Ecological Archives A022-040-A1

Ecological Archives A022-040-A2

Genevičve S. Metson, Rebecca L. Hale, David M. Iwaniec, Elizabeth M. Cook, Jessica R. Corman, Christopher S. Galletti, and Daniel L. Childers. 2012. Phosphorus in Phoenix: a budget and spatial representation of phosphorus in an urban ecosystem. Ecological Applications 22:705–721.

Appendix A. Calculations, assumptions, and values used to determine stocks and fluxes of phosphorus in Phoenix, Arizona, USA.

Table A1. Equations and data sources used for each P stock and P flow considered in the urban P budget of metropolitan Phoenix.

Category	P flux (Gg / yr)	P stock (Gg)	Material flux	Unit	Material Stock	Unit	P concentration	Unit	Generic calc for P	Sources for P concentration	Sources for material
Dry Deposition	0.195022861						0.195022861	Gg P	(avg dry dep × d^-1 × m^-2) × 365 d / yr × Area of CAP	CAP LTER Website
Wet Deposition	7.44692 × 10^-5		193	mm rain / yr			74.46919846	Kg P	avg wet dep conc per site × avg rainfall × Area of CAP	CAP LTER Website	CAP LTER Website
Xeric Residential Soil		3.86	1607	km²			2.4	g / m²	P conc × land use area	Kaye et al. (2008)	2000 Landsat imagery
Mesic Residential Soil		0.82	175	km²			4.7	g / m²	P conc × land use area	Kaye et al. (2008)	2000 Landsat imagery
Agriculture Soil		4.29	1130	km²			3.8	g / m²	P conc × land use area	Kaye et al. (2008)	2000 Landsat imagery
Desert Soil		8.45	4697	km²			1.8	g / m²	P conc × land use area	Kaye et al. (2008)	2000 Landsat imagery
Non-Residential, Urban Soil		0.4	176	km²			2.3	g / m²	P conc × land use area	Kaye et al. (2008)	2000 Landsat imagery
Chemical fertilizer to agricultural soils	1.6		3,006,844	kg of P in Maricopa					P for county × ( ag acres in CAP/ agr acres in county)		Ruddy et al. (2006)
Chemical fertilizer to urban soils	0.3		300,684	kg of P					directly from the lit.		Ruddy et al. (2006)
Litterfall, trees, desert	0.072963198		40.53511	Gg C / year			0.0009	% P by dry weight	flux of C × 2 × P conc in xeric trees and scaled to mesquite leaf	Xeric trees: Williams and da Silva (1997); Mesquite leaf: Muthaiya and Felker (1997)	McHale et al. In prep.
Litterfall, shrubs, desert	0.071507128		65.00648	Gg C / year			0.00055	% P by dry weight	flux of C × 2 × P conc whole plan (Larrea sp. And Parthenium sp.)	Lajtha and Schlesinger (1988)	McHale et al. In prep.
Uptake, ag, tree	0.00439796		1.5707	Gg C / year			0.0014	% P by dry weight	flux of C × C × 2 × weighted avg (40% root P conc, 40% wood P conc, 20% leaf P conc.)	Williams and Da Silva (1997)	McHale et al. In prep.
Uptake, ag, shrub	0.00131306		0.3955	Gg C / year			0.00166	% P by dry weight	flux of C × C × 2 × weighted avg (40% root P conc, 30% wood P conc, 30% leaf P conc.)	Williams and Da Silva (1997)	McHale et al. In prep.
Uptake, ag, other veg	1.356		678	Gg C / year			0.001	% P by dry weight	flux of C × 2 × P conc	Meyer and Brown (1985)	McHale et al. In prep.
Uptake, desert, tree	0.072963198		40.53511	Gg C / year			0.0009	% P by dry weight	flux of C × 2 × P conc in xeric trees and scaled to mesquite leaf	Xeric trees: Williams and da Silva (1997); Mesquite leaf: Muthaiya and Felker (1997)	McHale et al. In prep.
Uptake, desert, shrub	0.071507128		65.00648	Gg C / year			0.00055	% P by dry weight	flux of C × 2 × P conc whole plan (Larrea sp. And Parthenium sp.)	Lajtha and Schlesinger (1988)	McHale et al. In prep.
Uptake, desert, other veg	0.049089112		24.54455581	Gg C / year			0.001	% P by dry weight	flux of C × 2 × P conc	Meyer and Brown (1985)	McHale et al. In prep.
Uptake, urban nonres, tree	0.004169088		1.48896	Gg C / year			0.0014	% P by dry weight	flux of C × C × 2 × weighted avg (40% root P conc, 40% wood P conc, 20% leaf P conc.)	Williams and Da Silva (1997)	McHale et al. In prep.
Uptake, urban nonres, shrub	0.00087648		0.264	Gg C / year			0.00166	% P by dry weight	flux of C × C × 2 × weighted avg (40% root P conc, 30% wood P conc, 30% leaf P conc.)	Williams and Da Silva (1997)	McHale et al. In prep.
Uptake, urban nonres, lawns	0.012204544		2.77376	Gg C / year			0.0022	% P by dry weight	flux of C × 2 × P conc	Williams and Da Silva 1997	McHale et al. In prep.
Uptake, urban nonres, other veg	0.00081533		0.407665116	Gg C / year			0.001	% P by dry weight	flux of C × 2 × P conc	Meyer and Brown (1985)	McHale et al. In prep.
Uptake, urban residential mesic, tree	0.0111622		3.9865	Gg C / year			0.0014	% P by dry weight	flux of C × C × 2 × weighted avg (40% root P conc, 40% wood P conc, 20% leaf P conc.)	Williams and Da Silva (1997)	McHale et al. In prep.
Uptake, urban residential mesic, shrub	0.00099932		0.301	Gg C / year			0.00166	% P by dry weight	flux of C × C × 2 × weighted avg (40% root P conc, 30% wood P conc, 30% leaf P conc.)	Williams and Da Silva (1997)	McHale et al. In prep.
Uptake, urban residential mesic, lawns	0.0217756		4.949	Gg C / year			0.0022	% P by dry weight	flux of C × 2 × P conc	Williams and Da Silva 1997	McHale et al. In prep.
Uptake, urban residential mesic, other veg	0.001994186		0.997093023	Gg C / year			0.001	% P by dry weight	flux of C × 2 × P conc	Meyer and Brown (1985)	McHale et al. In prep.
Uptake, urban residential xeric, tree	0.052327134		29.07063	Gg C / year			0.0009	% P by dry weight	flux of C × 2 × P conc in xeric trees and scaled to mesquite leaf	Xeric trees: Williams and da Silva (1997); Mesquite leaf: Muthaiya and Felker (1997)	McHale et al. In prep.
Uptake, urban residential xeric, shrub	0.001803054		1.63914	Gg C / year			0.00055	% P by dry weight	flux of C × 2 × P conc whole plan (Larrea sp. And Parthenium sp.)	Lajtha and Schlesinger (1988)	McHale et al. In prep.
Uptake, urban residential xeric, other veg	0.014283614		7.141806977	Gg C / year			0.001	% P by dry weight	flux of C × 2 × P conc	Meyer and Brown (1985)	McHale et al. In prep.
Desert Trees		1.614913146			897.17397	Gg C	0.0009	% P by dry weight	stock of C × 2 × P conc in xeric trees and scaled to mesquite leaf	Xeric trees: Williams and da Silva (1997); Mesquite leaf: Muthaiya and Felker (1997)	McHale et al. In prep.
Desert Shrubs		2.5626832			2329.712	Gg C	0.00055	% P by dry weight	stock of C × 2 × P conc whole plan (Larrea sp. And Parthenium sp.)	Lajtha and Schlesinger (1988)	McHale et al. In prep.
Agriculture, trees		0.05090876			18.1817	Gg C	0.0014	% P by dry weight	Stock of C × 2 × weighted avg (40% root P conc, 30% woo P conc, 30% leaf P conc.)	Williams and Da Silva (1997)	McHale et al. In prep.
Agriculture shrubs		0.022734696			6.8478	Gg C	0.00166	% P by dry weight	Stock of C × 2 × weighted avg (40% root P conc, 30% woo P conc, 30% leaf P conc.)	Williams and Da Silva (1997)	McHale et al. In prep.
Urban non residential, trees		0.131030592			46.79664	Gg C	0.0014	% P by dry weight	Stock of C × 2 × weighted avg (40% root P conc, 30% woo P conc, 30% leaf P conc.)	Williams and Da Silva (1997)	McHale et al. In prep.
Urban non residential, shrubs		0.020784262			6.26032	Gg C	0.00166	% P by dry weight	Stock of C × 2 × weighted avg (40% root P conc, 30% woo P conc, 30% leaf P conc.)	Williams and Da Silva (1997)	McHale et al. In prep.
Urban residential mesic, trees		0.4373446			156.1945	Gg C	0.0014	% P by dry weight	Stock of C × 2 × weighted avg (40% root P conc, 30% woo P conc, 30% leaf P conc.)	Williams and Da Silva (1997)	McHale et al. In prep.
Urban residential mesic, shrubs		0.01776117			5.34975	Gg C	0.00166	% P by dry weight	Stock of C × 2 × weighted avg (40% root P conc, 30% woo P conc, 30% leaf P conc.)	Williams and Da Silva (1997)	McHale et al. In prep.
Urban residential xeric, trees		1.903504356			1057.50242	Gg C	0.0009	% P by dry weight	Stock of C × 2 × P conc in xeric trees and scaled to mesquite leaf	Xeric trees: Williams and da Silva (1997); Mesquite leaf: Muthaiya and Felker (1997)	McHale et al. In prep.
Urban residential xeric, shrubs		0.060932619			55.39329	Gg C	0.00055	% P by dry weight	stock of C × 2 × P conc whole plan (Larrea sp. And Parthenium sp.)	Lajtha and Schlesinger (1988)	McHale et al. In prep.
Export crop	0.305201741						0.81	lbs / acre	Number of 90 × 90m pixels under cotton production × conversion acres / pixel × P removal lbs / acre (at that yield) × conversion Gg / lb	USDA-NRCS (2000)	SS 2010 crop GIS layer and USDA naSS records, personal communication
Animal feed crop	1.74						1.44, 1.86, 0.84	lbs / acre for corn, alfalfa, other hay	Add for each crop - Number of 90 × 90m pixels under x crop production × conversion acres / pixel × P removal lbs / acre (at that yield) × conversion Gg / lb	USDA-NRCS (2000)	SS 2010 crop GIS layer and USDA naSS records, personal communication
Human consumption crop	0.1		see spatial data	see spatial data			24, 0.0037, 0.0051, 0.041, 1.01, 0.55, 0.73,	lbs / acre*	Add for each crop - Number of 90 × 90m pixels under x crop production × conversion acres / pixel × P removal lbs / acre (at that yield) × conversion Gg / lb	USDA-NRCS (2000)	SS 2010 crop GIS layer and USDA naSS records, personal communication
Surface water inputs - Salt River	0.010154461		3.54914 × 10¹¹	L / year			0.028611018	mg P / L	Baket et al. (2001) and USGS	USGS	USGS
Surface water inputs - Verde River	0.012505242		2.4205 × 10¹¹	L / year			0.051663985	mg P / L	Baket et al. (2001) and USGS	USGS	USGS
Surface water inputs - CAP Canal (Colorado R)	0.033402688		8.35067 × 10¹¹	L / year			0.04	mg P / L	Mean P conc for CAP × avg annual withdrawals from CAP canal to Maricopa County	CAP LTER	MAG (2002)
Surface water outputs - Gila River	0.112731597		1.28604 × 10¹¹	L / year			0.876579029	mg P / L	USGS and Baker et al. (2001)	USGS	USGS
CAP to urban uses	0.013666979		3.41674 × 10¹¹	L / year			0.04	mg P / L	Water flux × P conc.	CAP LTER	MAG (2002)
CAP to subsurface (underground storage or gw recharge)	0.019735709		4.93393 × 10¹¹	L / year			0.04	mg P / L	Water flux × P conc.	CAP LTER	MAG (2002)
Surface water to Irrigation	0.010847422		2.85772 × 10¹¹	L / year			0.03795825	mg P / L	Water flux × ( avg P conc= ( avg.salt annual load +avg. verde annual load)/(avg. salt discharge + avg. verde discharge)))	USGS	Kenny et al. (2008)
Surface water --> public supply	0.029394318		7.74385 × 10¹¹	L / year			0.03795825	mg P / L	Water flux × ( avg P conc= ( avg.salt annual load + avg. verde annual load)/(avg. salt discharge + avg. verde discharge)))	USGS	Kenny et al. (2008)
Drinking water to irrigation	0.006419892		6.41989 × 10¹¹	L / year			0.01	mg P / L	Water flux × P conc.	Tempe Water Quality Lab, personal communication.	Kenny et al. (2008)
GW to Public supply	0.007434566		3.09774 × 10¹¹	L / year			0.024	mg P / L	Water flux × Median P conc.	AzDEQ monitoring for Phoenix Active Management Area. Personal communication.	Kenny et al. (2008)
GW to domestic (self supply)	0.000213147		8881107000	L / year			0.024	mg P / L	Water flux × Median P conc.	AzDEQ monitoring for Phoenix Active Management Area. Personal communication.	Kenny et al. (2008)
Total GW withdrawals	0.039261393		1.63589 × 10¹²	L / year			0.024	mg P / L	Water flux × Median P conc.	AzDEQ monitoring for Phoenix Active Management Area. Personal communication.	Kenny et al. (2008)
GW to industrial	0.000182934		7622258500	L / year			0.024	mg P / L	Water flux × Median P conc.	AzDEQ monitoring for Phoenix Active Management Area. Personal communication.	Kenny et al. (2008)
GW to Irrigation	0.030803331		1.28347 × 10¹²	L / year			0.024	mg P / L	Water flux × Median P conc.	AzDEQ monitoring for Phoenix Active Management Area. Personal communication.	Kenny et al. (2008)
Waste water effluent --> Gila river	0.599779104		1.54982 × 10¹¹	L / year			3.87	mg P / L	Water flux × P conc.	CAP LTER	Lauver et al. (2000)
Waste water effluent --> irrigation (agriculture and golf courses)	0.921089338		2.38008 × 10¹¹	L / year			3.87	mg P / L	Water flux × P conc.	CAP LTER	Lauver et al. (2000)
Waste water effluent --> GW recharge	0.085682729		22140240080	L / year			3.87	mg P / L	Water flux × P conc.	CAP LTER	Lauver et al. (2000)
Waste water effluent --> Palo Verde powerplant (cooling)	0.535517057		1.38377 × 10¹¹	L / year			3.87	mg P / L	Water flux × P conc.	CAP LTER	Lauver et al. (2000)
Runoff from urban	0.041882363		31706222400	L / year			1.320950887	mg P / L	see Fossum 2001 for regression equations based on land use	Fossumet al.(2001)	Fossumet al. (2001)
Runoff from desert	0.003680982		?	L / year			0.051663985	mg P / L	Kg P / ha of desert × area of desert in CAP	USGS	Estimated from USGS NWIS data for Verde River.
Biosolids	1.6773282		55910.94	dry tons of biosolid produced in Maricopa per year			3	%	Biosolid produced / year × P conc	ADEQ (2006)	ADEQ (2006)
Asphalt		7.86			17272	Gg	0.16	% PPA in Asphalt by weight	area of asphalt × depth × density × % of PPA × % of P in PPA	Golden et al. (2009)	Stefinov et al. 2005^†
Paper and Cardboard import	0.231839873		297.05	kg paper / per day per person			0.024	%	import kg per capita per day × number to days a year × pop of CAP × P conc × conversion Gg / kg	Antikainen et al. (2004)	World Resources Institute (2007)
Textiles	0.906743032		0.07	lbs / per person per day			2.3	%	Waste produced lbs / per capita per day × number of days a year × pop of CAP × conversion Gg / lbs × % of textiles in waste × P conc	Yang & Yang (2005)	MAG. (2005)
Paper to landfills	1.137371111		0.88	lbs / per person per day			0.024	%	Waste produced lbs / per capita per day × number of days a year × population of CAP × conversion Gg / lbs × % of waste that is paper × P conc	Antikainen et al. (2004)	MAG. (2005)
Paper and Cardboard to recycling	0.379773923		743	tons / day			0.024	%	Recycling produced ton / per day × number of days a year × conversion Gg /tons × % of recycling that is (paper + newspaper + cardboard + woodwaste) × P conc	Antikainen et al. (2004)	MAG. (2005)
Humans		3.2386					1	%	(popl size × (avg human weight > 18 × % popl > 18 × P conc.) + (avg human weight < 18 × % popl < 18 × P conc))	Harper et al. (1977)	U.S. Census Bureau (2000);Avg Size of US popl by distr: CDC-NCHS
Humans Net of Immigration & Emigration	0.10004						1	%	Human P stock × % change in stock size	Harper et al. (1977)	Popl change: U.S. Census Bureau (2009); Avg Size of US popl by distr: CDC-NCHS
Dog Food Consumed	0.56267		113.9013	19.5	kg food / animal / yr		0.5	%	Dog Population in CAP × Dog Food requirement kg / dog per yr × %P in food	AAFCO; Personal communication Baker; U.S. Census Bureau (2009) %P: (Harper et al. (1977)	AAFCO
Dogs		0.0988					1	%	# of dog (proportional to humans) × %P in dogs	Harper et al. (1977)	Personal Communication Baker; human pop: U.S. Census Bureau (2009)
Dogs Net of Immigration & Emigration	0.0024						1	%	change in dog popl from 2000-2009 × % P in dogs	Harper et al. (1977)	Personal communication Baker; U.S. Census Bureau (2009)
Dog Poop	0.5507						1.425	kg / yr /Dog	# dogs (proportional to human pop) × P pre dog	Baker et al. (2007)
Cat Food Consumed	0.137081247		41.4186535	2.99	kg food / animal / yr			Cat Population in CAP × Cat Food requirement kg / cat per yr × %P in food	AAFCO	AAFCO
Cats		0.02					1	%	change in cat popl from 2000-2009 × % P in cats	Harper et al. (1977)	Perconal communication Baker;human popl: U.S. Census Bureau (2009)
Cat Poop	0.1688						1.425	kg / yr / cat	#cat (proportional to human pop) × P pre dog	Baker et al. (2007)
Cow Feed	1.535161675		29471.7259	kg / animal / yr			0.12	%P	Cow Population in CAP × Cow Feed requirements × %P in feed	Hall et al. (2009)	# cows: USDA (2007)
Cows		1.87	185322.5	cows					# cows × avg weight × %P	Harper et al. (1977)	# cows: USDA (2007), % cow in co. that is beef vs dairy: AASS & U of A (2005), avg weight of cows beef & dairy: ASAE. (2004).
Cow Manure	1.037806		185322.5	cows			5.6	(gP / g animal / yr)	P in manure × Popl of cows	Gilbertson et al. (1979)	# cows: USDA (2007), % cow in co. that is beef vs dairy: AASS & U of A (2005), avg weight of cows beef & dairy: ASAE. (2004).
Cow Milk	0.341763306		9131.2500	kg milk / animal / yr	0.5722	% of CAP cows that are dairy cows	0.0004	g P/ g milk	Dairy cow popl × Milk produced per dairy cow × Amount of P in milk	Bender & Bender (1999) and Gilbertson et al. (1979)	# cows: USDA (2007), % cow in co. that is beef vs dairy: AASS & U of A (2005), Gilbertson et al. (1979)
Milk export from CAP	0.14										see assumptions

* for watermelons, citrus (using grapefruit), oranges, greens, lettuce, wheat, shorghum, barley
^† See also: http://www.simetric.co.uk/si_materials.htm

Table A2. Assumptions and notes for the calculation each P stock and P flow considered in the urban P budget of metropolitan Phoenix.

Category	Assumptions	Notes
Dry Deposition		Specificity: 2005 from 4 locations (LDS, ORG, PSS, PVR), downloaded: data from CAP website on 15 May 2010
Wet Deposition		Specificity: 2005 from 3 locations (LDS, PSS, PVR), Downloaded: downloaded data from CAP website on 15 May 2010
Xeric Residential Soil	0–30cm avg soil conc by land use	These calculations are following the "traditional modeling approach" discussed in Kaye et al 2008
Mesic Residential Soil	0–30cm avg soil conc by land use	These calculations are following the "traditional modeling approach" discussed in Kaye et al 2008
Agriculture Soil	0–30cm avg soil conc by land use	These calculations are following the "traditional modeling approach" discussed in Kaye et al 2008
Desert Soil	0–30cm avg soil conc by land use	These calculations are following the "traditional modeling approach" discussed in Kaye et al 2008
Non-Residential, Urban Soil	0–30cm avg soil conc by land use	These calculations are following the "traditional modeling approach" discussed in Kaye et al 2008
Chemical fertilizer to agricultural soils	equally applied to ag. fields	53% of agriculture in Maricopa County is in CAP based in USDA field office data average 2002 and 2007 and the naSS crop layer data (see spatial section)
Chemical fertilizer to urban soils	equally applied to mesic soils
Litterfall, trees, desert	desert veg. is steady state over 1 yr and set litterfall equal to uptake
Litterfall, shrubs, desert	desert veg. is steady state over 1 yr and set litterfall equal to uptake
Uptake, ag, tree	We set uptake = net primary productivity and assume C:P of uptake is same as mean P content for each plant type. Our NPP data are in Gg C; we convert these to dry weight assuming biomass is 50% C by dry weight.
Uptake, ag, shrub	We set uptake = net primary productivity and assume C:P of uptake is same as mean P content for each plant type. Our NPP data are in Gg C; we convert these to dry weight assuming biomass is 50% C by dry weight.
Uptake, ag, other veg	We set uptake = net primary productivity and assume C:P of uptake is same as mean P content for each plant type. Our NPP data are in Gg C; we convert these to dry weight assuming biomass is 50% C by dry weight.
Uptake, desert, tree	We set uptake = net primary productivity and assume C:P of uptake is same as mean P content for each plant type. Our NPP data are in Gg C; we convert these to dry weight assuming biomass is 50% C by dry weight.
Uptake, desert, shrub	We set uptake = net primary productivity and assume C:P of uptake is same as mean P content for each plant type. Our NPP data are in Gg C; we convert these to dry weight assuming biomass is 50% C by dry weight.
Uptake, desert, other veg	We set uptake = net primary productivity and assume C:P of uptake is same as mean P content for each plant type. Our NPP data are in Gg C; we convert these to dry weight assuming biomass is 50% C by dry weight.	Assume cactus Prickly Pear value
Uptake, urban nonres, tree	We set uptake = net primary productivity and assume C:P of uptake is same as mean P content for each plant type. Our NPP data are in Gg C; we convert these to dry weight assuming biomass is 50% C by dry weight.
Uptake, urban nonres, shrub	We set uptake = net primary productivity and assume C:P of uptake is same as mean P content for each plant type. Our NPP data are in Gg C; we convert these to dry weight assuming biomass is 50% C by dry weight.
Uptake, urban nonres, lawns	We set uptake = net primary productivity and assume C:P of uptake is same as mean P content for each plant type. Our NPP data are in Gg C; we convert these to dry weight assuming biomass is 50% C by dry weight.
Uptake, urban nonres, other veg	We set uptake = net primary productivity and assume C:P of uptake is same as mean P content for each plant type. Our NPP data are in Gg C; we convert these to dry weight assuming biomass is 50% C by dry weight.	Assume cactus Prickly Pear value
Uptake, urban residential mesic, tree	We set uptake = net primary productivity and assume C:P of uptake is same as mean P content for each plant type. Our NPP data are in Gg C; we convert these to dry weight assuming biomass is 50% C by dry weight.
Uptake, urban residential mesic, shrub	We set uptake = net primary productivity and assume C:P of uptake is same as mean P content for each plant type. Our NPP data are in Gg C; we convert these to dry weight assuming biomass is 50% C by dry weight.
Uptake, urban residential mesic, lawns	We set uptake = net primary productivity and assume C:P of uptake is same as mean P content for each plant type. Our NPP data are in Gg C; we convert these to dry weight assuming biomass is 50% C by dry weight.
Uptake, urban residential mesic, other veg	We set uptake = net primary productivity and assume C:P of uptake is same as mean P content for each plant type. Our NPP data are in Gg C; we convert these to dry weight assuming biomass is 50% C by dry weight.	Assume cactus Prickly Pear value
Uptake, urban residential xeric, tree	We set uptake = net primary productivity and assume C:P of uptake is same as mean P content for each plant type. Our NPP data are in Gg C; we convert these to dry weight assuming biomass is 50% C by dry weight.
Uptake, urban residential xeric, shrub	We set uptake = net primary productivity and assume C:P of uptake is same as mean P content for each plant type. Our NPP data are in Gg C; we convert these to dry weight assuming biomass is 50% C by dry weight.
Uptake, urban residential xeric, other veg	We set uptake = net primary productivity and assume C:P of uptake is same as mean P content for each plant type. Our NPP data are in Gg C; we convert these to dry weight assuming biomass is 50% C by dry weight.	Assume cactus Prickly Pear value
Desert Trees
Desert Shrubs
Agriculture, trees
Agriculture shrubs
Urban non residential, trees
Urban non residential, shrubs
Urban residential mesic, trees
Urban residential mesic, shrubs
Urban residential xeric, trees
Urban residential xeric, shrubs
export crop
Animal feed crop
Human consumption crop		Ten % of food produced here is assumed to spoil before it can reach human food supply based on Pimentel, D., W. Dritschilo, J. Krummel, and J. Kutzman. 1975. Energy and land constraints in food protein production. Science;(United States) 190.
Surface water inputs - Salt River		Mean annual load 1999-2004 ( range 0.01-8.1 mg /L orthophosphate unfiltered)
Surface water inputs - Verde River		Mean annual load 1999-2004 (range 0.01-7.3 mg P/L unfiltered)
Surface water inputs - CAP Canal (Colorado R)		Mean annual load 1998-2004 (range 0.00-0.81 mg P/L)
Surface water outputs - Gila River		Calculated using USGS PO4 and discharge data, extrapolated chemistry data across discharge using method described in Baker et al 2001, summed loads for each year, and averaged annual loads across 1999–2004.Mean annual load 1999-2004 (range 0.01-9.4 mg P/L unfiltered)
CAP to urban uses		CAP canal data 1998-2004
CAP to subsurface (underground storage or gw recharge)
Surface water to Irrigation		P concentration were calculated using annual loads and discharge from the Salt and Verde Rivers averaged over 1999-2004. year used: 2005
Surface water --> public supply
Drinking water to irrigation		years used:1998 and 2005, P concentrations are < 0.02 mg P / L (below detection limit).
GW to Public supply		year used: 2005
GW to domestic (self supply)		year used: 2005
Total GW withdrawals		year used: 2005
GW to industrial		year used: 2005
GW to Irrigation		year used: 2005
Waste water effluent --> Gila river	Calculated as 28% of waste water treatment plant effluent production	Concentration is average total P value from 91st Ave treatment plant from 1998–2004. ( range in 1997 0.72-29.37 mg /L)
Waste water effluent --> irrigation (agriculture and golf courses)	Calculated as 43% of waste water treatment plant effluent production	Concentration is average total P value from 91st Ave treatment plant from 1998–2004. ( range in 1997 0.72-29.37 mg /L)
Waste water effluent --> GW recharge	Calculated as 4% of waste water treatment plant effluent production	Concentration is average total P value from 91st Ave treatment plant from 1998–2004. ( range in 1997 0.72-29.37 mg /L)
Waste water effluent --> Palo Verde powerplant (cooling)	Calculated as 25% of waste water treatment plant effluent production.	Concentration basted on 91st Ave WWTP 1998-2004.
Runoff from urban		Note that this is the sum of annual runoff and TP loads for 12 of the Phoenix metro cities. Regression equations are presented in Fossum 2001 and can be used with current CAP land use data to get a better estimate. Also note that these estimates are from small urban catchments and do not take into account stormwater infrastructure (ret basins, etc), and therefore are probably a big overestimate.
Runoff from desert
Biosolids
Asphalt
Paper and Cardboard import
Textiles
Paper to landfills
Paper and Cardboard to recycling
Humans		Data is for humans < 18 years of age and humans > 18 years of age (online tool year: 2009)
Humans Net of Immigration & Emigration	Linearity of data from 2000-2010	Averaged over from 2000-2010
Dog Food Consumed	see the note	Dog Food Requirements for a 19.5 kg dog. Low Estimate based on P requirement and not what they are actually consuming
Dogs	%P for dog is same as humans	Baker doesn't cite how he calc the ratio of # of dogs in CAP. This is based on the change in popl from 2000-2009.
Dogs Net of Immigration & Emigration		Avg from 2000-2010
Dog Poop		Baker et al 2007 Household Flux Calculator - dog food consumption is equal to dog excretion. Table 3 gives intake of P in kg / yr for dogs of several weights. The number listed here (1.425) is an average P (kg / yr) for 10, 20, 30 and 40 kg dogs (P = 0.5, 1.2, 1.7, 1.7 and 2.3). Note the units are kg / yr / dog and consumption of dog food = excretion by dog
Cat Food Consumed		Cat Food Requirements for a 2.99 kg cat. Low Estimate based on P requirement and not what they are actually consuming
Cats	%P for cat is same as humans
Cat Poop	assume it’s the same as dog numbers
Cow Feed		Cow Feed Requirements for a 1007.6667 kg Cow. Low Estimate based on P requirements and not what they are actually consuming
Cows	%P for dog is same as humans	Number of cows is an average in Maricopa County from 2002 & 2007
Cow Manure	%P for dog is same as humans	Number of cows is an average in Maricopa County from 2002 & 2007. This manure number is consistent with the cow to total manure production in the county extrapolated from 1997 USDS data
Cow Milk		40% of milk produced in the area is exported based on United Darymen Association of Arizona (2010) personal communication
Milk export from CAP	40 % of milk is exported. Based on personal communication with United Dairymen of Arizona saying 2/3 is exported but we also import a large amount.

Literature Cited

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Arizona Department of Environmental Quality. 2006. 2005 Annual Biosolids Report. Phoenix, AZ.

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