Why are median phosphorus concentrations improving in New Zealand streams and rivers?

Figures & data

Table 1. Summary of the types, sources, temporal and spatial scales of biophysical data used in the study.

Data type	Data source	Years covered	Spatial scale	References
Land cover	Land Cover Database	1996/97, 2001/2002, 2008/2009, 2012/2013	Sub-catchment	Landcare Research (2017)
Pastoral land use	AgriBase – AsureQuality	1999, 2002, 2006, 2013	Farm^a	Sanson (2005)
Numbers of different farm types	Statistics New Zealand	1996, 1999, 2003, 2007, 2012	Regional	Statistics New Zealand (2018)
Fertiliser N and P sales	Fertiliser Association of New Zealand, Ballance Agri-Nutrients, Ravensdown, Statistics New Zealand	1994–2015 (for P) 2002, 2012 (for N)	Regional	Statistics New Zealand (2018)
Imported P in dairy cow feed	DairyNZ	1994–2015	National	DairyNZ Economics Group (2016)
Soil Olsen P concentrations	Analytical Research Laboratories, Eurofins, Hill Laboratories, Soil Fertility Service	2001–2014 2000–2014 2008–2014 1994–2002	Regional

^a Incomplete as contributions are voluntary.

Table 2. Mean percentage change (and standard deviation) in catchment stock numbers and area for different stock classes for the periods 1999–2013 and 2006–2013 and their respective comparison (Pearson correlation coefficient) to trends between 1994–2013 and 2004–2013 for either in the percentage change in median annual FRP or TP concentrations and clarity.

Attribute	Land use	Mean % change	Standard deviation of change	Correlation to FRP trend	Correlation to TP trend	Correlation to clarity trend
Change in stock numbers 1999–2013 (%)	Beef	47.4	9.1	−0.07	−0.10	0.15
	Dairy	209.9	44.6	0.09	0.01	0.01
	Deer	152.7	35.1	0.08	0.08	−0.01
	Sheep	152.2	49.8	−0.10	−0.12*	−0.02
Change in catchment area 1999–2013 (%)	Beef	−2.4	0.3	−0.04	−0.03	0.06
	Dairy	1.8	0.3	0.12	0.07	−0.02
	Deer	−0.2	0.1	0.03	−0.06	0.05
	Sheep	−3.4	0.4	−0.14*	0.05	−0.18*
	Sheep/Beef	9.3	0.5	0.09	0.02	0.06
Change in stock numbers 2006–2013 (%)	Beef	−3.4	1.0	−0.01	−0.10	0.06
	Dairy	110.5	55.1	−0.02	−0.04	0.06
	Deer	7.6	12.0	0.02	0.00	−0.08
	Sheep	92.8	51.9	0.06	0.09	−0.08
Change in catchment area 2006–2013 (%)	Beef	0.0	0.1	0.04	0.03	0.05
	Dairy	0.8	0.2	0.07	0.12*	−0.06
	Deer	−0.1	0.0	−0.07	−0.03	−0.02
	Sheep	−0.4	0.1	−0.10	−0.03	−0.18*
	Sheep/Beef	0.0	0.1	−0.06	−0.09	−0.04

* Indicates a weak (P < .05), but significant correlation.

Figure 1. Co-location of trends for decreasing FRP or TP and increasing clarity for 1994–2013 and 2004–2013 and land use in each catchment for 2013. Blank areas within a catchment are most likely to be native forest or mountains.

Table 3. Count of sites for the 1994–2013 and 2004–2013 periods showing an increasing or decreasing trend in FRP or TP concentrations, and the count of sites for the same periods exhibiting a decreasing trend in FRP or TP concentrations and increasing clarity at the same site. Sites showing indeterminate trends were not considered.

Analyte and period	Increasing	Decreasing	Decreasing P and increasing clarity
FRP
1994–2013	142	71	27 (38%)a
–2013	189	122	75 (61%)
TP
–2013	46	99	26 (26%)
2004–2013	25	251	104 (41%)

^a Corresponds to the percentage of sites with decreasing FRP or TP and increasing clarity for the period.

Figure 2. Annual quantity (Mg) of imported P given as sales of superphosphate and RPR and imported feed (PKE = Palm Kernel Extract) using their average per cent P concentrations (DairyNZ 2018).

Figure 3. The relative percentage of samples in excess of the agronomic optimum in Olsen P concentration for pasture production (20, 35, 45 and 45 mg P L⁻¹ for Sedimentary, Volcanic, Pumice and Peat soils, respectively) submitted to Eurofins and Hills laboratories (n ∼ 500,000) between 1988–1996, 1997–2001 and 2002–2014. Data for 1988–1996 and 1997–2001 is from Wheeler et al. (2004).

Table 4. Trends in topsoil Olsen P concentrations (mg L⁻¹) between 2002 and 2014 and submitted to ARL, Eurofins and Hill Laboratories.

Region	Number of samples	Trend (mg L^−1 Olsen P yr^−1)	Significant
Auckland	8627	0.28	Y
Bay of Plenty	14,030	0.19	Y
Canterbury	111,348	0.08	Y
Gisborne	3434	1.15	Y
Hawkes Bay	19,538	0.45	Y
Manawatu/Wanganui	37,982	0.80	Y
Marlborough	5064	0.07	N
Northland	16,462	0.50	Y
Otago	58,679	0.02	N
Southland	96,596	0.22	Y
Tasman	8875	0.85	Y
Taranaki	16,391	0.05	N
Waikato	63,339	0.59	Y
Wellington	7106	0.29	Y
West Coast	11,652	0.39	Y

Figure 4. Mean annual load of FRP lost in leachate from the top 30-cm of three pasture soils of varying ASC (51–72%) receiving either no N or 150 or 300 kg N ha⁻¹ yr⁻¹ as urea (Dodd et al. 2014).

Table 5. Data for the regional tonnage of N fertiliser applied in New Zealand in 2002 and the percentage change in tonnes applied by 2012.

Region	Mass of N sold (Mg) in 2002	Change 2012 relative to 2002 (%)	Number of sites with decreasing FRP (TP) concentrations
Auckland	4638	−19	17 (19)
Bay of Plenty	11,358	6	13 (6)
Canterbury	42,228	93	31 (22)
Gisborne	2834	1	1 (2)
Hawkes Bay	8901	−8	12 (25)
Manawatu/Wanganui	20,757	2	6 (4)
Marlborough	1758	−24	1 (1)
Northland	11,446	9	10 (13)
Otago	12,016	49	5 (14)
Southland	17,155	79	16 (21)
Tasman	3142	3	4 (0)
Taranaki	13,264	49	3 (3)
Waikato	50,970	14	63 (87)
Wellington	5158	3	19 (39)
West Coast	6190	92	0 (0)

Table 6. The relative percentage of sites exhibiting increasing trends in nitrate (NO₃), decreasing trends in FRP and their co-location in streams and rivers or groundwater for data for 2004–2013.

Trend	Groundwater	Streams and rivers
Increasing NO3	82	51
Decreasing FRP	17	45
Collocation of increasing N with decreasing P	1	4

Table 7. Range of strategies used in management, as an amendment or at the edge of the field to decrease P losses to water, their effectiveness, cost and citation noting the year that their cost-effectiveness was assessed.

Strategy		Main targeted P form(s)	Effectiveness (% TP decrease)	Cost – Range (USD $ kg^−1 P conserved)^a	References
Optimum soil test P	Management	Filterable and Particulate	5–20	(Highly cost-effective)^b	Morton et al. (2003)
Low solubility P fertiliser		Filterable and Particulate	0–20	0–30	McDowell et al. (2010)
Low P near stream areas and P efficient pastures		Filterable and Particulate	26–46	(Highly cost-effective)^c	McDowell et al. (2014)
Stream fencing		Filterable and Particulate	10–30	2–45	McDowell (2008)
Restricted grazing of cropland		Particulate	30–50	30–200	McDowell et al. (2005)
Delayed strategic grazing of cropland gullies		Particulate	65	20 –80	Monaghan et al. (2017)
Greater effluent pond storage / application area		Filterable and Particulate	10–30	3–50	Houlbrooke et al. (2004)
Flood irrigation management^d		Filterable and Particulate	40–60	3–300	Houlbrooke et al. (2008)
Low rate effluent application to land		Filterable and Particulate	10–30	8–55	Monaghan et al. (2010)
P-sorptive backfill in tile drains	Amendment	Filterable and Particulate	50	30–110	McDowell et al. (2008)
Post wetland drainage filter		Filterable	49–98	80–200^e	Ballantine and Tanner (2010)
Red mud (bauxite residue)		Filterable	20–98	110–200	Vlahos et al. (1989)
Alum to pasture		Filterable	5–30	150 – >700	McDowell and Norris (2014)
Alum to grazed cropland		Filterable	30	180–340	McDowell and Houlbrooke (2009)
Grass buffer strips	Edge of field	Filterable	0–20	30 – >300	McKergow et al. (2007); Hille et al. (2018)
Sorbents in and near streams		Filterable and Particulate	20	400	McDowell, Hawke, et al. (2007)
Sediment traps		Particulate	10–20	>700	Olarieta et al. (1999)
Dams and water recycling		Filterable and Particulate	50–95	(300) – 700^f	Barlow et al. (2005)
Advanced effluent ponds		Filterable and Particulate	10–50	>10,000	Sukias et al. (2010); Craggs et al. (2014)
Constructed wetlands		Particulate	−426–77	130 – >700^g	Vymazal (2007)
Natural seepage wetlands		Particulate	<10%	130 – >700^g	Hughes et al. (2016)

Note: Costs were taken from McDowell et al. (2013) and McDowell et al. (2017).

^a The numbers in parentheses represent net profit, not cost.

^b Profitability depends on existing soil Olsen P concentration; greater savings are possible the more P-enriched the soil is beyond the agronomic optimum.

^c Profitable at about $40–50/ha assuming the strategy is implemented over 10% of the farm.

^d Includes adjusting clock timings to decrease outwash <10% of inflow, installation of bunds to prevent outwash, and re-levelling of old borders.

^e Excludes the cost of the wetland.

^f The upper bound is only applicable to retention dams combined with water recycling.

^g The potential for wetlands to act as a source of P renders their upper estimates for cost infinite.

Table 8. The percentage by region of dairy farms in full compliance (after comma = significant non-compliance) with effluent regulations at the beginning (2003/2004), middle (2007/2008) and end (2011/2012) of the Clean Streams Accord.

Region	2003/2004	2007/2008	2011/2012
Northland	34, n/a^a	43, 26	38, 27
Auckland	79, <1	73, 7	73, 5
Waikato	43, 16	48, 10	72, 12
Bay of Plenty	n/a	76, 9	67, 16
Taranaki	96, 0.5	96, <1	93, 1
Hawkes Bay	64, 1.6	74, 11	80, 3
Manawatu/Wanganui	85, n/a	78, 22	91, 7
Wellington	89, n/a	53, 28	95, 4
Tasman	9, 9.4	93, 2	94, 2
Marlborough	78, 7.0	75, <1	70, 3
Canterbury	52, 1.0	46, 20	70, 9
Otago	97, n/a	83, 8	94, 4
Southland	81, 6.2	65, 13	45, 12
Weighted national mean	n/a	64, 12	73, 10

Note: Data sourced from the Ministry of Agriculture and Forestry (2005) and the Ministry for Primary Industries (2013).

^a Data not available.

Figure 5. The employment characteristics of the 2093 rural professionals who will have completed a Sustainable Nutrient Management course in New Zealand Agriculture.

Figure 6. The employment characteristics of the 856 rural professionals who will have completed an Advanced Sustainable Nutrient Management course.

Figure 7. The origin of the 856 rural professionals who will have completed an Advanced Sustainable Nutrient Management course.

Figure 8. Number of web citations per year and the cumulative number of articles (popular and from scientific journals) on critical source areas (CSAs) and land–water–P interactions over time. Of the 159 scientific documents produced (as of April 2018), 47 were academic papers, 75 were from policy (central or regional), 30 were from industry, while 14 were from non-governmental organisations (Source = Google analytics).

Figure 9. The management of farm dairy effluent by Regional Authorities in New Zealand to decrease N and, by inference, P losses. Management focuses on restricting effluent application to soils to prevent ponding and runoff year-round (A: none, refers to no ponding or runoff allowed at any time; time limit, allows for some ponding and runoff; and direct discharge refers to discharges from effluent settling ponds directly to streams), limiting applications over the year to not exceed a N rate for the effluent block (B: <150–200 kg N ha⁻¹ yr⁻¹ via direct measurement of the effluent or a nutrient budget), and restricting applications to saturated soils in winter (C: applications are either not allowed, allowed if below a certain rate, or unrestricted). Figure modified from McDowell et al. (2017).

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