TRIX).     

Assessing wetland changes in the venice lagoon by means of satellite remote sensing data

Not only does lagoon ecology represent a transitional zone between the sea and the continent but it also expresses the equilibrium belt between erosion and sedimentation processes. Within the framework of a coastal management scheme, a precise and timely mapping of morphological changes in this environment is important. This paper illustrates the possible contribution of multi-temporal satellite observations in the monitoring of the erosion/sedimentation processes of coastal zones, where landscape features are subjected to highly morphodynamical modifications. In particular, an improved mapping accuracy was obtained by the successive application of the Maximum Likelihood (MLH) classifier and the Linear Mixture Model (LMM) techniques to the satellite image classification procedure. In fact, by estimating the amount of shallow water and wetland within each satellite pixel, the LMM technique allows for an accurate mapping of the transitional zones in the lagoon environment, thus permitting an optimal separation between land and water. The study concerns the Venice lagoon (Italy) which has been sinking slowly since the beginning of this century. This has led to widespread loss of wetlands. In order to monitor the development of the land cover, four Landsat Thematic Mapper scenes were examined, during the period 1984 to 1993. The results obtained proved that the digital analysis method of multitemporal satellite imagery, applied over a selected test area, enables the evolution of an estuarine environment landscape, with its different sequences of erosion and periods of accretion, to be monitored. The significant influence of tidal stages is discussed in the data analysis.     

Implications of a simple competition model for the stability of an intercropping system

It is a common view that intercropping systems of agricultural crops produce more stable yields than do systems in which the same crops are grown in monoculture. This paper discusses a modelling approach which has been used to support the notion that whether or not intercropping is more stable than monoculture depends on the mode of interaction among crops, i.e. whether two different crops suppress or enhance each other. It is shown here that this notion is not supported by the model used. We conclude that the relative merits of the two cropping systems depend on the proportion of land allocated to each crop rather than on the mode of interaction. The model suggests that if the optimum allocation of land is considered, both systems will be equally stable.     

Modelling partitioning and distribution of micropollutants in the lagoon of Venice: a first step towards a comprehensive ecotoxicological model

The model presented in this paper integrates a large amount of recent and ad hoc collected data concerning environmental contamination from micropollutants in the lagoon of Venice. This model represents the first step in setting up of an ecotoxicological model for the Venice lagoon, to simulate fate of contaminants from abiotic matrices to organisms. Distribution and partitioning of organic and inorganic contaminants are modelled by a two-dimensional model, based both on deterministic and empirical submodels and adapted to a large spectrum of different substances (polychlorinated dibenzo-dioxins/polychlorinated dibenzo-furans (PCDD/F), polychlorinated biphenyls (PCBs), heavy metals). The model was successfully calibrated on a wide set of experimental data. Sensitivity analysis showed that the model is generally not very sensible to parameters values but it is sensible to external conditions (e.g., pollutants loads). Distribution of dissolved and total concentrations of contaminants was obtained for a series of PCDD/F and PCBs congeners and for eight heavy metals. These distributions represent integrated information on ecosystem health, complementary to monitoring data and they are useful to be used for comparisons with various water quality criteria. Simulation scenarios under different external conditions are proposed as examples of use of the model for management purposes.     

A mathematical model for the distribution and abundance of benthic algae in a Norwegian fjord

A mathematical model has been developed to study the distribution and abundance of benthic algae species in a Norwegian fjord. The main forcing functions are the physical factors which have well defined gradients in this area, but biotic interactions are also accounted for in the model.The distribution of algae along vertical transects in the intermediate fjord area has been simulated, and the observed distribution is reproduced fairly well. This indicates that the major factors determining the equilibrium elevation between intertidal and subtidal vegetations in this area are adequately represented in the model.Based on observations in a fjord branch with a high level of freshwater influx and polluted by heavy metals, assumptions are made of the combined influence of these contaminants on growth characteristics of the species considered. The resulting effects on community development and community patterns are simulated. For a certain level of contamination, the decrease in abundance, community development rate and species separation have been determined. It is also shown that the fluctuations in biomass during a year are more pronounced than under unaffected conditions.The relative importance of external growth regulating factors and self-shading is demonstrated for different degrees of community development, and we have indicated that this may be an important factor in the assessment of transient and long-term responses to “natural” and man-made influences on the shore-line vegetation.One of the main problems during model development was the formulation of the interaction function for factors influencing growth parameters. Several alternatives were examined.The differences between the most frequently used forms were small with respect to abundance and not very large with respect to possible changes in distribution. It was noted that even by including only the most limiting factor at each instant, (Liebig's form) a high percentage of the potentially limiting factors did actually limit growth during periods of the year.The model is intended as a working tool for the studies of changes in the shore-line vegetation caused by man-made interferences like heavy metal and oil pollution, and we believe that the results presented demonstrate that it can successfully be used for this purpose.     

Mapping woodland vegetation in SW Ethiopia based on a hybrid model

SUMMARY

Despite the fact that indigenous inhabitants have sustainably managed the forests and woodlands for centuries, Ethiopia's woodland resources are now under severe pressure. At the request of the Ethiopian Government, in 1996/97 the Savanna Woodland Management Study Project was initiated by the German Technical Cooperation (GTZ). A detailed analysis of the woodland resources in SW Ethiopia and a vegetation map were produced. The map was generated using multispectral remote-sensing data, and provides details of the variety within Ethiopian woodlands. A hybrid data classification procedure was applied to incorporate relief and climatic conditions. After analysis of the remote sensing data by image processing, a spatial overlay was performed to incorporate the additional site condition factors. The vegetation map shows the spatial distribution of all existing woodland types in the area and enhances our knowledge of the rich biodiversity of SW Ethiopia. Such mapping gives us a better understanding of existing ecosystems and indigenous land-use systems, and hence, can lead to more sustainable management of the natural resources in the future.     

Application of a Random Forest algorithm to predict spatial distribution of the potential yield of Ruditapes philippinarum in the Venice lagoon, Italy

We present a modelling framework that combines machine learning techniques and Geographic Information Systems to support the management of an important aquaculture species, Manila clam (Ruditapes philippinarum). We use the Venice lagoon (Italy), the first site in Europe for the production of R. philippinarum, to illustrate the potential of this modelling approach. To investigate the relationship between the yield of R. philippinarum and a set of environmental factors, we used a Random Forest (RF) algorithm. The RF model was tuned with a large data set (n = 1698) and validated by an independent data set (n = 841). Overall, the model provided good predictions of site-specific yields and the analysis of marginal effect of predictors showed substantial agreement among the modelled responses and available ecological knowledge for R. philippinarum. The most influent environmental factors for yield estimation were percentage of sand in the sediment, salinity, and water depth. Our results agree with findings from other North Adriatic lagoons. The application of the fitted RF model to continuous maps of all the environmental variables allowed estimates of the potential yield for the whole basin. Such a spatial representation enabled site-specific estimates of yield in different farming areas within the lagoon. We present a possible management application of our model by estimating the potential yield under the current farming distribution and comparing it to a proposed re-organization of the farming areas. Our analysis suggests a reduction of total yield is likely to result from the proposed re-organization.     

Linking species- and ecosystem-level impacts of climate change in lakes with a complex and a minimal model

To study the interaction between species- and ecosystem-level impacts of climate change, we focus on the question of how climate-induced shifts in key species affect the positive feedback loops that lock shallow lakes either in a transparent, macrophyte-dominated state or, alternatively, in a turbid, phytoplankton-dominated state. We hypothesize that climate warming will weaken the resilience of the macrophyte-dominated clear state. For the turbid state, we hypothesize that climate warming and climate-induced eutrophication will increase the dominance of cyanobacteria. Climate change will also affect shallow lakes through a changing hydrology and through climate change-induced eutrophication. We study these phenomena using two models, the full ecosystem model PCLake and a minimal dynamic model of lake phosphorus dynamics. Quantitative predictions with the complex model show that changes in nutrient loading, hydraulic loading and climate warming can all lead to shifts in ecosystem state. The minimal model helped in interpreting the non-linear behaviour of the complex model. The main output parameters of interest for water quality managers are the critical nutrient loading at which the system will switch from clear to turbid and the much lower critical nutrient loading – due to hysteresis – at which the system switches back. Another important output parameter is the chlorophyll-a level in the turbid state. For each of these three output parameters we performed a sensitivity analysis to further understand the dynamics of the complex model PCLake. This analysis showed that our model results are most sensitive to changes in temperature-dependence of cyanobacteria, planktivorous fish and zooplankton. We argue that by combining models at various levels of complexity and looking at multiple aspects of climate changes simultaneously we can develop an integrated view of the potential impact of climate change on freshwater ecosystems.     

TWIN: a TWo-stage INdex to evaluate ecological quality status in lagoon environments by means of hard bottom zoobenthos

The macrobenthos colonizing the artificial hard bottoms in lagoons has been used in biomonitoring programs as it requires easy sampling procedures and provides a variety of responses to different environmental pressures, like marine or continental influence, eutrophication, and urban pollution. In this paper we present the development and application of a new TWo-stage INdex (TWIN), aimed to assess water quality of lagoon environments using the hard bottom macrobenthos community. TWIN is calculated in two separate stages. First, the presence and abundance of macrobenthic species are used to define, through a fuzzy model, a station's membership grade in six pre-defined ecological sectors (Lagoon Mouth, Vivified Lagoon, Rough Eutrophic, Calm Eutrophic, Urban, Estuarine), each corresponding to characteristic communities. Then a formula links the membership grades to the five ecological status classes ranging from high to bad quality, as requested by the European Water Framework Directive. This method was tested in four Adriatic lagoons: the results are consistent with literature information and expert judgement, therefore we propose its use in the definition of water quality in lagoons.     

Assessment of the effects of a port expansion on algae appearance in a costal bay through mathematical modelling. Application to San Lorenzo Bay (North Spain)

In the last years several episodes of algae appearance affecting bathing areas have been observed in San Lorenzo Bay (north of Spain). The analysis of the collected algae revealed that they might come from near intertidal or shallow subtidal zones due to eutrophication processes or through drift algae movement by the action of marine currents. In the vicinity of this area, the expansion of the Port of Gijón (now under construction) supposes a significant modification of the coastal geometry. The magnitude of such an expansion could cause changes in the patterns of currents in the bay, with the consequent alteration of the observed algal appearance phenomena. A mathematical modelling study to evaluate the risk of generation of eutrophication processes in the San Lorenzo Bay area and the transport of drift algae from near sea bed areas was developed. This study required the use of different hydrodynamic models in order to characterize the currents caused by tides, winds and waves. The eutrophication processes in the bay were analyzed with a depth-averaged two-dimensional eutrophication model which deals with eight water quality variables. Calibration of model parameters with the observed data from a field survey was performed. A reasonable agreement with the field measurements was achieved. Model results showed that the maximum phytoplankton concentrations were below eutrophic conditions. Although, the port expansion has led to an increment of phytoplankton concentrations, chlorophyll a levels were not representative of eutrophic conditions. To analyse the transport of drift algae, a methodology based on the utilization of a two-dimensional model which solves the depth-averaged advection-diffusion equation considering seaweed as a conservative tracer was developed and applied. Numerical modelling allowed the identification of the coastal areas that seems to be the source of the seaweed found on the beach. It was also proven that port expansion does not significantly affect drift algae transport in the area.     

Allowing macroalgae growth forms to emerge: Use of an agent-based model to understand the growth and spread of macroalgae in Florida coral reefs,with emphasis on Halimeda tuna

The growth patterns of macroalgae in three-dimensional space can provide important information regarding the environments in which they live, and insights into changes that may occur when those environments change due to anthropogenic and/or natural causes. To decipher these patterns and their attendant mechanisms and influencing factors, a spatially explicit model has been developed. The model SPREAD (SPatially-explicit Reef Algae Dynamics), which incorporates the key morphogenetic characteristics of clonality and morphological plasticity, is used to investigate the influences of light, temperature, nutrients and disturbance on the growth and spatial occupancy of dominant macroalgae in the Florida Reef Tract. The model species, Halimeda and Dictyota spp., are modular organisms, with an “individual” being made up of repeating structures. These species can also propagate asexually through clonal fragmentation. These traits lead to potentially indefinite growth and plastic morphology that can respond to environmental conditions in various ways. The growth of an individual is modeled as the iteration of discrete macroalgal modules whose dynamics are affected by the light, temperature, and nutrient regimes. Fragmentation is included as a source of asexual reproduction and/or mortality. Model outputs are the same metrics that are obtained in the field, thus allowing for easy comparison. The performance of SPREAD was tested through sensitivity analysis and comparison with independent field data from four study sites in the Florida Reef Tract. Halimeda tuna was selected for initial model comparisons because the relatively untangled growth form permits detailed characterization in the field. Differences in the growth patterns of H. tuna were observed among these reefs. SPREAD was able to closely reproduce these variations, and indicate the potential importance of light and nutrient variations in producing these patterns.     

A model of nematode dynamics in the Westerschelde Estuary

We developed a time dynamic model to investigate the temporal dynamics of nematode community in the brackish zone of the Westerschelde Estuary. The biomass of four nematode feeding groups observed from March 1991 to February 1992 is used to calibrate the model. Using environmental data as the input, the model predicts the temporal modification and interrelation of four nematode feeding groups. Nematodes achieve a dominant position in the community because of their lower loss rate (in respiration, excretion and natural death). Predators which are deposit-feeding macrobenthos control the variations of dominant nematodes, such as omnivores and non-selective deposit feeders. Food availability causes modification only for rare nematodes such as epigrowth feeders and selective deposit feeders. Temperature is a factor affecting both predation death and a loss including respiration, excretion and natural death. Overall, the modification of nematode community by food availability is much lower than by predator. The macrobenthos in the Westerschelde Estuary decrease from upstream to the estuarine mouth. The stability and standing stock of nematode population follow the opposite gradient of their predators. They increase from upstream to the estuarine mouth.     

Application of a spatial meta-population model with stochastic parameters to the management of the invasive grass Nassella trichotoma in North Canterbury, New Zealand

Optimising the management of invasive plants requires the identification of the population size outcomes for alternative management strategies. Mathematical models can be useful tools for making such management strategy comparisons. In this paper we develop a generic landscape meta-population model and apply it to the weedy grass, Nassella trichotoma, an invasive species occupying approximately 800 land parcels, predominantly pastoral farms, in the Hurunui district, North Canterbury, New Zealand. Empirical evidence reveals that this meta-population is currently stable (at a median density of 6 plants ha⁻¹) under a community strategy requiring manual removal (termed ‘grubbing’) of plants annually from all land parcels. Reduction in population size requires an alternative management strategy. Field data, collected over a 12 year period, were used to provide stochastic parameter values for land parcel size, carrying capacity, rates of local population growth and grubbing.The model reveals that at steady state, the most significant contribution to population growth on a land parcel comes from within the land parcel itself; the expected annual per capita growth on an individual land parcel is 4 orders of magnitude greater than the expected annual contribution from plants arising from other land parcels. This result implies that many of the farms currently supporting N. trichotoma may pose little or no threat to, nor are threatened themselves by, other farms infested by the weed. However, the steady state distribution (of the weed's population density) was sensitive to the spread rate, revealing a need for data on this process. It was also sensitive to how any increase in the grubbing rate is distributed; increasing it via a uniform distribution U(0, 1) where all rates between 0 and 100% year⁻¹ are equally probable did not affect the steady state, whereas increasing the rates via the uniform distribution U(0.25, 0.75) resulted in fewer farms with high population densities. In general the model provides a basis for exploring the effects of a wide range of alternative grubbing strategies on population growth in N. trichotoma.     

Assessment of petroleum hydrocarbon in a tropical brackish water lagoon: Chilika,India

Assessment of petroleum hydrocarbon (PHC) in the Chilika Lagoon, India, revealed a significant spatio-temporal variation in surface water (analysis of variance: n?=?120, p?相似文献   

黄河三角洲潮沟湿地植被空间分布对土壤环境的响应

潮沟在黄河三角洲广泛存在,且分布有多种独特的湿地植被类型。通过设置有代表性的28个样地,获取了植被种类、多度和土壤环境因子数据;并运用双指示物种（TWINSPAN）,对黄河三角洲潮沟分布区植被进行了群落类型划分,得出研究区共有7种类型植物群落;同时利用典范对应分析（CCA）阐明了这些植被群落空间分布与土壤环境因子之间的关系,其分析结果显示构成黄河三角洲土壤盐分的主要是Cl-和Na＋,距离海洋的远近和土壤含水量共同影响土壤含盐量,盐地碱蓬和中华柽柳分布主要取决于土壤含盐量、Na＋含量及距离海洋距离,而各种植被类型的分布与土壤全磷（TP）、全氮（TN）、有机质、Ca2＋及Mg2＋含量存在一定的关系。