Community Ecology of Absent Species: Hidden and Dark Diversity Meelis Partel€

Journal of Vegetation Science && (2014)

SPECIAL FEATURE: VEGETATION PATTERNS AND THEIR UNDERLYING PROCESSES Community ecology of absent species: hidden and dark diversity Meelis Partel€

Keywords Abstract Absent species; Community composition; Dark diversity; DNA; Ecological community; Missing Community ecologists have so far focused mainly on species identified at a species; Species diversity; Species pool; site. I suggest that we can understand better patterns and their underlying Species richness processes in ecological communities if we also examine those species absent from the sampled community. However, there are various types of absences, Received 19 September 2013 which all harbour different information. Hidden diversity comprises species Accepted 22 January 2014 that are absent from our sight: dormant or locally very rare species over- Co-ordinating Editor: Rein Kalamees looked by traditional sampling. Fortunately, modern DNA-based techniques can help us to find hidden species when analysing environmental samples. Partel,€ M. ([email protected]): Institute of Depending on habitat type and sampling scale, a large number of co-existing Ecology and Earth Sciences, University of species might be hidden. Dark diversity comprises absent species that consti- Tartu, Lai 40, Tartu, 51005, Estonia tute the habitat-specific species pool. Dark diversity can be determined based on data on species distribution, dispersal potential and ecological requirements. If we know both observed and dark diversity, we can estimate community completeness and infer those processes that determine which species in the species pool actually co-exist locally. In addition, most species in the world do not actually belong to the habitat-specific species pool of the community: their ecological requirements differ or their distribution area is else- where. Such other absent species are usually not directly relevant to a particular community. However, knowing ecologically suitable species from other regions can give early warning of possible future invasion of alien species (alien dark diversity). To conclude, species presences have meaning only if there are absences (and vice versa). Methods to detect absent species are rapidly developing and will soon form a standard toolbox for community ecology.

allow community ecologists and conservation practitioners Introduction to better understand community patterns and their under- An ultimate goal of community ecology is to understand lying processes. why different sites host different species (Vellend 2010). Species absent from a particular community sample pro- Studies of ecological communities have concentrated pri- vide valuable information. Without absences, all samples marily on observations of species found in local sites. Spe- host the same species and the table can be represented as a cies identiﬁed in a set of ecological communities are simple species list. There is no reason why species absences typically listed in species 9 sample tables. If species compo- cannot be used instead of presences; it is simply a matter of sition varies among samples, these tables also feature tradition that we count presences in a species 9 sample absences. In fact, absences are usually more frequent than table. Ultimately the maximum number of absences in a presences in such tables. Scientists generally focus on spe- species 9 sample table is the total global ﬂora or fauna. cies presences to examine variation in species diversity and For example, there are currently 283 556 accepted names community composition. Present species are also segre- of vascular plant species (www.theplantlist.org, accessed gated into groups of different functional types, alien or Dec 2013). An Estonian wooded meadow holds the world threatened species, etc. Here I outline the importance of record for the number of vascular plant species within a species absences and suggest how various types of absences 10 9 10 cm plot: 25 rooted species (Kull & Zobel 1991;

Wilson et al. 2012). The very same plot also holds the Twenty years ago, Eddy van der Maarel and Martin world record for the lowest number of species absences at Sykes proposed the Carousel Model (van der Maarel & that scale, ‘just’ 283 531 (i.e. 283 556–25) absent species. Sykes 1993) after examining 10 9 10 cm permanent Why are these species absent? This question is by no plots in dry calcareous grasslands in Sweden. They noticed means as trivial as it might seem. Some absent species are high small-scale species mobility: each subsequent year found adjacent to the 10 9 10 cm plot. Several species revealed the appearance and disappearance of several spe- common to wooded meadows in the region are absent cies in all permanent plots. This was especially surprising both in the plot and its close vicinity. Moreover, most spe- since most species were perennial. Species moved around cies absent from the 10 9 10 cm plot inhabit other conti- like children on a merry-go-round. This high small-scale nents, other biogeographic regions or simply other mobility was originally attributed to the short life span of habitats, e.g. wetlands or seashores. Consequently, by dis- plant individuals and frequent regeneration from the seed tinguishing relevant types of absences, we can make the bank. However, community recruitment from seeds observed diversity – recorded presences – much more use- depends on favourable local conditions and can be highly ful. For simplicity, I shall neglect species abundances, but it stochastic (Eriksson & Froborg€ 1996). More recent is theoretically possible to account for this as well, e.g. research has stressed the importance of the below-ground when working with the effective number of species (Hill bud bank (Klimesova & Klimes 2007). Some plant species 1973). Here I present an overview of different types of can stay dormant below ground, sometimes for several absences representing hidden diversity and dark diversity, years (Reintal et al. 2010). In temperate grasslands, often as well as an overview of other absent species that might more than 75% of plant biomass is below ground in com- ‘stalk’ our study sites. plex symbiosis with other trophic levels (Jackson et al. 1997; Steinaker & Wilson 2005; Mokany et al. 2006). This means that a plant community might be more of a below- Hidden diversity ground phenomenon than often realized. How many We can expect that some species from our sampled area plant species actually co-exist in soil? Do above-ground (or volume) remain unobserved. I call this set of species plant community patterns reﬂect those below ground? hidden diversity, because these species are not in fact These aspects of vegetation science have been badly absent from the sample, but merely absent from observa- neglected because, until recently, plant roots and rhi- tion. At larger spatial scales, it is also likely that some rare zomes of different species were mostly indistinguishable. species remain overlooked (Gaston et al. 1997). Several Current DNA-based methods have started to shed light on methods, however, are available to estimate if sampling is this phenomenon (Partel€ et al. 2012). We have used the sufﬁcient, e.g. species accumulation curves based on sam- next-generation sequencing to identify plant species in ples or individuals, rarefaction curves with resampling, temperate grasslands in 10 9 10 9 10 cm volume below Jackknife and Chao estimates which incorporate multiple the soil surface, the horizon where most roots in grass- subsamples (Gotelli & Colwell 2001; Cao et al. 2007). lands are located (Hiiesalu et al. 2012). We found that These methods can estimate how many species have been small-scale plant species richness below ground is up to overlooked but do not inform us of the identity of hidden twice that above ground. When we examined the whole diversity. Current developments in environmental DNA 2-ha grassland (cumulative data from several samples), metabarcoding have hinted that such methods might be there were still a number of species found only below sensitive enough to detect some rare species missed by tra- ground. All these species belonged to the local species pool ditional sampling (Taberlet et al. 2012; Ji et al. 2013; Zhan and were recorded in the study site in previous years. At et al. 2013). The potential and limitations of new DNA- the sampling time, however, they were present only in based methods await further testing. the soil. In addition, there are different species co-exis- When the sampling area is small, it is likely that all indi- tence patterns above and below the ground: more biotic viduals are counted and all species are observed above assembly rules were detected above ground, whereas the ground at any given time. At the same time, some species below ground part was largely determined abiotically in the community simply cannot be recorded by traditional (Price et al. 2012). Even relationships with other commu- visual inspection. This is readily apparent for mobile organ- nity properties such as productivity, heterogeneity or dis- isms; members of an ecological community might be turbance regime might differ between above- and below- absent temporarily (e.g. foraging for food). Sessile plants, ground realms (Partel€ et al. 2012). For example, if the however, can also be temporarily absent above ground. above-ground richness decreases with increasing soil fer- Species can be dormant, e.g. existing at the time of sam- tility, the number of species only found below ground pling as vegetative rhizomes or roots in the soil, or as part increases; hence, the total richness is independent of soil of the active seed bank. fertility (Hiiesalu et al. 2012).

The recent knowledge of hidden diversity provides a ful- from astrophysics, where dark matter is the term for the ler picture of co-existing species. It likely challenges cur- substance that cannot be seen directly but whose existence rent species richness records (Wilson et al. 2012) and and properties are inferred from its gravitational effects on might require reconsideration of species co-existence and visible matter. Similarly, dark diversity cannot be observed community assembly theories based on data obtained by directly in the field but is inferred from species distribution visual inspections (Partel€ et al. 2012). The thorough over- and habitat requirement data. In order to belong to dark view of all co-existing species is vital for nature conserva- diversity an absent species must have a reasonable proba- tion and ecosystem management. For example, restoration bility to disperse to the study site, and its ecological after adverse human influence might be possible if eradi- requirements must match the local conditions. Dark diver- cated species can persist as hidden diversity in the soil. sity is seemingly similar to but distinct from the beta-diver- Our below-ground diversity studies typify mostly tem- sity concept. Beta diversity does not consider potentially perate habitats where epiphytes are rare, very few annual inhabiting species and is limited to those species actually species are present and regeneration from seed is heavily observed in a set of samples. stochastic (Liira et al. 2012). Tropical rain forests with Dark diversity is defined by the likelihood to disperse diverse epiphytic flora likely behave differently. In com- into a study site and the subsequent probability to estab- munities where regeneration from seed is common (e.g. lish. Dispersal potential is usually inferred from the current arid ecosystems), the diaspore bank contributes consider- distribution by including species from the surrounding ably to hidden diversity. At the same time, care must be region, e.g. within a radius (Graves & Gotelli 1983). More taken since the diaspore bank might sometimes include sophisticated methods have recently been proposed, e.g. species that have dispersed to the study site but that cannot dispersion fields (Graves & Rahbek 2005; Carstensen et al. establish there, or are remnants from previous successional 2013). The habitat requirements of some species have been stages; such inactive species are not part of hidden diver- compiled in databases according to expert knowledge sity. Consequently, we need to consider species’ habitat (Sadlo et al. 2007; Zobel et al. 2011). Ellenberg indicator requirements. This leads us to the next group of species: values (Ellenberg et al. 1991) have often been used in Eur- dark diversity. ope as a semi-quantitative description of ecological requirements of plants. Similarly, habitat requirements can be inferred from spatial modelling of species distribu- Dark diversity tion (Guisan & Rahbek 2011; Mokany & Paini 2011). Absent species that can potentially reach and inhabit a par- Information on species co-occurrence has been accumulat- ticular community constitute its dark diversity – the frac- ing in recent years, which, by examining the set of present tion of the habitat-specific species pool absent at any species and those that often co-occur with them, can be particular time (Partel€ et al. 2011). Dark diversity is the applied to estimate dark diversity (Ewald 2002; Munzber-€ essence of the species pool concept – the idea that each par- gova & Herben 2004). ticular site or habitat is strongly influenced by its ‘own’ set Information on dark diversity can provide a better of expected species (Eriksson 1993; Zobel 1997). Concepts understanding of how ecological communities actually of potential diversity have deep roots in ecology, dating form and behave. If we relate observed and dark diversity, back to the pioneers of community ecology. The term ‘spe- we can calculate community completeness, i.e. how much cies pool’ was probably used for the first time in the equi- of the species pool is realized within the local community librium theory of island biogeography by MacArthur & (Partel€ et al. 2013). We have proposed a Community Wilson (1963) to distinguish a set of species that can poten- Completeness Index, ln(observed diversity/dark diversity), a tially reach and inhabit a study site (an island). Soon this logistic expression with statistical advantages over propor- term was picked up by others who used it with respect to tions or percentages (for details, see Partel€ et al. 2013). The different plant and animal communities (Golley et al. concept of community completeness allows us to compare 1965; Looman 1965). Since then ‘species pool’ has had different ecosystems, different regions and different taxo- rather different meanings, sometimes including all species nomic groups (e.g. trophic levels), because it expresses from a surrounding region, sometimes ecologically-fil- richness on a relative scale by accounting for the variation tered, habitat-specific subsets (Graves & Gotelli 1983). Just in species pool size. as physics can benefit from research on elementary parti- While use of the dark diversity concept can make diver- cles – even if the concept of atoms consisting of protons, sity patterns comparable, it also helps to infer underlying neutrons and electrons is well established – Iamconvinced processes of community assembly. One option is to explore that spotlighting a principal element of the species pool community saturation – a function of the relationship concept – dark diversity – strengthens the general concepts between local richness and species pool size (or regional of species pools. We borrowed the term ‘dark diversity’ richness; Szava-Kovats et al. 2012, 2013). Whereas

Journal of Vegetation Science Doi: 10.1111/jvs.12169 © 2014 International Association for Vegetation Science 3 Community ecology of absent species M. P€artel community completeness can be determined for a single other regions which have not yet invaded our study site site, community saturation can only be detected for multi- but which have a reasonable probability to arrive in the ple sites. Through analyses of community saturation, it is future since their ecological requirements match local hab- possible to distinguish stochastic (neutral) and determinis- itat conditions. For example, research indicates that just a tic community assembly. Another avenue by which to few of the >1000 Australian acacia species are currently explore community processes is to compare functional trait causing problems as invasive species worldwide (Richard- (or phylogenetic) patterns in an observed community and son et al. 2011). However, bioclimatic analysis suggests in its corresponding dark diversity. This approach extends that a third of the world’s surface could be invaded by at beyond habitat filtering – the rather trivial finding that spe- least some Australian acacia species, with several regions cies differ in their preference for ecological conditions – to suitable for 100 or more potential invaders. Knowing this see if a biotic filter exists that influences how local commu- alien dark diversity allows us to prepare in advance suit- nities are actually assembled (de Bello et al. 2012). able means to curtail invasion by alien species before their Dark diversity offers the means to improve strategies in establishment. nature conservation. By identifying relatively diverse sites Global changes in climate, nutrient cycles and land use within each region or habitat type (de Bello et al. 2010), have modified some natural and semi-natural communi- community completeness can serve as a valuable tool in ties, allowing native species from other communities to the design of nature reserve networks. Similarly, commu- invade (native invasive species; Valery et al. 2009). For nity completeness enables quantification of habitat degra- example, alkaline atmospheric emissions from a cement dation, as well as monitoring restoration (Suding 2011). factory in NE Estonia have raised soil pH in nearby peat Information on community assembly processes can inform bogs, leading to widespread invasion by grassland species nature management plans. If, for example, species in dark (Paal et al. 2010). All these species are native, some even diversity disperse more poorly than those in observed officially under protection, but are not typical of peat bog diversity, improved connectivity between habitats would communities. Their presence actually indicates a stressed promote community completeness. If species in dark diver- and degrading ecosystem. If the aim of nature conservation sity have weaker competitive abilities than those in is to preserve biodiversity of the original habitat, it is essen- observed diversity, local habitat management can be initi- tial to monitor both ‘suitable’ and ‘unsuitable’ species. ated (e.g. more frequent prescribed disturbances). The group of ‘other absent species’ is less clear than hid- A current trend in ecology is coordinated distributed den or dark diversity but still important for specific ques- experiments (Fraser et al. 2013) in which similar experi- tions, e.g. identifying absent species that might become ments are repeated in several locations throughout the troublesome alien or native invaders, or that contribute to world. Although this technique is well suited to distin- the formation of novel ecosystems. Our world is dynamic; guishing general patterns, omission of the differences in species ranges and habitat conditions continuously dark diversity in the analysis may mask other important change. This demands that we consider absent species patterns, ultimately leading to biased conclusions (Lessard dynamically, looking beyond species’ native ranges and et al. 2012). Since dark diversity methods are rapidly traditional habitats (Eriksson 2014). developing (Partel€ et al. 2011, 2013), in the future it should be possible to use community completeness instead Conclusions of raw richness to efficiently understand diversity patterns and processes globally, and to make improved nature con- Species presences only have meaning if there are absences servation decisions. (and vice versa). Moreover, different types of absent species contribute valuable information. Incorporating species hidden or belonging to dark diversity into community Other absent species analysis can reveal more insightful diversity patterns, What about species absent from the community and that which can then be examined to reveal underlying commu- do not belong to dark diversity, i.e. those not typically nity processes. Effective nature conservation demands pre- expected in the particular community? These are species dictions on potential alien species and opportunistic native native to other regions or other habitats within the sur- species. Current methods based on environmental DNA rounding area. These are seemingly less relevant to a par- now allow the detection of dormant species comprising ticular community although some potentially invasive hidden diversity. Dark diversity and potential invaders can species might ‘stalk’ the study site. be determined by using accumulating data on species dis- Alien invasive species pose a major threat to natural tribution, ecological requirements and co-occurrence pat- communities (Pysek & Chytry 2014). It is possible to iden- terns. Techniques to detect absent species are rapidly tify alien dark diversity – these species originating from developing and will soon form a standard toolbox for

Journal of Vegetation Science 4 Doi: 10.1111/jvs.12169 © 2014 International Association for Vegetation Science M. P€artel Community ecology of absent species community ecologists, just as methods for multivariate S.L., (...) & Turkington, R. 2013. Coordinated distributed analyses, or functional and phylogenetic structures have experiments: an emerging tool for testing global hypotheses now become routine. Knowing the community ecology of in ecology and environmental science. Frontiers in Ecology absent species would inform us about why some sites do and the Environment 11: 147–155. not host particular species, which would complement our Gaston, K.J., Blackburn, T.M. & Lawton, J.H. 1997. Interspecific – understanding of the distribution and function of the pres- abundance range size relationship: an appraisal of mecha- – ent species. nisms. Journal of Animal Ecology 66: 579 601. Golley, F.B., Gentry, J.B., Caldwell, L.D. & Davenport, L.B. Jr 1965. Number and variety of small mammals on the AEC Acknowledgements Savannah River Plant. Journal of Mammalogy 46: 1–18. Gotelli, N.J. & Colwell, R.K. 2001. Quantifying biodiversity: pro- I thank my colleagues in the Macroecology work group cedures and pitfalls in the measurement and comparison of (www.botany.ut.ee/macroecology/en/) for fruitful discus- species richness. Ecology Letters 4: 379–391. sions. Comments from two anonymous referees and the Graves, G.R. & Gotelli, N.J. 1983. Neotropical land-bridge avifa- editor Dr. Rein Kalamees were most helpful. This work has unas: new approaches to null hypotheses in biogegoraphy. been supported by the European Union 7th framework Oikos 41: 322–333. project SCALES (FP7-226852), European Regional Devel- Graves, G.R. & Rahbek, C. 2005. Source pool geometry and the opment Fund (Center of Excellence FIBIR) and University assembly of continental avifaunas. Proceedings of the National of Tartu (SF0180095s08, IUT 20-29). Academy of Sciences of the United States of America 102: 7871– 7876. – References Guisan, A. & Rahbek, C. 2011. SESAM a new framework inte- grating macroecological and species distribution models for de Bello, F., Lavorel, S., Gerhold, P., Reier, U.€ & Partel,€ M. 2010. predicting spatio-temporal patterns of species assemblages. A biodiversity monitoring framework for practical conserva- Journal of Biogeography 38: 1433–1444. tion of grasslands and shrublands. Biological Conservation 143: Hiiesalu, I., Opik,€ M., Metsis, M., Lilje, L., Davidson, J., Vasar, 9–17. M., Moora, M., Zobel, M., Wilson, S.D. & Partel,€ M. 2012. de Bello, F., Price, J.N., Munkem€ uller,€ T., Liira, J., Zobel, M., Plant species richness belowground: higher richness and Thuiller, W., Gerhold, P., Gotzenberger,€ L., Lavergne, S., new patterns revealed by next generation sequencing. Molec- (...)&Partel,€ M. 2012. Functional species pool framework ular Ecology 21: 2004–2016. to test for biotic effects on community assembly. Ecology 93: Hill, M.O. 1973. Diversity and evenness: a unifying notation and 2263–2273. its consequences. Ecology 54: 427–432. Cao, Y., Hawkins Charles, P., Larsen David, P. & Van Sickle, J. Jackson, R.B., Mooney, H.A. & Schulze, E.D. 1997. A global bud- 2007. Effects of sample standardization on mean species get for fine root biomass, surface area, and nutrient contents. detectabilities and estimates of relative differences in species Proceedings of the National Academy of Sciences of the United States richness among assemblages. The American Naturalist 170: of America 94: 7362–7366. 381–395. Ji, Y., Ashton, L., Pedley, S.M., Edwards, D.P., Tang, Y., Nakam- Carstensen, D.W., Lessard, J.-P., Holt, B.G., Borregaard, M.K. & ura, A., Kitching, R., Dolman, P.M., Woodcock, P., (...)& Rahbek, C. 2013. Introducing the biogeographic species Yu, D.W. 2013. Reliable, verifiable and efficient monitoring pool. Ecography 36: 1310–1318. of biodiversity via metabarcoding. Ecology Letters 16: 1245– Ellenberg, H., Weber, H.E., Dull,€ R., Wirth, V., Werner, W. & Pa- 1257. ulißen, D. 1991. Zeigerwerte von Pflanzen in Mitteleuropa. Klimesova, J. & Klimes, L. 2007. Bud banks and their role in veg- Scripta Geobotanica 18: 1–248. etative regeneration – A literature review and proposal for Eriksson, O. 1993. The species-pool hypothesis and plant com- simple classification and assessment. Perspectives in Plant Ecol- munity diversity. Oikos 68: 371–374. ogy, Evolution and Systematics 8: 115–129. Eriksson, O. 2014. Vegetation change and eco-evolutionary Kull, K. & Zobel, M. 1991. High species richness in an Estonian dynamics. Journal of Vegetation Science 25. wooded meadow. Journal of Vegetation Science 2: 715–718. Eriksson, O. & Froborg,€ H. 1996. “Windows of opportunity” for Lessard, J.-P., Belmaker, J., Myers, J.A., Chase, J.M. & recruitment in long-lived clonal plants: experimental studies Rahbek, C. 2012. Inferring local ecological processes amid of seedling establishment in Vaccinum shrubs. Canadian Jour- species pool influences. Trends in Ecology & Evolution 27: nal of Botany 74: 1369–1374. 600–607. Ewald, J. 2002. A probabilistic approach to estimating species Liira, J., Ingerpuu, N., Kalamees, R., Moora, M., Partel,€ M., pools from large compositional matrices. Journal of Vegetation Pussa,€ K., Roosaluste, E., Saar, L., Tamme, R., Zobel, K. & Science 13: 191–198. Zobel, M. 2012. Grassland diversity under changing produc- Fraser, L.H., Henry, H.A.L., Carlyle, C.N., White, S.R., Bei- tivity and the underlying mechanisms – results of a 10-yr erkuhnlein, C., Cahill, J.F., Casper, B.B., Cleland, E., Collins, experiment. Journal of Vegetation Science 23: 919–930.

Looman, J. 1965. Theoretical considerations of the plant asso- acacias – a global experiment in biogeography. Diversity and ciation. Netherlands Journal of Agricultural Science 13: 120– Distributions 17: 771–787. 128. Sadlo, J., Chytry, M. & Pysek, P. 2007. Regional species pools of van der Maarel, E. & Sykes, M.T. 1993. Small-scale plant species vascular plants in habitats of the Czech Republic. Preslia 79: turnover in a limestone grassland: the carousel model and 303–321. some comments on the niche concept. Journal of Vegetation Steinaker, D.F. & Wilson, S.D. 2005. Belowground litter contri- Science 4: 179–188. butions to nitrogen cycling at a northern grassland–forest MacArthur, R.H. & Wilson, E.O. 1963. An equilibrium theory of boundary. Ecology 86: 2825–2833. insular zoogeography. Evolution 17: 373–387. Suding, K.N. 2011. Toward an era of restoration in ecology: suc- Mokany, K. & Paini, D.R. 2011. Dark diversity: adding the grey. cesses, failures, and opportunities ahead. Annual Review of Trends in Ecology & Evolution 26: 264–265. Ecology, Evolution, and Systematics 42: 465–487. Mokany, K., Raison, R.J. & Prokushkin, A.S. 2006. Critical Szava-Kovats, R., Zobel, M. & Partel,€ M. 2012. The local-–regio- analysis of root:shoot ratios in terrestrial biomes. Global nal species richness relationship: new perspectives on the Change Biology 12: 84–96. null-hypothesis. Oikos 121: 321–326. Munzbergov€ a, Z. & Herben, T. 2004. Identiﬁcation of suitable Szava-Kovats, R., Ronk, A. & Partel,€ M. 2013. Pattern without unoccupied habitats in metapopulation studies using co- bias: local–regional richness relationship revisited. Ecology occurrence of species. Oikos 105: 408–414. 94: 1986–1992. Paal, J., Vellak, K., Liira, J. & Karofeld, E. 2010. Bog recovery in Taberlet, P., Coissac, E., Pompanon, F., Brochmann, C. & Wil- Northeastern Estonia after the reduction of atmospheric pol- lerslev, E. 2012. Towards next-generation biodiversity lutant input. Restoration Ecology 18(Suppl.): 387–400. assessment using DNA metabarcoding. Molecular Ecology 21: Partel,€ M., Szava-Kovats, R. & Zobel, M. 2011. Dark diversity: 2045–2050. shedding light on absent species. Trends in Ecology & Evolution Valery, L., Fritz, H., Lefeuvre, J.C. & Simberloff, D. 2009. Inva- 26: 124–128. sive species can also be native. Trends in Ecology & Evolution Partel,€ M., Hiiesalu, I., Opik,€ M. & Wilson, S.D. 2012. Below- 24: 585. ground plant species richness: new insights from DNA-based Vellend, M. 2010. Conceptual synthesis in community ecology. methods. Functional Ecology 26: 775–782. The Quarterly Review of Biology 85: 183–206. Partel,€ M., Szava-Kovats, R. & Zobel, M. 2013. Community com- Wilson, J.B., Peet, R.K., Dengler, J. & Partel,€ M. 2012. Plant spe- pleteness: linking local and dark diversity within the species cies richness: the world records. Journal of Vegetation Science pool concept. Folia Geobotanica 48: 307–317. 23: 796–802. Price, J.N., Hiiesalu, I., Gerhold, P. & Partel,€ M. 2012. Small-scale Zhan, A., Hulak, M., Sylvester, F., Huang, X., Adebayo, A.A., grassland assembly patterns differ above and below the soil Abbott, C.L., Adamowicz, S.J., Heath, D.D., Cristescu, M.E. surface. Ecology 93: 1290–1296. & MacIsaac, H.J. 2013. High sensitivity of 454 pyrosequenc- Pysek, P. & Chytry, M. 2014. Habitat invasion research: where ing for detection of rare species in aquatic communities. vegetation science and invasion ecology meet. Journal of Veg- Methods in Ecology and Evolution 4: 558–565. etation Science 25. Zobel, M. 1997. The relative role of species pools in determining Reintal, M., Tali, K., Haldna, M. & Kull, T. 2010. Habitat prefer- plant species richness: an alternative explanation of species ences as related to the prolonged dormancy of perennial coexistence? Trends in Ecology & Evolution 12: 266–269. herbs and ferns. Plant Ecology 210: 111–123. Zobel, M., Otto, R., Laanisto, L., Naranjo-Cigala, A., Partel,€ M. & Richardson, D.M., Carruthers, J., Hui, C., Impson, F.A.C., Miller, Fernandez-Palacios, J.M. 2011. The formation of species J.T., Robertson, M.P., Rouget, M., Le Roux, J.J. & Wilson, pools: historical habitat abundance affects current local J.R.U. 2011. Human-mediated introductions of Australian diversity. Global Ecology and Biogeography 20: 251–259.