The land-cover cascade: relationships coupling land and water

We introduce the land-cover cascade (LCC) as a conceptual framework to quantify the transfer of land-cover-disturbance effects to stream biota. We hypothesize that disturbance is propagated through multivariate systems through key variables that transform a disturbance and pass a reorganized disturbance effect to the next hierarchical level where the process repeats until ultimately affecting biota. We measured 31 hydrologic, geomorphic, erosional, and substrate variables and 26 biotic responses that have been associated with land-use disturbance in third- and fourth-order streams in the Blue Ridge physiographic province in western North Carolina (USA). Regression analyses reduced this set of variables to include only those that responded to land cover and/or affected biota. From this reduced variable set, hypotheses were generated that predicted the disturbance pathways affecting each biotic response following the land-cover-cascade design. Cascade pathways began with land cover and ended with biotic responses, passing through at least one intermediate ecosystem abiotic component. Cascade models were tested for predictive ability and goodness-of-fit using path analysis. Biota were influenced by near-stream urban, agricultural, and forest land cover as propagated by hydrologic (e.g., discharge), geomorphic (e.g., stream bank height), erosional (e.g., suspended sediments), and depositional streambed (e.g., substrate size) features occurring along LCC pathways, reflecting abiotic mechanisms mediating land-cover disturbance. Our results suggest that communities are influenced by land-cover change indirectly through a hierarchy of associated abiotic components that propagate disturbance to biota. More generally, the land-cover cascade concept and experimental framework demonstrate an organized approach to the generic study of cascades and the complex relationships between landscapes and streams.     

Meta-ecosystem engineering: nutrient fluxes reveal intraspecific and interspecific feedbacks in fragmented mussel beds

Ecologists still have to elucidate the complex feedback interactions operating among biodiversity and ecosystem processes in engineered systems. To address this, a field experiment was conducted to mimic natural mussel bed meta-ecosystems (Mytilus spp.) of the lower St. Lawrence Estuary (Quebec, Canada) and partition the effects of their biotic and abiotic properties and spatial structure on ecosystem processes and community dynamics of associated macro-invertebrates. We found positive intraspecific feedbacks between mussels and their recruits, and negative interspecific feedbacks between mussels and their associated ecosystem. These feedbacks were associated with mussel bed ecosystem processes (fluxes of ammonium and oxygen). In addition, we showed that proximity between mussel patches increased within-patch nutrient fluxes. Our study revealed the potential for meta-ecosystem engineering to drive feedback interactions between community and ecosystem functioning in marine fragmented systems. It also shows the relevance of meta-ecosystem theories as a conceptual framework to elucidate biotic and abiotic processes controlling ecosystem and community structure. Such framework could contribute to ecosystem-based management of spatially structured systems such as reserve networks and fragmented ecosystems.     

On maturation and spawning in some penaeid prawns of the Arabian Gulf

A mathematical model is presented of the ecosystem in the upper layers of the marine pelagic zone. The model has been constructed on the basis of presumed connections between biotic and abiotic ecosystem parameters typical of the Black Sea. Details on total model relations as well as on model analysis and construction may be obtained after gaining more insight into the behaviour of models constructed for the upper pelagic ecosystem of different marine aquatoria. The model is characterized by a rather complex behaviour. Realization of the model on the electronic computer is made by employing the method of random trajectories. As a result, a qualitative picture of model behaviour under different conditions is revealed and statistical characteristics of the parameters are obtained.     

Modeling the vegetation-atmosphere carbon dioxide and water vapor interactions along a controlled CO2 gradient

Ecosystem functioning is intimately linked to its physical environment by complex two-way interactions. These two-way interactions arise because vegetation both responds to the external environment and actively regulates its micro-environment. By altering stomatal aperture, and therefore the transpiration rate, plants modify soil moisture and atmospheric humidity and these same physical variables, in return, modify stomatal conductance. Relationships between biotic and abiotic components are particularly strong in closed, managed environments such as greenhouses and growth chambers, which are used extensively to investigate ecosystem responses to climatic drivers. Model-assisted designs that account for the physiological dynamics governing two-way interactions between biotic and abiotic components are absent from many ecological studies. Here, a general model of the vegetation-atmosphere system in closed environments is proposed. The model accounts for the linked carbon-water physiology, the turbulent transport processes, and the energy and radiative transfer within the vegetation. Leaf gas exchange is modeled using a carbon gain optimization approach that is coupled to leaf energy balance. The turbulent transport within the canopy is modeled in two-dimensions using first-order closure principles. The model is applied to the Lysimeter CO₂ Gradient (LYCOG) facility, wherein a continuous gradient of atmospheric CO₂ is maintained on grassland assemblages using an elongated chamber where the micro-climate is regulated by variation in air flow rates. The model is employed to investigate how species composition, climatic conditions, and the imposed air flow rate affect the CO₂ concentration gradient within the LYCOG and the canopy micro-climate. The sensitivity of the model to key physiological and climatic parameters allows it to be used not only to manage current experiments, but also to formulate novel ecological hypotheses (e.g., by modeling climatic regimes not currently employed in LYCOG) and suggest alternative experimental designs and operational strategies for such facilities.     

Ecosystem states: Creating a data-derived, ecosystem-scale ecological response model that is explicit in space and time

Increasing difficulties associated with balancing consumptive demands for water and achieving ecological benefits in aquatic ecosystems provide opportunities for new ecosystem-scale ecological response models to assist managers. Using an Australian estuary as a case study, we developed a novel approach to create a data-derived state-and-transition model. The model identifies suites of co-occurring birds, fish, benthic invertebrates and aquatic macrophytes (as ‘states’) and the changing physico-chemical conditions that are associated with each (‘transitions’). The approach first used cluster analysis to identify sets of co-occurring biota. Differences in the physico-chemical data associated with each state were identified using classification trees, with the biotic distinctness of the resultant statistical model tested using analysis of similarities. The predictive capacity of the model was tested using new cases. Two models were created using different time-steps (annual and quarterly) and then combined to capture both longer-term trends and more-recent declines in ecological condition. We identified eight ecosystem states that were differentiated by a mix of water-quantity and water-quality variables. Each ecosystem state represented a distinct biotic assemblage under well-defined physico-chemical conditions. Two ‘basins of attraction’ were identified, with four tidally-influenced states, and another four independent of tidal influence. Within each basin, states described a continuum of relative health, manifest through declining taxonomic diversity and abundances. The main threshold determining relative health was whether freshwater flows had occurred in the region during the previous 339 days. Canonical analyses of principal coordinates tested the predictive capacity of the model and demonstrated that the variance in the environmental data set was well captured (87%) with 52% of the variance in the biological data set also captured. The latter increased to >80% when long- and short-term biological data were analysed separately, indicating that the model described the available data for the Coorong well. This approach thus created a data-derived, multivariate model, where neither states nor transitions were determined a priori. The approach did not over-fit the data, was robust to patchy or missing data, the choice of initial clustering technique and random errors in the biological data set, and was well-received by local natural resource managers. However, the model did not capture causal relationships and requires additional testing, particularly during future episodes of ecological recovery. The approach shows significant promise for simplifying management definitions of ecological condition and, via scenario analyses, can be used to assist in manager decision-making of large, complex aquatic ecosystems in the future.     

Composite forces shape population dynamics of copepod crustaceans

Understanding the processes that control species abundance and distribution is a major challenge in ecology, yet for a large number of potentially important organisms, we know little about the biotic and abiotic factors that influence population size. One group of aquatic organisms that defies traditional demographic analyses is the Crustacea, particularly those with complex life cycles. We used likelihood techniques and information theoretics to evaluate a suite of models representing alternative hypotheses on factors controlling the abundance of two copepod crustaceans in a small, tropical floodplain lake. Quantitative zooplankton samples were collected at three stations in a Venezuelan floodplain lake from June through December 1984; the average sampling interval was two days. We constructed a series of models with stage structure that incorporated six biotic and abiotic covariates in various combinations to account for temporal changes in abundance of these target species and in their population growth rates. Our analysis produced several novel insights into copepod population dynamics. We found that multiple forces affected the abundance of particular stages, that these factors differed between species as well as among stages within each species, and that biotic processes had the largest effects on copepod population dynamics. Density dependence had a large effect on the survival of Oithona amazonica copepodites and on population growth rate of Diaptomus negrensis.     

On the vulnerability of woody riparian vegetation during flood events

Environmental Fluid Mechanics - Wood is recognized as a key element of river ecosystem for a large number of positive feedbacks with biotic and abiotic components, both when it is present as large...     

Long-term dynamics of biotic and abiotic resistance to exotic species invasion in restored vernal pool plant communities

Invasion of native ecosystems by exotic species can seriously threaten native biodiversity, alter ecosystem function, and inhibit conservation. Moreover, restoration of native plant communities is often impeded by competition from exotic species. Exotic species invasion may be limited by unfavorable abiotic conditions and by competition with native species, but the relative importance of biotic and abiotic factors remains controversial and may vary during the invasion process. We used a long-term experiment involving restored vernal pool plant communities to characterize the temporal dynamics of exotic species invasion, and to evaluate the relative support for biotic and abiotic factors affecting invasion resistance. Experimental pools (n=256) were divided among controls and several seeding treatments. In most treatments, native vernal pool species were initially more abundant than exotic species, and pools that initially received more native seeds exhibited lower frequencies of exotic species over time. However, even densely seeded pools were eventually dominated by exotic species, following extreme climatic events that reduced both native and exotic plant densities across the study site. By the sixth year of the experiment, most pools supported more exotics than native vernal pool species, regardless of seeding treatment or pool depth. Although deeper pools were less invaded by exotic species, two exotics (Hordeum marinum and Lolium multiflorum) were able to colonize deeper pools as soon as the cover of native species was reduced by climatic extremes. Based on an information-theoretic analysis, the best model of invasion resistance included a nonlinear effect of seeding treatment and both linear and nonlinear effects of pool depth. Pool depth received more support as a predictor of invasion resistance, but seeding intensity was also strongly supported in multivariate models of invasion, and was the best predictor of resistance to invasion by H. marinum and L. multilorum. We conclude that extreme climatic events can facilitate exotic species invasions by both reducing abiotic constraints and weakening biotic resistance to invasion.     

Evaluating the relative importance of intrinsic and extrinsic factors on the foraging activity of top predators: a case study on female little penguins

A complex interaction of biotic and abiotic factors influences animal foraging activity. It is often difficult to understand which factors may affect animals’ foraging and how it is affected. For instance, whereas the effect of sexual dimorphism on foraging activity has been reported in several species, little is known of the complex interactions between variables acting at a finer scale, e.g. the variability of body mass within a sex. Evaluating the importance of these finer scale factors is also essential to the understanding of foraging behaviour. We propose here a simple approach by applying principal component analysis (PCA) in a novel way to examine relationships between biotic and abiotic factors affecting foraging behaviour of top predators. We studied female little penguins (Eudyptula minor) of known age, carrying miniature accelerometers during the guard stage of breeding. Surprisingly, the body mass of the females did not influence any of the foraging parameters, but females foraging later in the breeding season dived shallower and more often, showing a strong correlation with laying date. Similarly, the diving effort of females was greater with increasing chick age within the same breeding stage. These results indicate that for female little penguin, the relationship between changes in prey availability and hunting effort can change at a fine scale, within a breeding stage. Therefore, any analysis of little penguin foraging behaviour during breeding should consider the timing in relation to the breeding season. We encourage researchers to develop the use of this PCA approach as it could help clarify the complexity of the underlying mechanisms determining foraging activity and we propose that it should be used as a first step of foraging behaviour analysis, before examining a particular relationship.     

EcoTroph: Modelling marine ecosystem functioning and impact of fishing

EcoTroph (ET) is a model articulated around the idea that the functioning of aquatic ecosystems may be viewed as a biomass flow moving from lower to higher trophic levels, due to predation and ontogenetic processes. Thus, we show that the ecosystem biomass present at a given trophic level may be estimated from two simple equations, one describing biomass flow, the other their kinetics (which quantifies the velocity of biomass transfers towards top predators). The flow kinetic of prey partly depends on the abundance of their predators, and a top-down equation expressing this is included in the model. Based on these relationships, we simulated the impact on a virtual ecosystem of various exploitation patterns. Specifically, we show that the EcoTroph approach is able to mimic the effects of increased fishing effort on ecosystem biomass expected from theory. Particularly, the model exhibits complex patterns observed in field data, notably cascading effects and ‘fishing down the food web’. EcoTroph also provides diagnostic tools for examining the relationships between catch and fishing effort at the ecosystem scale and the effects of strong top-down controls and fast-flow kinetics on ecosystems resilience. Finally, a dynamic version of the model is derived from the steady-state version, thus allowing simulations of time series of ecosystem biomass and catches. Using this dynamic model, we explore the propagation of environmental variability in the food web, and illustrated how exploitation can induce a decrease of ecosystem stability. The potential for applying EcoTroph to specific ecosystems, based on field data, and similarities between EcoTroph and Ecopath with Ecosim (EwE) are finally discussed.     

The theory behind,and the challenges of,conserving nature's stage in a time of rapid change

Most conservation planning to date has focused on protecting today's biodiversity with the assumption that it will be tomorrow's biodiversity. However, modern climate change has already resulted in distributional shifts of some species and is projected to result in many more shifts in the coming decades. As species redistribute and biotic communities reorganize, conservation plans based on current patterns of biodiversity may fail to adequately protect species in the future. One approach for addressing this issue is to focus on conserving a range of abiotic conditions in the conservation‐planning process. By doing so, it may be possible to conserve an abiotically diverse “stage” upon which evolution will play out and support many actors (biodiversity). We reviewed the fundamental underpinnings of the concept of conserving the abiotic stage, starting with the early observations of von Humboldt, who mapped the concordance of abiotic conditions and vegetation, and progressing to the concept of the ecological niche. We discuss challenges posed by issues of spatial and temporal scale, the role of biotic drivers of species distributions, and latitudinal and topographic variation in relationships between climate and landform. For example, abiotic conditions are not static, but change through time—albeit at different and often relatively slow rates. In some places, biotic interactions play a substantial role in structuring patterns of biodiversity, meaning that patterns of biodiversity may be less tightly linked to the abiotic stage. Furthermore, abiotic drivers of biodiversity can change with latitude and topographic position, meaning that the abiotic stage may need to be defined differently in different places. We conclude that protecting a diversity of abiotic conditions will likely best conserve biodiversity into the future in places where abiotic drivers of species distributions are strong relative to biotic drivers, where the diversity of abiotic settings will be conserved through time, and where connectivity allows for movement among areas providing different abiotic conditions.     

Relating effect and response traits in submersed aquatic macrophytes.

Reliably predicting the consequences of short- or long-term changes in the environment is important as anthropogenic pressures are increasingly stressing the world's ecosystems. One approach is to examine the manner in which biota respond to changes in the environment ("response traits") and how biota, in turn, affect ecosystem processes ("effect traits"). I compared the response and effect traits of four submersed aquatic macrophytes to understand how water level management may affect wetland plant populations and ecosystem processes. I measured resource properties (nutrients in sediment and water), non-resource properties (pH, alkalinity, sediment temperature, oxygen production), and biotic properties (periphyton biomass) in replicated outdoor monocultures of Stuckenia pectinata, Potamogeton nodosus, P. crispus, and Zannichellia palustris. After seven weeks, three of eight replicates of each species treatment were subjected to a temporary water draw-down that desiccated aboveground plant parts. The four species differed in their effects on ecosystem properties associated with nutrient uptake and photosynthetic activity. Shoot growth rate was negatively correlated with light transmittance to the sediment surface whereas root growth rate and root:shoot ratio were correlated with a species' ability to deplete nutrients in sediment interstitial water. Occupation of space in the water column was correlated with water alkalinity and pH and with sediment temperature. Root growth rate was related simultaneously to species effects on sediment nutrient dynamics and recovery of ecosystem properties after water draw-down. This suggests that this morphological trait may be used to predict the effects of environmental change on ecosystem functioning within the context of water level management. Expanding these analyses to more species, different environmental stressors, and across aquatic and terrestrial ecosystems should enhance predictions of the complex effects of global environmental change on ecosystem functioning.     

Application of eco-exergy for assessment of ecosystem health and development of structurally dynamic models

Eco-exergy has been widely used in the assessment of ecosystem health, parameter estimations, calibrations, validations and prognoses. It offers insights into the understanding of ecosystem dynamics and disturbance-driven changes. Particularly, structurally dynamic models (SDMs), which are developed using eco-exergy as the goal function, have been applied in explaining and exploring ecosystem properties and changes in community structure driven by biotic and abiotic factors. In this paper, we review the application of eco-exergy for the assessment of ecosystem health and development of structurally dynamic models (SDMs). The limitations and possible future applications of the approach are also addressed.     

A Method for Assessing Hydrologic Alteration within Ecosystems

Hydrologic regimes play a major role in determining the biotic composition, structure, and function of aquatic, wetland, and riparian ecosystems. But human land and water uses are substantially altering hydrologic regimes around the world. Improved quantitative evaluations of human-induced hydrologic changes are needed to advance research on the biotic implications of hydrologic alteration and to support ecosystem management and restoration plans. We propose a method for assessing the degree of hydrologic alteration attributable to human influence within an ecosystem. This method, referred to as the "Indicators of Hydrologic Alteration," is based upon an analysis of hydrologic data available either from existing measurement points within an ecosystem (such as at stream gauges or wells) or model-generated data. We use 32 parameters, organized into five groups, to statistically characterize hydrologic variation within each year. These 32 parameters provide information on ecologically significant features of surface and ground water regimes influencing aquatic, wetland, and riparian ecosystems. We then assess the hydrologic perturbations associated with activities such as dam operations, flow diversion, groundwater pumping, or intensive land-use conversion by comparing measures of central tendency and dispersion for each parameter between user-defined "pre-impact" and "post-impact" time frames, generating 64 Indicators of Hydrologic Alteration. This method is intended for use with other ecosystem metrics in inventories of ecosystem integrity, in planning ecosystem management activities, and in setting and measuring progress toward conservation or restoration goals.     

AQUATOX: Modeling environmental fate and ecological effects in aquatic ecosystems

AQUATOX combines aquatic ecosystem, chemical fate, and ecotoxicological constructs to obtain a truly integrative fate and effects model. It is a general, mechanistic ecological risk assessment model intended to be used to evaluate past, present, and future direct and indirect effects from various stressors including nutrients, organic wastes, sediments, toxic organic chemicals, flow, and temperature in aquatic ecosystems. The model has a very flexible structure and provides multiple analytical tools useful for evaluating ecological effects, including uncertainty analysis, nominal range sensitivity analysis, comparison of perturbed and control simulations, and graphing and tabulation of predicted concentrations, rates, and photosynthetic limitations. It can represent a full aquatic food web, including multiple genera and guilds of periphyton, phytoplankton, submersed aquatic vegetation, invertebrates, and fish and associated organic toxicants. It can model up to 20 organic chemicals simultaneously. (It does not model metals.) Modeled processes for organic toxicants include chemodynamics of neutral and ionized organic chemicals, bioaccumulation as a function of sorption and bioenergetics, biotransformation to daughter products, and sublethal and lethal toxicity. It has an extensive library of default biotic, chemical, and toxicological parameters and incorporates the ICE regression equations for estimating toxicity in numerous organisms. The model has been implemented for streams, small rivers, ponds, lakes, reservoirs, and estuaries. It is an integral part of the BASINS system with linkage to the watershed models HSPF and SWAT.     

Hierarchical analysis of species distributions and abundance across environmental gradients

Abiotic and biotic processes operate at multiple spatial and temporal scales to shape many ecological processes, including species distributions and demography. Current debate about the relative roles of niche-based and stochastic processes in shaping species distributions and community composition reflects, in part, the challenge of understanding how these processes interact across scales. Traditional statistical models that ignore autocorrelation and spatial hierarchies can result in misidentification of important ecological covariates. Here, we demonstrate the utility of a hierarchical modeling framework for testing hypotheses about the importance of abiotic factors at different spatial scales and local spatial autocorrelation for shaping species distributions and abundances. For the two orchid species studied, understory light availability and soil moisture helped to explain patterns of presence and abundance at a microsite scale (<4 m2), while soil organic content was important at a population scale (<400 m2). The inclusion of spatial autocorrelation is shown to alter the magnitude and certainty of estimated relationships between abundance and abiotic variables, and we suggest that such analysis be used more often to explore the relationships between species life histories and distributions. The hierarchical modeling framework is shown to have great potential for elucidating ecological relationships involving abiotic and biotic processes simultaneously at multiple scales.     

Effects of Changes in Biodiversity on Ecosystem Function in Tropical Forests

Changing land use in the tropics has resulted in vast areas of damaged and degraded lands where biodiversity has been reduced. The majority of research on biodiversity has been focused on population and community dynamics and has rarely considered the ecosystem processes that are intimately related. We present a framework for examining the effects of changes in biodiversity on ecosystem function in natural, managed, and damaged tropical forests. Using a whole-ecosystem approach, the framework identifies key nutrient and energy cycling processes and critical junctures or pathways, termed interfaces, where resources are concentrated and transferred between the biotic and abiotic components of the ecosystem. Processes occurring at these interfaces, and the organisms or attributes participating in these processes, exert a strong influence on ecosystem structure. We use examples from Puerto Rico, Southern China, Dominica, and Nicaragua to illustrate how the functional diversity framework can be applied to critically examine the effects of changes in biodiversity on ecosystem function, and the relative success or failure of rehabilitation strategies. The few available data suggest that functional diversity, and not just species richness, is important in maintaining the integrity of nutrient and energy fluxes. High species richness, however, may increase ecosystem resiliency following disturbance by increasing the number of alternative pathways for the flow of resources. We suggest ways in which the framework of functional diversity can be used to design research to examine the effects of changes in biodiversity on ecosystem processes and in the design and evaluation of ecosystem management and land rehabilitation projects in the tropics.     

基于植物重金属毒性的陆地生物配体模型(t-BLM)研究进展

陆地生物配体模型(t-BLM)是生物配体模型(BLM)理论在陆地生态系统中的应用,目的是通过量化土壤重金属形态、土壤基本性质以及生态毒理剂量-效应三者之间的关系,评价重金属对陆生生物的毒性。BLM已经成功地预测重金属对水生生物的毒性,但t-BLM的发展相对较为缓慢。基于植物重金属毒性综述了t-BLM近年来国内外的研究进展,介绍了t-BLM的原理、基于t-BLM的重金属(Cu、Ni、Zn、Cd等)的植物毒性及其影响因素,并且提出基于植物重金属毒性的t-BLM研究面临的主要挑战。