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Predicting leaf traits of herbaceous species from their spectral characteristics.

ABSTRACT: Trait predictions from leaf spectral properties are mainly applied to tree species, while herbaceous systems received little attention in this topic. Whether similar trait-spectrum relations can be derived for herbaceous plants that differ strongly in growing strategy and environmental constraints is therefore unknown. We used partial least squares regression to relate key traits to leaf spectra (reflectance, transmittance, and absorbance) for 35 herbaceous species, sampled from a wide range of environmental conditions. Specific Leaf Area and nutrient-related traits (N and P content) were poorly predicted from any spectrum, although N prediction improved when expressed on a per area basis (mg/m(2) leaf surface) instead of mass basis (mg/g dry matter). Leaf dry matter content was moderately to good correlated with spectra. We explain our results by the range of environmental constraints encountered by herbaceous species; both N and P limitations as well as a range of light and water availabilities occurred. This weakened the relation between the measured response traits and the leaf constituents that are truly responsible for leaf spectral behavior. Indeed, N predictions improve considering solely upper or under canopy species. Therefore, trait predictions in herbaceous systems should focus on traits relating to dry matter content and the true, underlying drivers of spectral properties.

SUBMITTER: Roelofsen HD

PROVIDER: S-EPMC3967897 | biostudies-other | 2014 Mar

REPOSITORIES: biostudies-other

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Predicting leaf traits of herbaceous species from their spectral characteristics.

Roelofsen Hans D HD van Bodegom Peter M PM Kooistra Lammert L Witte Jan-Philip M JP

Ecology and evolution 20140214 6

Trait predictions from leaf spectral properties are mainly applied to tree species, while herbaceous systems received little attention in this topic. Whether similar trait-spectrum relations can be derived for herbaceous plants that differ strongly in growing strategy and environmental constraints is therefore unknown. We used partial least squares regression to relate key traits to leaf spectra (reflectance, transmittance, and absorbance) for 35 herbaceous species, sampled from a wide range of ...[more]

PMID: 24683454

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Project description:Background and aimsSoil water availability is an important mechanism filtering plant species but the functional basis of this filtering in herbaceous dicots is poorly studied. The authors address three questions: Which physiological traits best predict different levels of drought tolerance or avoidance in herbaceous dicots? To what degree can species' habitat preferences along the gradient of soil moisture availability be predicted by their physiological responses to drought? What are the direct and indirect relationships between the physiological traits and how do they interact to determine the species' habitat preferences?MethodsTwenty-five species of herbaceous dicots whose field distributions span a gradient of soil moisture from continually moist to dry were chosen. Under controlled conditions, watering was stopped in a treatment group, the plants were monitored until death of the above-ground tissues and compared with a control group watered at field capacity. Fourteen traits related to plant water economy were measured, including stomatal conductance, net photosynthesis and the visual wilting of leaves. Traits were then analysed using a cumulative link model and path analysis.Key resultsFive physiological traits (stomatal conductance and net photosynthesis measured at soil field capacity, water use efficiency, stomatal conductance and soil water potential measured when leaves begin to wilt) related to the ability to acquire resources (when water is not limiting) or conserve water (when it is limiting) best predicted different levels of drought tolerance or avoidance in herbaceous dicots.ConclusionsSpecies' habitat preferences can be fairly predicted by their physiological responses to drought ( R 2 = 0·48). Strong direct and indirect relationships between the five identified traits (plus net photosynthesis at wilting and the time until death) led to synergistic and antagonistic relationship in a path analysis model. To allow better prediction of species distributions along a wetness gradient, the next step would be to link these physiological traits to more accessible functional traits.

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Predicting leaf traits of herbaceous species from their spectral characteristics.

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Predicting leaf traits of herbaceous species from their spectral characteristics.

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