Quercus-Acer (oak-maple) st'.111d in c~ntral l\ l~1ssac~1u selts, US/\. The key hy pothesis J!OVe rnmg the b1oloA1cal component of the model is Urnt stomata! conductance (g,.) is var ied s o that d ail y carbon uptake per unit of foliar nit r oj:!en is maximized wit hin the limitations of ca1101>Y water avr1ilability. T he h ydraulic system is modelled as :m a nalo~ue to simple electr ical circuits in parallel. includinJ! a separate soil hydraulic resistance. plant resistance and plant capacitance for each c:m op y layer. Stomata! openin(! is initially controlled to conserve plant water stores and delay the o nset or water stress. Stomata! clos ure at :i threshold minimum l~1f water potential prevents xyle m cavitation and contr ols the maximum r:itc of wate r llux through the h ydraulic system. We show a strong correlat ion between predicted hourly C0 2 exchange rate (r2 = 0·86) and LE (r 2 = 0·87) with independent whole-forest measurements made by the eddy correlation method during the s ummer of 1992. Our theoretical derivation s hows that observed relationships between C0 2 assimilation a nd LE nux can he explained on the basis of s tomata! behaviour 01>timizing c:irhon gain, and provides mt exi>licit link hetwecn canopy structure, soil pro1>erties. atmos pheric conditions and stomatal conductance.Ke\'-111ords: Q11erc11s r11hm: l\cl'r rulnw11: soil-pla11t-a1r~10spherc coniinuum model: photosynlhcsis: plant hydr:1ulic conductance: s1o ma1al conduc tance.
Our goal was to construct a simple, highly aggregated model, driven by easily available data sets, that accurately predicted terrestrial gross primary productivity (GPP; carboxylation plus oxygenation) in diverse environments and ecosystems. Our starting point was a fine‐scale, multilayer model of half‐hourly canopy processes that has been parametrized for Harvard Forest, Massachusetts. Over varied growing season conditions, this fine‐scale model predicted hourly carbon and latent energy fluxes that were in good agreement with data from eddy covariance studies. Using an heuristic process, we derived a simple aggregated set of equations operating on cumulative or average values of the most sensitive driving variables (leaf area index, mean foliar N concentration, canopy height, average daily temperature and temperature range, atmospheric transmittance, latitude, day of year, atmospheric CO2 concentration, and an index of soil moisture). We calibrated the aggregated model to provide estimates of GPP similar to those of the fine‐scale model across a wide range of these driving variables. Our calibration across this broad range of conditions captured 96% of fine‐scale model behavior, but was computationally many orders of magnitude faster. We then tested the assumptions we had made in generating the aggregated model by applying it in different ecosystems. Using the same parameter values derived for Harvard Forest, the aggregated model made sound predictions of GPP for wet‐sedge tundra in the Arctic under a variety of experimental manipulations, and also for a range of forest types across the OTTER (Oregon Transect Ecosystem Research) transect in Oregon, running from coastal Sitka spruce to high‐plateau mountain juniper.
Our goal was to construct a simple, highly aggregated model, driven by easily available data sets, that accurately predicted terrestrial gross primary productivity (GPP; carboxylation plus oxygenation) in diverse environments and ecosystems. Our starting point was a fine-scale, multilayer model of half-hourly canopy processes that has been parametrized for Harvard Forest, Massachusetts. Over varied growing season conditions, this fine-scale model predicted hourly carbon and latent energy fluxes that were in good agreement with data from eddy covariance studies. Using an heuristic process, we derived a simple aggregated set of equations operating on cumulative or average values of the most sensitive driving variables (leaf area index, mean foliar N concentration, canopy height, average daily temperature and temperature range, atmospheric transmittance, latitude, day of year, atmospheric CO 2 concentration, and an index of soil moisture). We calibrated the aggregated model to provide estimates of GPP similar to those of the fine-scale model across a wide range of these driving variables. Our calibration across this broad range of conditions captured 96% of fine-scale model behavior, but was computationally many orders of magnitude faster. We then tested the assumptions we had made in generating the aggregated model by applying it in different ecosystems. Using the same parameter values derived for Harvard Forest, the aggregated model made sound predictions of GPP for wetsedge tundra in the Arctic under a variety of experimental manipulations, and also for a range of forest types across the OTTER (Oregon Transect Ecosystem Research) transect in Oregon, running from coastal Sitka spruce to high-plateau mountain juniper.
The effects of a variety of agricultural land uses were studied using soil nutrients, forest structure, and species assemblages as indicators. We compared soil properties and successional forests between abandoned cacao (Theobroma cacao) and abandoned palm (Bactris gasipaes) orchards, abandoned pasture, and mature forest. These sites co‐occupy an alluvial terrace soil (Andic Dystropept) at La Selva Biological Station, Costa Rica. The agricultural sites were originally cleared of most or all forest vegetation approximately 30 years ago and went into succession approximately 7 years ago. Forest structure, species composition, soil nitrogen and phosphorus pools, and nitrogen‐mineralization and nitrification rates were measured for each site. The abandoned palm orchard had lower basal area and stem density than other secondary forests of the same age. It also had significantly smaller nitrate (NaOH‐extractable) and organic phosphorus pools and significantly lower net rates of nitrogen‐mineralization and nitrification. It is evident that preserving tree cover does not necessarily maintain soil fertility. We found species richness and diversity in the secondary forests to be positively correlated with basal area at the time of abandonment.
We used a process‐based model of ecosystem biogeochemistry (MBL‐GEM) to evaluate the effects of global change on carbon (C) storage in mature tropical forest ecosystems in the Amazon Basin of Brazil. We first derived a single parameterization of the model that was consistent with all the C stock and turnover data from three intensively studied sites within the Amazon Basin that differed in temperature, rainfall, and cloudiness. The range in temperature, soil moisture, and photosynthetically active radiation (PAR) among these sites is about as large as the anticipated changes in these variables in the tropics under CO2‐induced climate change. We then tested the parameterized model by predicting C stocks along a 2400‐km transect in the Amazon Basin. Comparison of predicted and measured vegetation and soil C stocks along this transect suggests that the model provides a reasonable approximation of how climatic and hydrologic factors regulate present‐day C stocks within the Amazon Basin. Finally, we used the model to predict and analyze changes in ecosystem C stocks under projected changes in atmospheric CO2 and climate. The central hypothesis of this exercise is that changes in ecosystem C storage in response to climate and CO2 will interact strongly with changes in other element cycles, particularly the nitrogen (N) and phosphorus (P) cycles. We conclude that C storage will increase in Amazonian forests as a result of (1) redistribution of nutrients from soil (with low C:nutrient ratios) to vegetation (with high C:nutrient ratios), (2) increases in the C:nutrient ratio of vegetation and soil, and (3) increased sequestration of external nutrient inputs by the ecosystem. Our analyses suggest that C:nutrient interactions will constrain increases in C storage to a maximum of 63 Mg/ha during the next 200 years, or about 16% above present‐day stocks. However, it is impossible to predict how much smaller the actual increase in C storage will be until more is known about the controls on soil P availability. On the basis of these analyses, we identify several topics for further research in the moist tropics that must be addressed to resolve these uncertainties.
A search has been made for charged particles with anomalously short mean free paths (irrespective of baryon number or charge) in the fast (momentum greater than 1 GeV/c) secondaries of deuteron-deuteron collisions at 7.9 GeV/c. Limits are given for production rates. At the 99% confidence level, compared to normal particles, these are of order 1% for a mean free path of 25 cm and of order 0.1% for a mean free path of 10 cm.
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