The inordinate complexity of nature,whether at the level of molecularprocesses or of the biosphere, has

puzzled biologists for some time. Does a cellular process need all those steps? Must anorganism have so many genes? Does an eco-system need all those species? Experimentalbiologists are currently making tremendous headway in tackling the problem of com-plexity, in part because of their increasinguse of powerful combinatorial methods.Such approaches deconstruct biological systems into their separate parts, then sys-tematically reconstruct arrays of replicatesystems that vary in their combinations ofthose parts. For example, combinatorialarrays of nucleic acids and proteins can beused in genomics and proteomics studies,respectively, to better understand geneexpression, metabolism and development.

Similarly, combinatorial arrays of species(Fig. 1) are becoming increasingly popularwith biodiversity researchers in their quest to understand ecosystem processes such asbiomass production (the amount of livingmatter produced), carbon cycling and nutri-ent retention. Combinatorial biodiversityresearch has been rife with debate, however1.Progress has been made towards resolvingthe controversies2, but the report by Pfistererand Schmid3 on page 84 of this issue is goingto upset the apple-cart.

Pfisterer and Schmid3 studied biomassproduction in a combinatorial plant-diversi-ty experiment, which consisted of an array ofreplicate grassland plots that varied both intheir number of plant species (from 1 to 32)and in their combination of species. Theauthors used their results to test the venera-ble ‘insurance’ hypothesis of ecosystem sta-bility. This hypothesis is one of several thathave featured in the long-standing ecologicaldebate over the relationship between com-plexity (diversity) and stability4. Over thecourse of this debate, the prevailing view hassee-sawed between the thesis that diversitybegets stability, and the antithesis that diver-sity either leads to instability or is irrelevant.

Chief among the ‘begets-stability’ theoriesis the insurance hypothesis — the impeccablylogical notion that having a variety of speciesinsures an ecosystem against a range of en-vironmental upsets. For example, suppose anecosystem faces a drought, then a flood, whichin turn is followed by a fire. According to theinsurance hypothesis, if that ecosystem is

diverse — if it has some species that can toler-ate drought, some that are flood-resistant andsome that are fire-tolerant — then two scenar-ios are likely. The ecosystem may show resis-tance, remaining broadly unchanged, becauseits many species buffer it against damage. Or itmay show resilience: if it does get hammered, itmay bounce back to its original state quicklybecause the tolerant species ultimately drivethe recovery process and compensate for thetemporary loss of their less hardy compatriots.

But Pfisterer and Schmid3 found that,when challenged with an experimentallyinduced drought, species-poor communi-

ties were both more resistant and moreresilient (as reflected by their ability to sus-tain and recover pre-drought biomass production) than plots of higher diversity.The higher-diversity plots were originallymore productive, but their resistance andresilience — that is, their stability — was low(Fig. 1). This is the opposite of what theinsurance hypothesis predicts. It also con-trasts with what combinatorial ‘microcosm’experiments have found5,6 and what theoret-ical models of biodiversity have claimed4.

Pfisterer and Schmid’s findings3 appear tosupport those who claim that diversity does

NATURE | VOL 416 | 7 MARCH 2002 | www.nature.com 23

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Biodiversity equals instability? Shahid Naeem

Figure 1 Combinatorial biodiversity experiments. a, A complex ecosystem, shown as a mixed plot of eightdifferent plant species. b, Combinatorial experiments deconstruct such ecosystems into equal-sizedreplicates that vary in composition from monocultures to polycultures. c, During growth, the amount ofbiomass produced (represented by plot size) varies among replicates. This might be due to one of severaleffects, such as ‘sampling’ (where some species contribute more than others to the accumulatingbiomass; illustrated by irregularly shaped segments), or ‘niche complementarity’ (illustrated by mostspecies contributing equally). d, Perturbations can reduce biomass (illustrated as shrinkage withinframes; large reductions indicate little resistance). Recovery is driven by species growth after theperturbation; fast recovery is indicative of resilience. Combinatorial biodiversity experiments help totease apart the relative contributions of individual species to resistance and resilience. Pfisterer andSchmid3 find that less diverse plots are more resistant and resilient than more varied communities.

Complex ecosystem Combinatorial experiment

PolyculturesMonoculturesMaturationMaturation

Perturbation Recovery

a b

c

d

An understanding of how ecosystems function is vital in guiding human useof natural resources. New work will fuel further debate over the knottyproblem of how an ecosystem’s diversity and stability are interlinked.

© 2002 Macmillan Magazines Ltd

not lead to stability. But there’s a twist, andthose on each side of the debate run the risk ofhaving their own pet theories turned againstthem. Pfisterer and Schmid suggest that theobserved inverse association between diversi-ty and stability is due to a theoretical mecha-nism known as niche complementarity. Thismechanism, however, is the very same as that touted as the chief cause of the positive bio-diversity–productivity relationships foundin other combinatorial biodiversity experi-ments, such as those at Cedar Creek7 andthose run by the BIODEPTH consortium8.

The central idea of niche complemen-tarity is that a community of species whose niches complement one another is more efficient in its use of resources than an equiv-alent set of monocultures. For example, auniform mixture of early- and late-seasonplants and shallow- and deep-rooting plantsthat are spread over 4 m2 will yield more biomass than combined 1-m2 monoculturesof each species7,9. So niche complementaritycan explain why higher diversity tends tolead to higher productivity, and has also beenadopted by those in the ‘diversity leads to stability’ camp because one would expectthat more efficient communities would farebetter in the face of stress.

Those on the other side, however, feel thatexisting data better support a mechanismknown as sampling, where diverse commu-nities produce more biomass simply becausethey are more likely to contain productivespecies10,11. In other words, we can’t read toomuch into experiments in which higherdiversity leads to greater productivity.

What Pfisterer and Schmid suggest is thatcomplementarity among species in a diverseplot could be its downfall when faced withperturbation. Niche complementarity is disrupted and so the whole community suffers. But this is not a problem for lessdiverse plots. So those in the ‘diversity begetsstability’ camp risk being hoist on the petardof their own theory of niche complementari-ty. Meanwhile, although Pfisterer andSchmid’s findings support the idea thatdiversity does not lead to stability, theauthors reject a large role for sampling — thetheory generally favoured by the camp thatdisagrees with the idea that biodiversity leads to stability.

As with other combinatorial studies,there are some limits to how widely Pfistererand Schmid’s findings can be applied.Although the authors provide evidence ofniche complementarity, some contributionsfrom sampling cannot be ruled out. Further-more, the experiment is small-scale, short-term, does not include other contributors tothe food web such as herbivores or decom-posers, and looks only at drought out of ahost of other possible stresses. These issues of scale and complexity, however, are facedby all combinatorial studies, includinggenomics and proteomics, where experi-

mental arrays are far removed from the complex systems being studied. The mainpoint of Pfisterer and Schmid’s study is thatthe relationship between diversity and stabil-ity may be determined by the pre-stress rela-tionship between diversity and productivity,and the mechanisms that drive it.

Until quite recently, the contributions ofliving organisms to ecosystem functioninghave been explored only by poking (smallexperiments) and peeking (observationalstudies). Combinatorial biodiversity re-search offers another approach. Some consensus will be needed before the results of combinatorial studies can be embracedwith confidence. But Pfisterer and Schmid’sreport3 provides insights worth considering,regardless of where it stands or how it fares in the debates on how ecosystem diversityrelates to ecosystem functioning and stabili-ty. The authors point out that the benefits ofhaving productive ecosystems that providenatural resources for humans must be coun-

terbalanced by the effects that diversity hason stability. Strategies for conserving thenatural world are likely to be most robustwhen they balance ecosystem performancewith stability, along with the many other reasons for conserving biodiversity12. ■

Shahid Naeem is in the Department of Zoology,University of Washington, 24 Kincaid Hall, Seattle,Washington 98195, USA.e-mail: naeems@u.washington.edu

1. Kaiser, J. Science 289, 1282–1283 (2000).

2. Loreau, M. et al. Science 294, 806–808 (2001).

3. Pfisterer, A. B. & Schmid, B. Nature 416, 84–86 (2002).

4. McCann, K. S. Nature 405, 228–233 (2000).

5. Naeem, S. & Li, S. Nature 390, 507–509 (1997).

6. McGrady-Steed, J., Harris, P. M. & Morin, P. J. Nature 390,

162–165 (1997).

7. Tilman, D. et al. Science 294, 843–845 (2001).

8. Hector, A. et al. Science 286, 1123–1127 (1999).

9. Loreau, M. & Hector, A. Nature 412, 72–76 (2001).

10.Huston, M. A. Oecologia 110, 449–460 (1997).

11.Wardle, D. A. et al. Bull. Ecol. Soc. Am. 81, 235–239

(2000).

12.Kunin, W. E. & Lawton, J. H. in Biodiversity: A Biology of

Numbers and Differences (ed. Gaston, K.) 283–308 (Blackwell,

Oxford, 1996).

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24 NATURE | VOL 416 | 7 MARCH 2002 | www.nature.com

Avisit to any hospital shows how magnet-ic resonance imaging (MRI) has revolu-tionized clinical medicine. Indeed, a

manifold of resonant-imaging techniquesnow permeate physics, chemistry, biology,medicine, engineering and even computerscience. For example, nuclear magnetic resonance, also known as MRI, can provideroutine non-invasive imaging down to millimetre scales. In the laboratory, state-of-the-art MRI measurements can push this resolution down to about 10mm. Meanwhile,the perhaps less familiar technique of electronspin resonance (ESR) has long been exploitedto characterize a variety of materials.

In Applied Physics Letters, Durkan andWelland1 report the successful marriage ofESR techniques to a newer technique — scan-ning tunnelling microscopy — to detectradio-frequency spin signals from clusters of afew organic molecules. In doing so, they com-bine the chemical sensitivity of spin resonancetechniques with the unrivalled spatial resolu-tion of the scanning tunnelling microscope.This result, together with the pioneeringefforts of others, opens the door to a new classof studies on, or below, the nanometre scale.

At the heart of the experimental tools is the unique interaction between an appliedmagnetic field and the electrons and nuclei of which all atoms are comprised. Most com-mon high-resolution imaging techniques (for

example, electron-beam microscopy) are sensitive to electronic charge, but newer, moreadvanced techniques rely on sensitivity toanother quantum degree of freedom — spin.Progress here has been driven by both scienceand technology. Spin leads to magnetism,which underpins the entire magnetic-storageindustry; it takes quite sophisticated tech-niques to image a modern-day computer harddisk in order to map out and refine the storedmagnetic patterns. Looking to the future, spincould provide the basis for new computingtechnologies based on quantum mechanics —efforts along these lines have spawned thefields of ‘spintronics’ and quantum computa-tion. But right now, the most common type ofmeasurements that routinely access spin arespin resonance techniques.

A simple physical analogy helps to under-stand the basic phenomenon. Imagine arapidly spinning top on a clean tabletop.Under the influence of gravity, the axisaround which the top spins will slowly beginto rotate in small circles around the vertical.This precession, well known from play-grounds or physics demonstrations, occursbecause gravity exerts a torque on the top.Because of its rotational motion, the top pre-cesses at a known frequency determined by,among other things, the gravitational forceand the spin rate of the top. Over time,because of friction, the spin axis of the top

Applied physics

Spin spotting Hari C. Manoharan

Being able to measure electronic spin is essential for future technologiessuch as ‘spintronics’. The combination of two imaging methods foreffective spin-detection has now been demonstrated.

© 2002 Macmillan Magazines Ltd