Browsing by Subject "plant functional type"

Now showing 1 - 3 of 3
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    Do evergreen and deciduous tree differ in their effects on soil nitrogen availability
    (Ecological Society of America, 2012) Mueller, Kevin E; Hobbie, Sarah E; Oleksyn, Jacek; Reich, Peter B; Eissenstat, David M
    Evergreen and deciduous plants are widely expected to have different impacts on soil nitrogen (N) availability because of differences in leaf litter chemistry and ensuing effects on net N mineralization (Nmin). We evaluated this hypothesis by compiling published data on net Nmin rates beneath co-occurring stands of evergreen and deciduous trees. The compiled data included 35 sets of co-occurring stands in temperate and boreal forests. Evergreen and deciduous stands did not have consistently divergent effects on net Nmin rates; net Nmin beneath deciduous trees was higher when comparing natural stands (19 contrasts), but equivalent to evergreens in plantations (16 contrasts). We also compared net Nmin rates beneath pairs of co-occurring genera. Most pairs of genera did not differ consistently, i.e., tree species from one genus had higher net Nmin at some sites and lower net Nmin at other sites. Moreover, several common deciduous genera (Acer, Betula, Populus) and deciduous Quercus spp. did not typically have higher net Nmin rates than common evergreen genera (Pinus, Picea). There are several reasons why tree effects on net Nmin are poorly predicted by leaf habit and phylogeny. For example, the amount of N mineralized from decomposing leaves might be less than the amount of N mineralized from organic matter pools that are less affected by leaf litter traits, such as dead roots and soil organic matter. Also, effects of plant traits and plant groups on net Nmin probably depend on site-specific factors such as stand age and soil type.
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    A global method for calculating plant CSR ecological strategies applied across biomes world‐wide
    (Wiley, 2017) Pierce, Simon; Negreiros, Daniel; Cerabolini, Bruno E. L.; Kattge, Jens; Díaz, Sandra; Kleyer, Michael; Shipley, Bill; Wright, Stuart Joseph; Soudzilovskaia, Nadejda A; Onipchenko, Vladimir G.; van Bodegom, Peter M; Frenette-Dussault, Cedric; Weiher, Evan; Pinho, Bruno X; Cornelissen, Johannes H. C.; Grime, John Philip; Thompson, Ken; Hunt, Roderick; Wilson, Peter J,; Buffa, Gabriella; Nyakunga, Oliver C; Reich, Peter B; Caccianiga, Marco; Mangili, Federico; Ceriani, Roberta M; Luzzaro, Alessandra; Brusa, Guido; Siefert, Andrew; Barbosa, Newton P. U.; Chapin, Francis Stuart, III; Cornwell, William K; Fang, Jingyun; Fernandes, Geraldo Wilson; Garnier, Eric; Le Stradic, Soizig; Peñuelas, Josep; Melo, Felipe P. L.; Slaviero, Antonio; Tabarelli, Marcelo; Tampucci, Duccio
    Competitor, stress-tolerator, ruderal (CSR) theory is a prominent plant functional strategy scheme previously applied to local floras. Globally, the wide geographic and phylogenetic coverage of available values of leaf area (LA), leaf dry matter content (LDMC) and specific leaf area (SLA) (representing, respectively, interspecific variation in plant size and conservative vs. acquisitive resource economics) promises the general application of CSR strategies across biomes, including the tropical forests hosting a large proportion of Earth's diversity. We used trait variation for 3068 tracheophytes (representing 198 families, six continents and 14 biomes) to create a globally calibrated CSR strategy calculator tool and investigate strategy–environment relationships across biomes world-wide. Due to disparity in trait availability globally, co-inertia analysis was used to check correspondence between a ‘wide geographic coverage, few traits’ data set and a ‘restricted coverage, many traits’ subset of 371 species for which 14 whole-plant, flowering, seed and leaf traits (including leaf nitrogen content) were available. CSR strategy/environment relationships within biomes were investigated using fourth-corner and RLQ analyses to determine strategy/climate specializations. Strong, significant concordance (RV = 0·597; P < 0·0001) was evident between the 14 trait multivariate space and when only LA, LDMC and SLA were used. Biomes such as tropical moist broadleaf forests exhibited strategy convergence (i.e. clustered around a CS/CSR median; C:S:R = 43:42:15%), with CS-selection associated with warm, stable situations (lesser temperature seasonality), with greater annual precipitation and potential evapotranspiration. Other biomes were characterized by strategy divergence: for example, deserts varied between xeromorphic perennials such as Larrea divaricata, classified as S-selected (C:S:R = 1:99:0%) and broadly R-selected annual herbs (e.g. Claytonia perfoliata; R/CR-selected; C:S:R = 21:0:79%). Strategy convergence was evident for several growth habits (e.g. trees) but not others (forbs). The CSR strategies of vascular plants can now be compared quantitatively within and between biomes at the global scale. Through known linkages between underlying leaf traits and growth rates, herbivory and decomposition rates, this method and the strategy–environment relationships it elucidates will help to predict which kinds of species may assemble in response to changes in biogeochemical cycles, climate and land use.
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    Predicting leaf functional traits from simple plant and climate attributers using the GLOPNET global data set
    (2007) Reich, Peter B; Wright, Ian J; Lusk, Christopher H
    Knowledge of leaf chemistry, physiology, and life span is essential for global vegetation modeling, but such data are scarce or lacking for some regions, especially in developing countries. Here we use data from 2021 species at 175 sites around the world from the GLOPNET compilation to show that key physiological traits that are difficult to measure (such as photosynthetic capacity) can be predicted from simple qualitative plant characteristics, climate information, easily measured (“soft”) leaf traits, or all of these in combination. The qualitative plant functional type (PFT) attributes examined are phylogeny (angiosperm or gymnosperm), growth form (grass, herb, shrub, or tree), and leaf phenology (deciduous vs. evergreen). These three PFT attributes explain between one-third and two-thirds of the variation in each of five quantitative leaf ecophysiological traits: specific leaf area (SLA), leaf life span, mass-based net photosynthetic capacity (Amass), nitrogen content (Nmass), and phosphorus content (Pmass). Alternatively, the combination of four simple, widely available climate metrics (mean annual temperature, mean annual precipitation, mean vapor pressure deficit, and solar irradiance) explain only 5–20% of the variation in those same five leaf traits. Adding the climate metrics to the qualitative PFTs as independent factors in the model increases explanatory power by 3–11% for the five traits. If a single easily measured leaf trait (SLA) is also included in the model along with qualitative plant traits and climate metrics, an additional 5–25% of the variation in the other four other leaf traits is explained, with the models accounting for 62%, 65%, 66%, and 73% of global variation in Nmass, Pmass, Amass, and leaf life span, respectively. Given the wide availability of the summary climate data and qualitative PFT data used in these analyses, they could be used to explain roughly half of global variation in the less accessible leaf traits (Amass, leaf life span, Nmass, Pmass); this can be augmented to two-thirds of all variation if climatic and PFT data are used in combination with the readily measured trait SLA. This shows encouraging possibilities of progress in developing general predictive equations for macro-ecology, global scaling, and global modeling.