Modeling phosphorus in the environment - Chapter 14 ppt

333 14 Challenges to Using and Implementing Phosphorus Indices in Nutrient Management Planning: an MMP Perspective Philip Hess Purdue University, West Lafayette, IN Bradley Eisenhauer Purdue University, West Lafayette, IN Brad Joern Purdue University, West Lafayette, IN CONTENTS 14.1 Introduction 334 14.2 Design Flaws Present in Many First-Generation PIs 334 14.2.1 Overview 334 14.2.2 Inconsistencies between Prescreening Tools and PIs 335 14.2.3 Lack of Sliding Scales in PI Subcategories 336 14.2.4 Lack of Sliding Scales in Overall PI Interpretations 336 14.2.5 The Chicken–Egg Problem 337 14.2.6 The Bermuda Triangle 339 14.2.7 Temporal Discontinuities 340 14.3 Challenges Commonly Encountered by First-Generation PI Users 341 14.3.1 Overview 341 14.3.2 Some Input Data May Not Be Known during Planning 341 © 2007 by Taylor & Francis Group, LLC 334 Modeling Phosphorus in the Environment 14.3.3 What If a Field Is Not Uniformly Manured? 342 14.3.4 Gaming the System 342 14.4 Challenges and Opportunities for Implementing PIs in the Future 343 14.4.1 Potential Implementation Approaches 343 14.4.2 Implementation Challenges 345 14.4.2.1 Interpreting the Risk Assessment Procedure 345 14.4.2.2 Supplying Soil Loss Estimates 346 14.4.2.3 Errors or Gaps in Soils Data 346 14.4.2.4 Program Support and Maintenance 347 14.5 Conclusions 348 References 349 14.1 INTRODUCTION Evaluating the potential risk of phosphorus (P) loss from crop fields to surface- and groundwater resources is an important component of the nutrient management plan- ning process. Nearly all states have developed a P index (PI) or other state-specific P risk assessment tool for this purpose. Though most PIs were originally imple- mented as paper worksheets or computer spreadsheets, in practice nearly all planners will use PI tools implemented via computer software to speed up the planning process. In developing the Manure Management Planner (MMP) software, we have programmed more than a dozen state-specific PI tools and have evaluated many others as we prepare to program them (MMP, 2006). During this process we dis- covered several significant challenges to both the use and implementation of PIs that must be addressed before they can be used effectively for writing and implementing nutrient management plans (NMPs). Our experience in programming and evaluating various PIs, and our interactions with planners who use them, inform much of the discussion presented in this chapter. The general topics covered in this chapter include design flaws present in many first-generation PIs, challenges commonly encountered by PI users, and challenges and opportunities related to future PI development and implementation. The infor- mation presented in this chapter should be useful to PI developers and programmers, planners using first-generation PIs, and state and federal agency personnel respon- sible for reviewing NMPs that include PI assessments. 14.2 DESIGN FLAWS PRESENT IN MANY FIRST-GENERATION PIs 14.2.1 O VERVIEW The purpose, use, and interpretation of PIs vary widely from state to state. In some states the PI interpretation is prescriptive and does limit the amount of P that can be applied to fields that fall into certain categories of risk. In other states, the PI © 2007 by Taylor & Francis Group, LLC Challenges to Using and Implementing Phosphorus Indices 335 result is more advisory in nature and is used to identify potential problems associated with P applications and to select fields and practices that present the lowest risk. Ideally, field assessment using a PI or other P risk assessment tool should include two steps. The first step should identify the inherent soil and landscape factors that may limit P applications to a field, and the second step should determine the optimum or maximum rate of P that may be applied based on application time and method. The planner should use the results of the initial assessment to discuss inherent risk factors with the producer and should determine how to address these issues with improved management — if this is an option — and then should use the PI to determine the optimum or maximum P rate. At a minimum, PIs should determine allowable P rates based on time and method of application and other field and management variables. Unfortunately, many PIs were originally designed as post mortem risk assess- ment tools rather than tools to help planners determine the optimum or maximum rates of P that can be applied to a field. In these PIs, the assessment includes the rate, time of year, and method of manure and commercial fertilizer P applications, and the planner must run multiple scenarios to determine the optimum or maximum rate of P that can be applied. If the objective of a PI is to help the user determine P application rates, then many first-generation PIs fall short of the mark. The following sections discuss some of the design flaws present in many PIs that limit their potential usefulness for developing effective NMPs. 14.2.2 I NCONSISTENCIES BETWEEN P RESCREENING T OOLS AND PI S Planners typically perform some type of P risk assessment on all crop fields as part of the nutrient management planning process. Due to the repetitive, computation- intensive nature of most PIs, PI developers in many states developed a prescreening procedure that eliminates the need to conduct the full PI on a field if certain criteria are met. These prescreening procedures typically look at distance to water body, soil test P level, field slope, or other readily available information. Though prescreening procedures do reduce the total number of PI calculations, they also increase the risk of overlooking potentially problematic fields and management scenarios and also may lead to management decisions that will dramatically change the assessment status of a field during the next round of plan development. For example, if a prescreening procedure looks only at a field’s soil test P level and distance to water, then the field will be exempt from the full PI assessment if its P level is below a certain value and its distance to water is greater than a certain value. If the field is exempt from further assessment, this usually means that manure can be applied annually at a rate that supplies crop nitrogen (N) needs or, in the case of legumes, the amount of N that the crop can utilize. In states where the rate can be increased to account for anticipated losses of N between the time of appli- cation and the time of plant N utilization, this can result in many years worth of P being applied between soil tests if the state does not have any other cap on the rate. In this case the planner is doing exactly what the assessment allows, but because © 2007 by Taylor & Francis Group, LLC 336 Modeling Phosphorus in the Environment the prescreening procedure allows the planner to skip the full PI assessment on certain fields, they may be setting up the producer for a shock the next time the soil in those fields is tested. In addition, since most PIs include the time, rate, and method of manure application, we often find that N-based manure applications to fields excluded from the full PI assessment based on prescreening results have PI results that would not allow N-based management if the full PI had been run on these fields. This lack of consistency in assessment makes the use of prescreening approaches questionable in some states. With PI tool automation via computer software, the additional increase in plan-writing efficiency made possible by using prescreening tools probably is not great enough to justify the risk of overlooking potentially problematic fields or of encouraging nonsustainable management strategies in the resulting NMP. 14.2.3 L ACK OF S LIDING S CALES IN PI S UBCATEGORIES Nonsustainable P management plans often occur when a state does not have a sliding scale on the upper ends of subcategories in traditional, matrix-based PIs. For example, a state that does not have a soil test P limit above which no additional P can be applied assigns the same number of points to any field above a certain soil test P level. In the original PI template, a field is assigned eight points if its soil test level is considered very high (Lemunyon and Gilbert, 1993). A state might set the breakpoint for the very high category at 100 parts per million (ppm), meaning a field with a soil test P level of 101 ppm would be assigned the same 8 points as a field with a soil test P level of 1001 ppm. The consequence of this is that, all other things being equal, no distinction is made in the assessment among fields that may be acceptable candidates for manure application and fields that are probably very poor candidates for manure application. This can create a false sense of security for the producer, who may continue managing the highest testing fields in the same way that caused them to become high testing fields in the first place. States that have implemented PIs with this problem could easily address this issue with a sliding scale on the high risk end categories of all PI inputs in matrix-based PIs. 14.2.4 L ACK OF S LIDING S CALES IN O VERALL PI I NTERPRETATIONS Though many PIs scale open-ended inputs like soil test P, soil loss, and P application rate to avoid abrupt changes in a factor’s risk category due to small changes in input values, the interpretation of the field’s overall PI value is usually not scaled. Instead, most PIs have threshold values that are used to assign a field’s overall PI value to one of several interpretation categories. For example, a PI might have a threshold value of 6.0, where a PI value above 6.0 indicates that no P can be applied and a PI value of 6.0 or below indicates that some P can be applied. What this means for the planner and producer is that there is a significant difference between, say, 6.0 and 6.1, even © 2007 by Taylor & Francis Group, LLC Challenges to Using and Implementing Phosphorus Indices 337 though the magnitude of the numeric difference is small and may simply be due to subtle differences in the way soil loss was estimated, for example. The overall implication of hard thresholds in PIs is that the accuracy, even of open-ended inputs, is critical, particularly soil loss. These thresholds also encourage the planner to play with the inputs when a field’s PI value falls slightly above a threshold rather than suggesting management changes that could actually reduce the risk of P loss from the field. In many PIs, no scientific basis is given for the choice of threshold values. And since the thresholds appear to be arbitrary, planners and producers understandably question why the interpretation is so inflexible. This issue could be resolved with minor modifications to many current PIs. 14.2.5 T HE C HICKEN –E GG P ROBLEM As stated previously, most PIs are post mortem assessment tools that include the rate, time of year, and method of manure or commercial fertilizer P application. With these PIs, the planner must run multiple scenarios to determine the optimum or maximum rate of P that can be applied. This is a common problem with nearly all PIs and is illustrated in the following scenario. A planner wants to know the greatest possible P application rate that presents an acceptable risk of P loss. The PI requires information about planned nutrient applications and will indicate, once it has this information, if the planned appli- cations are acceptable. For example, if the planner selects an application rate that supplies the planned crop’s N need, two outcomes are possible when this appli- cation is analyzed for risk. Either the application presents an acceptable risk, or it does not. If the risk is too great, the rate must be reduced or the management must be changed to lower the risk. However, if the rate is reduced, for example to supply only the crop’s P need, a subsequent PI run might indicate that the risk with the reduced rate is low enough that the rate can be increased. Somewhere in-between the N-based rate and the P-based rate is the optimal rate that the planner wants, but the assessment procedure is unable to determine it. So the planner is forced into a game of trial and error, oscillating between higher and lower rates until the desired rate is eventually discovered. Table 14.1 illustrates this iterative procedure. In practice, determining the ideal rate this way can be a time-consuming and frustrating experience. Though the risk assessment procedure is doing what it was designed to do, which is to assess the risk for a given nutrient application scenario, that is largely all it can do. For each application scenario, the planner must review the available sources of organic and commercial fertilizer nutrients; consider appli- cation equipment, timing windows, and labor availability; take into account hauling costs if manure is involved; and discuss these issues with the producer, only to discover after the risk assessment is performed that much of this work may have been for naught. Many planners intuitively understand that what is needed is a way of assessing risk before committing resources to the actual nutrient application planning. We have © 2007 by Taylor & Francis Group, LLC 338 Modeling Phosphorus in the Environment learned that some planners will run the PI report before planning any nutrient applications in MMP, hoping to discover something about the fields’ relative risk independent of any nutrient applications. Since planning nutrient applications can be one of the most time-consuming components of NMP development, planners naturally are looking for ways to expedite this process. Though the preapplication PI report will not be the final one, it may provide important clues about what fields are poor candidates for nutrient applications in any scenario and what fields are likely to be good candidates. We have identified a couple of ways to address this obvious planning need. One would be to develop a preliminary risk assessment procedure that considers only the field’s inherent properties such as soil type, soil properties, field slope, soil test levels, and distance to water, possibly including management factors that the producer would be unlikely to modify, such as crop rotation or even application timing. The results of this preliminary assessment could be fairly simple, for example, dividing fields into two groups: those that are not likely to be good TABLE 14.1 Chicken–Egg Iterative Process for Determining Maximum Manure Application Rate Allowed by PI Iteration Rate Basis Planned Rate (Gal/Acre) PI Rating PI Interpretation 1 No manure applied 0 Low Use N-based management 2 Crop N need 3900 Very high No P applied 3 1-year crop P removal 700 Low Use N-based management 4 2-year crop P removal 1400 Low Use N-based management 5 3-year crop P removal 2100 Medium Use N-based management 6 4-year crop P removal 2800 High P limited to crop removal 7 5-year crop P removal 3500 Very high No P applied 8 4.5-year crop P removal 3200 Very high No P applied 9 4.25-year crop P removal 3000 Very high No P applied 10 4.1-year crop P removal 2900 High P limited to crop removal Notes: In this hypothetical scenario, rates have been rounded up to the nearest 100 gallons. Equilibrium is reached when the highest rate with a high rating is found (iteration 10). In practice, a planner would likely stop iterating when the highest rate with a whole number of years’ P removal is found (iteration 6, but 7 iterations would be required to determine this). © 2007 by Taylor & Francis Group, LLC Challenges to Using and Implementing Phosphorus Indices 339 candidates for nutrient applications in any scenario and those that are good can- didates, or could become good candidates with appropriate management or con- servation practices. The planner could then concentrate initially on the good candidates, turning to the poorer candidates only if they are needed to utilize manure. A complete risk assessment would still be done on any field that receives manure, unlike some prescreening procedures, which exempt certain fields from any further assessment. Another approach would be to leave the current risk assessment procedures unchanged but to program the PI software tool to iterate through various rates until it finds the highest rate that still presents an acceptable level of risk for a particular application method and timing scenario. In other words, the PI tool would automate the trial-and-error process that the planner currently has to perform manually. 14.2.6 THE BERMUDA TRIANGLE The previous section describes the circular dependency of planned manure appli- cations and PI interpretation. A third element, estimated soil loss, is often involved as well because planned manure applications can affect estimated soil loss, and estimated soil loss is an input for most PIs. For example, surface- applied solid manure can add a significant amount of residue to a field, generally lowering soil loss, whereas incorporating liquid manure can disturb a field’s existing plant residue, generally increasing soil loss. This means that for each change in planned manure application rate, the Revised Universal Soil Loss Equation version 2 software (RUSLE2, 2006) needs to be run again to determine an adjusted soil loss estimate, and the new soil loss estimate must be entered into the PI to calculate an adjusted PI value. This revised PI value is then used to evaluate whether the new application rate is acceptable. If the rate is not acceptable, this three-step process — rate determination, soil loss estimation, PI calculation, hence the term Bermuda Triangle — needs to be repeated until an acceptable rate is discovered. In practice, some planners may not account for the impacts of manure applica- tions in RUSLE2, and fewer still likely determine the impacts of different manure application rates on estimated RUSLE2 soil loss. Should all changes to planned manure applications be reflected in RUSLE2? If changes to the planned crop rotation and yield goals must be reflected in RUSLE2, then the answer to this question is probably yes. Unfortunately, accounting for planned manure applications in RUSLE2 can be tricky. Though some RUSLE2 Crop Management Zone (CMZ) files include crop- management scenarios that account for typical manure applications for common crop rotations, these management scenarios may not match the field’s planned crop rotation or may differ in other assumptions about application rate, timing, and associated tillage operations. In these cases, the planner must create a custom crop- management scenario and manually enter all planned manure applications and asso- ciated tillage operations during the rotation, as well as manually calculate the amount © 2007 by Taylor & Francis Group, LLC 340 Modeling Phosphorus in the Environment of residue added to the field by each application based on the manure’s dry matter concentration. To manually solve the Bermuda Triangle, planners currently must use three separate software tools. This is a time-consuming, repetitive process. The only way to speed up the rate calculations is to dynamically link all three software tools to automate this iterative process in a manner similar to solving the chicken–egg scenario. 14.2.7 T EMPORAL D ISCONTINUITIES Guidance from the assessment procedure’s authors is usually helpful in determining the PI’s temporal scope. Some PIs are designed to assess fields over the entire rotation or planning period, whereas other PIs assess each crop year separately and may or may not combine these results into a summary interpretation. Once a decision has been made to calculate the assessment on an annual or rotational basis, related issues must then be addressed. For example, most risk assessment procedures utilize esti- mated soil loss by water, which historically has been calculated as a long-term annualized average for the entire rotation. However, if the risk assessment is deter- mined on an annual basis, soil loss also should be determined for each cropping year in the rotation because soil loss estimates can differ considerably from year to year as a field’s crop, tillage, and planned manure applications change. As a result, using a rotational average soil loss may overestimate risk in some years and under- estimate risk in other years. Using rotational average soil loss estimates in the PI also makes the process of determining appropriate manure application rates nearly impossible because the impact of a current planned manure application can change the PI result for a previous application. For example, if liquid manure is applied to a corn silage field in the first year of the plan, it will have some impact on rotational average soil erosion. If during the second year of the plan, solid manure is applied to this same field, soil erosion may decrease dramatically for that year and may lower the rota- tional average soil loss. This change in rotational average soil loss will actually change the PI value for the previous year’s application. Though a previous year’s manure application certainly may impact future applications, applications planned for future years should not impact the previous year’s planned application. The circular interaction cannot be solved with software. Any PI that uses the rotational average soil loss has this inherent design flaw. The solution to this problem is for PIs to use annual soil loss estimates for each crop year in the plan. However, per current PI guidelines, MMP’s PIs use the rotational average soil loss with annual assessments in most states. States that use a rotational risk assessment procedure, or a matrix-based PI that has no inherent temporal context, also face the issue of data that cannot be averaged. For example, many assessment procedures use information about the timing and method of nutrient applications, but these data cannot be averaged. If manure is applied differently to a field throughout the rotation — or even for multiple appli- cations within a given year — one time and method must be selected for use in the © 2007 by Taylor & Francis Group, LLC Challenges to Using and Implementing Phosphorus Indices 341 assessment. In general, if not specified by the assessment procedure, MMP’s PIs use the time and method that present the greatest risk. In most cases, this approach unfairly penalizes the producer in the overall PI assessment for a field. Second- generation PIs should use an annual PI assessment for each crop year and then, if appropriate, should generate a summary report for each field. 14.3 CHALLENGES COMMONLY ENCOUNTERED BY FIRST-GENERATION PI USERS 14.3.1 OVERVIEW Because the purpose, data requirements and interpretation of PIs vary widely across states, planners must have a solid understanding of these and other issues to properly use PIs in the plans they develop. Normally this requires instruction of some kind, either as training specific to the PI or as part of a larger nutrient management planning course. However, based on our experience, many planners, especially those working in multiple states, have received little or no in-depth training on PIs and have acquired their knowledge about various PIs from slide shows, sample nutrient management plans, extension publications, and USDA- NRCS Nutrient Management 590 standards (NRCS, 2006). Some states have developed nutrient management planning Web sites to provide required data and helpful reference materials at a single location. Even with PI software that auto- mates much of the assessment procedure, planners often struggle with operation- specific issues frequently encountered in the real world but that are not generally covered in training courses or reference materials. This section discusses a few of these common challenges. 14.3.2 S OME I NPUT D ATA M AY N OT B E K NOWN DURING P LANNING Some PIs depend on knowledge of soil and field conditions such as residue cover, hydrologic condition, soil condition, and field condition (e.g., whether the soil is frozen) in calculating runoff and other factors, even though these inputs will not be known when the NMP is created. With these inputs, MMP’s PI tools make an assumption based on crop rotation or application timing. For example, with field condition, a PI tool for a state in the north-central U.S. might assume that the soil is likely to be frozen during the winter months of December through February and not frozen during other months of the year. Even though in any given year there may be periods during the winter when the soil is not frozen, and there is always the possibility that the soil could be frozen outside of the winter months, from a planning perspective this assumption is simply indicating that it is risky to count on fields being available (unfrozen) during those months. This is consistent with the idea that multiyear NMPs are designed to demonstrate that the producer can manage the operation’s manure properly in a typical year. © 2007 by Taylor & Francis Group, LLC 342 Modeling Phosphorus in the Environment 14.3.3 WHAT IF A FIELD IS NOT UNIFORMLY MANURED? Many risk assessment procedures ask for the rate, method, and timing of P appli- cations. Though at first glance this may appear to be an easy question to answer, determining this information can be difficult in a number of situations. For example, most states have regulatory manure application setback areas such as streams, wells, sinkholes, roads, and property boundaries. In general, manure cannot be applied here. If the affected area is small, it may be possible to disregard this area in the field’s assessment. However, if the nonmanured area is large enough that the producer will likely apply commercial fertilizer to it, the result is a field that may have significant differences between its manured and nonmanured parts in the rate, method, and timing of P applications. A good rule of thumb is to subdivide these kinds of fields and then do an independent risk assessment on each subfield. Large fields also are sometimes not completely manured, usually because the producer does not have enough manure to cover the entire field. Ideally, these fields should also be subdivided so that each subfield can be uniformly manured from the same manure source, with the same equipment, and during the same time of year. If fields are not subdivided, MMP’s PI tools calculate a per-acre weighted average rate, even though there may be significant rate differences across the field. The PI assessment results can be misleading in these cases. 14.3.4 G AMING THE S YSTEM Gaming the system is the term we use to describe the process of determining manure application strategies that may be used by some experienced planners once they fully understand the design flaws inherent in the PI with which they are working. The circular chicken–egg problem discussed previously arises when the P application rate is a factor in determining the PI value, whereas the PI value in turn is used to limit the application rate. When RUSLE2 is included in the PI, the issue becomes even more complicated (i.e., the Bermuda Triangle). To further compound the P rate deter- mination dilemma, PIs often lack scaling in PI subcategories or in the final PI inter- pretation. Matrix-based first-generation PIs have most of these inherent design flaws. These PI design flaws also have another side effect. With P-based management, the maximum rate will usually put the field off limits for further manure applications until the P applied has been removed from the field as harvested crop material. In many cases, this will take several harvests. Reducing the rate to where the PI result allows N-based management may permit annual applications at a rate that in many cases is only slightly less than the multiyear P-based maximum rate. Although allowed by the PI, this can result in a rapid build-up of soil P, which may mean that fields managed in this way will abruptly become unavailable following the next round of soil testing if the state has a soil test P cutoff level above which no further P can be applied. Whether intentional or not, this application strategy could be problematic for the producer and surely is not what the designers of the PI intended. Table 14.2 illustrates this problem. © 2007 by Taylor & Francis Group, LLC [...]... implementing (programming) PIs One approach would be to implement the PI as part of the larger nutrient management planning software, in our case MMP The chief disadvantage to making the PI tool a built -in part of the planning software is that even minor changes or corrections to the PI procedure require a revision of the planning software Another disadvantage is that the source code for the PI tool... simplify the problem of using RUSLE2 efficiently and correctly, but it does eliminate the manual entry of these values into MMP and means that the soil loss estimates can be stored in the MMP plan file with the other data required to calculate the PI 14. 4.2.3 Errors or Gaps in Soils Data In addition to field and soil loss data, most PIs also are driven by soils data, specifically the underlying properties of the. .. with the PI because they cannot obtain help elsewhere, because the PI tool is the context where their questions arose or simply because they do not make a distinction between the PI and the PI tool This puts the PI tool developers in the awkward position of being considered experts about the PI As with many software support issues, there is no easy solution to this problem Maintaining a piece of software... debug, document, and maintain once a certain level of complexity is reached Spreadsheets date to the very first personal computers but now represent an approach that is out of step with modern software development best practices © 2007 by Taylor & Francis Group, LLC 344 Modeling Phosphorus in the Environment Linking the spreadsheet to other software also is unlikely, since getting data into or out of a spreadsheet... also has some of the same data linkage and duplication issues as the second approach Each state PI, too, would require its own link with the planning software, which could involve just as much programming effort as implementing the risk assessment procedure itself With a PI spreadsheet, this kind of link tends to be fragile since the planning software needs to write to specific cells in the spreadsheet... LLC 346 Modeling Phosphorus in the Environment 14. 4.2.2 Supplying Soil Loss Estimates RUSLE2 is the software used to estimate soil loss by water for official USDA-NRCS purposes RUSLE2 is a complex, stand-alone program with its own user interface and data storage RUSLE2 brings additional capabilities to soil loss estimation over its table-driven predecessor, RUSLE, although at the expense of increased... removal) Notes: 2900 gal/acre is the maximum rate determined in Table 14. 1, which puts the field off limits to further application for four years 2100 gal/acre is the highest rate from Table 14. 1 that still permits N-based management (annual applications) 14. 4 CHALLENGES AND OPPORTUNITIES FOR IMPLEMENTING PIs IN THE FUTURE 14. 4.1 POTENTIAL IMPLEMENTATION APPROACHES In developing MMP, we have identified several... slope length, which is the distance from the overland flow’s point of origin to where the slope decreases enough that soil deposition begins Slope length is also an input to RUSLE2 Though determining slope length in the field is the preferred method, there are situations where having a rough estimate based on soil type is adequate for RUSLE2 NASIS would be the natural source for these slope length estimates... short-term solution necessitated by the need to produce something that increases planner productivity compared to using a spreadsheet-based implementation Because of MMP’s dependency on both RUSLE2 and PIs in determining and evaluating manure application rates, in the longer term both RUSLE2 and PIs need to be integrated more closely with MMP, although stopping short of becoming part of MMP To further... Phosphorus in the Environment of P loss from crop fields, which may differ in both obvious and subtle ways from other states, the high-level structure of all PI tools is similar, differing primarily in the low-level implementation details 14. 5 CONCLUSIONS PIs present a variety of challenges not only to the planners who use them but also to the programmers who have taken on the job of implementing them as part . LLC 336 Modeling Phosphorus in the Environment the prescreening procedure allows the planner to skip the full PI assessment on certain fields, they may be setting up the producer for a shock the next. LLC 334 Modeling Phosphorus in the Environment 14. 3.3 What If a Field Is Not Uniformly Manured? 342 14. 3.4 Gaming the System 342 14. 4 Challenges and Opportunities for Implementing PIs in the Future. Taylor & Francis Group, LLC 344 Modeling Phosphorus in the Environment Linking the spreadsheet to other software also is unlikely, since getting data into or out of a spreadsheet programmatically