2012 Annual Report
1a.Objectives (from AD-416):
The objectives of our project are to: i) measure N and P loss in runoff from three pastures representing different grazing management strategies over at least 2 years, ii) use the runoff data to validate the ability of our SurPhos model to predict P loss in runoff from grazed pasture, and iii) use SurPhos to simulate annual P loss from 5 Wisconsin grazing farms using producer-collected data.
1b.Approach (from AD-416):
We will establish runoff plots at the USDA-ARS research farm in Prairie Du Sac, WI & install a runoff collection system. We will collect runoff year-round & analyze samples for total sediment, total N and P, & dissolved P, NH4, & NO3. We will collect initial & annual soil samples from plots & have them analyzed. We will stock runoff plots with nonlactating dairy cattle to achieve 3 management scenarios: normal supplementation & grazing intensity, normal supplementation/high grazing intensity, & high supplementation/normal grazing intensity. These strategies will result in different amounts of manure & associated nutrient amounts applied to runoff plots. After grazing periods, we will count the number of dung pats deposited in each runoff plot section & collect samples to determine total wet weight, dry matter content, total P and N, & water-extractable P. We will then quantify nutrient inputs to the runoff plots in cattle feces. We will collaborate with 5 grazing producers in WI whose farms represent a range of stocking densities. We will interview each farm operator quarterly to document farm structure & management, including herd size & composition, livestock facilities, land use, & grazing practices. We will develop grazing & manure spreading logs for producers to document actual manure spreading & grazing practices. These data will enable us to quantify the amount of manure nutrients applied to all pastures. During each visit, we will ask producers for the number of existing cows and their feed management, & take samples of each feed component & pasture grasses for analysis. To determine amount of manure collected & applied to pasture, we will assess herd management, barn cleaning, manure storage practices, & when, where, how, & how much collected manure is land-applied. We will ask where and how long livestock are outdoors to ascertain the amount of uncollected manure. We will collect feces or manure samples from outdoor areas & storage facilities. These data will enable us to determine nutrient mass flows on each farm & the amount of nutrients applied to pastures. Soil samples will be taken from all outside cattle areas for our environmental impact modeling & data validation exercises. We will also collect landscape data, such as slope & slope length to estimate runoff potential in later modeling exercises. Runoff data will be used to validate our SurPhos model, which simulates dissolved P loss in runoff from surface-applied manure. Validation of the model will determine its ability to accurately simulate P loss in runoff from cattle grazing pastures. We are currently adapting SurPhos to simulate grazing and validating the model with field data from Australia & England & small-plot, simulated grazing data from several locations in the U.S. We will use producer information & data to simulate P loss from areas where cows spend time outside, including pasture, over-wintering areas, & barnyards. We will then investigate the physical locations & management practices that represent the greatest risk of P loss, & assess the ability of alternative practices to minimize that loss.
This report relates to Objective 1 of that project: Determine the effects of dairy diets and herd management on manure nutrient excretions and nutrient losses to the environment. We monitored surface runoff from eight pasture watersheds at the University of Wisconsin Platteville Pioneer farm from August 2010 to June 1, 2012. We analyzed 117 samples from 19 runoff events for sediment, nitrogen, and phosphorus (P). Based on measured runoff volume and sediment and P concentration data, we estimated annual runoff, erosion, and P loss from the pastures. The Annual P Loss Estimator (APLE) model has been able to accurately predict P loss from the grazed pastures. We also tested APLE with pasture runoff data from 18 studies published in the literature, with a strong relationship between measured and predicted P loss. This validates that APLE is able to predict P loss from pastures. In turn, this gives confidence that APLE can be used to predict whole farm P loss from the four cooperating grazing farms. We visited each farm three times in 2011, and gathered management data to represent a full calendar year across different seasons. At each visit, we collected comprehensive herd, feed, and manure management information, and collected feed and manure samples for lab analysis of phosphorus. We used the manure and feed sample information to develop a relationship between the amounts of P fed to cows and in manure. The relationship was consistent with the published literature. We completed all whole farm simulations in the Soil Nutrient Application Planner-Plus (SNAP+) software, which generated information on runoff, erosion, and P loss for all farm fields, pastures, cattle holding areas, and barnyards. We use runoff and erosion information from SNAP+ as input into APLE, and we predicted whole-farm P loss with APLE and SNAP+. We are comparing APLE and SNAP+ results to determine any differences. Because we will have validated the APLE model, this process will help determine how well SNAP+ (and thus the Wisconsin P Index) estimates P loss from pastures. We are also determining the degree of runoff P loss from different areas on the four farms to identify areas potentially requiring management attention.