Potential climate change impacts on temperate forest ecosystem processesEmily B.Peters, Kirk R.Wythers, Shuxia Zhang, John B.Brandford, and Peter B.Reich

Introduction-Global and regional climate change have been proven. Relentless and drastic climate change have been forecasted in the near future. It has been estimated that in the year 2100 the global mean temperature would rise from 1.4 degrees to 5.8 degrees C. Human beings are heavily dependent on the forest resources. Due to the inevitable climate change the safety of the ecosystems is of great concern. Carbon Dioxide experiments and various other experiments have been studied and implemented in order to understand the potential effects of rising temperature in the forests ecosystems. Manipulative studies provide an insight towards understanding the response of an ecosystem under climate change. Therefore, ecosystem models are preferred in studying the environmental change factors on regional forests ecosystems. In this study the PnET-CN ecosystem model is applied to study the long term effects and forecast the climate change in the near future. The area covered is the Great lakes region of North America. Great lakes contains a diversity of forest types and intersection of three biomes that are southern hardwood forests, western tall-grass prairie and northern boreal forests. Prior to this study it is predicted that by 2069 the annual temperature will increase by 3 degree C and precipitation upto 6 degree C. The objectives of this study was to compare the long term effects of climate change, atmospheric carbon dioxide levels, evapotranspiration, run off and net mineralization. The ecosystem response is also taken into account.

Methodology-The North Great Lake (40.350.3 degree N latitude and 80.5-97.2 degree W longitude) comprises of 26 million hectares containing six major forests types known as Laurentian mixed forest. The climate type of the forests consists of short and mild summers and long winters. The PnET-CN model is well tested model that predicts the exact data of carbon, water and nitrogen dynamics in the forests. The model simulates the photosynthesis and transpiration activity in a multilayered canopy. PnET-CN model emphasizes on biogeochemical cycles and physiological activity of respiration, water balance, and carbon allocation. Nitrogen cycle along with the water cycle reacts with one another this allows the PnET-CN to simulate the productivity. The PnET-CN model can generate canopy N concentration, leaf area index, N deposition, tropospheric zone and atmospheric carbon dioxide. The model has been modified so that it can incorporate the respiration activity of plants to gradual changes in the climate. 96 cores on Linux cluster is a well-developed distributed parallel- computing framework for PnET-CN that reduces the simulation of 60 days to 5 hours. The calculation required to run PnET-CN is 1KM X 1KM respectively. PnET-CN depends on input information on soil, vegetation, atmospheric conditions. Two statistically downscaled climate projections that is PCMB1 and GFDL A1F1. The two models simulate the carbon dioxide emissions. The figure suggests that the PCMB1 predicts lower emissions than the GFDL A1F1 model. The projections suggest that the carbon dioxide concentration rises from 548-970ppm by 2099. PCMB1 predicts the increase in annual temperature of 1.5 degree C. and annual precipitation of 84mm. GFDL A1F1 scenario predicts 4.8 degree C increase in mean annual temperature and 1mm decline in annual precipitation.

Using Michaelis-Menton equation and after running the PnET-CN model increases the photosynthetic rates and reduces stomatal conductance. Solar radiation data was measured at 169 sites (1981 and 2011). Due to uncertainty of solar radiation in future climate change spatial interpolation of mean monthly photosynthetically active radiation (PAR) were applied in the model. Dry nitrate and ammonium data and troposphere ozone irregularities data was taken into account. Due to the uncertainty in future projections of N deposition and ozone concentration the concentrations assumed were 20% and 10% in 1930. Hence, the feedback mechanisms were not taken into consideration. N deposition affects the soil carbon and nitrogen pools. Tropospheric zones limit the photosynthesis activity in the model. Water holding capacity map (National Conservation Resource Services Soil Survey Geographic Database) was utilized the values were calculated based on soil texture and soil depth 1mm. The datasets used were SSURGO and STATGO. The model is used to explore how productivity would change the land composition. Above ground net primary productivity (ANPP) is focused used to measure the productivity. Pearson correlation between ANPP and temperature, water holding capacity and precipitation was conducted.Result:-Predicted changes in the ANPP were highly dependent on climate scenario and CO2 effects. It was observed that the PnET-CN showed a smaller average increase of 372gms per year and under the PCMB1 projection 750gms per year under GFDL A1F1, Average regional increase ANPP increased. This was only observed when the CO2 routine was implemented. When CO2 routine was omitted decline was observed under the GFDL A1F1 scenario. Resulting in complete confirmation that ANPP is sensitive to climate change and will experience future warming due to high concentrations of CO2. Under the implementation of CO2 routine the increase in ANPP occurred in eastern Minnesota, northern Wisconsin and upper Michigan. The four deciduous forests experienced highest average ANPP from 1960-2099, it peaked in the year 2080 under the PCM B1 scenario. ANPP strongly correlated with annual summer annual temperature, annual summer precipitation whereas spatial differences in future ANPP were most strongly and positively correlated with annual temperature and water holding capacity under the PCM B1 scenario. It was negatively correlated under the GFDL A1F1 scenario. The concept of first and last month assessment is known as growing season length it estimated the increase in positive net C balance. Average regional evapotranspiration increased by 3cm year. Average run off increased by 1cm year under the PCMB1 scenario 3cm year. Evapotranspiration ranged from -12 to +13 year. Largest increase in N mineralization occurred in north central and north eastern Minnesota, northern Wisconsin and upper Michigan.Discussion:-PnET-CN model predicted impacts of forests ecosystems in the Great lakes regions of North America. Based on results net primary productivity increased by 25%-88%, run off changed by -2% to +53%. Detailed hydrological model VIC predicted changes in evapotranspiration. 10% run off increased across the Lake Michigan region. CO2 effects and stomatal conductance were accounted for all models except for the hydrological model. Changes in CO2 greatly influence the climate change than precipitation or temperature. Increase in productivity was estimated when the CO2 routine was implemented. In the PnET-CN direct CO2 effects on photosynthesis represented as saturated response. Indirect effects via reduced stomatal conductance. There is no model that have examined CO2 concentrations greater than 700ppm in case of temperate forests. The model measures the CO2 concentration that simulates the effects of not only climate change but also the ecosystem dynamics. Warmest climate observed at GFDL A1F scenario for all forest types the future productivity was negatively correlated with temperature across the region. Areas with less water holding capacity is prone to less productivity. Four deciduous forest have different responses to future climate scenarios, it was observed that each parameter relating to the leaf mass per area and temperature for photosynthesis proved to be different. When interpreting the results of the model it was very important to understand various limitations and ambiguities of the PnET-CN model. Succession, migration, natural disturbances or calamities are not taken into consideration for this model. Climate change interactions, fragmentation, competition and dispersal is likely to influence the future composition and structure of the forest ecosystems. PnET-CN do not take into account the plant regeneration, germination and seedling establishment. Future emissions will exceed A1F1 it will be assessed by the Intergovernmental Panel on climate change in its fifth assessment report.

Conclusion:-The main motive of the model is to evaluate the long term effects of climate change on forest ecosystems and to estimate its productivity, evapotranspiration, runoff, N mineralization across the Great Lakes region of North America. CO2 routine was implemented and results suggested that average regional changes in climate would increase from 67% to 142%. Evapotranspiration could range from -3% to 6% runoff could increase from 2% to 22%. N mineralization could increase 10% to 12%. Once CO2 routine was eliminated the productivity was stable and eventually declined in some scenarios. This suggests that increase in productivity were the consequences of rising CO2 itself and not climate change. Ecosystem responses were different for different forests types. Increase in productivity was observed in the four deciduous forests and spatial drives of this variation were relatively consistent. Great Lake responses is useful for natural resource management it is suggested that the Great Lakes will switch from being temperature limited to water limited by the end of the century.

Vivek Bhojwani Roll No:1