ben chaffin chaffin farms ithaca, michigan · 2020-01-06 · resents any region, typically composed...

Ben ChaffinChaffin FarmsIthaca, Michigan

Crops• Sugar beets

• Corn

• Corn silage

- Soybeans

• Edible beans

- Blacks

- Navy

• Potatoes

- ground rented out

• Hay

• Peas

• Wheat

• Rye

• Organic Crops

- Peas

- String beans

- Corn

- Squash

Soil TestingFrequency• 3 Years manure

- Michigan regulation

• 4 Years no manure

- Industry standard

• Grid samples

- 10 acre grids $4.50 / acre

- 2.5 acre grids $8.50 / acre

Commercial Nutrient Management

Nutrient focus• Nitrogen

• Phosphorous

• Potassium

• Lime

• Micro nutrients

Variable rate applications• Changing amount applied while spreading a field based on

- Soil tests

- Yield goals

- Crop needs

Fertilizer Spreader Variable rate spreading Fall 2010 Spreader costs $110K 3 years old, new $225KGPS technology $15K

Animal Nutrients

• Manure management

- All nutrients mixed together

- Cost to haul

• Manures used

- Dairy 3,000 acres

* 3-5 miles or less transportation negotiated

* We incorporate same day applied

- Turkey & Chicken 1,500 acres

* 100 miles $50/ton delivered spread

- Swine 50 acres

* 5-10 miles all hauling costs

• Limited amount of manure

Irrigating ManureIrrigating ManureN 1.1 lbs / 1000 galP .9 lbs / 1000 galK 1.4 lbs / 1000 galN,P&K very lowIrrigated 2.4M gal in 2010

Manure lagoon

Pump to irrigation system

Fixed investment to irrigate 35 acres $70K

Commercial Phosphorous• Dry

- MAP 10-52-0 $0.52/lbs phos.

- DAP 18-46-0

* Dry mixes cheaper per lbs phosphorous

• Liquid

- 10-34-0 $0.64/lbs phos.

- 8-25-3

* More money per lbs phos phorous

Decision Points• Cost benefit

• Return on investment

- 10% on new products example fungicide on corn

• Time / effort

- Split applications verse 1 application

• Operational fit

• Risk management

Planting Corn Spring 2010 Seed and fertilizer applied with variable rate technology Rates based on yield goals for each segment of the field

Corn Harvest 2010 Combine mapping yields for future use

Ever Had One of These Days?Sugar Beet Harvest Fall 2010

GLOBAL PHOSPHORUS SCARCITY:CHALLENGES & OPPORTUNITIES FOR FOOD SECURITY

Dr Dana Cordell

Sustainable Phosphorus Summit, Tempe Arizona3rd February, 2011

THINK.CHANGE.DO

INSTITUTE FOR SUSTAINABLE FUTURES

• Joint initiative co-founded in 2008 (Linköping University & University of Technology, Sydney)

• Today -5 research organisations across Australia, Europe and North America

• Aim:

- to facilitate quality interdisciplinary research on global phosphorus security for future food production.

- networking, dialogue and awareness raising among policy makers, industry, scientists and the community on the implications of global phosphorus scarcity and possible solutions.http://phosphorusfutures.net/

Dependence On Phosphate Rock

Global Phosphorus Research Init iative

Phosphate rock commodity price

Background: The Current Situation2008price spike: US$50/tonne to US$430/tonne

Food riotsOil prices soarFertilizer (N, P, K) prices soarsFood prices soarFertilizer riots

• Vigorous debate today –will we run out of phosphorus? Peak phosphorus?

• 30 yrs –300 years

• IFDC report:

- 60 billion tonnes of phosphate rock (USGS 16 billion)

- No peak phosphorus 25 years, or this century

- 300-400 years left, at current production rates

- GPRI: Figures are unreliable and do not change underlying problems, nor the threat of peak P this century

Scarcity: More Than Just PhysicalPhysical Scarcity: Peak Phosphorus• Like oil, phosphate rock will eventually reach a production peak due to energy and economic constraints -estimated peak P by 2035

• No alternative sources of P on market today could replace demand for P rock: significant institutional and physical infrastructure will be required

• Timing of peak uncertain, but widely recognised:

tonnes ‘in the ground ’is not the same as tonnes ‘on the field’

accessible to farmers

Cordell & White, 2011

- qualityis declining

- (less P2O5, more impurities)

- access is more difficult

- energy increasing

- costsincreasing

- wastes increasing

- (e.g. phosphogypsum)

Peak phosphous curve

Managerial Scarcity: Inefficient Phosphorus Use In The Global Food System

Cordell et al, 2009

Cordell et al, 2009

Institutional Scarcity: Whose Responsibility?• Scarcity resulting from a lack of appropriate and effective institutional structures to ensure P supply will meet long-term demand.

- eg. there are currently no explicit international or national policies, regimes, guidelines or organisations responsible for ensuring long- term availability and accessibility of phosphorus for food production

• Market system governing by default –alone not sufficient to ensure equi table, timely, sustainable

• Whose responsibility is long-term phosphorus security? Governance of phosphorus is fragmented between many different sectors

Geopolitical Scarcity: Remaining ReservesAll farmers need phosphorus, yet just 5 countries control around 85%of the worlds remaining phosphate rock reserves

World phospate rock reserves by countryData: Jasinski, S (2010) Phospate Rock, Mineral commodity Summaries, US Geological Survey

Economic Scarcity: Lack Of Access To Phosphorus• Farmers need both short-and long-term access to fertilizers

• Lack of access to phosphorus fertilizers-eg. lack of farmer purchasing power, access to credit

• Phosphorus inequity: African continent

- largest high quality phosphate rock

- Low soil fertility

- Poorest farmers

- lowest P fertilizer application rates

- High food insecurity

- significant ‘silent’ demand from farmers with low purchasing powerin sub-Saharan Africa

Challenges: Achieving Phosphorus Security• Integrated approach is required: there is no single solution to meeting future phosphorus demand

• Multi-scale response: strategies need to respond to global issues but designed to be context specific

• Beyond the market focus

• Beyond ‘the field’ focus (eg. more than ag efficiency)

• Beyond eutrophication to scarcity

• current institutional fragmentation –lack of clear roles and responsibilities

• Data scarcity: lack of data, lack of transparency

• Research & policy gap: What are the most cost-effective, energy efficient, equitable, environmentally compatible means of using and reusing phosphorus in a given food production & consumption?

Opportunities: Achieving Phosphorus Security• New sustainable technologies and practices for efficient phos-phorus use and recovery

• New synergies between sanitation provision, food security, environmental protection, energy generation & livelihood security

• New partnerships between fertilizer sector, wastewater, urban planning, scientists, etc

• Evolution of the industry from product (fertilizer commodity) to service (soil fertility, food security)

• New actors and policies for ensuring short-and long-term phos-phorus security for crop production

For more information visit www.phosphousfutures.net or www.isf.uts.edu.au or email [email protected]

Hard Landing vs Soft Landing• If we don’t change current phosphorus use trajectory, we are heading for a hard landing of increasing energy, costs and waste, volatile prices, geopolitical tensions, reduced farmer accessto fertilizers and reduced crop yields and food insecurity.

• Softlanding:

- Phosphorus security ensures all farmers have short-and long-term access to sufficient phosphorus to grow enough crops to feed to world, while minimising adverse environmental and social impacts (Cordell 2010)

Framing the Problem: The P Cycle

Notes: An illustration of the P cycle that attempts to render the relative sizes of the dierent terrestrial pools (the marine and lithosphere pools are not drawn to the same scale). The data comes from several global balances, including Smil (2000); Liu et al. (2008); Cordell et al. (2009); Compton et al. (2000). Many of these numbers are back of the envelope estimates. We see that soils repre-sent potentially the largest store. If we naively divide this store by the annual P uptake of agricultural crops, we obtain a store lifespan of 1000 years. But this is a misleading calculation for at least 3 reasons. See next...

Issue 1: Soil P dynamics• I Plant available P (Pa) is only a small fraction of total P (PT )

• I The soil P reservoir is very dynamic: every reaction is reversible (although it may be very slow)

• I The behavior of P is sensitive to soil properties

Notes: Typical diagram conceptualizing P cycling in soils. Routine measures of soil Pa extract the soluble P, the labile P as well as some of the organic P

pool. The rest can be considered more or less “stable”. The extent and rate of each of the depicted transfers will depend on many soil properties. For a long time, it was assumed that soluble inorganic P quickly undergoes irreversible reactions with a number of soil minerals to form stable compounds that are use-less for plant growth. This view has been revised and we now know that most if not all reactions are reversible. Hence, all P compounds can eventually re-enter the Pa pool. At any one time, the equilibrium K = Pa=PT will be dominated by the reaction coecient of the least stable species in the stable pool. If these are very stable, the equilibrium will be low (low P availability).

The soil as an active reservoir of Phosphorus

Framing the problem

The P cycle

The soil as an active reservoir of PhosphorusModeling and implications for management

Marion Dumas, February 20, 2011


Framing the problem

Issue 1: Soil P dynamics� Plant available P (Pa) is only a small fraction of total P (PT )� The soil P reservoir is very dynamic: every reaction is

reversible (although it may be very slow)� The behavior of P is sensitive to soil properties

Issue 1: Implications• Very contrasted results when suppressing mineral P inputs: several decades without response in Sweden (Otabbong et al., 1997), Germany (Gransee and Merbach, 2000), New Zealand (Condron and Goh, 1989)

• Rapid yield collapse in many tropical soils. Bekunda et al. (1997) - experiment in the Sudanian zone of West Africa

Notes: The implications of the soil P dynamics above can be seen in long-term experiments (LTEs). Several LTEs show that yields can be maintained for several decades in the absence of P fertilizer inputs in mid-latitutes/northern soils that are not thoroughly weathered and have been heavily fertilized in the past. In contrast, LTEs in the tropics often show quasi-immediate decline in yields in the absence of P fertilizer inputs (sometimes even if PT is quite high). These dierences are not only due to absence in PT but also to dierences in the bioavailability of P.

Issue 2: Regional Imbalances

Notes: The second reason why the naive calculation of the soil P store’s lifes-pan is misleading is that there are major regional imbalances, some of which are highlighted in this graph (in kgP/ha). Hence, applying a uniform uptake rate to a uniform pool is wrong.


Framing the problem

Issue 1: Implications

Very contrasted results when

suppressing mineral P inputs:

� several decades without

response in Sweden (Otabbong

et al., 1997), Germany

(Gransee and Merbach, 2000),

New Zealand (Condron and

Goh, 1989)

� Rapid yield collapse in many

tropical soils.

Bekunda et al. (1997) - experiment

in the Sudanian zone of West Africa


Framing the problem

Issue 2: Regional Imbalances

12.07.09Sustainable Development Seminar

+ 27

- 7

+ 58

- 4.7

kgP/ha/yrmaps from Ramankutty et al. 2008

Issue 2: Poorly measured reservesThe pool is poorly quantied:• China: PT pool known thanks to Chinese Soil Database (Fig. 1)

• US: continental scale geochemical survey underway

• World: ISRIC World Soil Database contains at most a few hundred measures.

Figure: Spatial distribution of total soil phosphorus density in China (ppm) from 2400 soil proles (Zhang et al., 2005). Total PT pool: 3.5 Gt P.

Notes: The third reason is that the estimate of 40-50 Gt P in the 50 top cm of arable soils is a almost a guess: we do not know what the size of this pool is at the present time. The only precise quantication I am aware of was done for the soils of China (the Chinese soil database is the only one I know of that holds simultaneous measures of Pa and PT ). We see from this calculation that the global estimate may be too high. Because of the three issues above, we need a model to get a better sense of the impact of P flows on agricultural productivity (see next slide).

Notes: Phosphorus cycling through the human ecosystem: This graph rep-resents any region, typically composed of grassland and cropland. Food pro-duction consists of crops, conned livestock fed by fodder and grazing animals fed by grass. � signies the total yield of crops, animals etc. and x stand for the dierent fluxes (e.g. xhw for Human waste) in or out of the pool of . . Ps is the pool of stable P forms, Pa is the pool of bioavailable P forms (e.g. P Olsen or P Bray), ks is the observable rate coecient of the transfer from Pa to Ps while ka is the rate coecient of the opposite transfer.


Framing the problem

Issue 2: Poorly measured PT reserves

The PT pool is poorlyquantified:

� China: PT poolknown thanks toChinese SoilDatabase (Fig. 1)

� US: continental scalegeochemical surveyunderway

� World: ISRIC WorldSoil Databasecontains at most afew hundredmeasures.

Figure: Spatial distribution of total soilphosphorus density in China (ppm) from2400 soil profiles (Zhang et al., 2005).Total PT pool: 3.5 Gt P.

PTPT

Xhw

(recycling)

Human waste Agricultural residues

Livestock manure

y lYield from confined

livestock

Ps

Pa

PT

ks

ka

Cropland topsoil

Ps

Pa

PT

ka

ks

Grassland topsoil

Xhw

(recycling)

Xre

(recycling)

Xyg

(yield)

y T

y c

y g

y fXyf

(yield)

Xer

(erosion)

Xma

(recycling)

Xyc

(yield)

y ga

Xer

(erosion)

Fodder yield

Crop yield

Grass yieldYield from grazing

animals

Inflow/outflow of P from/to soil

Output

Relation

Import/Exports

Boundaries of analyzed region

waste

waste waste

P ores

Xf

(fertilization)

Xf

(fertilization)

PT

Model 1/3

Notes: The dynamics in the previous gure can be expressed quite simply by the following decomposition: dy/dt is the change in annual yields over time, which is equal to the change in yields with respect to a change in Pa ( dy/dPa , also called the yield response) times the change in Pa with respect to a change in (fracdPadPT ) the result of soil P dynamics described above) times the change in over time due to our management of P influxes and outfluxes. From a modeling point of view, the challenge is the middle term, usually mod-eled on small scales by very detailed crop-soil models, but hard to model on large spatial scales.

Yield Response Curve

Notes: The yield response curve is usually quite easy to model, using data from well-monitored plots and tting a function with a plateau to it. ymax is the potential yield in the region of interest once P is no longer a limiting factor. It is consid-ered to be a random variable with distribution f (ymax) (to take into account spatial and temporal heterogeneity of this variable).

Human Managed Mass Balance

Notes: The last term d /dt is the sum of influxes (inputs from recycling and/or mineral fertilizers) and outfluxes (P in harvest and in eroded soil). Erosion and inputs can be measured or can be assumed in the context of scenario analysis. The outflux of P in the harvest is proportional to the harvest obtained from the yield response function.


Model

Model 1/3


Model

Yield Response Curve

0 2 4 6 8 10

01

23

45

67

P available, ppm

yiel

d to

n/ha

f (y) = f (ymax)(1 − aeb×Pa)


Model

Human managed mass balance

dPT

dt= Inputs

− P in harvest

− P in eroded soil

= I (t) − yp(t) − E (t) (1)

PTPT

PT

The Bioavailability Curves 1/3 CS: Calcareous Soils SWS: Slightly Weathered Soils HWS: Highly Weathered Soils

Notes: Times series in over 20 LTEs were reviewed + evidence on the reactions undergone by dierent forms of P in the corresponding soils. I hypothesizedthat there is a non-linear relationship between Pa and and that it should differ systematically across broad categories of soils. In calcareous soils: weakadsorption of P when is low, then the Pa pool increases, until precipitation reactions kick in (early plateau). In highly weathered soils adsorption reactions predominate, with stronger bonds being formed at the lowest P contents, and these bonds gradually become weaker as the pool builds up (thus the slopebetween Pa and becomes steeper). Slightly weathered soils should lie somewhere in between. These relationships are not expected to hold exactly: we expect we can nd a classication of soils for which there exists a well-dened non-linear function f (Pa|PT ) describing Ps behavior. This relationship is only expected to hold on average, thus we formulate it as a conditional average.

The Bioavailability Curves 2/3

Notes: First data set I could nd: uncultivated soils from many locations (N=185) from Sharpley et al. (1987). We can see that the data points from the three classes of soils are potentially drawing the hypoth-esized pattern.

Notes: Time series from LTEs are overlayed on the Sharpley et al. (1987) data (these include no-P experiments where decreases over time, as well as fertilization experiment where increases over time). This gives some support for the hypothesized relationship.


Model

The bioavailability curves 2/3


Model

0 500 1000 1500 20000

5010

015

0Pt

Pa

(Res

inP

, ppm

)

Calcareous soils and some long-term-experimentsUncultivated CS soils, Sharpley & Cole 1987

LTEsWinchmore, Condron & Goh,2000Jindiress, Ryan et al.2008Zhejian province, Zhang et al., 2006

PT

PT

PT


Model


0 500 1000 1500 2000

050

100

150

200

Hypothesized bioavailability curves

PT (ppm)

Pa

(ppm

)

CS

SWS

HWS

E (Pa|PT ) = g(PT ) = h(1+exp(−r(PT−M)))1/ν

CS: Calcareous SoilsSWS: SlightlyWeathered SoilsHWS: HighlyWeathered Soils

PT PTPT

The Bioavailability Curves 3/3

Notes: The mathematical formulation of the joint probability distribution between Pa and . Both variables are assumed to be lognormally distributed and the parameters of the conditional average Pa | will depend on soil type.

Model 2/3

PTPT


Model

0 500 1000 1500 2000

050

100

150

Pt

Pa

(ppm

)Highly weathered soils and some long-term-experiments

Uncultivated HWS soils, Sharpley & Cole 1987LTEs

Siniloan, Dobermann et al., 2002Matalom, Dobermann et al., 2002Yurimaguas Peru, Beck and Sanchez, 1996


Model

0 500 1000 1500 2000

020

4060

8010

0

Replenishment curve for slightly weathered soils

Total P

Ava

ilabl

e P

Data set of uncultivated soilsSwiss experimental stationsBenchmark european soils

Richards' growth curve


Model


0 500 1000 1500 2000

020

4060

8010

0

Replenishment curve for slightly weathered soils

Total P

Ava

ilabl

e P

Data set of uncultivated soilsSwiss experimental stationsBenchmark european soils

Richards' growth curve

f (PT ) =1

PTσT

√2π

exp(−(log(PT ) − µT )2

2σT) (2)

f (Pa|PT ) =1

Paσa

√2π

exp(−(log(Pa) − µa)2

2σa) (3)

where µa = log(g(PT )) = h − 1

ν(1 + e−r(PT−M)) (4)The soil as an active reservoir of Phosphorus

Model

Model 2/3

f (PtT ) = f (Pt−1

T +1

ρD(−y t−1

p − E t−1 + I t−1) (5)

f (Pta) =

∫f (Pt

a |PtT )f (Pt

T )dPtT (6)

f (y t) =

∫f (ymax)(1 − a exp(b × Pt

a)dPta (7)

Notes: The dynamic model including the feedback from outflow of P in theharvest. The mass balance updates the distribution f ( ), the bioavailability function allows to deduce the distribution f (Pa) and this allows to estimate the distribution of yields.

Model 3/3

Notes: The dynamic probabilistic model is perhaps better understood in this graphical form. All variables are expressed probabilistically because of the heterogeneity and uncertainty associated with them. In particular, the flows of P in crop residues, manure and human waste must also be linked to the amount of P present in the harvests of crop (due to mass balance).

• As a toy model to answer stylized questions illuminating sustainability of P cycle

• As information rich simulation of the P cycle in particular regions

Given a region’s initial endowment of , what would be the decline of a represen-tative crop in absence of mineral P fertilizer?

Notes: This simple large-scale model could shed light on how dependent dier-ent regions are on inputs of P. Here we see time series for two dierent scenarios in the three classes of soils, using the hypothesized relationships and assuming no P fertilizer inputs. The black lines represent the average and the grey lines represent the condence intervals. We see that yields are not very sensitive to declines in due to the harvests, because this is in part buered by the Pa pool and the fact that at high , P is not limiting.

0 50 100 150

050

010

0015

0020

00

Pt i

n pp

m

0 50 100 150

050

010

0015

0020

00

Pt i

n pp

m

0 50 100 150

050

100

150

200

Pa

in p

pm

0 50 100 150

050

100

150

200

Pa

in p

pm

0 50 100 150

01

23

45

yiel

ds in

ton/

ha

0 50 100 150

01

23

45

yiel

ds in

ton/

ha

Time Time

High Initial Total soil PConventional tilling

Low Initial Total soil PNo-till

mean HWSmean CSmean SWSCI HWSCI CSCI SWS

Parameters of theavailability functionas in Fig 2Yield response curveparameters are: a=0.98, b=0.22

from barley yield data

Given a

region’s

initial

endowment

of PT , what

would be the

decline of a

representa-

tive crop in

absence of

mineral P

fertilizer?


Model

Model 3/3

PT

PT

PT

PT

How much mineral P is necessary to bring the soils of a region to a point where replacement of P taken up by harvest by means of recycling is suffcient?

Notes: Looking at the joint distribution Pa; allows us to estimate the proportion of soils that are decient in P. Deciency is dened in terms of a critical value ;crit under which Pa becomes limiting. ;crit varies from soil to soil. We can estimate how much P would have to be added to the soil to achieve > ;crit. In black is the joint distribution at t=0 and in grey at t=150 (years). In the second scenario, there is acute P deciency.

How much mineral P is necessary to bring the soils of a region to a point where replacement of P taken up by harvest by means of recycling is suffcient ?

PT

PT PT

PT

PT

0 1000 2000 3000 4000 5000

010

020

030

040

050

0

HWS t=0: 22% area deficient in P

t=150: 50% area deficient in P

0 1000 2000 3000 4000 5000

010

020

030

0

Pa in

ppm

CS t=0: 0% area deficient in P


0 1000 2000 3000 4000 5000

020

040

060

0 SWS t=0: 0.2% area deficient in P


Pt in ppm

Initial ConcentrationFinal Concentration

Threshold for PtThreshold for Pa

Scenario 1: High initial P and high erosion

Parameters of theavailability functionas in Fig 2Yield response curveparameters are: a=0.98, b=0.22from barley yield data

How much

mineral P is

necessary to

bring the

soils of a

region to a

point where

replacement

of P taken up

by harvest by

means of

recycling is

sufficient ?

0 500 1000 1500 2000

050

100

150

200

HWS t=0: 93% area deficient in P


0 500 1000 1500 2000

050

010

0015

00

Pa in

ppm

CS t=0: 0.09% area deficient in P


0 500 1000 1500 2000

020

060

010

00

SWS t=0: 24% area deficient in P


Pt in ppm

Initial ConcentrationFinal Concentration

Threshold for PtThreshold for Pa

Scenario 2: Low initial P and low erosion

Parameters of theavailability functionas in Fig 2Yield response curveparameters are: a=0.98, b=0.22from barley yield data

How much

mineral P is

necessary to

bring the

soils of a

region to a

point where

replacement

of P taken up

by harvest by

means of

recycling is

sufficient ?

Case Study: Canton Fribourg 1/2

Notes: This model could potentially be used for more localized and detailed case studies. Here is an example using data on soil P content, erosion and yields from Canton Fribourg.

Case Study: Canton Fribourg 2/2

Tentative Conclusions• Initial conditions are very important: key role of soils’ mineral capital

• P-enriched regions may be able to maintain stable yields even in the event of shortage: adaptation time

• P-enriched regions could maintain high productivity by closing the loop

• P-poor regions cannot rely on closing the loop to maintain high yields

Outlook• Indicates gaps in our knowledge of the P cycle:

- The size of the PT stock

- The link between PT and bioavailable P

• Could assess sensitivity and productivity potential of dierent regions

• Especially when combined with distribution of other key factors of production

• Highlights the role of soils as P capacitors:

- Assistance in the design of new stocks of P for the future?


Applications

Case study: Canton Fribourg 1/2

0 20 40 60 80 100

0.00

0.04

0.08

Evolution of Available P, ppm

Den

sity

yr 1

yr 100

0 500 1000 1500 2000 2500

0.00

000.

0015

Evolution of Total P, ppm

Den

sity

yr 1

yr 100

Figure: Simulation in simplest scenario: no recycling, just crop uptake


Applications

Case study: Canton Fribourg 2/2

0 20 40 60 80 100

0.0

0.4

0.8

Years

Inde

x of

Rel

ativ

e yi

eld

0 20 40 60 80 100

010

2030

40

Years

Ava

ilabl

e P

, ppm

Figure: Large soil stocks: limited sensibility.

Tentative Criteria to Evaluate Sustainability of the Exit-phase of Scenarios• Security: Ensure large enough extent of soils in the world have PT > Pcrit /T to feed world population

• Precaution: Ensure enough ores remain to counterbalance unavoidable dissipation of soil P through low level erosion and losses in transformation processes.

• Freedom: Ensure enough ores remain at any point in time to allow enrichment of soils in any region where PT < Pcrit /T whenever population desires to be agriculturally productive.

SourcesSmil, V. (2000). Phosphorus in the environment: Natural flows and human interferences. Annual Review of the Energy and the Environment, 25:53-88.

Liu, Y., Villalba, G., Ayres, R., and Schroder, H. (2008). Global phosphorus flows and environmental impacts from a consumption perspective. Industrial Ecology, 12(2):229-247.

Cordell, D., Drangert, J., and White, S. (2009). The story of phosphorus: Global food security and food for thought. Global Environmental Change, In press.

Compton, J., Mallinson, D., Glenn, C., Filippelli, G., Foellmi, K., Shields, G., a and Zanin, Y. (2000). Variations in the global phosphorus cycle.

Zhang, C., Tian, H., Liu, J., Wang, S., Liu, M., Pan, S., and Shi, X. (2005). Pools and distributions of soil phosphorus in China. Global Biogeochemical Cycles, 19(GB1020, doi:10.1029/2004GB002296).

Sharpley, A., H., T., and Cole, C. (1987). Soil phosphorus forms extracted by soil tests as a function of pedogenesis. Soil Sci. Soc. Am. J., Vol. 15.

Otabbong, E., Persson, J., Iakimenko, O., and Sadovnikova, L. (1997). The Ultuna long-term soil organic matter experiment. Plant and Soil, 195:17{23.

Bekunda, M., Bationo, A., and Ssali, H. (1997). Soil fertility management in africa: A review of selected research trials. In Buresh, R., Sanchez, P., and Calhoun, F., editors, Replenishing Soil Fertility in Africa. Soil Science Society of America.

Gransee, A. and Merbach, W. (2000). Phosphorus dynamics in a long-term P fertilization trial on luvic phaeozem at Halle. J. Plant Nutri. Soil Sci., 163:353-357.

Condron, L. M. and Goh, K. (1989). Eects of long-term phosphatic fertilizer applications on amounts and forms of phosphorus in soils under irrigated pasture in new zealand. Journal of Soil Science, 40:383-395.

Sustainable Phosphorus in Agriculture, Soils and WatersPhil Haygarth and many others, Centre for Sustainable Water Management,Environment Centre, Lancaster University, United Kingdom

2. MOBILISATION describes the start of the journey from soil or source P, either as a solute (solubilised) or attached to colloids and particles (detached)

3. DELIVERY/TRANSPORT describes the complex journey the solutes, colloids or particles take after mobilisation to connect to the stream

1. SOURCES include fertilizer applications, defecation from grazing animals, spreading of manure on soils

Infiltration-excess flow

Saturation-excess flow

Sub-surface flow

4. IMPACT describes the connection with the biological impact of the diffuse substance in the receiving water

The phosphorus ‘transfer continuum’ – from land to water

(Haygarth et al., STOTEN, 344, 2005)

INPUTS

grazing16.5

excreta9.6

cut - silage16

slurry & FYM 32

SOIL

OUTPUTS

58 kg TP/ha

33 kg TP/ha

Haygarth et al (1998) SUM

P farm balances often in surplus

0

1

2

3

4

5

6

0 10 20 30 40 50 60 70Microbial P (mg kg-1 dry soil)

Wat

er e

xtra

ctab

le o

rgan

ic P

in

crea

se (m

g kg

-1 d

ry s

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Soil wetting and drying releases organic P to solution from biomass

China has now become the largest country in consuming and producing P fertilizer in the world.

Phosphorus and Sustainability in Agriculture, Soils and Waters• P is limited in supply yet an essential contributor to agriculture & food production –fertilizer and animal feeds

• P is generally inefficiently used in soils)

• P leaks from land to waterways

Phosphorus Imperatives: What We Must Do

What we must do• Bring it back from rivers and estuaries onto land

• Strategic use of fertilisers and manure

• Make better use of P in soils and crops

• Reduce leaks to water

How we should start this• Raise awareness

• Cross discipline effort

• Identify priorities -global and regional audits

twitter@ProfPHaygarth

Phosphorous Issues: Initial thoughts from

an Environmental EconomistCatherine L. Kling

Department of EconomicsCenter for Agricultural and Rural Development

Iowa State University

Sustainable Phosphorous Summit: February 3, 2011

Phosphorous Issues: Init ial Thoughts From an Environmental Economist

Catherine L. Kling, Department of Economics, Center for Agricultural and Rural Development, Iowa State University

My Research Interests: Phosphorous as an Externality

• Externality: unintended side effect of economic activity:

- generally not accounted for in a market

- Phosphorous runoff from agricultural cropping systems is an externality

• Value of lost ecosystem services from water quality degradation

• Policy design: conservation programs (farm bill, etc.) using watershed models integrated with economic decisions

Other economic concepts central to P sustain-ability• Optimal use of exhaustible and renewable resources

- When will markets appropriately allocate resources across time in this case?

- When is market intervention necessary for social welfare?

• Technology adoption and incentives

- Does market provide adequate incentives for recycling, development of substitutes, etc.

Example of Watershed Modeling and Policy Design:Least Cost Control of Agricultural Nutri-ent Contributions to the Gulf of Mexico Hypoxic ZoneSergey Rabotyagov, T. Campbell, M. Jha, H. Feng, P. Gassman, L. Kurkalova, S. Secchi, and C. Kling “Least Cost Control of Agricultural Nutrient Contributions to the Gulf of Mexico Hypoxic Zone,” Ecological Applications 20 (2010):1542-1555

Hypoxia=Dead Zone

• Oxygen-depleted hypoxic (dead) zones have increased exponentially since the 1960s

• Over 400 hypoxic areas worldwide, affected area of 245,000 km2 (Diaz and Rosenberg, 2008)

• Naturally occurring, but far larger due to anthropogenic sources

• Hypoxic zones result in stressed marine and estuarine systems, mass mortality and dramatic changes in the structure of marine communities (Diaz and Rosenberg, 1995).






Historic Size of Hypoxic Zone: 1985-2008






Gulf Hypoxia: Emission Sources• Causes: nutrients from Mississippi river, nitrates and phosphorous,

• Limiting nutrient may now be P (scientific debate continues)

• Major Contributors:

- UMRB (1+2) = 43%N, 41%P

- Ohio-Tennessee (6+7) = 41%N, 59%P

Local Water Quality

• Nutrients (esp. phosphorous) and sediment primary source

• Agriculture accounts for over 50% of impairments (EPA)

• Multiple conservation practices can ameliorate(Land retirement, conservation tillage, grassed waterways, contours, terraces)

Modeling of Gulf Hypoxia






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Watershed Schematic

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Consequences of seeking a 30% reduction in P and NO3• Conservation and Land use to achieve reduction

- N fertilizer reductions

- grassed waterways (extensive)

- terraces (combined with N fertilizer reductions)

- additional (substantial) land retirement

• The annual additional cost is estimated to be $ 1.4 billion (more than quadrupling baseline cost)

• May important caveats to results and modeling framework, but proof of concept of approach

Example of Ecosystem Services Research:Eco-nomic Value and Recreational Use of Iowa LakesCatherine Kling, Joe Herriges, John Downing, Kevin Egan, and Greg Colson. Funding from EPA Star grant, Iowa DNR, and CARD

Measuring Economic Value of Iowa Lakes• DNR provided a list of 35 priority Lakes for possible restoration

- Resulting lake changes were projected assuming

- a 70% reduction in total nitrogen, total phosphorous and suspended solids

- a 90% reduction in cynobacteria

- corresponding changes in Secchidepth, chlorophyll, and total phytoplankton

A range of lake changes were considered, including less major changes

Single Lake Rankings Sorted By Total Net Bene-fits ($million)

Ranking Lake TB1 Big Creek 755.762 Brushy Creek 517.203 Hickory Grove 277.804 Lake McBride 226.215 Clear Lake 202.936 Lake Geode 166.117 Three Mile 163.678 Easter 113.489 Lake Ahquabi 88.5510 Little Wall 81.8511 Lake Anita 69.6712 Kent Park 61.9913 Springbrook 61.7914 Red Haw 55.1015 Don Williams 66.14

Using Travel Pattterns to Reveal Valuation






ben chaffin chaffin farms ithaca, michigan · 2020-01-06 · resents any region, typically composed...

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