Modeling Environmental Stress

The word stress when applied to ecosystems is ambiguous. Stress may be low-level, with accompanying near-linear strain, or it may be of finite magnitude, with nonlinear response and possible disintegration of the system. Since there are practically no widely accepted definitions of ecosystem strain, classification of models of stressed systems is tenuous. Despite appearances, most ecosystem models seem to fall into the low-level linear response category. Although they sometimes simulate systems behavior well, they do not provide necessary and sufficient information about sudden structural changes nor structure after transition. Dynamic models of finiteamplitude response to stress are rare because of analytical difficulties. Some idea as to future transition states can be obtained by regarding the behavior of unperturbed functions under limiting strain conditions. Preliminary work shows that, since community variables do respond in a coherent manner to stress, macroscopic analyses of stressed ecosystems offer possible alternatives to compartmental models.

Structural dynamic eutrophication models

This article discusses problems of modelling the seasonal succession of algal species in lakes and reservoirs, and the adaptive selection of certain groups of algae in response to changes in the inputs and relative concentrations of nutrients and other environmental variables. A new generation of quantitative models is being developed which attempts to translate some important biological properties of species (survival, variation, inheritance, reproductive rates and population growth) into predictions about the survival of the fittest, where ”fitness” is measured or estimated in thermodynamic terms. The concept of ”exergy” and its calculation is explored to examine maximal exergy as a measure of fitness in ecosystems, and its use for calculating changes in species composition by means of structural dynamic models. These models accomodate short-term changes in parameters that affect the adaptive responses (species selection) of algae.

Problems in estimating the response functions of natural climatic recording systems [abstract]

EXTRACT (SEE PDF FOR FULL ABSTRACT): High-resolution proxy records of climate, such as varves, ice cores, and tree-rings, provide the opportunity for reconstructing climate on a year-by-year basis. In order to do so it is necessary to approximate the complex nonlinear response function of the natural recording system using linear statistical models. Three problems with this approach were discussed, and possible solutions were suggested. Examples were given from a reconstruction of Santa Barbara precipitation based on tree-ring records from Santa Barbara County.

Determining the role of linear and nonlinear interactions in records of climate change: possible solar influences in annual to century-scale records

Time series analysis methods have traditionally helped in identifying the role of various forcing mechanisms in influencing climate change. A challenge to understanding decadal and century-scale climate change has been that the linkages between climate changes and potential forcing mechanisms such as solar variability are often uncertain. However, most studies have focused on the role of climate forcing and climate response within a strictly linear framework. Nonlinear time series analysis procedures provide the opportunity to analyze the role of climate forcing and climate responses between different time scales of climate change. An example is provided by the possible nonlinear response of paleo-ENSO-scale climate changes as identified from coral records to forcing by the solar cycle at longer time scales.

River salinity variations in response to discharge: examples from the western United States during the early 1900s

Major controls on river salinity (total dissolved solids) in the western United States are climate, geology, and human activity. Climate, in general, influences soil-river salinity via salt-balance variations. When climate becomes wetter, river discharge increases and soil-river salinity decreases; when climate becomes drier river discharge decreases and soil-river salinity increases. This study characterizes the river salinity response to discharge using statistical-dynamic methods. An exploratory analysis of river salinity, using early 1900s water quality surveys in the western United States, shows much river salinity variability is in response to storm and annual discharge. Presumably this is because river discharge is largely supported by surface flow.