Human production of food and energy is the dominant continental process that breaks the triple bond in molecular nitrogen (N 2

As regional and global scales become more important to ecologists, methods must be developed for the application of existing fine-scale knowledge to predict coarser-scale ecosystem properties. This generally involves some form of model in which fine-scale components are aggregated. This aggregation is necessary to avoid the cumulative error associated with the estimation of a large number of parameters. However, aggregation can itself produce errors that arise because of the variation among the aggregated components. The statistical expectation operator can be used as a rigorous method for translating fine-scale relationships to coarser scales without aggregation errors. Unfortunately this method is too cumbersome to be applied in most cases, and alternative methods must be used. These alternative methods are typically partial corrections for the variation in only a few of the fine-scale attributes. Therefore, for these methods to be effective, the attributes that are the most severe sources of error must be identified a priori. We present a procedure for making these identifications based on a Monte Carlo sampling of the fine-scale attributes. We then present four methods of translating fine-scale knowledge so it can be applied at coarser scales: (1) partial transformations using the expectation operator, (2) moment expansions, (3) partitioning, and (4) calibration. These methods should make it possible to apply the vast store of fine-scale ecological knowledge to model coarser-scale attributes of ecosystems.

Quantitative predictions of the effects of acid deposition onterrestrial and aquatic systems require physically based, process‐oriented models of catchment soil water and streamwater chemistry. A desirable characteristic of such models is that they include terms to describe the important phenomena controlling a system's chemical response to acidic deposition, yet be restricted in complexity so that they can be implemented on diverse systems with a minimum of a priori data. We present an assessment of a conceptual model of soil water and streamwater chemistry based on soil cation exchange, dissolution of aluminum hydroxide, and solution of carbon dioxide, all processes that occur in catchment soils and that have rapid equilibration times. The model is constructed using an “average” or lumped representation of these spatially distributed catchment processes. The adequacy of the model is assessed by applying it to 3 years of soil water and streamwater chemistry data from White Oak Run, Virginia, a second‐order stream in the Shenandoah National Park. Soil properties predicted by the model are in good agreement with presently available measurements of those soil properties. The success of the model suggests that lumped representations of complex and spatially distributed chemical reactions in soils can efficiently describe the gross chemical behavior of whole catchments (e.g., pH, alkalinity, and major ionic concentrations in surface waters). Further assessment of the adequacy of this conceptual approach will require more detailed empirical knowledge of the soil processes being modeled, particularly soil cation exchange and the variability of soil CO2 partial pressures.

The MAGIC model of the responses of catchments to acidic deposition has been applied and tested extensively over a 15 year period at many sites and in many regions around the world. Overall, the model has proven to be robust, reliable and useful in a variety of scientific and managerial activities. Over the years, several refinements and additions to MAGIC have been proposed and/or implemented for particular applications. These adjustments to the model structure have all been included in a new version of the model (MAGIC7). The log aluminium -pH relationship now does not have to be fixed to aluminium trihydroxide solubility. Buffering by organic acids using a triprotic analog is now included. Dynamics of nitrogen retention and loss in catchments can now be linked to soil nitrogen and carbon pools. Simulation of short-term episodic response by mixing fractions of different water types is also possible. This paper presents a review of the conceptual structure of MAGIC7 relating to long-term simulation of acidification and recovery, describes the conceptual basis of the new nitrogen dynamics and provides a comprehensive update of the equations, variables, parameters and inputs for the model.

Accurate quantification of biodiversity is fundamental to understanding ecosystem function and for environmental assessment. Molecular methods using environmental DNA (eDNA) offer a non-invasive, rapid, and cost-effective alternative to traditional biodiversity assessments, which require high levels of expertise. While eDNA analyses are increasingly being utilized, there remains considerable uncertainty regarding the dynamics of multispecies eDNA, especially in variable systems such as rivers. Here, we utilize four sets of upland stream mesocosms, across an acid–base gradient, to assess the temporal and environmental degradation of multispecies eDNA. Sampling included water column and biofilm sampling over time with eDNA quantified using qPCR. Our findings show that the persistence of lotic multispecies eDNA, sampled from water and biofilm, decays to non-detectable levels within 2 days and that acidic environments accelerate the degradation process. Collectively, the results provide the basis for a predictive framework for the relationship between lotic eDNA degradation dynamics in spatio-temporally dynamic river ecosystems.