Ecophysiological Model Research Articles

Environmental Influences on the 137Cs Kinetics of the Yellow‐Bellied Turtle (Trachemys Scripta)

Assessments of ecological risk require accurate predictions of contaminant dynamics in natural populations. However, simple deterministic models that assume constant uptake rates and elimination fractions may compromise both their ecological realism and their general application to animals with variable metabolisms or diets. In particular, the temperature—dependent metabolic rates characteristic of ectotherms may lead to significant differences between observed and predicted contaminant kinetics. We examined the influence of a seasonally variable thermal environment on predicting the uptake and annual cycling of contaminants by ectotherms, using a temperature—dependent model of 137Cs kinetics in free—living yellow—bellied turtles, Trachemys scripta. We compared predictions from this model with those of deterministic negative exponential and flexibly shaped Richards sigmoidal models. Concentrations of 137Cs in a population of this species in Pond B, a radionuclide—contaminated nuclear reactor cooling reservoir, and 137Cs uptake by uncontaminated turtles held captive in Pond B for 4 yr confirmed both the pattern of uptake and the equilibrium concentrations predicted by the temperature—dependent model. Almost 90% of the variance in the predicted time—integrated 137Cs concentration was explainable by linear relationships with model parameters. The model was also relatively insensitive to uncertainties in the estimates of ambient temperature, suggesting that adequate estimates of temperature—dependent ingestion and elimination may require relatively few measurements of ambient conditions at sites of interest. Analyses of Richards sigmoidal models of 137Cs uptake indicated significant differences from a negative exponential trajectory in the 1st yr after the turtles' release into Pond B. We also observed significant annual cycling of 137Cs concentrations, apparently due to temperature—dependent metabolism and its influence on ingestion and elimination rates. However, equilibrium concentrations of the radionuclide in the wild population were predictable from negative exponential models based on average annual temperature and its effects on intake and elimination rates, also suggesting that predicting ectotherm responses to long—lived contaminants (such as 137Cs) may be possible without complex ecophysiological modeling.

Individual-based simulation models for forest succession and management

Individual-based forest models simulate forest dynamics on the basis of establishment, growth and death of individual trees. This paper attempts to review and compare two major types of individual-based forest models: growth-yield and gap models. Although the two types of models share some similar features, they differ in model structure and data requirements and play several complementary roles. Growth-yield models are used by foresters to assist timber production and evaluate growth and yield of one to several commercial timber species in managed forests, while gap models are generally developed by ecologists to explore ecological mechanisms and patterns of structure and functional dynamics in natural forest ecosystems. Site-specific environmental and species information is necessary for constructing growth-yield models while gap models require species-specific biological information of individual trees and site-specific environmental data. The growth-yield models are more diverse in terms of model structure. In contrast, gap models belong to the same genealogy and later gap models are ultimately derived from the earliest one although they may vary in detail. In the future, we expect to see more individual-based hybrid models which integrate gap models with growth-yield models and ecophysiological models. As computer technology advances explosively, individual-based models could be much more efficient and user-friendly. There have existed disproportionately few individual-based models for biodiverse forests such as evergreen tropical rain forests. Development of individual-based models for tropical rain forests is more challenging and is being stimulated by new international conservation efforts.

Evaluating the type and state of Alaska taiga forests with imaging radar for use in ecosystem models

Changes in the seasonal CO/sub 2/ flux of the boreal forests may result from increased atmospheric CO/sub 2/ concentrations and associated global warming patterns. To monitor this potential change, a combination of information derived from remote sensing data, including forest type and growing season length, and ecophysiological models which predict the CO/sub 2/ flux and its seasonal amplitude based on meteorological data, are required. The authors address the use of synthetic aperture radar (SAR) to map forest type and monitor canopy and soil freeze/thaw, which define the growing season for conifers, and leaf on/off, which defines the growing season for deciduous species. Aircraft SAR (AIRSAR) data collected in March 1988 during a freeze/thaw event are used to generate species maps and to determine the sensitivity of SAR to canopy freeze/thaw transitions. These data are also used to validate a microwave scattering model which is then used to determine the sensitivity of SAR to leaf on/off transitions and soil freeze/thaw. Finally, a CO/sub 2/ flux algorithm is presented which utilizes SAR data and an ecophysiological model to estimate CO/sub 2/ flux. CO/sub 2/ flux maps are generated, from which areal estimates of CO/sub 2/ flux are derived. >

Vegetation responses and feedbacks to climate: a review of models and processes

Vegetation changes both in stationary and changing climates. Such changes can significantly affect hydrological and climate dynamics. Probabilistic, inferential, empirical, statistical, threshold, ecophysiological, and mechanistic vegetation models provide tools and ideas to construct coupled climate and vegetation schemes to study climate/vegetation feedbacks. Their logic is discussed, typical applications are presented, and their usefulness is assessed. Developing coupled climate and vegetation schemes also implies tackling scaling issues explicitly. Just as the Courant-Friedrichs-Lewy (CFL) criterion guarantees that information is not transferred faster through space than time in climate models, information should be transmitted fast enough in vegetation models for the landscape to register vegetation responses. To guarantee that this is the case, a ‘migration criterion’, or ‘m criterion’, is proposed. The CFL criterion and the m criterion set formal constraints on the design of coupled atmosphere and vegetation schemes. In particular, the ratio of climate and vegetation space scales should be approximately five orders of magnitude less than the ratio of climate and vegetation time scales.

IMPACT OF INCREASED TEMPERATURE AND CO2 ON RICE PRODUCTIVITY IN CAUVERY DELTA ZONE, INDIA-A SIMULATION ANALYSIS

Using an eco-physiological model, the changes in the growth characteristics and grain yield for elevated atmospheric CO2 level and temperature are explored. The main prediction is for harvest indices to fall. The model was used to develop strategies for mitigating the combined effects of increased temperature and CO2, and define rice ideotypes suited to changing climate.

Increasing the Yield Plateau in Rice and the Role of Global Climate Change

To cope with estimated population growth in Asia, attainable rice yield potential must increase in the irrigated lowlands. At odds with this goal is the fact that yield potential of released high yielding rice varieties has remained constant since the release of IR8 in the late 1960s, although yield per day increased as a result of shorter growth duration and host plant resistance was improved. For example, highest rice yields of IR72 (released in 1987) were 6 and 9.5tha-1, in the 1991 wet season and the 1992 dry season, respectively, in a tropical environment with good agronomic management. These yields are comparable but no higher, than the highest yields attained by IR8 in the same environment more than 20 years ago. Detailed growth analysis from these recent studies allowed us to improve an eco-physiological model for rice growth. Subsequent simulations demonstrated accurate prediction of wet and dry season rice yield. The model was then used to evaluate the effects of global climate change as expected by the year 2020. Changes in temperature and atmospheric CO2 had relatively small effects on simulated rice growth and yield compared with (1) the impact of crop management practices in high-yielding environments and (2) genetic improvement that could further increase yield potential. Varieties with a longer grain filling duration will be needed to increase the yield plateau and to reverse negative effects of increased temperature.

Predicting effects of global warming on growth and mortality of upland oak species in the midwestern United States: a physiologically based dendroecological approach

This study combined an ecophysiological model and dendroecological analyses to evaluate potential effects of global warming on the physiology, growth, and mortality of white oak (Quercusalba L.) and black oak (Quercusvelutina Lam.) in the Ohio River region. The model integrated data for ecophysiology of oak species, site attributes, and daily temperature and precipitation to model nonlinear responses of stomatal conductance (gs), net photosynthesis (Pnet), and woody respiration (Rw) to variations in temperature and soil water content. Relationships between modeled physiological response indices and actual white and black oak annual radial growth indices were evaluated by regression analyses, using growth and weather data for the period 1900–1987 for seven upland oak–hickory forests. Modeled physiological response indices explained 40–60% of variation in radial growth indices. To evaluate the effects of global warming, daily temperature values for the period 1900–1987 were increased by 2 or 5 °C, without changing precipitation values, and physiological response indices were computed. Model indices generated in warming simulations were entered into dendroclimatic regression models calibrated under conditions without any warming to predict radial growth under warming scenarios. Under the warming scenarios, OAKWBAL predicted a substantial increase in growing season Rw, but little change in growing season Pnet. Warming merely shifted the period of near-maximal Pnet earlier in the growing season, without changing its duration. However, this result was somewhat dependent upon the ability of leaf-out phenology to track changes in temperature regime. The net effect of increased Rw, with little change in Pnet, was a reduction in radial growth and a higher frequency of years with climatic conditions stressful to oaks on upland sites. A historical association between severe drought and increased incidence of oak growth decline and mortality indicated that global warming could increase the incidence of decline and mortality in oak populations on upland sites similar to those in this study.

Use of Ecophysiological Models for Crop-Weed Interference: Relations Amongst Weed Density, Relative Time of Weed Emergence, Relative Leaf Area, and Yield Loss

The performance of a mechanistic simulation model of crop-weed competition was evaluated with data on the effects of weed density, relative time of weed emergence, and environmental conditions on crop yield for three different crop-weed combinations. Reductions in crop yields due to weed competition were simulated accurately for all experiments, except for one case in which severe water stress combined with weed competition altered crop morphological development (height and leaf area). The mechanistic model was then used to assess the potential and constraints of two empirical models of crop-weed competition, one based upon weed density and relative time of emergence, and the other on relative leaf area. The empirical model describing the relationship between relative leaf area of the weeds shortly after crop emergence and yield loss appeared to have several advantages for management applications, whereas the mechanistic model is more suited for research purposes.

Phytoplankton-bacteria relationship in the Antarctic marine ecosystem

Time series data of phytoplanktonic and bacterial biomass during the ice retreat period at different latitudes in the Weddell Sea and Prydz Bay areas show a distinct delay in the development of bacteria with respect to phy'oplankton. Use of a general ecophysiological model of bacterial growth, along with direct in situ measurements of growth and mortality rates, allowed the simulation of the observed timing of bacterial development. It is suggested that the uncoupling between phytoplanktonic and bacterial development at the earliest stage of the spring ice-edge related algal bloom is not the result of the low temperatures occurring in the Southern Ocean but rather is due to the macromolecular nature of the dissolved organic matter released from phytoplankton.

The structure and evolution of the top layers of the water column across the marginal ice zone during spring 1988 in the Scotia-Weddell Sea sector of the Southern Ocean

The evolution of the wind-mixed layer and surface temperature in a period of ice retreat is studied with a one-dimensional turbulent erosion model. This model is established to provide values for a number of physical parameters to be used in ecophysiological modelling of plankton blooms in an area with a retreating ice cover. The wind-mixed layer (WML) model is driven by parameters obtained by regular on-board meteorological observations, visual ice cover estimates and global radiation measurements. The results of numerous conductivity-temperature-depth (CTD) casts performed during the EPOS leg-2 cruise provided the data for the initial conditions and validation.

Atmosphere‐biosphere exchange of carbon dioxide in boreal forests

An ecophysiological model of photosynthesis and respiration by forest ecosystems was used to examine CO2 fluxes in 23 mature boreal forests near Fairbanks, Alaska. Simulated soil respiration, photosynthesis, decomposition, and moss and tree productivity were consistent with observed data. Monthly ecosystem CO2 flux and net photosynthesis, averaged over the 23 sites, were correlated with atmospheric CO2 concentrations and δ13 ratios, respectively, at Barrow, Alaska, suggesting the boreal forests of Alaska play an active role in the seasonal dynamics of atmospheric CO2 at Barrow. Only one of the 23 stands was a source of CO2, and the 23 stands absorbed (mean ± SE) 1173±211 g CO2 m−2 yr−1. Observed productivity in these forests spans the range of productivity in the circumpolar boreal forest, suggesting the simulated CO2 fluxes are representative of the circumpolar boreal forest. If so, metabolic activity in the circumpolar boreal forest results in a significant annual uptake of CO2.

Validation of photosynthate production in ECOPHYS, an ecophysiological growth process model of Populus.

A model of photosynthate production is the central component of a larger whole-tree ecophysiological growth process model for Populus (ECOPHYS). This photosynthesis model was validated by comparing predicted photosynthate production values for individual leaves and the total tree with hourly field measurements collected on four days spaced throughout a growing season. Simulated trees had identical numbers of leaves and leaf areas as the sample trees studied in the field, and hourly weather data collected on the plantation site were supplied as a model input. Total production for the four sample days ranged between 200 and 4900 mg CO(2) tree(-1) day(-1). Model predictions of total daily photosynthate production were within 12% of the observed rates for three of the four sampling days. Diurnal variations in stomatal conductance and ambient CO(2) concentrations and seasonal variations in area leaf weight were the primary sources of error. Total leaf area, proportion of sunlit leaf area, and photosynthetic efficiency were the most important factors influencing carbon dioxide exchange rates.

Nutrient status and nutrient competition of phytoplankton in a shallow, hypertrophic lake

The nutritional status of phytoplankton in a shallow, hypertrophic lake was analyzed by stoichiometry of seston and by enrichment bioassays during a 6‐month period. Both methods suggested moderate and temporally interrupted nutrient limitation of reproductive rates. Nitrogen was the most frequently limiting nutrient, phosphorus was next, and silicate limitation of three diatom species occurred only once. The nutritional status of the most abundant individual species could be described by the Monod equation. The nutritional status of the entire phytoplankton assemblage could be described by a modified version of the Droop equation. In accordance with competition theory, phytoplankton species were arrayed along resource ratio gradients. These results are consistent with ecophysiological models derived from culture experiments.

An ecophysiological model of nitrification in the Scheldt Estuary

A model of nitrification in the Scheldt Estuary by planktonic microorganisms is constructed; this model includes (i) the description of the complex hydrodynamical factors resulting from the mixing of freshwater and seawater; (ii) the influence of environmental parameters (salinity, redox potential, substrate concentration, temperature) on the activity of nitrifying organisms. The model accurately simulates the longitudinal profiles of nitrate and ammonium nitrogen in the estuary.