This article appeared in a journal published by Elsevier. The attachedcopy is furnished to the author for internal non-commercial researchand education use, including for instruction at the authors institution

and sharing with colleagues.

Other uses, including reproduction and distribution, or selling orlicensing copies, or posting to personal, institutional or third party

websites are prohibited.

In most cases authors are permitted to post their version of thearticle (e.g. in Word or Tex form) to their personal website orinstitutional repository. Authors requiring further information

regarding Elsevier’s archiving and manuscript policies areencouraged to visit:

http://www.elsevier.com/copyright

Author's personal copy

Europ. J. Agronomy 44 (2013) 109– 123

Contents lists available at SciVerse ScienceDirect

European Journal of Agronomy

jo u r n al hom epage: www.elsev ier .com/ locate /e ja

Prospects for ecological intensification of Australian agriculture

Z. Hochmana,∗, P.S. Carberryb, M.J. Robertsonc, D.S. Gaydond, L.W. Bellb, P.C. McIntoshe

a CSIRO Ecosystems Sciences and Sustainable Agriculture Flagship, GPO Box 2583, Brisbane, QLD 4001, Australiab CSIRO Ecosystems Sciences and Sustainable Agriculture Flagship, 203 Tor Street, Toowoomba, QLD 4350, Australiac CSIRO Ecosystems Sciences and Sustainable Agriculture Flagship, Private Bag 5, PO Wembley, WA 6913, Australiad CSIRO Ecosystems Sciences and Climate Adaptation Flagship, GPO Box 2583, Brisbane, QLD 4001, Australiae CSIRO Marine and Atmospheric Research and Wealth from Oceans Flagship, GPO Box 1538 Hobart, Tasmania 7001, Australia

a r t i c l e i n f o

Article history:Received 11 June 2011Received in revised form 28 October 2011Accepted 1 November 2011

Keywords:Water use efficiencyNutrient use efficiencyClimate risk managementPrecision agricultureCrop–livestock integrationDeficit irrigation

a b s t r a c t

World population growth, changing diets and limited opportunities to expand agricultural lands willdrive agricultural intensification in the decades ahead. Concerns about the reliance of past agriculturalintensification on non-renewable resources, about its negative impacts on natural resources both on andoff farm and on greenhouse gas emissions, provide an imperative for future agricultural intensificationto become ecologically efficient. We define ecological intensification of agriculture (EIA) as: producingmore food per unit resource use while minimising the impact of food production on the environment.Achieving it will require increased precision in the use of inputs and reduction in inefficiencies and losses.It will also require a more holistic view of farming, going beyond efficiencies of single inputs into a singlefield in a single season to consideration of efficiencies of whole systems over decades. This paper exploresthe ecological intensification issues facing agricultural production in Australia where opportunities foragricultural intensification are centred on more efficient use of limited and unreliable water resourcesin both dryland and irrigated agriculture. Ecological efficiencies can be achieved by better matching thesupply of nutrients to crops’ requirements both temporally and spatially. This has the added benefit ofminimising the opportunities for excessive nutrients to impact on soil health (acidity and dryland salinity)and water quality (pollution of groundwater and eutrophication of lakes and rivers). Opportunities forecologically efficient intensification are also identified through better integration of crop and livestockenterprises on mixed crop–livestock farms. We define nine desirable attributes of an EIA system: (1)increased agricultural production; (2) efficient use of limited resources; (3) minimal impact on globalwarming; (4) minimal negative on-site impacts; (5) minimal negative off-site impacts; (6) minimal riskand maximum resilience; (7) preservation of biodiversity in agriculture; (8) preservation of biodiversity innature and; (9) positive social outcomes. We focus on four technologies and production systems emergingin Australian agriculture: climate risk management; precision agriculture; crop–livestock integration anddeficit irrigation. For each of these systems we identify how well they are likely to match the nine desirableattributes of an EIA system. While it seems unlikely that any single technology can satisfy all nine desirableattributes, there is hope that in combination emerging and future technologies will progress Australianagriculture towards greater productivity and ecological efficiency.

© 2011 Elsevier B.V. All rights reserved.

1. The imperative for ecological intensification ofagriculture – global considerations

The imperative to satisfy a growing demand for agricultural pro-duce is the key driver for agricultural intensification. Three globaltrends combine to drive this intensification: population growth;growing affluence and changing diets of populous countries suchas China and India; pressures on the area of arable land due to limits

∗ Corresponding author. Tel.: +61 7 3833 5733; fax: +61 7 3833 5505.E-mail address: Zvi.Hochman@csiro.au (Z. Hochman).

to expansion, competition from urbanisation and alternative usesto food production (e.g. biofuels).

The world’s population (6.8 billion in 2008) is projected to reach9.2 billion people (7.9–10.4 billion) by 2050 (U.N., 2009; Nelsonet al., 2010). In 2010 the total number of undernourished peoplein the world was estimated to be 925 million (FAO, 2010) whichis well above the target set by The World Food Summit’s Millen-nium Development Goal. In addition to producing more food, futurefood security will require allied approaches including reducing foodwaste, controlling population growth, liberalisation of trade andmore equitable distribution of food.

By 2050 the world’s average daily calorie demand per personcould rise by 11% over the 2003 level (FAO, 2006). This modest

1161-0301/$ – see front matter © 2011 Elsevier B.V. All rights reserved.doi:10.1016/j.eja.2011.11.003

Author's personal copy

110 Z. Hochman et al. / Europ. J. Agronomy 44 (2013) 109– 123

calorific increase is mainly due to expected changes in diet withincreasing wealth: a shift away from grains to lower calorie, highervalue foods such as fruit and vegetables and to livestock products.Meat consumption per person is projected to rise from 37 to 52 kgby 2050. These trends imply an added challenge as it requires moreresources to produce a calorie of fruits; vegetables or meat than acalorie of grains, especially if meat is to be raised on grains.

Around 1.5 billion hectare (ha) of arable land is available glob-ally. Agriculture faces competition for suitable land resources fromforests (800 million ha), nature reserves (200 million protected ha)and urbanisation (60 million ha). The potential to increase food andfibre production by expanding the area farmed is reduced by thiscompetition. It is estimated that by 2050 the amount of arable landwill expand by less than 5%. Consequently, 90% of the growth incrop production will need to come from higher yields per hectareand increased cropping intensity (from 84% in 2000 to 92% in2050) (Bruinsma, 2009; Fischer, 2009). The lack of suitable land foragricultural expansion is an important argument for agriculturalintensification. However, it largely negates the argument that agri-cultural intensification is sparing land for nature (Balmford et al.,2005; and references therein) or avoiding significant green housegas (GHG) emissions (Burney et al., 2010) as both arguments arebased on a counterfactual scenario in which the amount of landused by agriculture would have or will expand dramatically.

Past intensification has been characterised by more produc-tion from improved germ-plasm and more inputs. Intensificationwas based on more fertiliser, more pesticides, more irriga-tion, more intensive cropping, and mechanisation (Matson et al.,1997; Cassman, 1999). The imperative for ecologically basedland management arises from concerns about the negative con-sequences of agricultural intensification (Matson et al., 1997;Cassman, 1999; WBCSD, 2000). The ‘ecological’ imperative placesfurther demands on agriculture to reduce its dependence on non-renewable resources, to maintain soil fertility and biodiversity, tominimise off-site consequences such as soil erosion, pollution ofgroundwater and eutrophication of rivers and lakes and to reduceGHG emissions. Ecological intensification of Agriculture (EIA) canbe defined as: producing more food per unit resource use whileminimising the impact of food production on the environment. Thispaper will explore the prospects for EIA from the perspective ofAustralian agriculture. It will focus on emerging technologies andproduction systems that have the potential to increase agriculturaloutput per unit of resource use and minimise negative ecologicalimpacts.

2. Is ecological intensification of agriculture feasible?

Agricultural intensification has been going on since the tran-sition from hunting and gathering to agriculture and settlement7–10,000 years ago, but has gathered pace dramatically since the“Green Revolution” of the 1960s. The aggregate value of the world’sagricultural production has been growing at rates of 2.1–2.3% p.a.in the last 4 decades. To meet anticipated world food demand itwill need to continue growing at 1.5% to 2030 and at 0.9% to 2050(FAO, 2006; Bruinsma, 2009). Achieving these growth rates can-not be taken for granted as land and water resources are scarcerthan in the past and the potential for continued growth of yieldis more limited (Bruinsma, 2009). EIA demands that agriculturesatisfy the anticipated increased demand for food with minimalnegative environmental impacts. Is this feasible?

The first law of thermodynamics, an empirical law of physics,states that energy within an isolated system can neither be creatednor destroyed, it can only change form. In agriculture, as in nature,solar energy is transformed into food. This transformation requiresinputs of water and nutrients that are accessed from the soil.

However, agriculture is not a closed system; additional resourcessuch as labour and capital are required to change a natural systemto a managed agricultural system. When food or fibre leave the agri-cultural system, the system either becomes depleted or resourcesfrom outside the agricultural production system are required tomaintain a balance of inputs to assure a balanced and sustain-able production system. Although some inputs might be recycledfrom food (e.g. “night soil” in traditional agricultural systems) oracquired from the atmosphere (e.g. N2 fixation), agriculture is ulti-mately dependent on outside inputs and to the extent that theseinputs are non-renewable, there is a limit to the sustainability ofagriculture. In other words, sustainable agriculture can only be anaspiration or a relative goal and some trade-offs between food secu-rity and ecological imperatives are inevitable.

Concepts of eco-efficient agriculture were recently reviewedby Keating et al. (2010) who described eco-efficiency as multidi-mensional and influenced by multiple factors interacting in nonlinear and non additive ways. Citing De Wit (1992) they pointed outthat while the response to any single input (e.g. nitrogen fertiliser)is subject to the law of diminishing returns, “...most productionresources are used more efficiently with increasing yield level dueto further optimizing of growing conditions”. While there is a limiton the amount of scarce or non-renewable resources that can beused, it is at least theoretically feasible to simultaneously intensifyproduction and either reduce resource use or at least increase theefficiency with which resources are used. Hence, the EIA conceptdepends on identifying and reducing inefficient use of resourceswhile maintaining soil fertility and biodiversity and reducing off-site environmental consequences of agriculture.

3. Relevance of ecological intensification to Australianagriculture

Having described the imperatives for EIA, we turn our attentionto three questions about its feasibility in Australian agriculture: (1)Do the global drivers for EIA apply with equal force to Australianagriculture? (2) If they do, what attributes would we expect Aus-tralian EIA to have? (3) What technologies might be available toachieve EIA in Australia?

3.1. Australian agriculture and national food security

Australian agriculture is largely defined by its climate, the qual-ity of its soils, and its topography. It is commonly stated thatAustralia is the world’s driest inhabited continent with the largestvariability in rainfall. However, across the continent there is a largerange in total rainfall, its seasonal distribution and reliability; aswell as the suitability of its soils to support agricultural production.

Fifty three per cent or about 409 million hectares of the totalland area of Australia is dedicated to agriculture (ABS, 2010b). Inexcess of 80% of this land is used for extensive livestock graz-ing on rangelands which are dominated by native vegetation. Theremaining 20%, in the higher rainfall and irrigated areas, is usedfor more intensive livestock grazing of improved pastures andfor cropping. Approximately 6% of agricultural land in Australiais used for growing crops (26.1 M ha), the majority of which israinfed (ABS, 2003/2004 survey). Only 0.6% of agricultural land(2.6 M ha) is used for irrigated agriculture, though this produces23% of Australia’s agricultural production while consuming 65%of its blue-water (water in aquifers, lakes, and dams) resources.From an EIA perspective it is noteworthy that since European set-tlement around 13 per cent of Australia’s original vegetation hasbeen cleared (Beeton et al., 2006) and that compared to MidwesternAmerica and Europe, only one tenth to half the amount of fertiliserand agri-chemicals are used per hectare of cropland (Price, 2006).

Author's personal copy

Z. Hochman et al. / Europ. J. Agronomy 44 (2013) 109– 123 111

More detailed descriptions of Australian agriculture can be found inSquires and Tow (1991), NLWRA (2001) and Freebairn et al. (2006).We expect that EIA in Australia will apply primarily to the croppingand crop–livestock sectors and will therefore limit the scope of thispaper to these industries.

In 2009, 409 million hectares of agricultural land in Australiasupported 240,000 farmers and 397,000 employees and con-tributed more than $27 billion to the gross domestic product, ofwhich $20 billion (74%) came from export income (ABS, 2010b).If $7b worth of produce was required to feed Australia’s domes-tic population of 18m people, then $27b worth of produce couldhave fed 69.4 million people at Australia’s food consumption levels.While it required about 5.9 ha to feed one person, one unit of agri-cultural labour (counting farmers plus their employees) annuallyfeeds about 109 people. Thus a defining characteristic of Australianagriculture is that it is predominantly a low input, low output sys-tem, where labour efficiency is extremely high.

The Australian population was 21.0 million in 2007 and is pro-jected to grow to between 30.9 and 42.5 million by 2050 dependingon immigration intake (ABS, 2010a). Providing current levels ofproduction are maintained, the current agricultural production inAustralia is more than sufficient to feed the projected populationto 2050 and beyond. It is therefore more likely that economicforces, rather than concern for national food security, will con-tinue to drive agricultural intensification in Australia. This raises thequestion of whether these forces will continue to drive increasingefficiency and productivity in agriculture. Recent trends (estimatedafter controlling for the effects of deteriorating climate condi-tions) are not encouraging. In cropping and mixed crop–livestockfarms Australia-wide, productivity increases declined from 1.95%per annum in the period 1977–1999 to just 0.4% per annum over theperiod 1999–2007 (Hughes et al., 2011). This productivity growthrate is below the previously mentioned 1.5% per annum target forworld growth to 2030.

3.2. Prospects for expansion of agricultural land use in Australia

There has been a decline in the overall area of agricultural activ-ity in recent years (e.g. from 456 million ha in 2000 to 409 millionha in 2009). Non agricultural land area consists of unoccupied land(mainly desert in western and central Australia), Aboriginal landreserves, forests, mining leases, national parks and urban areas(ABS, 2006, 2010a).

It is likely that with competition for land use from urbanisation,forestry, conservation, mining and other activities the area avail-able for agricultural production will be less in 2050 than it is today.As with other developed economies, agricultural activity will takeplace on less land and any future increases in agricultural produc-tion will need to come from more intensive land use (e.g. changingland use from pasture to cropping) and from greater productivityper hectare. This situation is further constrained by deterioratingsoil fertility, erosion, acidification and dryland salinity (NLWRA,2001).

3.3. Scarcity of resources required for agricultural production

Ecological intensification in Australia will require efficient useof scarce resources such as water (both for dryland and irrigatedagriculture) fertilisers and agri-chemicals. Efficient use of theseresources is made more challenging by a climate that is both vari-able and changing.

3.3.1. Climate change mitigation and adaptationClimate change has been described as one of the big drivers of

change in Australian agriculture in the future, leading to changes inrainfall patterns, temperatures, frost risk, heat stress and extreme

weather events. In combination, these will lead to effects on plantgrowth, natural resources and animal production. In the long term,farmers will adjust their land management practices to suit thechanged climatic conditions or risk further land degradation andthe loss of new production opportunities (McKeon et al., 2004).Farmers will need to adapt by adjusting practices, processes andcapital in response to real or perceived threats. Adapting to climatechange is also likely to require responses in the decision envi-ronment, such as changes in social and institutional structures, oraltered technical options, to allow the capacity for adaptive optionsto become a reality (Howden et al., 2007).

Climate change is projected to significantly affect the productivepotential in many of Australia’s important agricultural regions. Esti-mates of annual warming and precipitation change to Australia’sclimate towards 2050 are somewhat dependent on the modelsused and the scenario chosen (CSIRO, 2007). Using marker sce-nario A1FI representing a fossil fuel intensive future (Nebojsa andSwart, 2002), the range of annual warming over Australia by 2050is 1.5–2.8 ◦C, with a best estimate of 2.2 ◦C. The range of annual pre-cipitation change is −20% to +10% in central, eastern and northernareas, with a best estimate of little change in the far north grad-ing to around a 7.5% decrease elsewhere. The range of change insouthern areas is from a 20% decrease to little change, with a bestestimate of around a 7.5% decrease. The projected decreases in thesouth-west in winter and spring range up to 30% (CSIRO, 2007).Stream-flows in major river systems feeding irrigation districts arelikely to experience even greater percentage reductions, due to thenon-linear relationship between rainfall and runoff. The MurrayDarling Basin Sustainable Yields Project (CSIRO, 2007) suggesteda 9–14% reduction in water diversions for irrigation by 2030. A16–25% reduction in average Murray Darling stream-flows by 2050has also been predicted (Pittock, 2003; Christensen et al., 2007;Hennessy et al., 2004). The distribution, abundance and responseto current control measures of many agricultural pests, diseasesand weeds are strongly influenced by climatic factors and they aretherefore likely to respond to climate change in varied and largelyunpredictable ways (Chakraborty and Datta, 2003, Howden et al.,2010).

Near-term changes in climate (e.g. to 2030) are strongly affectedby inertia in the climate system due to past GHG emissions, whereasclimate changes to 2050 and beyond are more dependent on theparticular pattern of GHG emissions that will occur in the future.In 2006 agriculture was responsible for 88 Mt CO2-e (carbon diox-ide equivalents) or around 16% of Australia’s GHG emissions. Thiscontrasts with other developed countries such as the US (5.5%) andthe EU (10%) on the one hand and NZ (50%) on the other. Globallyit is unsustainable to adapt to a changing climate without takingsignificant steps to mitigate further climate change. Australian agri-culture can contribute by reducing emissions and by sequesteringof organic matter in soils and farm tree plantings. While some emis-sion savings can be achieved through more efficient practices (e.g.controlled traffic; Tullberg, 2010) significant mitigation will comeat a cost. The extent to which farmers contribute to mitigation willmostly depend on future policy settings.

3.3.2. Water use efficiency in dryland agricultureAgricultural water use is largely dependent on rainfall and

is consequently impacted by reduced water availability due todrought. Australia’s dryland farmers face extremely variable rain-fall (Nicholls, 2006) and thus extreme variation in potential andactual grain production (NLWRA, 2001). This extreme variability inannual and seasonal rainfall makes it difficult to efficiently utilisethis scarce resource. The efficiency of Australian farmers is there-fore best judged relative to their water-limited potential yields.

The concept of water use efficiency (WUE) was developed inAustralia around cereal grain production. French and Schultz (1984)

Author's personal copy

112 Z. Hochman et al. / Europ. J. Agronomy 44 (2013) 109– 123

pragmatically expressed water use efficiency (WUE) as the ratioof grain yield (kg/ha) to crop water use by evapotranspiration(mm). This concept has been applied to other crops such as canola(Robertson and Kirkegaard, 2005) and to pastures (Bolger andTurner, 1999). A framework has also been developed for apply-ing the WUE concept to the analysis of crop rotations and ofcrop–livestock systems (Moore et al., 2011). Improved WUE canbe achieved through synergistic deployment of multiple man-agement strategies both in-crop and pre-crop and by matchingcropping system management to the environment and the geno-type (Kirkegaard and Hunt, 2010).

Across Australia there is a large variation in crop WUE. Beestonet al. (2005) aggregated WUE over agro-ecological zones, andshowed that yields varied from 36% of potential in North West NSW– South West Queensland to 61% of potential in Bordertown SA –Wimmera Victoria. They calculated that achieving a benchmark of70% of potential would on average increase grain production byabout 40% or 14 million tonnes per annum. Hochman et al. (2009a)showed that reaching this benchmark is possible from an analysisof crop yields achieved by 334 elite Australian farmers over a 4-year period. Thus the gap between current low average WUE andthe attainable 70% of potential represents a huge opportunity forincreasing the production and water use efficiency of grain produc-tion in Australia. The challenge is to bridge this gap while meetingthe EIA goals including reduced use of fertiliser inputs per unit ofoutput.

3.3.3. Water for irrigationOf the 6.989 × 109 m3 of water used for agricultural production

in 2007–2008, dairy farming had the highest water use (19% of allirrigation water used by the agriculture industry), pastures (exclud-ing those for dairy) followed with 16% and cotton growing with 15%.The activities of sugar growing, grain production and livestock rais-ing each used about a one-tenth share of the total water consumed.Horticulture (fruit, grape and vegetable growing) used about 15%yet it was able to generate about half of Australia’s gross valueof irrigated agricultural production. Rice and cotton crops are themost water intensive requiring average irrigation water applica-tions per crop of 1300 and 600 mm respectively, with other sectorsranging from less than 300 mm on cereals (excluding rice) to anaverage of about 400–500 mm on pastures, sugar and horticulturalcrops. In 2006/2007, water productivity of irrigated crops variedwidely from 5.9 $/m3 for vegetables; 5.2 $/m3 for fruits and nuts;2.1 $/m3 for rice; to 1.6 $/m3 for cotton. It is not surprising that dur-ing the “millennium drought” (between 2001and 2008) reducedwater allocations resulted in dramatically reduced planting of irri-gated rice and cotton and that production of these crops fell by 99%and 84% respectively (ABS, 2010b).

With water supplies expected to become less secure under cli-mate change (CSIRO, 2008), there is considerable debate aboutwater allocation in Australia. Some of the questions being askedinclude: ‘how much water should be allocated for environmen-tal flows‘; ‘is agriculture the most essential and efficient wayto use such large volumes of Australia’s limited water supply?’;‘what commodities should be priorities for irrigation?’; ‘how shouldwater use be regulated?’ and ‘can market forces be left to resolvethese issues?’ While irrigated agriculture is currently the most pro-ductive agricultural land use, it is clear that future intensification ofagriculture will need to contend with less rather than more wateravailable for irrigation.

3.3.4. Dependence of Australian agriculture on non-renewablefertilisers

Harvested crops remove nitrogen, phosphorus and other nutri-ents from agricultural soils and globally the main source ofreplenishing these nutrients is by adding fertilisers (Vitousek et al.,

2009). Historically in Australia, nitrogen derived from soil organicmatter and legume residues contributed more to crop nitrogensupply than in most other major grain producing countries. How-ever this situation has changed. In 2005, nitrogen fertiliser use inAustralia was 1000 kt N (701 kt for cereals, 55 kt for oilseeds andpulses, and 76 kt for pastures) or 2.5 times the amount used in 1990(Source Fertiliser Industry Federation of Australia) representing themajor source of N for crops on mixed farms. The rapid growth inuse of N fertiliser in south eastern Australia has been attributedto the greater and more reliable responses by cereals when grownafter a break crop and to the decreasing soil N fertility followingreduced areas sown to legume pastures in mixed farm systems(Angus, 2001).

In Australia most crops and animal products are exported over-seas or to urban centres. The nutrients removed off the farm withthese products cannot be readily recycled. One exception is the useof manure from feedlots as a fertiliser in grain production systems.For some nutrients (P, Cu, Zn, and Mo), soil reserves in Australiancropping systems have increased due to past fertiliser applicationwhile for other nutrients such as potassium (K) and sulphur (S),exports in grain have not been matched by inputs (Chen et al.,2009). Sustaining crop production requires that these nutrients bereplaced either with fertilisers or through biological processes likenitrogen fixation or by recycling organic animal wastes or otherwaste products as long as they can be efficiently purified and trans-ported.

Nitrogen (N) fertiliser is produced from natural gas, a non-renewable resource and is thus subject to energy-market relatedfluctuations in supply and price. Efficient use of N by crops resultsin higher yields, increased protein in grain and increased return ofstubble cover and maintenance of soil organic matter. Inefficientuse of N by crops and pastures can result in increased emissionsof potent greenhouse gases including nitrous oxide (N2O) and inloss of N from the root zone. These losses lead to subsequent acid-ification of soils and to nitrate contamination of water resources.Inefficient use of N fertiliser is clearly inconsistent with conceptsof agricultural sustainability and ecological efficiency.

Most Australian soils are naturally P deficient and despite inputsof P over several decades most soils used for mixed farming areconsidered to be below target for economic production (NLWRA,2001). Further intensification of agriculture would require farm-ers to increase soil P inputs and to increase demand for fertiliserP. Mined rock phosphate is a finite resource and it has been esti-mated that current global P reserves, that are economic to mine,will be depleted in 50–100 years. A period of increasing scarcityand rising prices is likely to precede this timeframe (Cordell et al.,2009; Cornish, 2010). Concerns about efficient use of phosphorushave also been expressed in response to loss of phosphorus fromagricultural lands and its association with eutrophication and toxicalgal blooms in water bodies. This too is likely to be exacerbatedby excessive and inefficient use of P fertilisers. There are prospectsfor improving the efficiency of P fertilisers via new P fertilisers, byimproved placement of P fertiliser and through systems that accessthe pool of slowly available soil P making better use of the residualP already in the soil (Cornish, 2009).

3.4. Impacts of cropping practices on weeds and pests

Insecticide resistance first occurred in the early 1990s in north-eastern Australia when Helicoverpa armidgera developed high levelresistance to all insecticide groups available at the time (Syntheticpyrethroids, organophosphates, carbamates and endosulfan). Thiswas exacerbated by the non-selectivity of most of these insecti-cides which decimated the beneficial insect populations (Brier et al.,2008). Similarly, widespread resistance to most herbicide groups,including glyphosate, in economically important weeds mirrored

Author's personal copy

Z. Hochman et al. / Europ. J. Agronomy 44 (2013) 109– 123 113

the decline of pastures and regular break crops and the replacementof soil disturbance with chemical fallowing in Australian croppingsystems (Kirkegaard et al., 2011).

Insecticide and herbicide resistance developed due to unsus-tainable use of agri-chemicals. The response to herbicide resistancewas to develop and adopt integrated weed management (IWM)principles (Preston, 2010). Managing weed seed banks requiresa diversity of options including sound agronomy, competitivecrops, green/brown manures, herbicide rotation, weed seed har-vesting and destruction and strategic tillage (Kirkegaard et al.,2011). Recognition of insecticide resistance triggered integratedpest management (IPM) strategies including new, more selectiveinsecticides and biopesticides for caterpillar pests, increased recog-nition of the significant role of beneficial insects, the developmentand validation of sampling techniques and threshold models thathave raised the action threshold for Helicoverpa spp. Continuedresearch and development effort is required to develop multi-pestIPM and area wide management (AWM) strategies based on usingan understanding of a pest’s ecology, biology and host range tomanage its abundance across a region. (Brier et al., 2008, and ref-erences therein).

Development and realisation of IWM, IPM and AWM requiredstrong links between researchers, extension personnel, growers,consultants and industry associations. Additionally, adoption ofIWM was shown to be associated with the herbicide resistance sta-tus of a farm (Llewellyn et al. 2004). The incentive to adopt IWM isreduced by farmers’ expectation that new herbicides with differentmodes of action will become available, despite the fact that noneare known to be in late stage development for major weeds of crops(Llewellyn et al., 2002, 2004). Similarly Brier et al. (2008) found that75% of consultants attending IPM courses were not able to immedi-ately recognise 50% of the moist common insects in summer pulses.These are knowledge-intensive technologies and continued insti-tutional investment in strong linkages between stakeholders andin education of farmers and advisers will be required to fully realiseeffective IWM, IPM and AWM in Australia’s cropping systems.

3.5. Impacts of Australian agriculture on the environment

Since European settlement of Australia around 13% of the orig-inal vegetation has been cleared for agricultural production. Thecondition of the remaining 87% is variable and many ecologicalcommunities are in decline and highly fragmented. The compo-nents of many ecosystems, especially the understorey in forestsand woodlands, have been severely disrupted by overgrazing indry years on low-productivity pastoral properties. These changes invegetation condition and extent have implications for biodiversity.In ecological communities that have already been extensively mod-ified, such as in the wheat–sheep belt and semi-arid areas, manynative species have suffered a significant decline in numbers andrange and even extinction. More than half of the ecosystems inthe Murray Darling Basin are under severe pressure and furthersignificant declines are likely (Beeton et al., 2006 and referencestherein).

Compared with erosion under natural conditions, soil erosionrates have doubled in pasture lands and increased fivefold inimproved pastures. Sheet wash erosion from hill-slopes has trebled(NLWRA, 2001). After many years of acidification under legume-based pastures, such as clovers, and related cropping rotations,approximately 50 million hectares of Australia’s agricultural land(around half the total area) have a surface soil pH value less than 5.5.Analysis of such systems has attributed between 40% and 51% of thisacidification to nitrate losses from the plant-soil system, 34–43%to accumulation of organic matter in the system and 12–15% toexport of organic anions in products (e.g. meat and wool) and wasteproducts. The rate of acidification in these grazing systems was

equivalent to 173–211 kg CaCO3 ha−1 year−1 (Helyar and Porter,1989).

In many agricultural landscapes excess rainfall (i.e. rainfall notcaptured by crops and pastures) drains beyond the reach of rootsand carries with it soluble salts from the soil. These salts are thentransported elsewhere in the landscape, and eventually emergeeither in waterways or as dryland salinity. It has been estimatedthat about 2 million ha on 20,000 farms across Australia showedsome signs of salinity (ABS, 2002).

Irrigation poses the greatest risks to groundwater resources andto aquatic ecosystems resulting in polluted runoff, and changes toriver flow regimes (Hart, 2004). Excess drainage and runoff fromintensive agriculture also contributes to N and P contamination ofgroundwater and of rivers that flow to the ocean (Beeton et al.,2006). Case studies from Australia and New Zealand showed thatoptimizing irrigation efficiency mitigated N and P contaminationof groundwater. A shift from border check irrigation to a centrepivot system completely eliminated surface runoff in one trial. Inthe Goulburn Broken catchment (270,000 ha) simple actions takento reduced P loads from irrigation runoff (withholding of irrigationfor at least 3 days after application of fertiliser and reusing irriga-tion water) achieved an 82% reduction in average annual P loadsbetween 1996 and 2007(Wilcock et al., 2011).

Over the past three decades successive Australian governmentshave responded to a growing tension between conservation andproduction in agricultural landscapes by developing a range ofpolicies and investment strategies to improve sustainability ofagricultural landscapes. Audits of these programs have producedlittle evidence that programs are producing the intended outcomes(Hajkowicz, 2009).

A study of options for improving the conservation of naturalresources on three mixed cropping-livestock enterprises in east-ern Australia showed that in all cases applying conservation basedscenarios resulted in reduced agricultural production and incurredsubstantial opportunity income losses with limited options to off-set these with changed farming practices. This study showed thatunder current policy settings much of the cost of conservation isexpected to be borne by farmers (House et al., 2008).

A more comprehensive vision for natural resource policies andprograms would abandon the most degraded and unproductiveparts of farms and landscapes and retire large tracts of land alongwaterways and watersheds back into native vegetation or otherperennial woody species. This would stabilise the landscape againsterosion and dryland salinity and create green corridors to betterconnect isolated nature reserves (Hamblin, 2009).

4. The desired attributes of an ecological intensification ofagriculture system

We propose that increased production per hectare will needto be achieved in ways that: sustain the natural resource base;use non-renewable resources such as fertilisers as efficiently aspossible and reduce the rate of global warming per hectare ofagricultural land while adapting to the inevitable warming that isalready projected under all climate change scenarios to 2050. Inter-relationships with biodiversity impacts and social values will alsoneed to be considered.

A realistic aspiration for EIA is to increase food and fibre pro-duction through a more efficient use of limited and non-renewableresources by better deployment of technologies and of human andgenetic resources. This will require increased precision in the use ofinputs and reduction in inefficiencies and losses. It will also requirea more holistic view of farming, going beyond efficiencies of sin-gle inputs into a single field in a single season to consideration ofefficiencies of whole systems over decades. We also recognise that

Author's personal copy

114 Z. Hochman et al. / Europ. J. Agronomy 44 (2013) 109– 123

agriculture is a human activity and recognise the essential role thatagriculture must continue to have in sustaining inland rural andregional communities.

In view of considerations discussed so far, we propose nine spe-cific attributes that are desirable in an EIA system:

(1) Increased agricultural production to meet global demand forfood, fibre and protein.

(2) Efficient use of limited resources such as water, fertilisers, her-bicides and pesticides.

(3) Minimal impacts of agriculture on global warming by reducingemissions of methane, carbon dioxide and nitrous oxides, whileadapting agriculture to inevitable global change.

(4) Minimal negative on-site impacts of agriculture on soil acidifi-cation, compaction and erosion.

(5) Minimal negative off-site impacts of agriculture on watertables, pollution of groundwater and dryland salinity.

(6) Minimal risk and maximum resilience of agriculture in responseto climate variability, fluctuating markets and extreme weatherevents.

(7) Preservation of biodiversity in agriculture through diversityof crop and pasture species and maintenance of healthy soilmicrobial activity.

(8) Preservation of biodiversity in nature by integrating farm andnature lands within the landscape and by sparing land fornature.

(9) Positive social outcomes reflected in: farmer incomes, employ-ment conditions for rural workers, viable rural communities,decentralisation, equity throughout the supply chain, and inter-generational equity.

5. Prospects for implementing ecological intensification ofagriculture in Australia?

The arguments for world and Australian agriculture to progresstowards EIA are readily made, given the global demand drivers forfood and for conservation of natural and non-renewable resources.Where possible it is important to identify technologies that willdeliver more food with less resources and lower negative impactson the environment. However, such outcomes are likely to be fewand we must also consider the next best option which is to ensurethat additional resources are used sparingly and efficiently so thatboth resource use and environmental impacts are reduced per unitof food produced. A focus on efficient use of fertiliser nitrogen andwater is justified for Australian cropping and crop–livestock sys-tems because in addition to preserving a non-renewable resource(nitrogen) and maximizing the production value of a limited andcontested resource (water), it is the inefficient use of soil nitrogen,combined with the inefficient use of water that result in negativeenvironmental impacts such as contamination of groundwater andrivers, acidification of soils and dryland salinity. EIA is not entirelynew to Australian agriculture. Carberry et al. (2010) outlined a num-ber of technologies which influenced the productivity of Australianfarms either by reducing the yield gap (e.g. integrated pest andweed management; use of break crop; controlled traffic; emer-gence of farmer groups and farm consultants) or improving yieldpotential at similar levels of input (e.g. breeding and conservationagriculture) or by achieving similar production levels with reducedinputs (e.g. through enterprise mix, fallow management, and fer-tiliser management). The question now is: what are the innovationsand resultant on-farm technologies which will lead to future eco-logically efficient production increases?

5.1. Efficiency frontier framework

Economic analysis of the performance of agricultural enterprisesover recent decades can quantify the past drivers of productivitygrowth. For any enterprise and region, production functions canbe established which generally show farm outputs increasing ata diminishing rate to increasing inputs (Dillon, 1977). By survey-ing annual farm performance, a sample of farms in a region canbe mapped relative to the outermost production frontier set bycurrently available technologies and assessed as to how produc-tivity growth has been achieved (Byerlee, 1992; O’Donnell, 2010;Hughes et al., 2011). A recent analysis was made of total factor pro-ductivity (TFP) in Australia’s dryland cropping industry over thepast 30 years (Hughes et al., 2011). It suggested that lifting pro-duction potential (technical change) has been the primary driverof productivity growth, with correspondingly little narrowing ofthe performance gap between the best and poorest farm perform-ers (technical efficiency). Surprisingly, this study suggested littleimpacts from improved efficiency due to changes in scale or mix inAustralian cropping industries.

Keating et al. (2010) adopted a similar trade-off relation-ship to formulate an efficiency frontier framework against whichpathways for productivity increases are proposed. Risk is intro-duced as critical in influencing the motivation to progress anypathway towards increased productivity. In reviewing innova-tions potentially leading to productivity growth in Australiandryland agriculture, Carberry et al. (2010) employed the return-risk framework to nominate the technologies likely to generatenew production efficiencies. Technologies could remove systeminefficiencies (e.g. removal of soil biotic constraints), increase theefficiency of resource use (e.g. precision agriculture) or generatenew yield potentials (e.g. genetic engineering).

The prospects for increasing farm productivity in Australiathrough implementation of EIA will depend on an assessment ofthe current performance of farm enterprises relative to their poten-tial productivity and on the availability of ready-to-be adoptedtechnologies. We now turn our attention to benchmarking currentfarm performance and to nitrogen use efficiency. Benchmarking isimportant because it has implications for assessing the potential tobridge the gap between current and potential yields. Nitrogen useefficiency similarly has implications for identifying the potential touse non-renewable farm inputs more efficiently.

5.2. Benchmarking current farm performance

The econometric analysis of Hughes et al. (2011) tracked theproduction performance of Australian farms over 30 years rela-tive to a production frontier drawn from the best performing farmsin each survey. Yet, they did not consider how close this realisedannual change in the production frontier has been to the environ-mental potential which could be achieved given the climate, soiland management resources available to these farmers.

Using simulation modelling to determine the environmentalpotential, Hochman et al. (2009a) analysed the performance of334 commercial wheat crops in Australia based on their wateruse efficiency (WUE, kg grain ha–1 mm–1). They found the aver-age performance of these farms was within 90% of the averagesimulated WUE when input resources were constrained to actualcrop management. However, when management and inputs otherthan water were unconstrained in the simulations, to represent theenvironmental potential which was accessible to these crops, theachieved average WUE was 71% of potential. This assessment ofaverage performance leaves the question of how close any indi-vidual crop is to the production frontier set by the environment itexperiences.

Author's personal copy

Z. Hochman et al. / Europ. J. Agronomy 44 (2013) 109– 123 115

Fig. 1. (a) Nitrogen use efficiency of 209 Australian dryland wheat farmers’ fields(Hochman et al., 2009a). N used is the sum of crop N uptake and N lost to the croproot zone. The solid line represents the linear regression line through the origin(Grain yield (kg) = 19.7 × N used (kg); r2 = 0.51) while the dashed line (fitted by eye)suggests an N-use efficiency frontier. (b) The normalised input–output relationshiprelative to an assumed response function for 334 wheat crops grown in Australia(Hochman et al., 2009a). The solid line (—) signifies a representative N response curveon which the dotted line (. . .) specifies the point where simulated constrained yieldis half of the predicted unconstrained yield. The two dashed lines (- - -) delineatefour categories of crop response to N inputs.

Fig. 1a and b attempts to map the 334 wheat crops of Hochmanet al. (2009a) onto production frontiers within output-input rela-tionships. Fig. 1a plots observed crops yields versus nitrogen (N)used by these crops. This production frontier is explored furtherin Section 5.3 below. These crops were grown across a wide rangeof environments and so cannot easily be compared directly, giventhat their environmental potential and responsiveness to inputswill differ markedly. Therefore, in Fig. 1b, these same data aretransformed to represent a normalised input–output relationshiprelative to an assumed response function – the generalised Nresponse curve depicted by Lawlor (2002) is normalised and usedin Fig. 1b. The normalised level of N input for each of the 334crops is back-calculated based on the relative difference betweenthe simulated yields with constrained and unconstrained inputs. Inessence, this normalisation attempts to estimate the shortfall in Ninput of the actual crop relative to the N input required to reachthe environmental yield potential. To take two examples: firstly ifthe simulated crop yield using actual crop N supply (constrained)equals the simulated yield with unlimited N (unconstrained), thenthe relative input level equals 1.0; in the second example, if the sim-ulated crop yield using actual crop N supply is half the simulated

yield with unlimited N, then the relative input level equals 0.17(Fig. 1b) as the N response function is assumed to capture the dimin-ishing response to increases in N inputs. The relative yield term inFig. 1b is calculated as the actual harvested crop yield divided bythe simulated (constrained) yield multiplied by the assumed yieldresponse to N. Values greater than 1.0 were constrained to a valueof 1.0.

The analysis represented in Fig. 1b suggests that 64% of thesecrops attained an actual yield which was within 80% of the expectedyield as simulated using the actual level of N input for each crop.Further disaggregation of the results revealed four categories:

Crops with high N input that achieved close to their expectedyield – 43% of crops were fertilised at rates which enabled yields toreach greater than 80% of their environmental potential and, at thesame time, attained greater than 80% of simulated yield.

Crops with high N input but their attained yield was less thanwhat could be expected – 26% of crops were fertilised at rates whichenabled greater than 80% potential but actual yields were below80% of simulated yield.

Crops with lower N inputs that achieved close to their expectedyield – 21% of crops were within 80% of the simulated yield but atN rates less than required for 80% potential yield; and

Crops with lower N inputs and lower than expected yields –10% of crops yielded less than 80% of the simulated yield and werefertilised at rates less than 80% required to reach the environmentalpotential.

This disaggregation within an assumed production function sug-gests that 69% of these wheat crops had sufficient N nutrition toattain close to the environmental potential for the site and sea-son experienced by the crop. In contrast, 31% of crops had lowerN status and so were restricted from attaining the environmen-tal potential. The 64% of crops which achieved yields close towhat could be expected in the season experienced and under theimposed management conditions is the good news from this anal-ysis. Many farmers are managing their crops with high technicalefficiency. In contrast, the 36% of crops which underperformed rep-resent inefficiency in the production system but also an opportunityfor significant production improvements through farmers simplyperforming better with current technologies.

This simple analysis of a production frontier provides a snapshotbenchmark of the performance of Australian agriculture. It justi-fies further exploration of this approach. Crop performance couldbe assessed against resource inputs other than nitrogen and forcropping sequences where under-utilised resources in one seasoncould be well used in the next. Keating et al. (2010) argue that areturn-risk frontier is critical for considering systems performance.However, the crop performance data of Hochman et al. (2009a) forwheat, similar data of Lisson et al. (2007) for canola and Carberryet al. (2009) for a range of crops, are rare in having crop man-agement and resource supply explicitly quantified for every crop.Access to such datasets and extrapolation of results from individualcrops to sequences and farming regions will be the next challenge.

5.3. Nitrogen use efficiency

Nitrogen fertiliser is used with highly variable levels ofefficiency. For rainfed wheat, McDonald (1989) reported that agro-nomic efficiency ranged from −4 to 43 kg grain yield/kg N applied,with apparent recovery ranging from 6% to 78%. Angus (2001)estimated that, over a period of 11 years up to 1999, the effi-ciency of N use (apparent recovery of applied fertiliser N) hadincreased from 18% to 32%. A more recent estimate of agro-nomic N-use efficiency (NUE) of cereal crops showed an average of8 kg grain yield/kg N applied, with apparent recovery of 54% (Ladhaet al., 2005). These figures compare unfavourably (even after allow-ing for different N requirements of wheat and maize crops) with

Author's personal copy

116 Z. Hochman et al. / Europ. J. Agronomy 44 (2013) 109– 123

data from US grown maize which achieved 57 kg grain yield/kg Napplied (Cassman et al., 2002). The contrast in these efficiency val-ues suggests the potential for Australian farmers to make significantimprovements in fertiliser use efficiency. However it may simplyreflect the greater dependency of the US crops on fertiliser N asthese figures only consider the response to fertiliser which is alwayssteeper when indigenous soil mineral N is lower.

Angus (2001) suggested that inefficient use of N is largely dueto lack of balance between N supply and N demand by the crop. Heproposed that an optimal strategy to match N supply to N demandinvolves using nitrogen from retained crop residues and soil organicmatter to supply sufficient N for a low crop demand and to apply fer-tiliser N to supplement the demand for optimum yield and proteinas the season progresses.

Matson et al. (1998) suggested that a knowledge-intensiveapproach to fertiliser management can substitute for higher lev-els of inputs, saving farmers money and reducing environmentalcosts. In the previously mentioned WUE study, farmers who wereusing the decision support system Yield Prophet® (Hochman et al.,2009b) varied widely in their N fertiliser strategies (Hochman et al.,2009a). Pre-crop soil nitrate-N ranged from 32 to 588 kg N/ha(mean = 124 kg N/ha); nitrogen fertiliser applied either before or atsowing ranged from 0 to 146 kg N/ha (mean = 18 kg N/ha); and 127crops were fertilised in-crop (top dressed) with an average appli-cation rate of 37 kg N/ha. Total mineral nitrogen supply to crops(soil nitrate-N plus fertiliser added) ranged from 38 to 592 kg N/ha(mean = 154 kg N/ha). A sub-sample of 209 of the fields (where therequisite data were available) in this study achieved an averagenitrogen use efficiency (NUE, the efficiency with which the plantuses each unit of N, whether added as fertiliser, removed fromthe soil by plant uptake or lost to the crop root zone, to producegrain) of 19.7 kg of grain per kg N used (the solid line in Fig. 1a).The wide scatter of NUE values reflects the wide range of N sup-ply to the crops and the wide range of yields achieved. However,the data also suggest an NUE frontier indicated by the dashed linewhich was fitted by eye to envelop the data. Yield response to thefirst 70 kg/ha N used along this frontier is quite steep at about 50 kggrain per kg of N, yet as N use exceeds 70 kg/ha, the frontier sloperemains steady at about 20 kg grain per kg of N used. This NUE fron-tier represents those fields in which N supply most closely matchedthe crops’ N demand. Compared with the frontier, a vast majority ofthe crops in this study were relatively inefficient in their utilisationof the available nitrogen. This is not surprising as the aver-age nitrogen supply to these crops (154 kg N/ha) was well abovethe amount of nitrogen required for the average yield (2.0 t/ha)achieved.

In the same study, simulated scenarios suggested that a strat-egy of matching N supply to N demand by adding 50 kg N/ha anytime between sowing and anthesis when soil N level fell below50 kg N/ha, increased average yields by 10% and WUE by 28%(Hochman et al., 2009a). Hence, while some farmers are clearlyapplying excessive nitrogen, others are not providing enough. Ina highly variable environment with the relatively high cost ofnitrogenous fertilisers, risk-averse farmers are reluctant to supplycrops with sufficient fertiliser unless they feel confident of a goodreturn on investment at harvest.

In more intensive industries such as sugarcane production,where the relative cost of nitrogen inputs is low, there is a historyof high N usage associated with N contamination of surface andground waters. For sugarcane production, this practice has likelyimpacts on the ecosystems of the Great Barrier Reef World Her-itage Area. In 11 experiments comparing a nitrogen replacementstrategy with conventional management, cumulative sugar yieldswere maintained or increased while average N applications were35% lower and N lost to the environment was estimated to be about50% lower (Thorburn et al., 2011 and references therein).

5.4. Innovations with potential to contribute to ecologicalintensification of agriculture in Australia – case studies

The prospects for implementing EIA, whether by bridging yieldgaps, by improving WUE or NUE, or by moving to new efficiencyfrontiers, require the adoption of new technologies or innovations.Carberry et al. (2010) nominated a range of technologies whichwill likely lead to increases in production and/or resource use effi-ciency in Australian agriculture. Here, we explore briefly four ofthese emerging innovations that may move Australian agriculturetowards an EIA paradigm. The innovations explored are: climaterisk management; precision agriculture and variable rate tech-nologies; closer integration of crop and livestock production; anddeficit irrigation (leading to extensification of agriculture) whichmay reduce productivity per hectare but increase productivity ofirrigated water. These case studies are not meant to be compre-hensive. They were chosen because they offer different pathwaysand thus illustrate the likely case that EIA will be achieved throughmany small steps rather than through a single solution.

5.4.1. Climate risk managementWith both dryland and irrigated agriculture depending on sea-

sonal rainfall that is amongst the most variable in the world, themost enticing innovations demanded by Australian farmers are reli-able multi-week and seasonal climate forecasts, as well as toolsand skills in managing for climate variability. The ability to flexi-bly adjust investments in farm enterprises in response to reliableclimate forecasts would enable farmers to take full advantage ofthe limited number of good seasons and avoid the risks associatedwith seasons which ultimately turn out poorly. Understandably,Australia leads the world in searching for useable seasonal climateforecasts in agriculture (Hammer et al., 2000; Ash et al., 2007) andtheir deployment in decision support is being actively progressed(Hochman et al., 2009b).

The Australian Bureau of Meteorology currently provides sea-sonal outlooks across Australia every month. These are generalstatements about the probability of rainfall or temperature exceed-ing the long-term average over a 3-month period. The outlooksare based on historical statistical relationships between Australianrainfall or temperature and sea surface temperatures in the tropicalPacific and Indian Oceans (Drosdowski and Chambers, 2001). Addi-tional information including the probabilities of seasonal rainfallexceeding given totals (e.g. chance of receiving at least 100 mm),and the consistency of these forecasts is available through the“Water and the Land” (WATL) website. Progress in seasonal fore-casting is expected from continuing development of the PredictiveOcean Atmosphere Model for Australia (POAMA) a dynamic com-puter model of the climate system (Hudson et al., 2011). In recentyears the Bureau has published outlooks based on POAMA’s fore-casts of the NINO3.4 index that is closely related to Australianrainfall (Wang and Hendon, 2007) and of the Indian Ocean Dipole(IOD) that modulates seasonal rainfall in IOD positive and IOD neg-ative years (Saji et al., 1999). Experimental rainfall forecasts overmulti-week, monthly and seasonal timescales have also been tri-alled.

Progress in seasonal forecast skill is likely to parallel theimprovement of short-term weather forecast skill over the last fewdecades. Since 1980, weather forecasts have increased their leadtime at a fixed level of skill by about 1 day per decade for thenorthern hemisphere, and 1 day per 3 years for the southern hemi-sphere (Simmons and Hollingsworth, 2002). Increases in physicalunderstanding together with improvements in observations, mod-elling techniques and computer speed will all lead to an increasein seasonal forecast skill. The use of an ensemble of POAMA modelforecasts will provide better knowledge about forecast skill and

Author's personal copy

Z. Hochman et al. / Europ. J. Agronomy 44 (2013) 109– 123 117

reliability (e.g. Yin et al., 2011). Nonetheless, progress is likely to beevolutionary rather than revolutionary.

Seasonal forecasts are a complex technology for farmers andadvisers to adopt as an aid to risk management because of theirprobabilistic nature and imperfect skill. Clear thinking is requiredto incorporate such information into farm planning (Hayman et al.,2007). Given that forecasts will never be completely accurate in agiven season, climate risk management requires more information.McIntosh et al. (2007) calculated that, compared to an optimal con-stant management strategy for a wheat crop in north–west Victoria,the added value of a forecasting system based on SOI phases (Stoneet al., 1996) was close to zero. However, a perfect six category fore-cast of rainfall total from sowing to harvest would increase grossmargin per hectare by 26% and grain yield by 17%, so any improve-ment on current forecast skill could have positive impacts on bothyields achieved and resource use efficiency.

The McIntosh et al. (2007) analysis of the value of seasonal fore-casting did not consider the added value of knowing the soil wateror soil nitrogen status of the soil when decisions were made. Soilwater measurements provide certainty about water that is avail-able for use by crops regardless of seasonal rainfall (e.g. Moelleret al., 2009). Much can be achieved by farmers through improvedmonitoring of the state of their soil resource and iteratively adjust-ing their management based on updated production prospects.Experience with farmers exploring their soil in the northern grainsregion strongly suggested that progress in providing farmers withcheap and accurate means of assessing soil water content will helpfarmers to better manage climate related risk (Dalgliesh et al.,2009). Classic decision support systems (DSS) developers havecountenanced the aim of integrating seasonal climate forecastingwith soil data to predict production prospects but have struggledto achieve wide adoption (McCown et al., 2002; Hochman andCarberry, 2011). The uptake by Australian farmers of knowledge-intensive, discontinuous technologies, where the innovation is notcontained in a currently used (continuous) form (e.g. seed of newvarieties) and where the intent is knowledge to guide action,must be a continued objective for innovation. Here innovationis required both in developing the appropriate and reliable toolswhich provide quantifiable benefits and in understanding how suchknowledge-based analyses can contribute to farmers’ current intu-itive approaches to decision-making under uncertainty (McCown,2011). The Yield Prophet® on-line support for Australian farmers(Hochman et al., 2009b) is making some strides in addressing thesechallenges.

5.4.2. Precision agricultureWith the advent of grain yield monitors attached to harvesters

and access to spatial information there has been a growing appreci-ation of the value of variable rate fertiliser application (VR) in grainproduction systems (Robertson et al., in press). The implementationof VR invokes many of the principles of EIA.

The soil-landscape systems on which Australian grain produc-tion occurs are characterised by significant spatial variability in soiltype and hence plant production. It is not uncommon with a sin-gle field of 100 ha for there to be significant areas of soil that differin their plant available water capacity by a factor of two to three-fold (Lawes et al., 2009). In a dryland production system, whereproduction is dependent upon rainfall, such variability leads toassociated variability in water-limited plant growth, grain yield andnutrient demand. Adoption of a uniform application of fertiliser insuch situations commonly leads to a mismatch between nutrientsupply and demand and hence over-fertilising in the low yieldingareas of the field and under-fertilising of the high yielding areas.However, because of the flatness of the payoff curve between cropyield and nutrient rate around the optimum nutrient rate, unlessthere is a significant difference between areas in water-limited

potential crop yield there will not be a significant difference in opti-mum nutrient rates between the uniform rate and rates optimizedfor each soil type or management zone (Robertson et al., 2008). Thisobservation invokes an important principle of VR management –that precision in rates around the yield-maximizing (or profit max-imizing) rate will not necessarily lead to returns in increased yieldor profit.

Because VR can lead to a lessening of the wastage of nutrientson low-demand areas and increase the yield on the high-demandareas, the returns to VR on a whole-of-field basis accrue mostlythrough forestalling yield loss on the high-yielding areas ratherthan savings on reduced wastage on the low-yielding areas. Thisobservation of course is conditional upon the relative prices foryield and nutrients.

The most straight-forward application of VR in the grains indus-try in Australia has been in better matching of nutrient rates tocrop yield potential. This has been driven by farmer observationof yield variation garnered from yield maps and knowledge thatthe underlying cause of yield variation is associated with soil watersupply to the crop (as mediated by soil texture, rooting depth andsub-soil constraints to root activity), rather than nutrient limita-tions (Oliver et al., 2010). In such situations, if nutrients have beenapplied uniformly to such fields over a number of seasons it is pre-dictable, due to the imbalance between supply and demand fornutrients, that soil nutrient levels will build up in the low-yieldingareas and decline in the high-yielding areas, especially for nutrientssuch as P that have a residual value from one season to the next.Some investigations of farmer fields have shown this spatial seg-regation of nutrients. Studies have shown that adjusting nutrientrates to account for both the demand (yield potential) and back-ground supply (soil test levels) can double or treble the benefitsto VR above that gained by accounting for yield potential alone(Robertson et al., 2008; Lawes and Robertson, 2011). Few farmerssoil test in different management zones in their fields, even thosethat practice VR (Robertson et al., in press). There appears to bescope for improving nutrient use efficiency via VR by accountingfor the spatial variability of soil nutrient levels.

Some have advocated the use of yield mapping to identify zonesthat consistently generate low or negative profits, so that they canbe culled from production (Cook and Bramley, 2001), with theprospects of converting them to alternative low-input land usessuch as pasture or trees and thus enhance on-farm biodiversity andreduce off farm impacts from unproductive and potentially “leaky”use of resources. The limited studies that have considered this haveshown that such areas may form as little as 10% of the landscape,due to their fragmented nature (Oliver et al., 2010) and with discon-nection from existing areas of native vegetation or pasture, effectivebiodiversity impacts from such a change may be difficult to achieve(Lawes and Dodd, 2009).

Precision Agriculture has the potential to fulfil most of the desir-able attributes of EIA. It can be used to improve the efficiency withwhich nutrients are used and to increase yields. Reduced wasteof nitrogen based fertilisers can lead to reduced NOx emissions,reduced potential for soil acidification, and reduced potential for Nleaching. Precision Agriculture can enable farmers to cull unprof-itable areas from intensive cropping and to use the land to increaseon-farm biodiversity; however prospects for such gains are likelyto be modest.

5.4.3. Crop–livestock integrationThe integration of crops and livestock that share and transact

resources such as forage, nutrients and land for improvements inwhole-farm productivity and sustainability provide another casewhere agricultural intensification can be achieved while also reduc-ing agriculture’s ecological footprint. Given that much of the extraglobal demand for grain is driven by trends towards increased

Author's personal copy

118 Z. Hochman et al. / Europ. J. Agronomy 44 (2013) 109– 123

meat production, agricultural practices that increase livestock pro-duction without a proportionate decrease in grain productionare desirable. Australia has a history of improvements to agri-cultural productivity and efficiency via integration of crops andlivestock. The introduction of self-regenerating annual legumes(annual medics or subterranean clover) during the 1930s led todevelopment of cereal-ley pasture rotations (typically 1 year pas-ture – 1 year wheat crop) across southern Australia. This systemimproved soil fertility and led to increased cereal yields and greatercattle and sheep production (Puckridge and French, 1983). How-ever, the availability of cheap synthetic fertilisers and the collapseof the price of wool have seen a decline in these traditionalannual legume-cereal-ley systems. Cheap inputs for cropping haveincreased specialisation of crop and livestock production in manyparts of the developed world (Wilkins, 2008; Russelle et al., 2007),yet in Australia, mixed crop–livestock farming still dominates in themajor cropping zones of southern Australia. Two relatively recenttechnologies being adopted in Australia demonstrate the capacityof crop–livestock integration to achieve the dual goals of increas-ing production and reducing the ecological footprint of agriculture.They are (i) perennial pasture phases in cropping systems and (ii)long-season, dual-purpose grain crops with tolerance for grazing.

5.4.3.1. Perennial pasture phases in cropping systems. Research overthe past 10 years has shown that integrating perennial pastures,in particular lucerne (Medicago sativa), into mixed crop–livestocksystems in southern Australia can simultaneously increase whole-farm production and profitability while addressing both on-siteand off-site problems such as soil erosion and degradation, drylandsalinity and nutrient leaching. Perennial pastures used in 2–5-yearphase rotations with crops can provide rotational benefits for sub-sequent crops by reducing weed seed banks (Doole and Pannell,2008), improving soil structure (McCallum et al., 2004) and increas-ing soil fertility (Holford, 1980; Hirth et al., 2001).

Deep-rooted perennial pastures extract and utilise soil waterand nutrients from below the root zone of annual crops.

This reduces rates of leaching of water, nutrients and associ-ated problems of dryland salinity and subsoil acidification, issuesof significant concern to the future viability of Australian agricul-ture (Angus et al., 2001; Latta et al., 2001; Ridley et al., 2001). Overthe pasture phase, the extra water use by the deep-rooted peren-nial establishes a dry soil buffer that can then absorb any excessdrainage that would otherwise have leaked below the root zoneduring the subsequent cropping phase (Ward et al., 2002). Thissystem is flexible, allowing tactical decisions about the length ofthe pasture or crop phase based on climatic conditions. During dryconditions the dry soil buffer takes longer to fill allowing a longercropping phase, while under wetter conditions where leakage ratesare higher, the buffer may be filled more quickly and require ashorter cropping phase before the risk of drainage and solute move-ment increases dramatically. Wider use of perennial pastures alsooffers potential improvements in biodiversity conservation (Bridleet al., 2009) and in bio-sequestration of soil carbon to mitigategreenhouse gas emission (Dalal et al., 1995; Young et al., 2005).

Whole-farm bio-economic modelling across many regions ofsouthern Australia has shown that the integration of lucerne intomixed crop–livestock systems can substantially increase farm prof-itability (Byrne et al., 2010; Dear et al., 2010). Lucerne’s benefitinvolves providing high quality feed to livestock during a gap infeed supply and quality during late summer/early autumn enablingfarm stocking rate to increase. Because of this change in feed sup-ply, changing the livestock enterprise from wool to meat sheepis required to obtain the greatest economic benefit from lucerneunder current economic conditions (Byrne et al., 2010). Optimalfarm profitability is achieved with no more than 30% of the farmallocated to lucerne, which replaces some annual pastures as well

as displacing some cropping on the farm. Despite the reductionin grain crop area the proportional increase in livestock productionfar outweighs this loss, and overall farm agricultural productivity isincreased. Recent modelling shows there are additional benefits bysowing a variety of perennial pastures on the farm, which furtherincrease livestock and whole-farm productivity and profitability(Dear et al., 2010).

5.4.3.2. Dual-purpose graze and grain crops. Dual purpose cropsprovide the opportunity to obtain additional grazing for livestockduring early winter while maintaining or increasing grain produc-tion. These systems have developed in cereals, but are now beinginvestigated in other crops such as canola (Kirkegaard et al., 2008).Simulation modelling, suggested that in south-eastern Australia’shigh rainfall zone, replacement of pastures with dual-purpose cropson 20% of the farm increases farm profit by $23/ha (or 7%) dueto increased grain production as well as higher livestock produc-tion and stocking rate (Moore et al., 2004). Similarly, bio-economicmodelling suggests that grazing of wheat crops could increase farmprofit by 10% in high-rainfall zone of Western Australia (Doole et al.,2009). In regions where spring varieties are sown later but earliersowing opportunities occur regularly, long-season dual-purposecrops could increase productivity by producing similar grain yieldsto spring cultivars as well as providing additional grazing for live-stock (McMullen and Virgona, 2009). Moore (2009) also suggeststhere is some scope to expand the use of dual-purpose cereals intolower rainfall regions (350–500 mm), where they could also helpto increase livestock production.

While dual-purpose crops can increase farm productivity theirimpacts on the other components of the farming system are lessobvious. Firstly, such systems also provide significant flexibilityto growers, potentially widening the planting-window; hence thiscould provide significant benefits for managing risk as well asreducing the intensity of labour requirements at certain times ofthe year. Secondly, grazing crops can reduce grazing pressure onother pastures on the farm, which can improve their productivityand persistence, allowing pastures to provide better groundcoverand reduced soil erosion (Moore, 2009). Finally, because of theirlonger growing season there is potential for deeper root growth andgreater extraction of subsoil water and hence benefits for reducedloss of water via drainage under dual-purpose crops (Virgona et al.,2006).

Despite the potential increases in productivity and reductionsin ecological footprint that can be achieved by the integration ofcrop–livestock enterprises, there are key constraints to greateradoption of the practices outlined above. These constraints includeloss of the infrastructure required for grazing livestock, and thegreater demand for knowledge, skills and management required toobtain optimal performance from these systems.

5.4.4. Deficit irrigationIn Australia’s Riverina region (area between the Murrumbidgee

and Murray Rivers, Southern NSW and Northern Victoria), irri-gated agricultural intensification since 1912 has driven tremendousincreases in food production, typical of such irrigated develop-ments worldwide (Matson et al., 1997). Riverina irrigators arecurrently experiencing unprecedented restrictions in productiondue to water shortages brought about by a combination of climaticand political factors. The recent decade has seen significantly lowercatchment inflows than any previous period in recorded history.Over the past decade, the volume of available water in the south-ern Basin has been around 40% less than the long-term average(MDBA, 2010), resulting in average annual allocations over the last15 years well below 50% of licensed amount, in stark contrast to aprior history of receiving at least 100% every season since 1927(Gaydon et al., 2010). Recent future climate change projections

Author's personal copy

Z. Hochman et al. / Europ. J. Agronomy 44 (2013) 109– 123 119

or

100% wat erOptions for < 1 00% wat er

Fully-irr iga te,

Aim for maximum production from each f ield

Fully i rri gate a smaller s ect ion

Partially-irriga te a larger section

Reduc e inpu ts cfB.

(Land Limited Product ion ) (Water Limited Produ ction )

Partially-irrig ate even more are a

(Reduce irr igated inputs even fur the r than C.)

or

A. B. C. D.

or

100% wat erOptions for < 1 00% wat er

Fully-irr iga te,

Aim for maximum production from each f ield

Fully i rri gate a smaller s ect ion

Partially-irriga te a larger section

Reduc e inpu ts cfB.

(Land Limited Product ion ) (Water Limited Produ ction )

Partially-irrig ate even more are a

(Reduce irr igated inputs even fur the r than C.)

or

A. B. C. D.

Fig. 2. The options which present themselves when changing from a land-limited to a water-limited production system. (A) Represents the historical situation – ample waterto irrigate entire farm; (B–D) represent a range of options for using limited irrigation water. Reducing irrigated inputs means partial or supplementary irrigation (rather thanfull) together with reduced fertiliser inputs as per yield expectations. (C and D) Represent different degrees of input reduction.

0

0.2

0.4

0.6

0.8

1

4000003000002000001000000

Farm GM ($)

Pro

babi

lity

of R

etur

n (0

-1)

D.C.B.

Median

Fig. 3. Real farm case-study (MIA) of Fig. 2 concepts, simulated using the APSIMmodel (with historical 1957–2009 climate data), for an annual allocation of 50%licensed water amount. Adaptation options C and D, with decreased field-levelinputs (water, nitrogen), present lower gross margins (GMs) at the field-scale, yetpotentially increased GMs at the whole-farm scale, because more irrigated land areacan be sown. Risk, however, increases. Additional dryland cropping is not consideredin this analysis. (Reference and case study details – Gaydon, 2010.)

suggest further average decreases in regional water supply arelikely (CSIRO, 2007).

Riverina irrigators now find themselves in an unfamiliar ‘water-limited’ situation. Prior to the mid 1990s, Irrigation water wasalways available in excess, and farmers were ‘land-limited’ interms of increasing their production. All available fields were fullyirrigated, with fertiliser rates and plant populations selected tomaximize production per hectare. Excess drainage of irrigationwater below the crop roots was common and salinity was a grow-ing threat due to rising water tables (Proust, 2003). Also, irrigationreturn flows due to excess drainage typically carry more salt, min-erals, and nutrients than the surface water source which suppliedthem, potentially damaging downstream agricultural and naturalsystems (Matson et al., 1997; Jolly et al., 2001) with significanteconomic consequences (Quiggan, 2001).

With the advent of water shortages, farming practices arefocussing on maximizing the return from each m3 of limited irriga-tion water in an environment where land is no longer the limitingfactor. Whereas in the past, farmers could focus on achieving max-imal production from each field, they now must change their focusto maximizing returns from each m3 of irrigation water. This may

mean targeting sub-optimal field yields (through partial irrigationtechniques) in order to maximize returns from available waterfor the whole farm (Gaydon, 2010). Spreading out the water bypartially irrigating a larger area offers the potential of increasedfarm returns from the same water allocation (Figs. 2 and 3), yet atincreased risk. Such modifications in practice may be consideredthe region’s first venture into ecological agricultural extensifica-tion, and is the direct result of growing limitations in one of theirkey resources – irrigation water.

New circumstances and practices are likely to result in reduceddrainage losses (English et al., 2002), and overall reduced pro-duction from the irrigation areas (Gaydon et al., 2010), howeverpotentially greater production per m3 of irrigation water (Fereresand Soriano, 2007). It is also likely that many of the associated prob-lems of fully watered irrigation districts (rising water tables, riversalinity) will fade in significance under new practices and regimes(Postel and Carpenter, 1997).

6. Conclusions

Anticipated growing global demand for food, coupled with theneed to conserve natural and non-renewable resources and toreduce GHG emissions, make a clear case for EIA on a global scale.The case for EIA in Australia is equally compelling. While Australiais unlikely to face food shortages in this half of the 21st century,global shortages will provide opportunities for Australian farm-ers to respond by increasing production from crops and livestock.Australia’s farmers will be constrained by the same input resourcelimitations as the rest of the world and will need to use water, fer-tilisers and other inputs as sparingly and as efficiently as possible.The Australian environment and particularly its soil resources arefragile and agriculture is highly exposed to the impacts of globalwarming.

Over the past 30 years technical change has been the primarydriver of productivity growth, with correspondingly little contri-bution from improved technical efficiency and change in scale ormix in Australian cropping industries. In the last decade, a declineto 0.4% in the rate of increase in technical change in cropping andmixed crop–livestock farms underlines the challenge ahead.

Against this background of declining growth in productivity andecological imperatives constraining future growth, we identifiedmajor intensification pathways that can be achieved with ecologi-cal efficiency. Currently a very large gap exists between the wateruse efficiencies achieved by Australia’s average and elite grain

Author's personal copy

120 Z. Hochman et al. / Europ. J. Agronomy 44 (2013) 109– 123

Table 1Assessment of the likely matching of four agricultural innovations with the desirable attributes of ecological intensification of agriculture.

Attribute/innovation Climate risk management Precision agriculture Crop–livestock integration Deficit irrigation

(1) Increased production ++Higher production in thebetter seasons

+Yield potential achieved inmore responsive zones.

+Increased livestock productionmore than compensates for lossesin grain yields

−Overall production willdecline due to restrictedwater availability

(2) Efficient use ofresources

++Resources matched toseasonal conditions

++Reduced use of fertilisers inless responsive zones

++Nitrogen fixation by legumepastures

++Production per m3 ofirrigated water will rise

(3) Impact on climate +Reduced NOx emissions

+Reduced NOx emissions

±Increased methane emissions fromlivestock (at lower emissions perlivestock product) vs increasedcarbon bio-sequestration

+Reduced NOx emissions

(4) Minimal impacts on soilhealth

+Reduced potential for soilacidification

++Reduced potential for soilacidification

++Reduced potential for soil erosionand sub-soil acidification

+Reduced potential forrising water tables andincreasing salinity

(5) Minimal offsite impacts +Reduced risks of N leachingand water drainage

++Reduced potential for Nleaching

++Reduced potential for drylandsalinity and nutrient leaching

+Reduced drainage lossesand impacts on riversalinity and water quality

(6) Minimal risk ++A key requirement toimprove risk management

+Need to reduce temporalrisk remains

+Multiple enterprises diversifymarket risk

−Risk is increased withgreater exposure to rainfallvariability

(7) Preservation ofbiodiversity on farm

0No direct link

+Potential for sparingunprofitable land fornature

+Reduced weed seed burden,increased crop diversity,biodiversity conservation

−Potentially negative effectson wildlife with reducedrice areas (McIntyre et al.,2011)

(8) Preservation ofbiodiversity in nature

0No direct link

+Increased productionreduces pressure on landclearing

±Increased production reducespressure on land clearing but couldbe some change from pasture tocrop in some regions.

+Less years in a“land-limited” productionsituation reduces pressureon land clearing

(9) Positive socialoutcomes

+Reduced stress indecision-making and morestable income for farmersand their communities

+Opportunity for small ruralmanufacturers andmachinery serviceproviders. Increaseddemand for knowledge andmanagement skills

+Increased labour requirementoverall, with some relief on labourpressure during peak periods.Increased demand for knowledgeand management skills

+Keep generating income tosupport inland ruralcommunities but incomewill be more volatile

producers. This provides a major opportunity for intensification ofproduction by promoting benchmark agronomic practices. Farm-ers who are currently close to the productivity frontier can focuson maintaining their current level of production with lower lev-els of inputs. The scope for reduced fertiliser inputs without lossof yield was illustrated by the wide range of NUE achieved by elitewheat farmers. Additionally, farmers can explore technologies suchas new crops or varieties (from conventional or genetically modi-fied breeding) and exploit synergies by better matching of geneticresources with environment and management settings. This wouldenable greater production at existing input levels and define newproduction frontiers.

Four enabling innovations were explored here: climate-riskmanagement tools; precision agriculture; crop–livestock integra-tion; and deficit irrigation. A summary assessment of how wellthese case study innovations match our list of desirable attributesof EIA is provided in Table 1. This assessment illustrates the chal-lenge for any innovation to meet all the desired attributes of anEIA technology. All four innovations are likely to achieve a pos-itive result with regards to more efficient use of limited inputs.They are also likely to achieve improved outcomes with regard tosoil health and offsite impacts on soil and water resources and toachieve small improvements in terms of GHG emissions. Prospectsfor better risk management, for preservation of biodiversity on andoff farm and for achieving positive social outcomes appear to beless certain or mixed. Achievement of these goals and mitigation ofGHG emissions will depend on well targeted policy interventions.

We conclude that there are compelling reasons to pursue eco-logical intensification in Australian agriculture. While each ofthe case study technologies we reviewed here is likely to moveagriculture towards EIA, it seems unlikely that any single technol-ogy can satisfy all nine desirable attributes as some tradeoffs areinevitable. Yet there is reason to hope that with the help of govern-ment policy interventions and support for research and extension,emerging and future technologies will in combination progressAustralian agriculture towards greater productivity and positiveecological outcomes.

Acknowledgements

We thank Dr Rick Llewellyn of CSIRO Ecosystem Sciences, Dr.John Kirkegaard and Dr. Graham Bonnett of CSIRO Plant Industryand two anonymous reviewers for their constructive comments ona draft manuscript.

References

ABS, 2002. Salinity on Australian Farms 2002. Australian Bureau of Statistics Cata-logue No. 4615.0, Canberra.

ABS, 2006. Agricultural Commodities, 2005-06, Australia Australian Bureau of Statis-tics Catalogue No. 7121.0, Canberra.

ABS, 2010a. Year Book Australia, 2009–10. Australian Bureau of Statistics CatalogueNo. 1301.0, Canberra.

ABS, 2010b. Agricultural Commodities, 2008–09, Australia Australian Bureau ofStatistics Catalogue No. 7121.0, Canberra.

Author's personal copy

Z. Hochman et al. / Europ. J. Agronomy 44 (2013) 109– 123 121

Angus, J.F., 2001. Nitrogen supply and demand in Australian agriculture. Aust. J. Exp.Agric. 41, 277–288.

Angus, J.F., Gault, R.R., Peoples, M.B., Stapper, M., van Herwaarden, A.F., 2001. Soilwater extraction by dryland crops, annual pastures, and lucerne in south-easternAustralia. Aust. J. Agric. Res. 52, 183–192, doi:10.1071/AR00103.

Ash, A., McIntosh, P., Cullen, B., Carberry, P., Stafford Smith, M., 2007. Constraints andopportunities in applying seasonal climate forecasts in rural industries. Aust. J.Agric. Res. 58, 952–965.

Balmford, A., Green, R.E., Scharlemann, J.P.W., 2005. Sparing land for nature: explor-ing the potential impact of change in agricultural yield on the area needed forcrop production. Global Change Biol. 11, 1594–1605.

Beeston, G., Stephens, D., Nunweek, M., Walcott, J., Ranatunga, K., 2005. GRDC strate-gic planning for investment based on agro-ecological zones. Final Report toGRDC, June 2005. Commonwealth of Australia, Canberra, Australia.

Beeton, R.J.S., Buckley, K.I., Jones, G.J., Morgan, D., Reichelt, R.E., Trewin D., 2006.Australia State of the Environment 2006. Independent report to the AustralianGovernment Minister for the Environment and Heritage. Department of theEnvironment and Heritage, Canberra.

Bolger, T.P., Turner, N.C., 1999. Water use efficiency and water use of Mediterraneanannual pastures in southern Australia. Aust. J. Agric. Res. 50, 1035–1046.

Bridle, K., Fitzgerald, M., Green, D., Smith, J., McQuillan, P., Lefroy, T., 2009. Rela-tionships between site characteristics, farming system and biodiversity onAustralian mixed farms. Anim. Prod. Sci. 49, 869–882.

Brier, H.B., Murray, D.A.H., Wilson, L.J., Nicholas, A.H., Miles, M.M., Grundy, P.R.,McLennan, A.J., 2008. An overview of integrated pest management (IPM)in north-eastern Australian grain farming systems: past, present and futureprospects. Aust. J. Exp. Agric. 48, 1574–1593.

Bruinsma, J., 2009. The resource outlook to 2050: by how much do land, water andcrop yields need to increase by 2050? In: Proceedings of FAO Expert Meeting onHow to Feed the World in 2050, (also available at www.fao.org).

Burney, J.A., Davis, S.J., Lobell, D.B., 2010. Greenhouse gas mitigation by agriculturalintensification. Proc. Natl. Acad. Sci. U.S.A. 107, 12052–12057.

Byerlee, D., 1992. Technical change, productivity, and sustainability in irrigated crop-ping systems of South Asia: emerging issues in the post-green revolution era. J.Int. Dev. 4, 477–496.

Byrne, F., Robertson, M.J., Bathgate, A., Hoque, Z., 2010. Factors influencing poten-tial scale of adoption of a perennial pasture in a mixed crop–livestock farmingsystem. Agric. Syst. 103, 453–462.

Carberry, P.S., Bruce, S.E., Walcott, J.J., Keating, B.A., 2010. Innovation and productiv-ity in dryland agriculture: a return-risk analysis for Australia. J. Agric. Sci. 149,77–89.

Carberry, P.S., Hochman, Z., Hunt, J.R., Dalgliesh, N.P., McCown, R.L., Whish, J.P.M.,Robertson, M.J., Foale, M.A., Poulton, P.L., van Rees, H., 2009. Re-inventing model-based decision support with Australian dryland farmers: 3. Relevance of APSIMto commercial crops. Crop Pasture Sci. 60, 1044–1056.

Cassman, K.G., 1999. Ecological intensification of cereal production systems: yieldpotential, soil quality, and precision agriculture. Proc. Natl. Acad. Sci. U.S.A. 96,5952–5959.

Cassman, K.G., Dobermann, A., Walters, D., 2002. Agroecosystems, nitrogen-use effi-ciency, and nitrogen management. AMBIO 31, 132–140.

Chakraborty, S., Datta, S., 2003. How will plant pathogens adapt to host plant resis-tance at elevated CO2 under a changing climate? New Phytol. 159, 733–742,doi:10.1046/j.1469-8137.2003.00842.x.

Chen, W., Bell, R.W., Brennan, R.F., Bowden, J.W., Dobermann, A., Rengel, Z., Porter,W., 2009. Key crop nutrient management issues in Western Australia grainsindustry: a review. Aust. J. Soil Res. 47, 1–18.

Christensen, J.H., Hewitson, B., et al., 2007. IPCC WG1 Chapter 11. Regional cli-mate projections. In: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M.,Averyt, K., Tignor, M., Miller, H. (Eds.), Contribution of Working Group I to theFourth Assessment Report of the Intergovernmental Panel on Climate Change.Cambridge University Press, Cambridge, UK, pp. 849–926.

Cook, S.E., Bramley, R.G.V., 2001. Is agronomy being left behind by preci-sion agriculture? Proceedings of the 10th Australian Agronomy Confer-ence. Hobart, TAS. (The Australian Society of Agronomy) Available at:www.regional.org.au/au/asa/2001/plenary/2/cook.htm.

Cordell, D., Drangert, J., White, S., 2009. The story of phosphorus: global food securityand food for thought. Glob. Environ. Change 19, 292–305.

Cornish, P.S., 2009. Research directions: Improving plant uptake of soil phosphorus,and reducing dependency on input of phosphorus fertiliser. Crop Pasture Sci. 60,190–196.

Cornish, P.S., 2010. A postscript to “Peak P” – an agronomist’s response to diminish-ing P reserves , Proceedings of the 15th Australian Agronomy Conference, NewZealand.

CSIRO, 2007. The Murray Darling Basin Sustainable Yields Project(http://www.csiro.au/partnerships/MDBSY.html). CSIRO Water for a HealthyCountry Flagship, Canberra.

CSIRO, 2008. Water Availability in the Murray-Darling Basin. A report from CSIROto the Australian Government. CSIRO, Collingwood, Victoria, Australia.

Dalal, R.C., Strong, W.M., Cooper, J.E., Lehane, K.J., King, A.J., Chicken, C.J., 1995.Sustaining productivity of a Vertisol at Warra, Queensland, with fertilisers, no-tillage, or legumes. 1. Organic matter status. Aust. J. Exp. Agric. 35, 903–913.

Dalgliesh, N.P., Foale, M.J., McCown, R.L., 2009. Re-inventing model-based deci-sion support with Australian dryland farmers: 2. Pragmatic provision of soilinformation for paddock-specific simulation and farmer decision making. CropPasture Sci. 60, 1031–1043.

De Wit, C.T., 1992. Resource use efficiency in agriculture. Agric. Syst. 40, 125–151.

Dear, B., Li, G., Casburn, G., Reynolds, M., Bathgate, A., Robertson, M.J., Llewellyn,R., Hayes, R., 2010. Impact of including luceren and other perennials incrop–livestock enterprises in southern NSW. In: Proceedings of the 15th Aus-tralian Agronomy Conference, New Zealand.

Dillon, J.L., 1977. An Analysis of Response in Crop and Livestock Production, seconded. Pergamon, Oxford.

Doole, G.J., Bathgate, A.D., Robertson, M.J., 2009. Labour scarcity restricts the poten-tial scale of grazed pasture plants in Western Australian wheatbelt. Animal Prod.Sci. 49, 883–893.

Doole, G.J., Pannell, D.J., 2008. Role and value of including lucerne (Medicago sativa L.)phases in crop rotations for management of herbicide-resistant Lolium rigidumin Western Australia. Crop Prot. 27, 497–504.

Drosdowski, W., Chambers, L.E., 2001. Near global sea surface temperature anoma-lies as predictors of Australian seasonal rainfall. J. Clim. 14, 1677–1687.

English, M.J., Solomon, K.H., Hoffman, G.J., 2002. A paradigm shift in irrigation man-agement. J. Irrig. Drain. Eng. 128, 267–277.

FAO, 2006. World agriculture: towards 2030/2050. Rome.FAO, 2010. The State of Food Insecurity in the World: Addressing Food Insecurity in

Protracted Crises. Rome.Fereres, E., Soriano, M.A., 2007. Deficit irrigation for reducing water use. J. Exp. Bot.

58, 147–159.Fischer, G., 2009. World Food and Agriculture to 2030/50: how do climate change

and bioenergy alter the long-term outlook for food agriculture and resourceavailability. In: Proceedings of FAO Expert Meeting on How to Feed the Worldin 2050, (also available at www.fao.org).

Freebairn, D.M., Cornish, P.S., Anderson, W.K., Walker, S.R., Robinson, J.B., Beswick,A.R., 2006. Management systems in climate regions of the world-Australia. In:Peterson, G.A., Unger, P.W., Payne, W.A. (Eds.), Dryland Agriculture. , second ed.ASA, CSSA, SSSA, Madison, WI, pp. 837–878.

French, R.J., Schultz, J.E., 1984. Water use efficiency of wheat in a Mediterranean-type environment. I. The relation between yield, water use and climate. Aust. J.Agric. Res. 35, 743–764.

Gaydon, D., Beecher, H.G., Reinke, R., Crimp, S., Howden, S.M., 2010. Rice. In: Stokes,C.J., Howden, S.M. (Eds.), Adapting Australian Agriculture to Climate Change.CSIRO Publishing, Melbourne (Chapter 5).

Gaydon, D., 2010. Adapting to climate change in broad-acre irrigated farmingsystems. In: NCCARF International Climate Change Adaptation Conference,29 June–1 July 2010. Gold Coast Convention Centre, Gold Coast, Australia,http://www.nccarf.edu.au/conference2010/wp-content/uploads/Donald-Gaydon.pdf.

Hajkowicz, S., 2009. The evolution of Australia’s natural resource management pro-grams: towards improved targeting and evaluation of investments. Land UsePolicy 26, 471–478, doi:10.1016/j.landusepol.2008.06.004.

Hamblin, A., 2009. Policy directions for agricultural land use in Australiaand other post-industrial economies. Land Use Policy 26, 1195–1204,doi:10.1016/j.landusepol.2009.01.002.

Hammer, G., Carberry, P., Stone, R., 2000. Comparing the value of seasonal cli-mate forecasting systems in managing cropping systems. In: Hammer, G.L.(Ed.), Application of Seasonal Climate Forecasting in Agricultural and Nat-ural Ecosystems – the Australian Experience. Kluwer Academic Publishers,pp. 183–196.

Hart, B.T., 2004. Environmental risks associated with new irrigation schemesin Northern Australia. Ecol. Manage. Restor. 5, 101–106, doi:10.1111/j.1442-8903.2004.00184.x.

Hayman, P., Crean, J., Mullen, J., Parton, K., 2007. How do probabilistic seasonalclimate forecasts compare with other innovations that Australian farmers areencouraged to adopt? Aust. J. Agric. Res. 58, 975–984.

Helyar, K.R., Porter, W.M., 1989. Soil acidification, its measurement and the processesinvolved. In: Robson, A.D. (Ed.), Soil Acidity and Plant Growth. Academic Press,Sydney, pp. 61–101.

Hennessy, K.J. et al., 2004. Climate Change in New South Wales – part 1:past climate variability and projected changes in average climate. Con-sultancy report for the New South Wales Greenhouse Office by CSIROAtmospheric Research and Australian Government Bureau of Meteorology, p.46, http://www.dar.csiro.au/publications/hennessy 2004b.pdf.

Hirth, J.R., Haines, P.J., Ridley, A.M., Wilson, K.F., 2001. Lucerne in crop rotations onthe Riverine Plains 2. Biomass and grain yields, water use efficiency, soil nitrogenand profitability. Aust. J. Agric. Res. 52, 279–293.

Hochman, Z., Carberry, P.S., 2011. Emerging consensus on desirable characteristicsof tools to support farmers’ management of climate risk in Australia. Agric. Syst.104, 441–450, doi:10.1016/j.agsy.2011.03.001.

Hochman, Z., Holzworth, D.P., Hunt, J.R., 2009a. Potential to improve on-farm wheatyield and water-use efficiency in Australia. Crop Pasture Sci. 60, 708–716.

Hochman, Z., van Rees, H., Carberry, P.S., Hunt, J.R., McCown, R.L., Gartmann, A.,Holzworth, D., van Rees, S., Dalgliesh, N.P., Long, W., Peake, A.S., Poulton, P.L.,McClelland, T., 2009b. Re-inventing model-based decision support: 4. YieldProphet® , an Internet-enabled simulation-based system for assisting farmers tomanage and monitor crops in climatically variable environments. Crop PastureSci. 60, 1057–1070.

Holford, I.C.R., 1980. Effect of duration of grazed lucerne on long-termyields and nitrogen uptake of subsequent wheat. Aust. J. Agric. Res. 31,239–250.

House, A.P.N., MacLeod, N.D., Cullen, B., Whitbread, A.M., Brown, S.D., McIvor, J.G.,2008. Integrating production and natural resource management on mixed farmsin eastern Australia: the cost of conservation in agricultural landscapes. Agric.Ecosyst. Environ. 127, 153–165, doi:10.1016/j.agee.2008.03.011.

Author's personal copy

122 Z. Hochman et al. / Europ. J. Agronomy 44 (2013) 109– 123

Howden, S.M., Soussana, J.F., Tubiello, F.N., Chhetri, N., Dunlop, M., Meinke, H.,2007. Adapting agriculture to climate change. Proc. Natl. Acad. Sci. U.S.A 104,19691–19696.

Howden, S.M., Gifford, R.G., Meinke, H., 2010. Grains. In: Stokes, C.J., Howden, S.M.(Eds.), Adapting Agriculture to Climate Change. CSIRO, Australia, pp. 211–248(Chapter 3).

Hudson, D., Alves, O., Hendon, H.H., Wang, G., 2011. The impact of atmosphericinitialisation on seasonal prediction of tropical Pacific SST. Clim. Dyn. 36,1155–1171.

Hughes, N., Lawson, K., Davidson, A., Jackson, T., Sheng, Y., 2011. Productivitypathways: climate adjusted production frontiers for the Australian broadacrecropping industry. In: Paper Presented to 55th Annual Conference of the Aus-tralian Agricultural and Resource Economics Society, Melbourne, 9–11 February.

Jolly, I.D., Williamson, D.R., Gilfedder, M., Walker, G.R., Morton, R., Robinson, G.,Jones, H., Zhang, L., Dowling, T.I., Dyce, P., Nathan, R.J., Nandakumar, N., Clarke, R.,McNeill, V., 2001. Historical stream salinity trends and catchment salt balancesin the Murray–Darling Basin, Australia. Mar. Freshw. Res. 52, 53–63.

Keating, B.A., Carberry, P.S., Bindraban, P.S., Asseng, S., Meinke, H., Dixon, J., 2010.Eco-efficient agriculture: concepts, challenges and opportunities. Crop Sci. 50(suppl. 1), S109–S119.

Kirkegaard, J.A., Conyers, M., Hunt, J., Kirby, C., Watt., M., Rebetzke, G., 2011. Senseand nonsense in conservation agriculture: principles, pragmatism and produc-tivity in Australian mixed farming systems. In: Proceedings of the 5th WorldCongress of Conservation Agriculture incorporating 3rd Farming Systems DesignConference, Brisbane, Australia, September 2011, pp. 3–8, www.wcca2011.org.

Kirkegaard, J.A., Sprague, S.J., Dove, H., Kelman, W.M., Marcroft, S.J., Lieschke, A.,Howe, G.N., Graham, J.M., 2008. Dual purpose canola – a new opportunity inmixed farming systems. Aust. J. Agric. Res. 59, 291–302.

Kirkegaard, J.A., Hunt, J.R., 2010. Increasing productivity by matching farming sys-tem management and genotype in water-limited environments. J. Exp. Bot. 61,4129–4143.

Ladha, J.K., Pathak, H., Krupnik, T.J., Six, J., van Kessel, C., 2005. Efficiency of fertil-izer nitrogen in cereal production: retrospects and prospects. Adv. Agron. 87,85–156.

Latta, R.A., Blacklow, L.J., Cocks, P.S., 2001. Comparative soil water, pasture produc-tion, and crop yields in phase farming systems with lucerne and annual pasturein Western Australia. Aust. J. Agric. Res. 52, 295–303, doi:10.1071/AR99168.

Lawes, R.A., Dodd, M.B., 2009. Does re-vegetating poor-performing patches in agri-cultural fields improve ecosystem function in the northern sandplain of theWestern Australian wheatbelt? Crop Pasture Sci. 60, 912–920.

Lawes, R.A., Oliver, Y.M., Robertson, M.J., 2009. Integrating the effects of climate andplant available soil water holding capacity on wheat yield. Field Crops Res. 113,297–305.

Lawes, R.A., Robertson, M.J., 2011. Whole farm implications on the applicationof variable rate technology to every cropped field. Field Crops Res. 124,142–148.

Lawlor, D.W., 2002. Carbon and nitrogen assimilation in relation to yield: mech-anisms are the key to understanding production systems. J. Exp. Bot. 53,773–787.

Lisson, S.N., Kirkegaard, J.A., Robertson, M.J., et al., 2007. What is limiting canolayield in southern New South Wales? A diagnosis of causal factors. Aust. J. Exp.Agric. 47, 1435–1445.

Llewellyn, R.S., Lindner, R.K., Pannell, D.J., Powles, S.B., 2002. Resistance and herbi-cide resource: perceptions of Western Australian grain growers. Crop Prot. 21,1067–1075.

Llewellyn, R.S., Lindner, R.K., Pannell, D.J., Powles, S.B., 2004. Grain grower per-ceptions and the use of integrated weed management. Aust. J. Exp. Agric. 44,993–1001.

Matson, P.A., Naylor, R., Ortiz-Monasterio, I., 1998. Integration of environmen-tal, agronomic, and economic aspects of fertilizer management. Science 280,112–115.

Matson, P.A., Parton, W.J., Power, A.G., Swift, M.J., 1997. Agricultural intensificationand ecosystem properties. Science 277, 504–509.

McCallum, M.H., Kirkegaard, J.A., Green, T.W., Cresswell, H.P., Davies, S.L., Angus,J.F., Peoples, M.B., 2004. Improved subsoil macroporosity following perennialpastures. Aust. J. Exp. Agr. 44, 299–307.

McCown, R.L., 2011. A cognitive systems framework to inform delivery of analyticsupport for farmers’ intuitive management of climatic risk. Agric. Syst. 105, 7–20.

McCown, R.L., Hochman, Z., Carberry, P.S., 2002. Probing the enigma of the decisionsupport system for farmers: learning from experience and from theory. Agric.Syst. 74, 1–10.

McDonald, G.K., 1989. The contribution of N fertiliser to the N nutrition of rainfedwheat crops in Australia: a review. Aust. J. Exp. Agric. 29, 455–481.

McIntosh, P.C., Pook, M.J., Risbey, J.S., Lisson, S.L., Rebbeck, M., 2007. Seasonal climateforecasts for agriculture: towards better understanding and value. Field CropsRes. 104, 130–138.

McIntyre, S., McGinness, H.M., Gaydon, D.S., Arthur, A.D., 2011. Introducingirrigation efficiencies: prospects for water-dependent biodiversity in a rice agro-ecosystem. Environ. Conserv. 38, 353–365.

McKeon, G.M., Hall, W.B., Henry, B.K., Stone, G.S., Watson, I.W., 2004. PastureDegradation and Recovery in Australia’s Rangelands: Learning from History.Queensland Department of Natural Resources, Mines and Energy, Brisbane.

McMullen, K.G., Virgona, J.M., 2009. Dry matter production and grain yield fromgrazed wheat in southern New South Wales. Anim. Prod. Sci. 49, 769–776.

MDBA, 2009. Guide to the Proposed Basin Plan: overview. Murray–Darling BasinAuthority, Canberra, ISBN 978-1-921557-73-6 (online).

Moeller, C., Asseng, S., Berger, J., Milroy, S.P., 2009. Plant available soil water atsowing in Mediterranean environments – is it a useful criterion to aid nitrogenfertiliser and sowing decisions? Field Crops Res. 114, 127–136.

Moore, A.D., 2009. Opportunities and trade-offs in dual-purpose cereals across thesouthern Australian mixed-farming zone: a modelling study. Anim. Prod. Sci.49, 759–768.

Moore, A.D., Robertson, M.J., Routley, R., 2011. Evaluation of the water use effi-ciency of alternative farm practices at a range of spatial and temporal scales:a conceptual framework and a modelling approach. Agric. Syst. 104, 162–174.

Moore, A.D., Salmon, L., Dove, H., 2004. The whole-farm impact of includingdual-purpose winter wheat and forage brassica crops in a grazing system: asimulation analysis. New Directions for a Diverse Planet. Proceedings of the4th International Crop Science Congress. Brisbane, Australia, 26 September–1October 2004 (The Regional Institute Ltd: Gosford, NSW). Available athttp://www.cropscience.org.au/icsc2004/symposia/6/3/693 mooread.htm.

NLWRA, 2001. Australian Agriculture Assessment 2001: a Report of the NationalLand and Water Resources Audit. Commonwealth of Australia, Canberra.

Nebojsa, N., Swart, R., 2002. Special report on emissions scenarios. In: Nebojsa, N.,Swart, R. (Eds.), Intergovernmental Panel on Climate Change. Cambridge Uni-versity Press, Cambridge, UK, p. 612.

Nelson, G.C., Rosegrant, M.W., Palazzo, A., Gray, I., Ingersoll, C., Robertson, R., Tokgoz,S., Zhu, T., Sulser, T.B., Ringler, C., Msangi, S., You, L., 2010. Food Security, Farming,and Climate Change to 2050: Scenarios, Results, Policy Options. InternationalFood Policy Research Institute, Washington.

Nicholls, N., 2006. Detecting and attributing Australian climate change: a review.Aust. Met. Mag. 55, 199–211.

O’Donnell, C.J., 2010. Measuring and decomposing agricultural productivity andprofitability change. Aust. J. Agric. Resour. Econ. 54, 527–560.

Oliver, Y.M., Robertson, M.J., Wong, M.T.K., 2010. Integrating farmer knowledge, pre-cision agriculture tools, and crop simulation modelling to evaluate managementoptions for poor performing patches in cropping fields. Eur. J. Agron. 32, 40–50.

Pittock, B., 2003. Climate Change – An Australian Guide to the Science and PotentialImpacts. Australian Greenhouse Office, Canberra.

Postel, S., Carpenter, S., 1997. Freshwater ecosystem services. In: Daily, G.C. (Ed.),Nature’s Services – Societal Dependence on Natural Ecosystems. Island Press,Washington, DC, pp. 195–214.

Preston, C., 2010. Australian Glyphosate Resistance Register. AustralianGlyphosate Sustainability Working Group. http://glyphosateresistance.org.au/register%20summarys.htm.

Price, G.H., 2006. Plant nutrients in the environment. In: Australian Soil FertilityManual, 3rd ed. CSIRO, Melbourne, 176 p. (Table 10.1, Chapter 10).

Proust, K., 2003. Ignoring the signals: irrigation salinity in New South Wales,Australia. Irrig. Drain. 52, 39–49.

Puckridge, D.W., French, R.J., 1983. The annual legume pasture in cereal-ley farmingsystems of southern Australia: a review. Agr. Ecosys. Environ. 9, 229–267.

Quiggan, J., 2001. Environmental economics and the Murray–Darling river system.Aust. J. Agr. Resour. Econ. 45, 67–94.

Ridley, A.M., Christy, B., Dunin, F.X., Haines, P.J., Wilson, K.F., Ellington, A., 2001.Lucerne in crop rotations on the Riverine Plains. 1. The soil water balance. Aust.J. Agric. Res. 52, 263–277, doi:10.1071/AR99165.

Robertson, M.J., Kirkegaard, J.A., 2005. Water-use efficiency of dryland canola in anequi-seasonal rainfall environment. Aust. J. Agric. Res. 56, 1373–1386.

Robertson, M.J., Lyle, G., Bowden, J.W., 2008. Within-field variability of wheat yieldand economic implications for spatially variable nutrient management. FieldCrops Res. 105, 211–220.

Robertson, M.J., Llewellyn, R.S., Mandel, R., Lawes, R., Bramley, R.G.V., Swift, L., Metz,N., O’Callaghan, C. Adoption of variable rate fertiliser application in the Aus-tralian grains industry: status, issues and prospects. Precis. Agric., in press.

Russelle, M.P., Entz, M.H., Franzluebbers, A.J., 2007. Reconsidering integratedcrop–livestock systems in North America. Agron. J. 99, 325–334.

Saji, N.H., Goswami, B.N., Vinayachandran, P.N., Yamagata, T., 1999. A dipole modein the tropical Indian Ocean. Nature 401, 360–363.

Simmons, A.J., Hollingsworth, A., 2002. Some aspects of the improvement in skill ofnumerical weather prediction. Q. J. R. Meteorol. Soc. 128, 647–677.

Squires, V.R., Tow, P.G., 1991. Dryland farming: a systems approach. In: An Analysisof Dryland Agriculture in Australia. Sydney University Press, North Melbourne(Pages xi + 306 p.).

Stone, R.C., Hammer, G.L., Marcussen, T., 1996. Prediction of global rainfallprobabilities using phases of the Southern Oscillation Index. Nature 384,252–255.

Thorburn, P.J., Biggs, J.S., Webster, A.J., Biggs, I.M., 2011. An improved way todetermine nitrogen fertiliser requirements of sugar cane crops to meet globalenvironmental challenges. Plant Soil 339, 51–67, doi:10.1007/s11104-010-0406-2.

Tullberg, J., 2010. Tillage, traffic and sustainability—a challenge for ISTRO. Soil TillageRes. 111, 26–32.

U.N., 2009. World Population Prospects: the 2008 Revision.Virgona, J.M., Gummer, F.A.J., Angus, J.F., 2006. Effects of grazing on wheat growth,

yield, development, water use, and nitrogen use. Aust. J. Agric. Res. 57,1307–1319.

Vitousek, P.M., Naylor, R., et al., 2009. Nutrient imbalances in agricultural develop-ment. Science 324, 1519–1520.

Wang, G., Hendon, H.H., 2007. Sensitivity of Australian rainfall to inter-El Nino vari-ations. J. Clim. 20, 4211–4226.

Ward, P.R., Dunin, F.X., Micin, S.F., 2002. Water use and root growthby annual and perennial pastures and subsequent crops in a phase

Author's personal copy

Z. Hochman et al. / Europ. J. Agronomy 44 (2013) 109– 123 123

rotation. Agric. Water Manage. 53, 83–97, doi:10.1016/S0378-3774(01)00157-3.

WBCSD, 2000. Eco-efficiency – creating more value with less impact.http://www.wbcsd.org/web/publications/eco efficiency creating more value.pdf.

Wilcock, R.J., Nash, D., Schmidt, J., Larned, S.T., Rivers, M.R., Feehan, P., 2011.Inputs of nutrients and fecal bacteria to freshwaters from irrigated agricul-ture: case studies in Australia and New Zealand. Environ. Manage. 41, 198–211,doi:10.1007/s00267-011-9644-1.

Wilkins, R.J., 2008. Eco-efficient approaches to land management: a case forincreased integration of crop and animal production systems. Philos. Trans. R.Soc. Br. 363, 517–525.

Yin, Y., Alves, O., Oke, P.R., 2011. An ensemble ocean data assimilation system forseasonal prediction. Mon. Wea. Rev. 139, 786–808.

Young, R., Wilson, B.R., McLeod, M., Altson, C., 2005. Carbon storage in the soils andvegetation of contrasting land uses in northern New South Wales, Australia.Aust. J. Soil Res. 43, 21–31.