Resource heterogeneity increases plant diversity (Hypothesis 3)
The heterogeneity-diversity relationship is one of the central hypotheses explaining the diversity of plant species. It states that environmental heterogeneity should prevent competitive equilibrium, increasing the available niche space and thus allowing more species to coexist (Huston 1979, Tokeshi 2009). Although it is often tested at the macro-ecological scale (Stein et al. 2014), it should in principle be applicable at smaller scales as well. In terms of light conditions, this hypothesis predicts coexistence of species that are adapted to different levels of light. Our findings generally support this view. Species richness was found to increase with light heterogeneity. To our knowledge, only one other study(Reich et al. 2012) explicitly tested the heterogeneity-diversity hypothesis for light with direct measurements of light heterogeneity. In that study, understory species richness was also found to increase with increasing light heterogeneity.
Light heterogeneity increased species richness significantly, while the heterogeneity of other resources such as soil pH, C:N ratio, P and K did not. This finding can be explained in two ways: either the scale was not suitable (see above, i.e. if grain size of heterogeneity in soil resources does not match the sampling size of the plant community), or the level of heterogeneity was simply not large enough to provide different resource niches for understory plants. Moreover, among tested resources, light was the most important factor for increased species richness. Possibly there is a link between the importance of a resource and the effect of its heterogeneity on species richness.
Canopy complexity begets plant diversity (Hypothesis 4)
We have shown that the structural complexity of the forest canopy results in spatio-temporal heterogeneity of light conditions at the forest floor. We have further shown that this heterogeneity in light conditions promotes plant species richness. These findings suggest that the determination of canopy complexity by remote sensing techniques might have considerable potential for predicting environmental conditions and understory plant diversity of forests. Former studies have shown that the structural complexity index SSCI, which was also used here, reliably predicts important microclimatic parameters such as diurnal temperature and vapour pressure differences (Ehbrecht et al. 2019). Getzin et al. (2012) found a significant relationship between gap size and species richness, which points to the importance of light availability for species richness in forests. Nevertheless, for both a mechanistic understanding of ecosystem functioning and nature conservation, not only the number of species present, but also species composition, including the occurrence of dominant or rare species, are important aspects of local biodiversity. Thus, methods for indirectly predicting species richness will never replace field surveys, but may be helpful under certain circumstances, as in remote areas or inaccessible terrains.
This study indicates that both light quantity and heterogeneity at the microscale positively affect understory plant species diversity in mountainous temperate forests of Germany. By confirming the heterogeneity-diversity hypothesis, we were able to answer a fundamental research question. However, these results also have important practical implications for how best to manage these forests to maintain understory plant diversity. As plants are primary producers and are important for many other species at higher trophic levels, it is essential to preserve or enhance plant diversity in the understory. In this study the relationship found between canopy crown complexity and light heterogeneity suggests that understory plant diversity could be increased in forests managed by single tree harvesting by spatially varying the quantities of trees to be logged to create more heterogenous understory light environment.
Acknowledgements – We are grateful to the foresters of the state of Baden-Württemberg for the provided facilities in the forests. We thank Ilse Storch and Johannes Penner for the coordination of ConFoBi. Further, we thank Lana Ruddick for language revision.
Funding – This study was funded by the German Research Foundation (DFG) within the Research Training Group ConFoBi (grant number GRK 2123/1 TPX) and a scholarship from the Internationale Graduiertenakademie (IGA) at University of Freiburg to JH.
Data accessibility statement – The data that support the findings of this study are openly available in Dryad Digital Repository. (Data will be uploaded by acceptance of the manuscript)
References
Abd Latif, Z. and Blackburn, G. A. 2010. The effects of gap size on some microclimate variables during late summer and autumn in a temperate broadleaved deciduous forest. - Int. J. Biometeorol. 54: 119–129.
Allouche, O. et al. 2012. Area–heterogeneity tradeoff and the diversity of ecological communities. - Proc. Natl. Acad. Sci. 109: 17495–17500.
Ampoorter, E. et al. 2015. Disentangling tree species identity and richness effects on the herb layer: first results from a German tree diversity experiment. - J. Veg. Sci. 26: 742–755.
Ampoorter, E. et al. 2016. Driving mechanisms of overstorey–understorey diversity relationships in European forests. - Perspect. Plant Ecol. Evol. Syst. 19: 21–29.
Angert, A. L. et al. 2009. Functional tradeoffs determine species coexistence via the storage effect. - Proc. Natl. Acad. Sci. U. S. A. 106: 11641–11645.
Aubry, K. B. et al. 2009. Variable-retention harvests in the Pacific Northwest: A review of short-term findings from the {DEMO} study. - For. Ecol. Manag. 258: 398–408.
Baethgen, W. E. and Alley, M. M. 1989. A manual colorimetric procedure for measuring ammonium nitrogen in soil and plant Kjeldahl digests. - Commun. Soil Sci. Plant Anal. 20: 961–969.
Bartels, S. F. and Chen, H. Y. H. 2010. Is understory plant species diversity driven by resource quantity or resource heterogeneity? - Ecology 91: 1931–1938.
Bartoń, K. 2019. MuMIn: Multi-Model Inference - R package version 1.6 (2019).
Bates, D. et al. 2015. Fitting Linear Mixed-Effects Models Using lme4. - J. Stat. Softw. 67: 1–48.
Bengtsson, J. et al. 2000. Biodiversity, disturbances, ecosystem function and management of European forests. - For. Ecol. Manag. 132: 39–50.
Bergholz, K. et al. 2017. Environmental heterogeneity drives fine-scale species assembly and functional diversity of annual plants in a semi-arid environment. - Perspect. Plant Ecol. Evol. Syst. 24: 138–146.
Charrad, M. et al. 2014. NbClust: An R Package for Determining the Relevant Number of Clusters in a Data Set. - J. Stat. Softw. 61: 1–36.
Chazdon, R. L. and Pearcy, R. W. 1991. The Importance of Sunflecks for Forest Understory Plants. - BioScience 41: 760–766.
Chesson, P. 2000. Mechanisms of Maintenance of Species Diversity. - Annu. Rev. Ecol. Syst. 31: 343–366.
Connell, J. H. 1978. Diversity in Tropical Rain Forests and Coral Reefs. - Science 199: 1302–1310.
Delignette-Muller, M. L. and Dutang, C. 2015. fitdistrplus: An R Package for Fitting Distributions. - J. Stat. Softw. 64: 1–34.
Duguid, M. C. and Ashton, M. S. 2013. A meta-analysis of the effect of forest management for timber on understory plant species diversity in temperate forests. - For. Ecol. Manag. 303: 81–90.
Ehbrecht, M. et al. 2017. Quantifying stand structural complexity and its relationship with forest management, tree species diversity and microclimate. - Agric. For. Meteorol. 242: 1–9.
Ehbrecht, M. et al. 2019. Effects of structural heterogeneity on the diurnal temperature range in temperate forest ecosystems. - For. Ecol. Manag. 432: 860–867.
Ewald, J. 2003. The calcareous riddle: Why are there so many calciphilous species in the Central European flora? - Folia Geobot. 38: 357–366.
Fedrowitz, K. et al. 2014. Can retention forestry help conserve biodiversity? A meta-analysis (C Baraloto, Ed.). - J. Appl. Ecol. 51: 1669–1679.
Forrester, D. I. et al. 2018. Effects of crown architecture and stand structure on light absorption in mixed and monospecific Fagus sylvatica and Pinus sylvestris forests along a productivity and climate gradient through Europe. - J. Ecol. 106: 746–760.
Frey, J. et al. 2018. UAV Photogrammetry of Forests as a Vulnerable Process. A Sensitivity Analysis for a Structure from Motion RGB-Image Pipeline. - Remote Sens. 10: 912.
Getzin, S. et al. 2012. Assessing biodiversity in forests using very high‐resolution images and unmanned aerial vehicles. - Methods Ecol. Evol. 3: 397–404.
Grime, J. P. and others 1973. Competitive exclusion in herbaceous vegetation. - Nat. UK 242: 344–347.
Gustafsson, L. et al. 2012. Retention Forestry to Maintain Multifunctional Forests: A World Perspective. - BioScience 62: 633–645.
Gustafsson, L. et al. 2019. Retention as an integrated biodiversity conservation approach for continuous-cover forestry in Europe. - Ambio 49: 85–97.
Halpern, C. B. et al. 2012. Level and pattern of overstory retention interact to shape long-term responses of understories to timber harvest. - Ecol. Appl. 22: 2049–2064.
Hardin, G. 1960. The Competitive Exclusion Principle. - Science 131: 1292–1297.
Hofmeister, J. et al. 2009. The influence of light and nutrient availability on herb layer species richness in oak-dominated forests in central Bohemia. - Plant Ecol. 205: 57.
Huston, M. 1979. A General Hypothesis of Species Diversity. - Am. Nat. 113: 81–101.
Hutchinson, G. E. 1957. Concluding Remarks. - Cold Spring Harb. Symp. Quant. Biol. 22: 415–427.
Kriebitzsch, W.-U. et al. 2013. Forest-specific diversity of vascular plants, bryophytes, and lichens. In: Integrative approaches as an opportunity for the conservation of forest biodiversity (D Kraus and F Krumm, Eds.). - European Forest Institute Freiburg.
Legendre, P. and Gallagher, E. D. 2001. Ecologically meaningful transformations for ordination of species data. - Oecologia 129: 271–280.
Leuschner, C. et al. 2017. Vegetation ecology of Central Europe. Volume I.
Liira, J. et al. 2007. The forest structure and ecosystem quality in conditions of anthropogenic disturbance along productivity gradient. - For. Ecol. Manag. 250: 34–46.
Lindenmayer, D. B. et al. 2012. A major shift to the retention approach for forestry can help resolve some global forest sustainability issues. - Conserv. Lett. 5: 421–431.
Lundholm, J. T. 2009. Plant species diversity and environmental heterogeneity: spatial scale and competing hypotheses. - J. Veg. Sci. 20: 377–391.
MacArthur, R. H. and MacArthur, J. W. 1961. On Bird Species Diversity. - Ecology 42: 594–598.
MacArthur, R. and Levins, R. 1967. The Limiting Similarity, Convergence, and Divergence of Coexisting Species. - Am. Nat. 101: 377–385.
Márialigeti, S. et al. 2016. Environmental drivers of the composition and diversity of the herb layer in mixed temperate forests in Hungary. - Plant Ecol 217: 549–563.
Mehlich, A 1953. Rapid determination of cation and anion exchange properties and pHe of soils. - J. Assoc. Off. Agric. Chem. 11: 445–457.
Miranda, K. M. et al. 2001. A Rapid, Simple Spectrophotometric Method for Simultaneous Detection of Nitrate and Nitrite. - Nitric Oxide 5: 62–71.
Morzaria-Luna, H. et al. 2004. Relationship between Topographic Heterogeneity and Vegetation Patterns in a Californian Salt Marsh. - J. Veg. Sci. 15: 523–530.
Murtagh, F. and Legendre, P. 2014. Ward’s Hierarchical Agglomerative Clustering Method: Which Algorithms Implement Ward’s Criterion? - J. Classif. 31: 274–295.
Nakagawa, S. and Schielzeth, H. 2013. A general and simple method for obtaining R2 from generalized linear mixed-effects models. - Methods Ecol. Evol. 4: 133–142.
Richard, M. et al. 2000. Environmental Heterogeneity and the Spatial Structure of Fern Species Diversity in One Hectare of Old-Growth Forest. - Ecography 23: 231–245.
Reich, P. B. et al. 2012. Understorey diversity in southern boreal forests is regulated by productivity and its indirect impacts on resource availability and heterogeneity. - J. Ecol. 100: 539–545.
Rothmaler 2017, Exkursionsflora von Deutschland. Gefäßpflanzen: Grundband, (EJ Jäger, Ed.). - Springer Spektrum.
Schleppi, P. et al. 2007. Correcting non-linearity and slope effects in the estimation of the leaf area index of forests from hemispherical photographs. - Agric. For. Meteorol. 144: 236–242.
Sedio, B. E. and Ostling, A. M. 2013. How specialised must natural enemies be to facilitate coexistence among plants? - Ecol. Lett. 16: 995–1003.
Silvertown, J. 2004. Plant coexistence and the niche. - Trends Ecol. Evol. 19: 605–611.
Stein, A. et al. 2014. Environmental heterogeneity as a universal driver of species richness across taxa, biomes and spatial scales. - Ecol. Lett. 17: 866–880.
Storch, I. et al. 2020. Evaluating the effectiveness of retention forestry to enhance biodiversity in production forests of Central Europe using an interdisciplinary, multi-scale approach. - Ecol. Evol. 10: 1489–1509.
Su, X. et al. 2019. Forest Understorey Vegetation: Colonization and the Availability and Heterogeneity of Resources. - Forests 10: 944.
Taboada, Á. et al. 2008. Plant and carabid beetle species diversity in relation to forest type and structural heterogeneity. - Eur. J. For. Res. 129: 31.
Tamme, R. et al. 2010. Environmental heterogeneity, species diversity and co-existence at different spatial scales. - J. Veg. Sci. 21: 796–801.
Tokeshi, M. 2009. Species Coexistence: Ecological and Evolutionary Perspectives. - John Wiley & Sons.
Venables, W. N. and Ripley, B. D. 2002. Modern Applied Statistics with S. - Springer.
Wilson, M. F. J. et al. 2007. Multiscale Terrain Analysis of Multibeam Bathymetry Data for Habitat Mapping on the Continental Slope. - Mar. Geod. 30: 3–35.
Wright, J. S. 2002. Plant diversity in tropical forests: a review of mechanisms of species coexistence. - Oecologia 130: 1–14..
Zielewska-Büttner, K. et al. 2016. Automated Detection of Forest Gaps in Spruce Dominated Stands Using Canopy Height Models Derived from Stereo Aerial Imagery. - Remote Sensing 8: 175.