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More than ever, ecologists seek to employ herbarium collections to estimate plant functional traits from the past and across biomes. However, many trait measurements are destructive, which may preclude their use on valuable specimens. Researchers increasingly use reflectance spectroscopy to estimate traits from fresh or ground leaves, and to delimit or identify taxa. Here, we extend this body of work to non-destructive measurements on pressed, intact leaves, like those in herbarium collections. Using 618 samples from 68 species, we used partial least-squares regression to build models linking pressed-leaf reflectance spectra to a broad suite of traits, including leaf mass per area (LMA), leaf dry matter content (LDMC), equivalent water thickness, carbon fractions, pigments, and twelve elements. We compared these models to those trained on fresh- or ground-leaf spectra of the same samples. The traits our pressed-leaf models could estimate best were LMA (R2 = 0.932; %RMSE = 6.56), C (R2 = 0.855; %RMSE = 9.03), and cellulose (R2 = 0.803; %RMSE = 12.2), followed by water-related traits, certain nutrients (Ca, Mg, N, and P), other carbon fractions, and pigments (all R2 = 0.514–0.790; %RMSE = 12.8–19.6). Remaining elements were predicted poorly (R2 < 0.5, %RMSE > 20). For most chemical traits, pressed-leaf models performed better than fresh-leaf models, but worse than ground-leaf models. Pressed-leaf models were worse than fresh-leaf models for estimating LMA and LDMC, but better than ground-leaf models for LMA. Finally, in a subset of samples, we used partial least-squares discriminant analysis to classify specimens among 10 species with near-perfect accuracy (>97%) from pressed- and ground-leaf spectra, and slightly lower accuracy (>93%) from fresh-leaf spectra. These results show that applying spectroscopy to pressed leaves is a promising way to estimate leaf functional traits and identify species without destructive analysis. Pressed-leaf spectra might combine advantages of fresh and ground leaves: like fresh leaves, they retain some of the spectral expression of leaf structure; but like ground leaves, they circumvent the masking effect of water absorption. Our study has far-reaching implications for capturing the wide range of functional and taxonomic information in the world’s preserved plant collections.more » « less
Reflectance spectra provide integrative measures of plant phenotypes by capturing chemical, morphological, anatomical and architectural trait information. Here, we investigate the linkages between plant spectral variation, and spectral and resource-use complementarity that contribute to ecosystem productivity. In both a forest and prairie grassland diversity experiment, we delineated n -dimensional hypervolumes using wavelength bands of reflectance spectra to test the association between the spectral space occupied by individual plants and their growth, as well as between the spectral space occupied by plant communities and ecosystem productivity. We show that the spectral space occupied by individuals increased with their growth, and the spectral space occupied by plant communities increased with ecosystem productivity. Furthermore, ecosystem productivity was better explained by inter-individual spectral complementarity than by the large spectral space occupied by productive individuals. Our results indicate that spectral hypervolumes of plants can reflect ecological strategies that shape community composition and ecosystem function, and that spectral complementarity can reveal resource-use complementarity.more » « less
null (Ed.)As the effects of anthropogenic climate change become more severe, several approaches for deliberate climate intervention to reduce or stabilize Earth’s surface temperature have been proposed. Solar radiation modification (SRM) is one potential approach to partially counteract anthropogenic warming by reflecting a small proportion of the incoming solar radiation to increase Earth’s albedo. While climate science research has focused on the predicted climate effects of SRM, almost no studies have investigated the impacts that SRM would have on ecological systems. The impacts and risks posed by SRM would vary by implementation scenario, anthropogenic climate effects, geographic region, and by ecosystem, community, population, and organism. Complex interactions among Earth’s climate system and living systems would further affect SRM impacts and risks. We focus here on stratospheric aerosol intervention (SAI), a well-studied and relatively feasible SRM scheme that is likely to have a large impact on Earth’s surface temperature. We outline current gaps in knowledge about both helpful and harmful predicted effects of SAI on ecological systems. Desired ecological outcomes might also inform development of future SAI implementation scenarios. In addition to filling these knowledge gaps, increased collaboration between ecologists and climate scientists would identify a common set of SAI research goals and improve the communication about potential SAI impacts and risks with the public. Without this collaboration, forecasts of SAI impacts will overlook potential effects on biodiversity and ecosystem services for humanity.more » « less
Ecologists often invoke interspecific facilitation to help explain positive biodiversity–ecosystem function relationships in plant communities, but seldom test how it occurs. One mechanism through which one species may facilitate another is by ameliorating abiotic stress. Physiological experiments show that a chronic excess of light can cause stress that depresses carbon assimilation. If shading by a plant's neighbours reduces light stress enough, it may facilitate that plant's growth. If light is instead most often a limiting factor for photosynthesis, shading may have an adverse, competitive effect.
In a temperate tree diversity experiment, we measured stem growth rates and photosynthetic physiology in broadleaf trees across a gradient of light availability imposed by their neighbours. At the extremes, trees experienced nearly full sun (monoculture), or were shaded by nearby fast‐growing conifers (shaded biculture).
Most species had slower growth rates with larger neighbours, implying a net competitive effect. On the other hand, the two most shade‐tolerant species (
Tilia americanaand Acer negundo) and the most shade‐intolerant one ( Betula papyrifera) had faster stem growth rates with larger neighbours. The two shade‐tolerant species had the greatest increases in photoinhibition (reduced dark‐acclimated Fv/ Fm) across the gradient of increasing light availability, which suggests they are more vulnerable to chronic light stress. While most species had lower carbon assimilation rates in the shaded biculture treatment, T. americanahad rates up to 25% higher. T. americanaalso dropped its leaves 3–4 weeks earlier in monocultures, curtailing its growing season.
We conclude that although large neighbours can cause light limitation in shade‐intolerant species, they can also increase growth through abiotic stress amelioration in shade‐tolerant species. Finally, in shade‐intolerant
B. papyrifera, we find a pattern of stem elongation in trees with larger neighbours, which suggests that a shade avoidance response may account for the apparent positive trend in stem volume. Synthesis. Both positive and negative species interactions in our experiment can be explained in large part by the photosynthetic responses of trees to the light environment created by their neighbours. We show that photosynthetic physiology can help explain the species interactions that underlie biodiversity–ecosystem function relationships. The insights that ecologists gain by searching for such physiological mechanisms may help us forecast species interactions under environmental change.