• Home   /  
  • Archive by category "1"

Resource Use Efficiency Hypothesis Statement

In economics, the Jevons paradox (; sometimes the Jevons effect) occurs when technological progress increases the efficiency with which a resource is used (reducing the amount necessary for any one use), but the rate of consumption of that resource rises because of increasing demand.[1] The Jevons paradox is perhaps the most widely known paradox in environmental economics.[2] However, governments and environmentalists generally assume that efficiency gains will lower resource consumption, ignoring the possibility of the paradox arising.[3]

In 1865, the English economist William Stanley Jevons observed that technological improvements that increased the efficiency of coal-use led to the increased consumption of coal in a wide range of industries. He argued that, contrary to common intuition, technological progress could not be relied upon to reduce fuel consumption.[4][5]

The issue has been re-examined by modern economists studying consumption rebound effects from improved energy efficiency. In addition to reducing the amount needed for a given use, improved efficiency also lowers the relative cost of using a resource, which increases the quantity demanded. This counteracts (to some extent) the reduction in use from improved efficiency. Additionally, improved efficiency accelerates economic growth, further increasing the demand for resources. The Jevons paradox occurs when the effect from increased demand predominates, and better efficiency leads to more resources being used.[5]

Considerable debate exists about the size of the rebound in energy efficiency and the relevance of the Jevons paradox to energy conservation. Some dismiss the paradox, while others worry that it may be self-defeating to pursue sustainability by increasing energy efficiency.[3] Environmental economists have proposed that efficiency gains be coupled with conservation policies that keep the cost of use the same (or higher) to avoid the Jevons paradox.[6] Conservation policies (such as cap and trade) do not display the paradox, and can be used to control the rebound effect.[7]


The Jevons paradox was first described by the English economist William Stanley Jevons in his 1865 book The Coal Question. Jevons observed that England's consumption of coal soared after James Watt introduced the Watt steam engine, which greatly improved the efficiency of the coal-fired steam engine from Thomas Newcomen's earlier design. Watt's innovations made coal a more cost-effective power source, leading to the increased use of the steam engine in a wide range of industries. This in turn increased total coal consumption, even as the amount of coal required for any particular application fell. Jevons argued that improvements in fuel efficiency tend to increase (rather than decrease) fuel use, writing: "It is a confusion of ideas to suppose that the economical use of fuel is equivalent to diminished consumption. The very contrary is the truth."[4]

At that time, many in Britain worried that coal reserves were rapidly dwindling, but some experts opined that improving technology would reduce coal consumption. Jevons argued that this view was incorrect, as further increases in efficiency would tend to increase the use of coal. Hence, improving technology would tend to increase the rate at which England's coal deposits were being depleted, and could not be relied upon to solve the problem.[4][5]

Although Jevons originally focused on the issue of coal, the concept has since been extended to the use of any resource, including, for example, water usage[8] and interpersonal contact[9]. It is perhaps the most widely known paradox in environmental economics.[2]


Main article: Rebound effect (conservation)

Economists have observed that consumers tend to travel more when their cars are more fuel efficient, causing a 'rebound' in the demand for fuel.[10] An increase in the efficiency with which a resource (e.g. fuel) is used, causes a decrease in the cost of using that resource when measured in terms of what it can achieve (e.g. travel). Generally speaking, a decrease in the cost (or price) of a good or service will increase the quantity demanded (the law of demand). With a lower cost for travel, consumers will travel more, increasing the demand for fuel. This increase in demand is known as the rebound effect, and it may or may not be large enough to offset the original drop in demand from the increased efficiency. The Jevons paradox occurs when the rebound effect is greater than 100%, exceeding the original efficiency gains.[5]

The size of the rebound effect is dependent on the price elasticity of demand for the good.[11] In a perfectly competitive market where fuel is the sole input used, if the price of fuel remains constant but efficiency is doubled, the effective price of travel would be halved (twice as much travel can be purchased). If in response, the amount of travel purchased more than doubles (i.e. demand is price elastic), then fuel consumption would increase, and the Jevons paradox would occur. If demand is price inelastic, the amount of travel purchased would less than double, and fuel consumption would decrease. However, goods and services generally use more than one type of input (e.g. fuel, labour, machinery), and other factors besides input cost may also affect price. These factors tend to reduce the rebound effect, making the Jevons paradox less likely to occur.[5]

Khazzoom–Brookes postulate[edit]

Main article: Khazzoom–Brookes postulate

In the 1980s, economists Daniel Khazzoom and Leonard Brookes revisited the Jevons paradox for the case of society's energy use. Brookes, then chief economist at the UK Atomic Energy Authority, argued that attempts to reduce energy consumption by increasing energy efficiency would simply raise demand for energy in the economy as a whole. Khazzoom focused on the narrower point that the potential for rebound was ignored in mandatory performance standards for domestic appliances being set by the California Energy Commission.[12][13]

In 1992, the economist Harry Saunders dubbed the hypothesis that improvements in energy efficiency work to increase (rather than decrease) energy consumption the Khazzoom–Brookes postulate, and argued that the hypothesis is broadly supported by neoclassical growth theory (the mainstream economic theory of capital accumulation, technological progress and long-run economic growth). Saunders showed that the Khazzoom–Brookes postulate occurs in the neoclassical growth model under a wide range of assumptions.[12][14]

According to Saunders, increased energy efficiency tends to increase energy consumption by two means. First, increased energy efficiency makes the use of energy relatively cheaper, thus encouraging increased use (the direct rebound effect). Second, increased energy efficiency leads to increased economic growth, which pulls up energy use for the whole economy. At the microeconomic level (looking at an individual market), even with the rebound effect, improvements in energy efficiency usually result in reduced energy consumption.[15] That is, the rebound effect is usually less than 100%. However, at the macroeconomic level, more efficient (and hence comparatively cheaper) energy leads to faster economic growth, which increases energy use throughout the economy. Saunders argued that, taking into account both microeconomic and macroeconomic effects, technological progress that improves energy efficiency will tend to increase overall energy use.[12]

Energy conservation policy[edit]

See also: Steady-state economy § Resource decoupling and the rebound effect

Jevons warned that fuel efficiency gains tend to increase fuel use. But this does not imply that improved fuel efficiency is worthless: higher fuel efficiency enables greater production and a higher material quality of life.[16] For example, a more efficient steam engine allowed the cheaper transport of goods and people that contributed to the Industrial Revolution. However, if the Khazzoom–Brookes postulate is correct, increased fuel efficiency, by itself, will not reduce the rate of depletion of fossil fuels.[12]

The Jevons paradox is sometimes used to argue that energy conservation efforts are futile, for example, that more efficient use of oil will lead to increased demand, and will not slow the arrival or the effects of peak oil. This argument is usually presented as a reason not to enact environmental policies or pursue fuel efficiency (e.g. if cars are more efficient, it will simply lead to more driving).[17][18] Several points have been raised against this argument. First, in the context of a mature market such as for oil in developed countries, the direct rebound effect is usually small, and so increased fuel efficiency usually reduces resource use, other conditions remaining constant.[10][15][19] Second, even if increased efficiency does not reduce the total amount of fuel used, there remain other benefits associated with improved efficiency. For example, increased fuel efficiency may mitigate the price increases, shortages and disruptions in the global economy associated with peak oil.[20] Third, environmental economists have pointed out that fuel use will unambiguously decrease if increased efficiency is coupled with an intervention (e.g. a fuel tax) that keeps the cost of fuel use the same or higher.[6]

There is considerable debate about whether the Khazzoom-Brookes Postulate is correct, and of the relevance of the Jevons paradox to energy conservation policy. Most governments, environmentalists and NGOs pursue policies that improve efficiency, holding that these policies will lower resource consumption and reduce environmental problems. Others, including many environmental economists, doubt this 'efficiency strategy' towards sustainability, and worry that efficiency gains may in fact lead to higher production and consumption. They hold that for resource use to fall, efficiency gains should be coupled with other policies that limit resource use.[3][14][21]

The Jevons paradox indicates that increased efficiency by itself may not reduce fuel use, and that sustainable energy policy must rely on other types of government interventions.[7][22] As the Jevons paradox applies only to technological improvements that increase fuel efficiency, the imposition of conservation standards or other government interventions that increase costs do not display the paradox and can be used to control the rebound effect.[7] To ensure that efficiency-enhancing technological improvements reduce fuel use, efficiency gains can be paired with government intervention that reduces demand (e.g. green taxes, cap and trade, or higher emissions standards). The ecological economistsMathis Wackernagel and William Rees have suggested that any cost savings from efficiency gains be "taxed away or otherwise removed from further economic circulation. Preferably they should be captured for reinvestment in natural capital rehabilitation."[6] By mitigating the economic effects of government interventions designed to promote ecologically sustainable activities, efficiency-improving technological progress may make the imposition of these interventions more palatable, and more likely to be implemented.[23]

See also[edit]



  1. ^Bauer, Diana; Papp, Kathryn (March 18, 2009). "Book Review Perspectives: The Jevons Paradox and the Myth of Resource Efficiency Improvements". Sustainability: Science, Practice, & Policy. 5 (1). Archived from the original on 29 May 2015. Retrieved 29 May 2015. 
  2. ^ abYork, Richard (2006). "Ecological paradoxes: William Stanley Jevons and the paperless office"(PDF). Human Ecology Review. 13 (2): 143–147. Retrieved 2015-05-05. 
  3. ^ abcAlcott, Blake (July 2005). "Jevons' paradox". Ecological Economics. 54 (1): 9–21. doi:10.1016/j.ecolecon.2005.03.020. Retrieved 2015-05-28. 
  4. ^ abcJevons, William Stanley (1866). "VII". The Coal Question (2nd ed.). London: Macmillan and Company. OCLC 464772008. Retrieved 2008-07-21. 
  5. ^ abcdeAlcott, Blake (2008). "Historical Overview of the Jevons paradox in the Literature". In JM Polimeni; K Mayumi; M Giampietro. The Jevons Paradox and the Myth of Resource Efficiency Improvements. Earthscan. pp. 7–78. ISBN 1-84407-462-5. 
  6. ^ abcWackernagel, Mathis; Rees, William (1997). "Perceptual and structural barriers to investing in natural capital: Economics from an ecological footprint perspective". Ecological Economics. 20 (3): 3–24. doi:10.1016/S0921-8009(96)00077-8. 
  7. ^ abcFreire-González, Jaume; Puig-Ventosa, Ignasi (2015). "Energy Efficiency Policies and the Jevons Paradox". International Journal of Energy Economics and Policy. 5 (1): 69–79. Retrieved 29 May 2015. 
  8. ^Dumont, A.; Mayor, B.; López-Gunn, E. (2013). "Is the Rebound Effect or Jevons Paradox a Useful Concept for Better Management of Water Resources? Insights from the Irrigation Modernisation Process in Spain". Aquatic Procedia. 1: 64–76. doi:10.1016/j.aqpro.2013.07.006. Retrieved 5 June 2015. 
  9. ^Glaeser, Edward (2011), Triumph of the City: How Our Best Invention Makes Us Richer, Smarter, Greener, Healthier, and Happier, New York: Penguin Press, pp. 37–38, ISBN 978-1-59420-277-3 
  10. ^ abSmall, Kenneth A.; Kurt Van Dender (2005-09-21). "The Effect of Improved Fuel Economy on Vehicle Miles Traveled: Estimating the Rebound Effect Using U.S. State Data, 1966–2001". Policy and Economics. University of California Energy Institute, UC Berkeley. Retrieved 2010-09-01. 
  11. ^Chan, Nathan W.; Gillingham, Kenneth (1 March 2015). "The Microeconomic Theory of the Rebound Effect and Its Welfare Implications". Journal of the Association of Environmental and Resource Economists. 2 (1): 133–159. doi:10.1086/680256. ISSN 2333-5955. Retrieved 4 February 2018. 
  12. ^ abcdSaunders, Harry D. (October 1992). "The Khazzoom-Brookes Postulate and Neoclassical Growth". The Energy Journal. 13 (4): 131–148. JSTOR 41322471. 
  13. ^Herring, Horace (19 July 1999). "Does energy efficiency save energy? The debate and its consequences". Applied Energy. 63 (3): 209–226. doi:10.1016/S0306-2619(99)00030-6. ISSN 0306-2619. 
  14. ^ abSorrell, Steve (April 2009). "Jevons' Paradox revisited: The evidence for backfire from improved energy efficiency". Energy Policy. 37 (4): 1456–1469. doi:10.1016/j.enpol.2008.12.003. Retrieved 29 May 2015. 
  15. ^ abGreening, Lorna; David L. Greene; Carmen Difiglio (2000). "Energy efficiency and consumption—the rebound effect—a survey". Energy Policy. 28 (6–7): 389–401. doi:10.1016/S0301-4215(00)00021-5. 
  16. ^Ryan, Lisa; Campbell, Nina (2012). "Spreading the net: the multiple benefits of energy efficiency improvements". IEA Energy Papers. IEA Energy Papers. doi:10.1787/20792581. Retrieved 5 June 2015. 
  17. ^Potter, Andrew (2007-02-13). "Planet-friendly design? Bah, humbug". Maclean's. 120 (5): 14. Archived from the original on 2007-12-14. Retrieved 2010-09-01. 
  18. ^Strassel, Kimberley A. (2001-05-17). "Conservation Wastes Energy". The Wall Street Journal. Wall St. Journal—Opinion. Archived from the original on 2005-11-13. Retrieved 2009-07-31. 
  19. ^Gottron, Frank (2001-07-30). "Energy Efficiency and the Rebound Effect: Does Increasing Efficiency Decrease Demand?"(PDF). National Council for Science and the Environment. Retrieved 2012-02-24. 
  20. ^Hirsch, R. L.; Bezdek,, R.; and Wendling, R. (2006). "Peaking of World Oil Production and Its Mitigation". AIChE Journal. 52 (1): 2–8. doi:10.1002/aic.10747. 
  21. ^Owen, David (December 20, 2010). "Annals of Environmentalism: The Efficiency Dilemma". The New Yorker. pp. 78–. 
  22. ^Amado, Nilton Bispo; Sauer, Ildo L. (February 2012). "An ecological economic interpretation of the Jevons effect". Ecological Complexity. 9: 2–9. doi:10.1016/j.ecocom.2011.10.003. Retrieved 29 May 2015. 
  23. ^Laitner, John A.; De Canio, Stephen J.; Peters, Irene (2003). "Incorporating Behavioural, Social, and Organizational Phenomena in the Assessment of Climate Change Mitigation Options". Society, Behaviour, and Climate Change Mitigation. Advances in Global Change Research. 8: 1–64. doi:10.1007/0-306-48160-X_1. ISBN 0-7923-6802-9. Retrieved 2010-08-08. 

Further reading

  • Jenkins, Jesse; Nordhaus, Ted; Shellenberger, Michael (February 17, 2011). Energy Emergence: Rebound and Backfire as Emergent Phenomena (Report). Oakland, CA: The Breakthrough Institute. Retrieved 29 May 2015. 
  • Lords Select Committee on Science and Technology (5 July 2005). "3: The economics of energy efficiency". Select Committee on Science and Technology Second Report (Report). Session 2005–06. London, UK: House of Lords. 
  • Michaels, Robert J. (July 6, 2012). Energy Efficiency and Climate Policy: The Rebound Dilemma(PDF) (Report). Washington, D.C.: Institute for Energy Research. Retrieved 5 June 2015. 
Elastic Demand: A 20% increase in efficiency causes a 40% increase in travel. Fuel consumption increases and the Jevons paradox occurs.
Inelastic Demand: A 20% increase in efficiency causes a 10% increase in travel. The Jevons paradox does not occur.


Alien plant invasions are considered a major threat globally to biodiversity and ecosystem function (Simberloff, 2011; Vilà et al., 2011; Strayer, 2012). Considerable research effort has gone into understanding the mechanisms that drive invasion success in order to direct effective weed management activities (Blumenthal, 2006; Barney and Whitlow, 2008; Catford et al., 2009). Invasion drivers vary and are mediated or filtered by characteristics of the ecosystem being invaded, which can also differ in space and time (D’Antonio, 1993; Levine et al., 2003; Theoharides and Dukes, 2007). One of the major drivers of successful invasion is resource competition (Levine et al., 2003; Vilà and Weiner, 2004). Successful invaders are typically considered to possess a superior ability to acquire limiting resources (e.g., light, nutrients), and/or allocate resources to different plant parts for improved performance (Goldberg et al., 1999). Generally, high resource environments tend to be more invasible than low-resource environments (Gross et al., 2005; Funk, 2013); native species are considered more likely to have a competitive advantage over alien plants in low-resource environments (Funk, 2013). However, in a major review on this topic, Gioria and Osborne (2014) found few studies that compared resource competition directly and most studies were undertaken in high resource environments. Many studies were also confounded by factors such as comparisons of different life forms or dominant alien versus subordinate native species. The effects on carbon sequestration and water use when species replacement is by another of the same life form will depend largely on individual species attributes and climate and may be difficult to predict (Cavaleri and Sack, 2010).

This study focuses on the mechanisms facilitating the invasion of C4Andropogon gayanus Kunth. (gamba grass) in Australia’s mesic (>900 mm annual rainfall) savannas. Large areas (>200,000 ha) of invasion are occurring across the ‘Koolpinyah surface’ (Nott, 1995), a regional geomorphological formation that consists of ancient (Late Tertiary), leached, undulating sandy plains of low soil N and low organic carbon (Scott et al., 2009; Smith and Hill, 2011). Savanna ecosystems being invaded can be considered a resource-limited ecosystem due to these low fertility soils coupled with annual drought (6 months per year) and frequent fire (2 in 3 years) (Hutley and Setterfield, 2008). Despite the limiting resources, A. gayanus is one of a number of introduced pasture species that have become successful invaders in this region (Cook and Dias, 2006; Setterfield et al., 2013). Some drivers of A. gayanus invasion success have been previously demonstrated. For example, A. gayanus produces large amounts of seed annually compared to native grasses (Flores et al., 2005; Setterfield et al., 2005), resulting in high propagule pressure typical of successful invaders (Eppstein and Molofsky, 2007; Catford et al., 2009). Seedling establishment occurs in intact savanna but is greatly facilitated by both canopy cover and/or ground layer disturbance (Setterfield et al., 2005). Like many successful invaders, A. gayanus alters the abiotic characteristics of invaded sites to enhance its ability to colonize and survive (Catford et al., 2009). In this situation, the dominant fire regime changes as a consequence of the increased A. gayanus derived fuel loads and fire intensity (Rossiter et al., 2003; Setterfield et al., 2010) resulting in reduced canopy cover and ground layer vegetation and increased site suitability for establishment of the invader (Rossiter et al., 2003; Setterfield et al., 2005). These drivers contribute to the initial invasion of A. gayanus but the rapid establishment and expansion of this species is likely to be due to other mechanisms that allow the alien species to have competitive advantages over the native species in this low-resource environment.

Studies examining invasion by C4 grass into low-resource environments suggests the importance of understanding ecophysiological differences between the invaders and native species (Chapin et al., 1996; Williams and Baruch, 2000; Daehler, 2003). In South America’s neotropical savannas, the higher maximum stomatal conductance, photosynthesis, and transpiration rates of two invasive C4 grasses compared to the dominant native C4 grasses were suggested as partially explaining their invasion success (Baruch and Fernandez, 1993; Baruch and Gomez, 1996). Similarly, in Hawaii, the invasion of alien C4Pennisetum setaceum (Forsk.) Chiov. was partially attributed to high maximum photosynthetic rates compared to the native C4Heteropogon contortus (Williams and Black, 1994). Despite this competitive advantage, in both of these studies, the native grass was found to have a greater tolerance to soil water deficit and the growth of the alien grass was constrained by water availability (Baruch and Fernandez, 1993; Williams and Black, 1994). This would limit the spatial distribution and growing season of the alien C4 grasses, providing insights into how to control these species and restore the ecosystem (Funk, 2013). At present it is uncertain what constraints may limit the spread of A. gayanus and this study provides further assessment of the likely ecophysiological mechanisms and their importance driving the replacement of a resident native C4 grass flora by an alien and invasive C4 grass. We compared 13 ecophysiological and growth traits of the alien A. gayanus and native Alloteropsis semialata (R. Br.) Hitchc. In particular, we investigated the (1) diurnal and seasonal patterns of leaf gas exchange and stomatal conductance, (2) maximum photosynthesis and transpiration rates under saturating radiation, (3) photosynthetic responses to leaf to air vapour pressure difference (LAVPD), (4) leaf scale efficiencies of light, water and nitrogen use, (5) canopy scale carbon and water fluxes, (6) foliar nitrogen, and (7) foliar C and N isotopes.

Materials and Methods

Study Location

The study was undertaken at Mary River National Park (formerly Wildman Reserve; 12°43′S, 131°49′E), Northern Territory, Australia. The savanna vegetation at the site is dominated by canopy Eucalyptus miniata (Cunn. Ex Schauer) and E. tetrodonta (F. Muell) with a cover of 40–50% and a canopy height of 15–20 m. This vegetation assemblage occupies approximately 246, 600 km2 across Australia’s savanna region (Fox et al., 2001). The climate is characterized by distinct wet season (October–March) and dry seasons (May–September), the latter of which has high vapor pressure deficits (VPD, 2–5 kPa; Egan and Williams, 1996). Mean annual rainfall at Mary River National Park is 1433 mm and mean annual temperature is 27°C (Commonwealth Bureau of Meteorology). Soil types at Mary River National Park are sandy loam red and gray Kandosols (after Isbell, 1996) that are characterized by low nutrient levels with a soil organic carbon content (<2%) and low nitrogen content in the surface horizons of from 0.01 to 0.11% (Day et al., 1979; Rossiter-Rachor, 2008). These soils are coarse textured and well drained, but with low water holding capacity.

The native grass understorey consists of perennial C4 grasses such as Alloteropsis semialata, Heteropogon triticeus, Chrysopogon fallax, Eriachne triseta Nees ex Steud., and C4 annual grasses such as Pseudopogonatherum irritans (Br.) and Sorghum sp. Following the release of a commercial seed supply in 1983, the alien grass A. gayanus (cultivar ‘Kent’) was planted at a range of locations across northern Australia (Oram, 1987) including near Mary River National Park and has since invaded vast areas of the high rainfall savanna (>1000 mm annual rainfall; Petty et al., 2012; Adams and Setterfield, 2013). It is now a dominant feature of the understorey in the northern section of the national park. A. gayanus can form dense monospecific sward up to 4 m high with a biomass of 20–30 t ha-1 in heavily invaded patches (Rossiter et al., 2003), with a sharp invasion front adjacent to non-invaded savanna (Figures 1A,B). Comparisons were undertaken at paired non-invaded, and invaded sites. Invaded sites had a minimum of 70% cover of A. gayanus in the understorey, whereas non-invaded sites had no A. gayanus and were dominated by A. semialata.

FIGURE 1.(A) Tropical savanna invaded with A. gayanus at Mary River National Park, Northern Territory, Australia. The alien grass forms extensive blocks with a sharp invasion front adjacent to (B) uninvaded savanna blocks with an understorey of the native C4 grass A. semialata, as used in this study. (Photo credits N. Rossiter-Rachor).

Leaf Gas Exchange

Leaf scale physiological traits of A. gayanus and A. semialata were compared using two approaches. Firstly, observations of diurnal patterns of leaf gas exchange were tracked for the two species using plants from three plots-pairs (A. gayanus vs native grasses) within the Mary River National Park. Measurements were made in situ during the wet (March) and dry seasons (May) using a portable photosynthesis system (Li-Cor 6400, Li-Cor Inc., Lincoln, NE, USA) on plants within adjacent sward of A. gayanus and A. semialata across an invasion front (Figures 1A,B). Ambient conditions were maintained within the leaf chamber with the instrument in standard measurements mode. Care was taken to ensure the exposure to incident radiation to a leaf was maintained during measurements. Afternoon air temperatures reached 35°C and heating of the instrument occurred requiring regulation of the chamber temperature which was set to 35°C to prevent artificial warming of leaves during measurement.

Native grasses were not measured in the dry season as leaves had senesced by this phase of the seasonal cycle, whereas A. gayanus plants still supported green foliage enabling wet and dry season comparisons. Dry season measurements for A. gayanus were at the same site using the same population of plants and leaves. These diurnal gas exchange measurements provided in situ measurements of leaf performance over a range of leaf and air temperature and light conditions. Secondly, a further set of observations were made during the wet season (March) at an additional three sites within the Mary River National Park. This was undertaken to examine spatial variation of maximum net photosynthesis (Amax) and transpiration (Tmax) of both species under conditions of saturating light. Again, A. gayanus and A. semialata were sampled across an invasion front at these additional sites.

Gas exchange measurements were made on fully expanded, mature leaves approximately two thirds along the leaf lamina of five randomly selected individual plants. Measurements were made on three leaves per A. gayanus plant and two leaves per A. semialata plant, given the small plant and leaf size of the latter. This provided a total of 25 leaves sampled across both species per sampling run, which took approximately 1 h to complete. This sampling cycle was repeated continuously from 1000 to 1700 h local time. Variables collected per leaf included leaf temperature (Tleaf), leaf to air vapour pressure deficit (LAVPD), photosynthetically-active flux density incident at the leaf surface (PAR), assimilation (A), transpiration (T), and stomatal conductance (gs).

Gas exchange measurements were made at three additional sites under saturating light conditions with measurements occurring between 11 am and 1500 h local time. These measures were used for the analysis of instantaneous transpiration efficiency (ITE) and intrinsic water use efficiency (IWUE). ITE was calculated as μmol of CO2 assimilated per mol of water transpired (A/T). IWUE was defined as the ratio of light saturated net assimilation rate to stomatal conductance (A/gs) which is thought to have low dependence on environmental parameters and reflects intrinsic plant physiological functioning (Jones, 1992). To determine the light compensation points, the light saturation point and apparent quantum yields light use efficiency, (LUE; Kuppers and Schulze, 1985), non-linear regressions (A = a × ln(PAR) - b) were fitted to the PAR and A data for each species. Instantaneous LUE of each species was quantified as μmol of CO2 assimilated per μmol-1 PAR in the light limited region of the light response curves.

Above-Ground Biomass and Leaf Area Index

In March and May 2003, the above-ground live plant material (leaves and stems) of each species was harvested in three random 2 m × 2 m quadrats at each of the three paired invaded and non-invaded sites used in the gas exchange measurements. Plant material was dried and weighed to give above-ground biomass (AGB) and scaled to leaf area using allometric equations developed for A. gayanus (Rossiter, 2001). A generic allometric equation for native grass biomass and leaf area was used as a surrogate for A. semialata as this relationship has been shown to hold across a range of northern Australian tropical savanna C4 grasses (Hutley and Williams, unpublished data). Native grass species used to derive the allometric equations were all C4 grasses common in these tropical savanna woodlands (Scott et al., 2012) and included Aristida hygrometrica, Chrysopogon latifolius, Sorghum intrans, Heteropogon triticeus, Themeda triandra, Sehima nervosum, Sorghum plumosum, Chrysopogon fallax, Setaria apiculata, Pseudopogonatherum contortum variously from four sites (Howard Springs, Claravale, Larrimah, and Katherine). Estimates of leaf area sampled from the 2 m × 2 m area enabled the mean leaf area index (LAI) for each site (invaded or non-invaded) to be estimated.

Leaf Nitrogen, Carbon, and Isotopes

All leaves used in the gas exchange measurements of both species were collected, dried, pooled, and ground in a Culatti Type grinder (Model MFC CZ13) with a 1 mm screen. Percent elemental carbon (%C) and nitrogen (%N) and stable carbon (δ13C) and nitrogen (δ15N) isotope ratios were determined via Dumas combustion in an IsoChrom which was connected to an EA-1110 Elemental CHN-O Analyser. Analysis was conducted by the Australian National University stable isotope facility. Foliar nitrogen values (g N/g leaf) were divided by Amax values for each leaf to calculate photosynthetic nitrogen use efficiency (PNUE). Foliar δ13C values indicate long term water use efficiency (LTWUE, Dawson et al., 2002). Foliar leaf δ15N values are somewhat indicative of nitrogen source and soil availability, with lower values suggesting preferential uptake of ammonium or higher soil ammonium to nitrate ratios (Handley et al., 1998).

Statistical Analysis

All statistical analyses were performed using SPSS Version 6.0 (2007, SPSS Inc., Chicago, IL, USA). Clear outliers (>2 SD from the mean) were removed prior to analysis. Outliers were clearly identified from raw data plots and data points that were approximately 2 SD from a measurement run mean were examined. In the wet season, the percentage of outliers was larger than 5% and was 11% for A. gayanus and 10% for A. semialata. None were identified for the A. gayanus dry season data set. Variable PAR conditions and shifts in temperature and VPD with cloud cover of the wet season resulted in a population of leaves that were not at a stable equilibrium when measured and were not included in calculations.

Diurnal leaf temperature, PAR, LAVPD, A, T, and gs, at each time period (10:00, 11:00, 13:00, 14:00, and 16:00 or 17:00) were analyzed using a one-way ANOVA to compare differences between the species/season factor (fixed). Data was normal (skewness, kurtosis values <2) and variances homogeneous (Levene’s significance test <0.05). Data for diurnal analyses were based on plants at one paired site only. Differences between species and seasons were assessed using the Student-Neumann–Keuls post hoc test. The species/season factor included three variables: A. gayanus in the wet season, A. semialata in the wet season, and A. gayanus in the dry season.

Estimates of daily carbon uptake rates and water use per ground area (canopy scale fluxes) were determined by scaling up integrated diurnal measures of A and T, respectively, to rates per square meter ground area using site based LAI estimates. Extrapolation of leaf gas exchange parameters to the canopy scale using LAI is based on the assumption that for these grasses, canopy self-shading is limited and simple scaling using LAI to obtain canopy level estimates is feasible (Larcher, 2003). Leaf scale estimates and foliar δ13C, δ15N, foliar %N, foliar %C, foliar C:N, and PNUE (Amax/N per g leaf, PNUE) for each species/season were analyzed using one-way ANOVA and Student-Neumann–Keuls post hoc tests to assess differences between species and season (for A. gayanus data). Differences in ITE (A/T) and IWUE (A/gs) for each species/season (all sites data) were analyzed using a one-way ANOVA, Student-Neumann–Keuls post hoc tests and pair-wise comparisons with a Bonferroni adjustment.

The LUE of each species was determined as the slope of the linear relationship between PAR and A when light was limiting. Light limitation was assumed to have occurred at PAR <480 μmol m-2 s-1. Differences were analyzed using an ANCOVA with PAR as the covariate and species/season as the fixed factor. Differences in Amax, Tmax, and gs for each species were determined from the light saturated leaves when PAR >750 μmol m-2 s-1 for A. gayanus and A. semialata in the wet season and PAR >500 μmol m-2 s-1 for A. gayanus in the dry season. Differences were compared using ANCOVA, with PAR as the covariate and species/season as the fixed factor.


Leaf Microclimate

During the wet season, A. gayanus and A. semialata leaves experienced a broadly similar microclimate in terms of Tleaf, leaf incident PAR and LAVPD, enabling direct species comparisons of physiological variables (Figure 2A, T, gs.). Leaf temperatures of both species were similar throughout the day, although at approximately 1400 h Tleaf of A. gayanus was higher than that of A. semialata (Figure 2A). Levels of PAR were also similar for both species except at 1000 h, when PAR was significantly higher for A. gayanus (Figure 2B). The diurnal range of LAVPD of A. semialata leaves was similar to that of A. gayanus from 1100 to 1600 h, although leaves of A. gayanus had significantly higher LAVPD in the morning and afternoon (Figure 2C). By the dry season, early morning, and late afternoon Tleaf and PAR were significantly lower for the persistent A. gayanus compared to measurements in the wet season (Figures 2A,B). The LAVPD of A gayanus in the dry season was significantly higher than wet season measurements from 1100 to 1600 h (Figure 2C).

FIGURE 2.Diurnal patterns of leaf scale (A) temperature (Tleaf), (B) photosynthetically active flux density incident at the leaf surface (PAR), (C) leaf to air vapor pressure difference (LAVPD), (D) assimilation (A), (E) transpiration (T) and (F) stomatal conductance (gs) of A. gayanus in the wet (closed squares, n = 120), A. semialata in the wet (triangles, n = 120), and A. gayanus in the dry (open squares, n = 120) seasons. Error bars represent one standard error of the mean. Different letters at each time indicate significant differences at P = 0.05.

Leaf and Canopy Scale Physiology

Both species showed similar decreasing linear trends in A throughout the day; however, in the wet season A. gayanus assimilated carbon at significantly higher rates than A. semialata (Figure 2D). Mean wet season rates of A. gayanus Amax and Tmax were 30% higher than A. semialata (Table 1), with A. gayanus maintaining a longer daily period of assimilation compared to A. semialata. A. semialata exhibited net respiration by 1600 h while A remained positive for A. gayanus leaves until 1700 h (Figure 2D). Although lower than wet season rates, leaves of A. gayanus, were still assimilating carbon and transpiring in the dry season (Figures 2D,E) whereas A. semialata was physiologically dormant. In the wet season, morning levels of T and gs for A. gayanus and A. semialata leaves were similar, however, by 1300 h, A. gayanus had significantly higher rates than A. semialata. A. gayanus was still transpiring water at 1700 h by which time A. semialata rates of T and gs was close to zero (Figures 2E,F. Wet season gas exchange (A, T) was largely driven by PAR (Figures 2B,D,E).

TABLE 1.Mean eco-physiological traits of A. gayanus and A. semialata in the wet season, and A. gayanus in the dry season.

Leaf gas exchange rates were extrapolated to a canopy level using LAI estimates to provide mean daily A and T per unit ground area. In the wet season, A. gayanus stands assimilated ~5 times more C per day and transpired six times more water than A. semialata (Table 1). Stand scale A. gayanus assimilation and water use in the dry season was still double that of the wet season rates of A. semialata, although this difference was not significant (Table 1).

Foliar N, C, and Isotopic Signatures

There was no significant difference between foliar %N, %C, or δ13C for leaves of both species and nor between seasons for A. gayanus (Table 2). A. semialata and A. gayanus foliar δ15N values were similar in the wet season but were significantly lower than dry season values for A. gayanus (Table 2).

TABLE 2.Mean (SE) and ANOVA results for foliar percentage and isotopic nitrogen and carbon (%) of A. gayanus (n = 210) and A. semialata (n = 108) in the wet season and A. gayanus in dry season (n = 120).

Resource Use Efficiency Traits

Andropogon gayanus and A. semialata had similar water use efficiency (WUE) according to three different measurements: IWUE (Figure 3), LTWUE (δ13C, Table 2) and ITE (Figure 4; Table 1). The PNUE and Amax, Tmax, gs of A. gayanus in the wet season were significantly higher than A. semialata (Table 1), while there were no differences in LUE (Figure 5; Table 1). From the wet to dry seasons, A. gayanus leaves showed significant increases in IWUE and ITE (Figure 4; Table 1); however, there was no change in LTWUE (δ13C, Table 2). By the dry season, Amax of A. gayanus leaves had decreased by 82% (Figure 5; Table 1) relative to wet season rates, while PNUE was significantly higher (Table 1). The LUE of A. gayanus was significantly lower in the dry season compared to the wet season (Table 1; Figure 5).

FIGURE 3.Intrinsic water use efficiency (IWUE) of A. gayanus leaves in the wet (solid squares) and dry (open squares) seasons and A. semialata in the wet (triangles) seasons.

FIGURE 4.Instantaneous transpiration efficiency (ITE) of A. gayanus leaves in the wet (solid squares and solid lines, n = 210), A. semialata in the wet (triangles and broken lines, n = 120), and A. gayanus in the dry (open squares, n = 120) seasons.

FIGURE 5.Light response curves for leaves of A. gayanus (closed squares, solid line) and A. semialata (closed triangles, dashed line) in the wet season and A. gayanus in the dry season (open squares, dotted line).


Along with land use change and climate change, alien plant invasion is one of the most threatening processes for the maintenance of biodiversity and ecosystem function. Interdisciplinary research is clearly needed combining ecology, eco-physiology, hydrology, and invasion biology to better understand differences between native and invasive alien species that will assist management and restoration of invaded ecosystems (Gioria and Osborne, 2014). Both instantaneous and time-integrated resource use efficiency (RUE) measures are required to assess performance on short-term (seasonal) as well growth cycles and phases of invasion. In this study, we used comparative measures of both instantaneous (A, Amax, T, Tmax, gs, ITE, LUE) and integrated measures of RUE (PNUE, LTWUE, LAI, biomass) to assess both resource acquisition and resource conservation performance in a highly seasonal environment.

Tropical savanna may represent a strong ‘habitat filter’ (after Weiher et al., 1998) as species grow and persist in a low N, annual drought affected, high water deficit, high VPD, and fire prone ecosystem. In such an environment, successful invasive species may exhibit similar resource conservation or RUE traits to native species that enable survival, however, this was not the case in this study. Under wet season conditions of high light, moisture, and N availability, rates of stomatal conductance, A and T of the alien species were 30–40% higher than the native species, with assimilation occurring for an additional 2 months of the year supported by a deep (up to 80 cm) and profusely branched, fibrous root mass (Rossiter-Rachor et al., 2009). Growth was maintained into the dry season with A. gayanus stand biomass and LAI exceeding that of the wet season (Table 1). This finding is consistent with the meta-analysis of Cavaleri and Sack (2010) who found that invaders typically have significantly higher rates of gs, water use and assimilation, although their analysis included few studies comparing invasive and native grasses.

While rates of A, T, and gs were higher for the invader, there were no species differences in instantaneous water and light use efficiencies measures (IWUE, ITE, LTWUE, LUE), also consistent with meta-analysis of WUE of Cavaleri and Sack’s (2010), even when this analysis was restricted to arid and semi-arid ecosystems (Funk, 2013). While both species are perennial grasses, in this environment leaf function (and age) is essentially annual, with leaf initiation, development, and gas exchange occurring only after the onset of wet season rainfall. This is followed by senescence after seed set in March–April (native species) or May–June (A. gayanus). As a consequence, leaves of both species develop in high water availability and low LAVPD conditions with little difference in leaf-scale WUE. A. gayanus showed stomatal down-regulation and increases in IWUE and ITE (Figures 3 and 4) during the dry season, suggesting physiological plasticity in response to the higher LAVPD and reduced soil moisture availability. Physiological plasticity has been demonstrated for a number of invasive species compared to native species in low-resource environments where resource availability fluctuates (Funk, 2008; Davidson et al., 2011). This is a favorable attribute for persistence in the seasonal tropics, which are characterized by large seasonal changes in resource availability, in particular available N, P, and moisture (Hutley et al., 2000; Soper et al., 2015).

Differences in leaf scale traits alone were unable to explain the 5–10 times greater stand scale biomass accumulation and fourfold increase in LAI of the invader at these sites (Table 1). The exception was PNUE, reflecting one of the most significant limiting resource in these mesic savannas, soil available N (Rossiter-Rachor et al., 2009; Soper et al., 2015). Most studies comparing nutrient-use efficiency in native and alien plants have found higher PNUE in the invasive species (Funk, 2013). For example, the alien African lovegrass (Eragrostis curvula) had a higher PNUE compared to native grasses in the low-nutrient soils of eastern Australia (Firn et al., 2012). Plant invasion is thought to mostly occur in resource rich environments, with invasion driven by altered growing conditions and release of resources via disturbance that differentially increases an invader’s competitive attributes (Daehler, 2003). Recent evidence suggests that invasion and persistence does occur in low resource environments; however, drivers of this are poorly understood (Gioria and Osborne, 2014).

The invasive traits of A. gayanus identified in this study exhibit all three attributes suggested by Funk and Vitousek (2007) that are critical for invasion and perseverance in low-resource environments; (1) high resource acquisition and high RUE, (2) an active increase in resource availability following invasion, and (3) continued disturbance following invasion. Firstly, resource acquisition and RUE were exhibited by A. gayanus via higher rates of gs, A, and T, a longer growing season, high biomass and LAI and significantly higher PNUE. Secondly, an invasive species must actively increase resource availability. Comparative values of leaf δ15N (Table 2) suggested A. gayanus is likely to use more soil ammonium or have increase soil ammonium levels when compared to native grass dominated patches. This is consistent with findings of Rossiter-Rachor et al. (2009) who used labeled 15N experiments that showed A. gayanus’ preference for ammonium as an N source over nitrate. The presence of A. gayanus stimulated soil ammonification and potentially inhibited nitrification (Rossiter-Rachor et al., 2009). This mechanism drives a positive plant–soil feedback that promotes a broader niche width and improved habitat suitability for A. gayanus, in this N-limited ecosystem. Thirdly, Funk and Vitousek (2007) suggest an invader must promote continued disturbance that increases resource availability enabling persistence. A feature of A. gayanus invasion is high biomass (fuel) production and a shift to a high severity fire regime as described by Rossiter et al. (2003) and Setterfield et al. (2010). Severe invasion reduces woody cover by up to 80% within a decade post invasion (Brooks et al., 2010) and initiates a grass-fire feedback. The loss in woody cover releases water, nutrient resources and increases radiation to the understory that further accelerates A. gayanus growth and invasion.


This study has shown that collectively, instantaneous, and time-integrated RUE traits, invasion-derived feedback loops combined with high propagule pressure confers substantial a competitive advantage to A. gayanus over both native grassy and woody lifeforms. These attributes largely explain its current invasiveness and persistence in Australia’s low-resource savanna ecosystems. This is an ecosystem transformation that is resulting in a rapid loss of biodiversity and significantly increasing fire risk (Setterfield et al., 2013). This study provides evidence from a seasonal tropical savanna ecosystem to support Funk’s (2013) assertion that invasive species in low-resource environments possess traits that allow both increased resource acquisition and resource conservation. This superior capacity of A. gayanus to compete for resources also supports modeling predictions of continued rapid invasion across the vast savanna region of northern Australia (Adams et al., 2015).

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


We would like to thank Kath Ryan and Jane Barratt for field data collection. We also thank the Rangers and NT Parks for access to Mary River National Park (formerly Wildman Reserve). Funding was provided by Charles Darwin University research grant, the Land and Water Australia and the National Environmental Research Programme (NERP).


Adams, V. M., Petty, A., Douglas, M. M., Buckley, Y. M., Ferdinands, K. A., Okozaki, T., et al. (2015). Distribution, demography and dispersal model of spatial spread of invasive plant populations with limited data. Methods Ecol. Evol. 6, 782–794. doi: 10.1111/2041-210X.12392

PubMed Abstract | CrossRef Full Text | Google Scholar

Adams, V. M., and Setterfield, S. A. (2013). Estimating the financial risks of Andropogon gayanus to greenhouse gas abatement project in northern Australia. Environ. Res. Lett. 8, 025018. doi: 10.1088/1748-9326/8/2/025018

CrossRef Full Text | Google Scholar

Barney, J., and Whitlow, T. (2008). A unifying framework for biological invasions: the state factor model. Biol. Inv. 10, 259–272. doi: 10.1007/s10530-007-9127-8

CrossRef Full Text | Google Scholar

Baruch, Z., and Fernandez, D. S. (1993). Water relations of native and introduced C4 grasses in a neotropical savanna. Oecologia 96, 179–185. doi: 10.1007/BF00317730

CrossRef Full Text | Google Scholar

Baruch, Z., and Gomez, J. A. (1996). Dynamics of energy and nutrient concentration and construction cost in a native and two alien C4 grasses from two neotropical savannas. Plant Soil 181, 175–184. doi: 10.1007/BF00012051

CrossRef Full Text | Google Scholar

Brooks, K. J., Setterfield, S. A., and Douglas, M. M. (2010). Exotic grass invasions: applying a conceptual framework to the dynamics of degradation and restoration in Australia’s tropical savannas. Rest. Ecol. 18, 188–197. doi: 10.1111/j.1526-100X.2008.00470.x

CrossRef Full Text | Google Scholar

Catford, J. A., Jansson, R., and Nilsson, C. (2009). Reducing redundancy in invasion ecology by integrating hypotheses into a single theoretical framework. Divers. Distrib. 15, 22–40. doi: 10.1111/j.1472-4642.2008.00521.x

CrossRef Full Text | Google Scholar

Cavaleri, M. A., and Sack, L. (2010). Comparative water use of native and invasive plants at multiple scales: a global meta-analysis. Ecology 91, 2705–2715. doi: 10.1890/09-0582.1

PubMed Abstract | CrossRef Full Text | Google Scholar

Chapin, F. S. III, Torn, M. S., and Tateno, M. (1996). Principles of ecosystem sustainability. Am. Nat. 148, 1016–1037. doi: 10.1086/285969

CrossRef Full Text | Google Scholar

Cook, G. D., and Dias, L. (2006). It was no accident: deliberate plant introductions by Australian government agencies during the 20th century. Aus. J. Bot. 54, 601–625. doi: 10.1071/BT05157

CrossRef Full Text | Google Scholar

D’Antonio, C. M. (1993). Mechanisms controlling invasion of coastal plant communities by the alien succulent carpobrotus edulis. Ecology 74, 83–95. doi: 10.2307/1939503

CrossRef Full Text | Google Scholar

Daehler, C. C. (2003). Performance comparisons of co-occurring native and alien plants: implications for conservation and restoration. Annu. Rev. Ecol. Evol. Syst. 34, 183–211. doi: 10.1146/annurev.ecolsys.34.011802.132403

CrossRef Full Text | Google Scholar

Davidson, A. M., Jennions, M., and Nicotra, A. B. (2011). Do invasive species show higher phenotypic plasticity than native species and, if so, is it adaptive? A meta-analysis. Ecol. Lett. 14, 419–431. doi: 10.1111/j.1461-0248.2011.01596.x

PubMed Abstract | CrossRef Full Text

One thought on “Resource Use Efficiency Hypothesis Statement

Leave a comment

L'indirizzo email non verrà pubblicato. I campi obbligatori sono contrassegnati *