Increasing Dairy Sustainability with Integrated Crop–Livestock Farming

Abstract

Dairy farms are predominantly carbon sources, due to high livestock emissions from enteric fermentation and manure. Integrated crop–livestock systems (ICLSs) have the potential to offset these greenhouse gas (GHG) emissions, as recycling products within the farm boundaries is prioritized. Here, we quantify seasonal and annual greenhouse gas budgets of an ICLS dairy farm in Wisconsin USA using satellite remote sensing to estimate vegetation net primary productivity (NPP) and Intergovernmental Panel on Climate Change (IPCC) guidelines to calculate farm emissions. Remotely sensed annual vegetation NPP correlated well with farm harvest NPP (R2 = 0.9). As a whole, the farm was a large carbon sink, owing to natural vegetation carbon sinks and harvest products staying within the farm boundaries. Dairy cows accounted for 80% of all emissions as their feed intake dominated farm feed supply. Manure emissions (15%) were low because manure spreading was frequent throughout the year. In combination with soil conservation practices, ICLS farming provides a sustainable means of producing nutritionally valuable food while contributing to sequestration of atmospheric CO2. Here, we introduce a simple and cost-efficient way to quantify whole-farm GHG budgets, which can be used by farmers to understand their carbon footprint, and therefore may encourage management strategies to improve agricultural sustainability.

Aircraft-based inversions quantify the importance of wetlands and livestock for Upper Midwest methane emissions

“…In our previous work, we applied aircraft-based mass balance to quantify facilitylevel emissions for concentrated animal feeding operations in the Upper Midwest and found (as here) good topdown/bottom-up agreement for enteric emissions but discrepancies for manure (Yu et al, 2020). A recent site-level study at a large Wisconsin dairy farm observed low manure emissions (~30% of the enteric flux) owing to frequent field application throughout the year (Wiesner et al, 2020), further supporting our characterization of manure management as a key uncertainty in current large-scale bottom-up inventories.…”

Quantifying the Natural Climate Solution Potential of Agricultural Systems by Combining Eddy Covariance and Remote Sensing

“…Harvest NEP was then compared to annual sums of (a) RS NEP without improvements (RS Lit ), (b) ERF NEP, and (c) improved RS NEP (RS ERF ). Finally, we estimated farm emissions following Wiesner et al (2020), to calculate the farm-scale GHG balance for 2019. Please refer to the Supporting Information S1 for a detailed description of emission calculations.…”

“…Harvest biomass was weighed and stored on site, except for winter wheat harvests, 53% of dry corn kernels, and 22% of soybean harvests, which were sold (Table 3). We used harvest index data (HI; established from personal conversation with the farm manager; Wiesner et al., 2020), dry matter fractions (Table S1 in Supporting Information ), and root to shoot ratios from the literature (Agostini et al., 2015; Bolinder et al., 2007; IPCC, 2006; Little et al., 2017; Saggar et al., 2015) to calculate NEP Harvest . To check whether literature values for root:shoot and dry matter mass would bias our results, we calculated harvest NEP using data from a 2019 field campaign, where aboveground and belowground biomass were collected at three different time points during 2019 (May, July and September).…”

“…While MODIS data have relatively low spatial resolution (250–1,000 m), Landsat imagery with its higher resolution (30 by 30 m) can better resolve field scales of typical agricultural farms. Remote sensing (RS) data have successfully predicted aboveground biomass with relatively low uncertainty in agricultural systems (Pique et al., 2020; Wiesner et al., 2020). However, their implementation into full farm GHG budgets is still limited (Sleeter et al., 2018).…”

Sheep Excrement Increases Mass of Greenhouse Gases Emissions from Soil Growing Two Forage Crop and Multi-Cutting Reduces Intensity

“…Furthermore, the cutting frequency of forage crop was often overlooked, despite being an important factor in forage harvesting or simulated grazing. There have been some important reports on GHG emission inventories from sources of ruminant agriculture based on emission factor methods [16,17] or remote sensing [18], and more field trials are worth implementing in localized emission factor studies. Moreover, studies on the emissions of the three dominant components of GHGs, global warming potential, and the mechanisms of different forage crops should be conducted under a combination of ingestion, excrement, and trampling of grazing livestock, which could be simulated by multi-cutting and animal excrements to a certain extent [19][20][21].…”