Agenda - Planning Commission - 03/02/1999

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Spores of Scutellospora calospora, an arbuscular mycorrhizal fungus that ac- cumulates in the presence of Plantago. Plantago benefits less from S. calospora than from fungi that accumulate in soil in which Panicum is grown. Photo: Jim Bever. agriculture. Negative feedbacks through changes in soil microorgan- isms may also play a role in some instances of succession. Recognition of the importance of negative feedbacks involving AM fungi may also turn out to enhance ecosystem restoration. Bever is cur- rently examining whether AM fungi may contribute to the diversity of prairie vegetation. Some plant spe- cies that are found in prairie rem- nants are resistant to establishment in.restored prairie; Bever notes that AM diversity is lower in restored prairie than in prairie remnants, which raises the possibility that res- toration of the AM fungi may be necessary for full recovery of the vegetation. --RC ONE HUNDRED YEARS ~ OF FOREST MODELING Among ecologists, foresters have perhaps the longest tradition of quan- titative modeling, dating back to the era of European forest scientist Rob- ert Hartig (1839-1901 ), who is cred- ited with producing the first yield table. This type of table, and subse- quent refinements to it, predict the volume of wood that can be har- vested from s,tands at different ages. "Models are still being produced for the principal purpose of predicting forest yield," Harry Valentine, a re- search forester with the USDA For- est Service in Durham, New Hamp- shire, says, "but the newer models predict yield fr6m stands tinder dif- ferent silvicultural treatments, such as weed control, thinning, pruning, fertilization, irrigation, or prescribed burning." Today's forest modelers are also faced with the challenge of account- ing for the effects of global changes, such as the increase of atmospheric carbon dio3dde, on individual stands. This means modeling primary pro- ductivity according to the specific characteristics of the stand in ques- tion arid including such variables as atmospheric carbon dioxide concen- tration and temperature.'Valentine's contribution to this effort has been to link a carbon-allocation model, which predicts the rates of produc- tion of the various organs and tissues of the trees in a stand, to a canopy- level model, which estimates assimi- lation of atmospheric carbon under changing environmental conditions. Valentine and his colleagues use the carbon allocation model known as Pipestem, which views stands as consisting of leaves and feeder roots with active and disused pipes be- tween them. The pipes represent all the woody mattermthe branches, boles, and transport roots. The model projects growth in even-aged single- species stands and is driven by the annual rate of photosynthesis. The rate of photosynthesis is estimated by the canopy-level model MAE- i STRO, which, in turn, is driven by meteorological variables such as tem- perature, vapor-pressure deficit, amount of sunlight, and atmospheric carbon dioxide concentration. For a one-time estimate of a stand's primary productivity, a canopy model alone may suffice. Valentine notes, however, that canopy models generally do not contain the struc- tural detail needed to estimate ad- equately how production of dry mat- ter or respiration will change over time. The carbon allocation model provides this missing information. Pipestem has been calibrated to planted stands oflobloIly pine (Pinus taeda) in Virginia and North Caro- lina. By running Pipestem under a climate change scenario that assumes that the current rate of increase of atmospheric carbon dioxide will con- tinue, Valentine found that "the pro- ductivity of stands of loblolly pine is predicted to increase by 10 to 12 percent in the next 30 to 50 years." He adds, however, that if climatic warming occurs as well, as many scientists predict, this productivity increase will be reduced as a result of increased plant respiration, roDS SCANNING THE GLOBE WITH REMOTE SENSING We may be living in the information age, but ecological modelers con- tinue to confront a scarcity of appro- priate data for driving and validat- ing their theoretical models. For scientists Steve Prince, Sam Goward, Scott Goetz, and Kevin Czajkowski of the Department of Geography at the University of Maryland in Col- lege Park, part of the solution lies in developing a model that can exploit an existing data set. -The group is seeking to estimate a parameter central to forecasting trends in climate change--global net primary productivity. This is the rate at which the biosphere assimilates atmospheric carbon through photo- synthesis minus the rate at which plants release carbon through respi- ration. The mother lode of data used to drive the group's Global Produc- tion Efficiency Model, or GLO-PEM, lies in the optical and thermal re- mote-sensing measurements that have been continuously collected by weather satellites for more than 15 years. Traditionally, scientists have de- rived primary productivity from ob- servations on the ground, through estimates of rates of biomass pro- duction, or through gas-exchange measurements. In the 1980s, how- ever, ecologists discovered that weather satellites were fortuitously collecting data in the spectral re- gions relevant to monitoring the pro- January 1998 7