The Reynolds transport theorem: Application to ecological compartment modeling and case study of ecosystem energetics

The Reynolds transport theorem (RTT) from mathematics and engineering has a rich history of success in mass transport dynamics and traditional thermodynamics. This paper introduces RTT as a complementary approach to traditional compartmental methods used in ecological modeling and network analysis. A universal system equation for a generic flow quantity is developed into a generic open-system differential expression for conservation of energy. Nonadiabatic systems are defined and incorporated into control volume (CV) and control surface (CS) perspectives of RTT where reductive assumptions in empirical data are then formally introduced, reviewed, and appropriately implemented. Compartment models are abstract, time-dependent systems of simultaneous differential equations describing storage and flow of conservative quantities between interconnected entities (the compartments). As such, they represent a set of flexible and somewhat informal, assumptions, definitions, algebraic manipulations, and graphical depictions subject to influence and selectively parsed expression by the modeler. In comparison, RTT compartment models are more rigorous and formal integro-differential equations and graphics initiated by the RTT universal system equation, forcing an ordered identification of simplifying assumptions, ending with clearly identified depictions of the transfer and transport of conservative substances in physical space and time. They are less abstract in the rigor of their equation development leaving less ambiguity to modeler discretion. They achieve greater consistency with other RTT compartment style models while possibly generating greater conformity with physical reality. Characteristics of the RTT approach are compared with those of a traditional compartment model of energy flow in an intertidal oyster-reef community.     

A Markov model for assessing ecological stability properties

Ecological systems are frequently modeled as dynamic systems. It is natural then to use the techniques of dynamic systems theory to analyze such models. However, the methods and results that are produced by dynamic systems theory do not always capture the aspects of ecological systems that are of greatest interest to managers and decision-makers. We identify some of the challenges of using dynamic systems theory to explore ecological systems and propose an alternative approach that emphasizes the understanding of transient effects in light of uncertainty and variability. We illustrate this method by an examination of a model for phosphorus levels in fresh water lakes.     

Multiple-pattern parameter identification and uncertainty analysis approach for water quality modeling

This paper presents a multiple-pattern parameter identification and uncertainty analysis approach for robust water quality modeling using a neural network (NN) embedded genetic algorithm (GA). The modeling approach uses an adaptive NN–GA framework to inversely solve the governing equations in a water quality model for multiple parameter patterns, along with an alternating fitness method to maintain solution diversity. The procedure was demonstrated through a coupled 2D hydrodynamic and eutrophication model for Loch Raven Reservoir in Maryland. The inverse problem was formulated as a nonlinear optimization problem minimizing the degree of misfit (DOM) between model results and observed data. A set of NN models was developed to approximate the input-output response relationship of the Loch Raven Reservoir model and was incorporated into a GA framework in an adaptive fashion to search for near-optimal solutions minimizing the DOM. The numerical example showed that the adaptive NN–GA approach is capable of identifying multiple parameter patterns that reproduce the observed data equally well. The resulting parameter patterns were incorporated into the numerical model, and a multiple-pattern robust water quality modeling analysis, along with a compound margin of safety (CMOS) method, was proposed and applied to analyze the parameter pattern uncertainty.     

Connectivity or demography: Defining sources and sinks in coral reef fish metapopulations

The identity of an individual patch as a source or a sink within a metapopulation is a function of its ability to produce individuals and to disperse them to other patches. In marine systems patch identity is very often defined by dispersal ability alone—upstream patches are sources—while issues of variable habitat quality (which affects local production) are ignored. This can have important ramifications for the science of marine reserve siting. This study develops a spatially explicit source–sink metapopulation model for reef fish and uses it to evaluate the relative importance of connectivity versus demography and how this depends upon the level of local larval retention and the strength of density-dependent recruitment. Elasticity analyses indicated that patch contribution (source or sink) was more sensitive to demographic parameters (particularly survival) than connectivity and this effect was conserved even under strong levels of density-dependence and was generally strengthened as local retention increased. Variability in the relationship between parameter elasticity and local retention was shown to be dependent upon the magnitude of connectivity for an individual patch relative to a critical connectivity value. The proportion of larvae lost due to transport processes was an important parameter which directly affected the magnitude of this critical connectivity value. Patches with connectivity values less than the critical value contributed to the metapopulation largely via production (i.e., local demographics most important). As local retention increased, so did the importance of demographic parameters in these patches. Patches with connectivity values greater than the critical value contributed largely via dispersal of larvae and thus the importance of local demographics decreased as local retention increased.     

Plant Diversity Hotspots in the Atlantic Coastal Forests of Brazil

Abstract:  Plant-diversity hotspots on a global scale are well established, but smaller local hotspots within these must be identified for effective conservation of plants at the global and local scales. We used the distributions of endemic and endemic-threatened species of Myrtaceae to indicate areas of plant diversity and conservation importance within the Atlantic coastal forests ( Mata Atlântica ) of Brazil. We applied 3 simple, inexpensive geographic information system (GIS) techniques to a herbarium specimen database: predictive species-distribution modeling (Maxent); complementarity analysis (DIVA-GIS); and mapping of herbarium specimen collection locations. We also considered collecting intensity, which is an inherent limitation of use of natural history records for biodiversity studies. Two separate areas of endemism were evident: the Serra do Mar mountain range from Paraná to Rio de Janeiro and the coastal forests of northern Espírito Santo and southern Bahia. We identified 12 areas of approximately 35 km² each as priority areas for conservation. These areas had the highest species richness and were highly threatened by urban and agricultural expansion. Observed species occurrences, species occurrences predicted from the model, and results of our complementarity analysis were congruent in identifying those areas with the most endemic species. These areas were then prioritized for conservation importance by comparing ecological data for each.     

Database-driven models of the world's Large Marine Ecosystems

We present a new methodology for database-driven ecosystem model generation and apply the methodology to the world's 66 currently defined Large Marine Ecosystems. The method relies on a large number of spatial and temporal databases, including FishBase, SeaLifeBase, as well as several other databases developed notably as part of the Sea Around Us project. The models are formulated using the freely available Ecopath with Ecosim (EwE) modeling approach and software. We tune the models by fitting to available time series data, but recognize that the models represent only a first-generation of database-driven ecosystem models. We use the models to obtain a first estimate of fish biomass in the world's LMEs. The biggest hurdles at present to further model development and validation are insufficient time series trend information, and data on spatial fishing effort.     

TECIIMQUES FOR DETECTING HYDROLOGIC CHANGE IN HIGH RESOURCE STREAMS1

ABSTRACT: A “synthetic paired basin” technique that combines hydrologic monitoring and watershed modeling proves to be a useful tool in detecting hydrologic change in creeks draining basins undergoing urbanization. In this approach, measured stream flow following subbasin treatment (a period of urbanization) is compared with flow from a control subbasin over the same time period. The control subbasin is the pretreatment subbasin itself as represented by a well‐calibrated hydrologic model that is input with post‐treatment meteorological data. The technique is illustrated for stream monitoring sites at the outlets of two high‐resource sub‐basins in the Bear Creek basin of King County, Washington. Application of this technique holds promise to provide earlier warning of cumulative, human impacts on aquatic resources and to better inform adaptive watershed management for resource protection.     

GIS‐BASED HYIROLOGIC MODELING OF RIPARIAN AREAS: IMPLICATIONS FOR STREAM WATER QUALITY1

ABSTRACT: Riparian buffers have potential for reducing excess nutrient levels in surface water. Spatial variation in riparian buffer effectiveness is well recognized, yet researchers and managers still lack effective general tools for understanding the relevance of different hydrologic settings. We present several terrain‐based GIS models to predict spatial patterns of shallow, subsurface hydrologic flux and riparian hydrology. We then link predictions of riparian hydrology to patterns of nutrient export in order to demonstrate potential for augmenting the predictive power of land use/land cover (LU/LC) maps. Using predicted hydrology in addition to LUILC, we observed increases in the explained variation of nutrient exports from 290 sites across Lower Michigan. The results suggest that our hydrologic predictions relate more strongly to patterns of nutrient export than the presence or absence of wetland vegetation, and that in fact the influence of vegetative structure largely depends on its hydrologic context. Such GIS models are useful and complimentary tools for exploring the role of hydrologic routing in riparian ecosystem function and stream water quality. Modeling efforts that take a similar GIS approach to material transport might be used to further explore the causal implications of riparian buffers in heterogeneous watersheds.     

IMPACTS OF CLIMATE CHANGE ON MISSOURI RWER BASIN WATER YIELD1

ABSTRACT: Water from the Missouri River Basin is used for multiple purposes. The climatic change of doubling the atmospheric carbon dioxide may produce dramatic water yield changes across the basin. Estimated changes in basin water yield from doubled CO₂ climate were simulated using a Regional Climate Model (RegCM) and a physically based rainfall‐runoff model. RegCM output from a five‐year, equilibrium climate simulation at twice present CO₂ levels was compared to a similar present‐day climate run to extract monthly changes in meteorologic variables needed by the hydrologic model. These changes, simulated on a 50‐km grid, were matched at a commensurate scale to the 310 subbasin in the rainfall‐runoff model climate change impact analysis. The Soil and Water Assessment Tool (SWAT) rainfall‐runoff model was used in this study. The climate changes were applied to the 1965 to 1989 historic period. Overall water yield at the mouth of the Basin decreased by 10 to 20 percent during spring and summer months, but increased during fall and winter. Yields generally decreased in the southern portions of the basin but increased in the northern reaches. Northern subbasin yields increased up to 80 percent: equivalent to 1.3 cm of runoff on an annual basis.     

胡敏酸对铜的鱼鳃生物有效性影响的计算机模拟

以彩虹方头鱼为模拟对象,用鱼鳃微环境测定装置和化学平衡计算方法(MINTEQA2),计算了含和不含胡敏酸的人工河水及暴露于其中的鱼鳃微环境中,不同pH条件下,铜的形态分布.研究了胡敏酸对鱼鳃内外的铜的形态分布及其生物有效性的影响,并讨论了pH对此的影响.计算结果表明,当胡敏酸存在时,胡敏酸络合态铜成为鱼鳃内外铜形态分布体系中的优势态,并引起铜生物有效性的降低.鱼鳃粘液和胡敏酸的共同作用使鱼鳃微环境中的生物有效铜含量低于外部水相.pH对铜形态分布及生物有效性的影响主要发生在碱性环境下.