An indicator of freeze-kill damages to fruit trees during flowering.

This paper demonstrates the use of climatological data and published information to develop a thaw-freeze/freeze-kill indicator for fruit trees during flowering. In fruit-producing regions, when budding and flowering occur before the last spring freeze, a freeze-kill event can cause substantial losses. As spring onset is occurring earlier with climate change, thaw-freeze events have the potential to become more of a hazard both in terms of current production and in terms of potential adaptation strategies. To model the spring thaw-freeze and its magnitude or intensity, we proposed an indicator based on the accumulation of daily minimum temperature between successive freezing dates and its maximum value over the spring. This indicator was tested on apple and peach production in southern Ontario, Canada, using data from eight climate stations in southern Ontario. The indicator showed promise in its utility in that its magnitude was greater when freezing occurred after blooming and it was demonstrated to be correlated to the estimated blooming dates of apple and peach fruits grown in southern Ontario. The annual series was shown to fit the generalized extreme value distribution thereby allowing the extreme risk to be modelled and the return period to be calculated. It was also shown that the reported thaw-freeze events that caused significant apple and peach losses had a return period on the order of 10 years.

Influence of two management practices in the Canadian Prairies on radiative forcing.

Surface albedo and soil carbon sequestration are influenced by agricultural management practices which impact the Earth's radiation budget and climate change. In this study we investigate the impact of reduced summer fallowing and reduced tillage in the Canadian Prairies on climate change by estimating the change in radiative forcing due to albedo and soil carbon sequestration. Seasonal variations of albedo, which are dependent on agricultural management practices and soil colour in three soil zones, were derived from 10-day composite 250-m Moderate Resolution Imaging Spectroradiometer (MODIS) data. Using this information, we found an overall increase of surface albedo due to the conversion from summer fallowing to continuous cropping and from conventional tillage (CT) to either no-tillage (NT) or reduced tillage (RT). The increase was dependent on soil brightness, type of vegetation and snow cover. Using data from the Census of Agriculture and taking into consideration both albedo and soil carbon changes, we estimated that from 1981 to 2016, the total radiative forcing for the cropland area in the Canadian Prairies was -405 µW m-2 due to the conversion of CT to either NT or RT and about 70% was due to the change in albedo. During the same period, the total radiative forcing was -410 µW m-2 due to a reduction in the area under summer fallow and about 62% was due to the change in albedo. The equivalent atmospheric CO2 drawdown from these two management changes from albedo change was about 7.8 and 8.7 Tg CO2 yr-1, respectively. These results demonstrate that it is important to consider both the changes of soil carbon and surface albedo in evaluating climate change impacts due to agricultural management practices.

Assessing the effects of manure application rate and timing on nitrous oxide emissions from managed grasslands under contrasting climate in Canada.

It is uncertain whether process-based models are currently capable of simulating the complex soil, plant, climate, manure management interactions that influence soil nitrous oxide (N2O) emissions from perennial cropping systems. The objectives of this study were (1) to calibrate and evaluate the DeNitrification DeComposition (DNDC) model using multi-year datasets of measured nitrous oxide (N2O) fluxes, soil moisture, soil inorganic nitrogen, biomass and soil temperature from managed grasslands applied with manure slurry in contrasting climates of Canada, and (2) to simulate the impact of different manure management practices on N2O emissions including slurry application i) rates (for both single vs. split); and ii) timing (e.g., early vs. late spring). DNDC showed "fair" to "excellent" performance in simulating biomass (4.7% ≤ normalized root mean square error (NRMSE) ≤ 29.8%; -9.5% ≤ normalized average relative error (NARE) ≤ 16.1%) and "good" performance in simulating soil temperature (13.2% ≤ NRMSE ≤ 18.1%; -0.7% ≤ NARE ≤ 10.8%) across all treatments and sites. However, the model only showed "acceptable" performances in estimating soil water and inorganic N contents which was partially attributed to the limitation of a cascade water sub-model and inaccuracies in simulating root development/uptake. Although, the DNDC model only demonstrated "fair" performance in simulating daily N2O fluxes, it generally captured the impact of the timing and rate of slurry application and soil texture (loam vs. sandy loam) on total N2O emissions. The DNDC model simulated N2O emissions from spring better than split manure application (fall and spring) at the Manitoba site partially due to the overestimation of available substrates for microbial denitrification from fall application during the wet spring periods. Although DNDC performed adequately for simulating most of the manure management impacts considered in this study we recommend improvements in the simulation of soil freeze-thaw cycles, manure decomposition dynamics, soil water storage, rainfall canopy interception, and microbial denitrification and nitrification activities in grasslands.

Carbon footprint of Canadian dairy products: calculations and issues.

The Canadian dairy sector is a major industry with about 1 million cows. This industry emits about 20% of the total greenhouse gas (GHG) emissions from the main livestock sectors (beef, dairy, swine, and poultry). In 2006, the Canadian dairy herd produced about 7.7 Mt of raw milk, resulting in about 4.4 Mt of dairy products (notably 64% fluid milk and 12% cheese). An integrated cradle-to-gate model (field to processing plant) has been developed to estimate the carbon footprint (CF) of 11 Canadian dairy products. The on-farm part of the model is the Unified Livestock Industry and Crop Emissions Estimation System (ULICEES). It considers all GHG emissions associated with livestock production but, for this study, it was run for the dairy sector specifically. Off-farm GHG emissions were estimated using the Canadian Food Carbon Footprint calculator, (cafoo)(2)-milk. It considers GHG emissions from the farm gate to the exit gate of the processing plants. The CF of the raw milk has been found lower in western provinces [0.93 kg of CO2 equivalents (CO2e)/L of milk] than in eastern provinces (1.12 kg of CO2e/L of milk) because of differences in climate conditions and dairy herd management. Most of the CF estimates of dairy products ranged between 1 and 3 kg of CO2e/kg of product. Three products were, however, significantly higher: cheese (5.3 kg of CO2e/kg), butter (7.3 kg of CO2e/kg), and milk powder (10.1 kg of CO2e/kg). The CF results depend on the milk volume needed, the co-product allocation process (based on milk solids content), and the amount of energy used to manufacture each product. The GHG emissions per kilogram of protein ranged from 13 to 40 kg of CO2e. Two products had higher values: cream and sour cream, at 83 and 78 kg of CO2e/kg, respectively. Finally, the highest CF value was for butter, at about 730 kg of CO2e/kg. This extremely high value is due to the fact that the intensity indicator per kilogram of product is high and that butter is almost exclusively fat. Protein content is often used to compare the CF of products; however, this study demonstrates that the use of a common food component is not suitable as a comparison unit in some cases. Functionality has to be considered too, but it might be insufficient for food product labeling because different reporting units (adapted to a specific food product) will be used, and the resulting confusion could lead consumers to lose confidence in such labeling. Therefore, simple units might not be ideal and a more comprehensive approach will likely have to be developed.

Methane emissions from a dairy feedlot during the fall and winter seasons in Northern China.

Accurately determining methane emission factors of dairy herd in China is imperative because of China's large population of dairy cattle. An inverse dispersion technique in conjunction with open-path lasers was used to quantify methane emissions from a dairy feedlot during the fall and winter seasons in 2009-2010. The methane emissions had a significant diurnal pattern during both periods with three emission peaks corresponding to the feeding schedule. A 10% greater emission rate in the fall season was obtained most likely by the higher methane emission from manure during that period. An annual methane emission rate of 109±6.7 kg CH4 yr(-1) characterized with a methane emission intensity of 32.3±1.59 L CH4 L(-1) of milk and a methane conversion factor (Ym) of 7.3±0.38% for mature cattle was obtained, indicating the high methane emission intensity and low milk productivity in Northern China.

Aircraft monitoring of surface carbon dioxide exchange.

Aircraft-mounted sensors were used to measure the exchange of carbon dioxide above a cornfield, a forest, and a lake under midday conditions. Mean absorption values of 3400, 1200, and 100 milligrams of carbon dioxide per square meter per hour, respectively, are consistent with reported ground-based observations of carbon dioxide flux. Such information, gathered by aircraft, could be used to provide a quantitative evaluation of source and sink distributions of carbon dioxide in the biosphere, to establish a correlation between satellite data and near-surface measurements, and to monitor crop performance.