An official website of the United States government
Plant traits are important for understanding community assembly and ecosystem processes, yet our understanding of intraspecific trait variation (ITV) is limited. This gap in our knowledge is partially because collecting trait data across a species' entire range is impractical, let alone across the ranges of multiple species within a plant family. Using machine learning techniques to predict spatial ITV is an attractive and cost‐effective alternative to sampling across a species range, although this has not been applied beyond regional scales. We compiled a trait database of over 1000 grass species (family: Poaceae), encompassing six key functional traits: specific leaf area (SLA), leaf dry matter content (LDMC), plant height, leaf area, leaf nitrogen (Nmass) and leaf phosphorus content (Pmass). Using a random forest machine learning approach, we predicted local trait values within species' ranges considering climate, soil type, phylogeny, lifespan, and photosynthetic pathway as influential factors. An iterative random forest modeling technique incorporated correlations between traits, resulting in improved model performance (observed versus predicted R range of 0.72–0.91). Our models also highlight the importance of climate in predicting trait variation. For a subset of species (n = 860), we projected trait predictions across their known distribution, informed by expert maps from Royal Botanic Gardens, Kew, to create global maps of ITV for grasses. Such maps have the potential to inform conservation efforts and predictions of grazing and fire dynamics in grasslands worldwide. Overall, our research demonstrates the value and ecological applications of predicting plant traits.
more »
« less
Global intraspecific trait–climate relationships for grasses are linked to a species' typical form and function
Plant traits are useful for predicting how species may respond to environmental change and/or influence ecosystem properties. Understanding the extent to which traits vary within species and across climatic gradients is particularly important for understanding how species may respond to climate change. We explored whether climate drives spatial patterns of intraspecific trait variation for three traits (specific leaf area (SLA), plant height, and leaf nitrogen content (Nmass)) across 122 grass species (family: Poaceae) with a combined distribution across six continents. We tested the hypothesis that the sensitivity (i.e. slope) of intraspecific trait responses to climate across space would be related to the species' typical form and function (e.g. leaf economics, stature and lifespan). We observed both positive and negative intraspecific trait responses to climate with the distribution of slope coefficients across species straddling zero for precipitation, temperature and climate seasonality. As hypothesized, variation in slope coefficients across species was partially explained by leaf economics and lifespan. For example, acquisitive species with nitrogen-rich leaves grew taller and produced leaves with higher SLA in warmer regions compared to species with low Nmass. Compared to perennials, annual grasses invested in leaves with higher SLA yet decreased height and Nmass in regions with high precipitation seasonality (PS). Thus, while the influence of climate on trait expression may at first appear idiosyncratic, variation in trait–climate slope coefficients is at least partially explained by the species' typical form and function. Overall, our results suggest that a species' mean location along one axis of trait variation (e.g. leaf economics) could influence how traits along a separate axis of variation (e.g. plant size) respond to spatial variation in climate.
more »
« less
- Award ID(s):
- 2046733
- PAR ID:
- 10425108
- Date Published:
- Journal Name:
- Ecography
- ISSN:
- 0906-7590
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract Background and Aims The acquisitive–conservative axis of plant ecological strategies results in a pattern of leaf trait covariation that captures the balance between leaf construction costs and plant growth potential. Studies evaluating trait covariation within species are scarcer, and have mostly dealt with variation in response to environmental gradients. Little work has been published on intraspecific patterns of leaf trait covariation in the absence of strong environmental variation. Methods We analysed covariation of four leaf functional traits [specific leaf area (SLA) leaf dry matter content (LDMC), force to tear (Ft) and leaf nitrogen content (Nm)] in six Poaceae and four Fabaceae species common in the dry Chaco forest of Central Argentina, growing in the field and in a common garden. We compared intraspecific covariation patterns (slopes, correlation and effect size) of leaf functional traits with global interspecific covariation patterns. Additionally, we checked for possible climatic and edaphic factors that could affect the intraspecific covariation pattern. Key Results We found negative correlations for the LDMC–SLA, Ft–SLA, LDMC–Nm and Ft–Nm trait pairs. This intraspecific covariation pattern found both in the field and in the common garden and not explained by climatic or edaphic variation in the field follows the expected acquisitive–conservative axis. At the same time, we found quantitative differences in slopes among different species, and between these intraspecific patterns and the interspecific ones. Many of these differences seem to be idiosyncratic, but some appear consistent among species (e.g. all the intraspecific LDMC–SLA and LDMC–Nm slopes tend to be shallower than the global pattern). Conclusions Our study indicates that the acquisitive–conservative leaf functional trait covariation pattern occurs at the intraspecific level even in the absence of relevant environmental variation in the field. This suggests a high degree of variation–covariation in leaf functional traits not driven by environmental variables.more » « less
-
Henn, J (Ed.)Abstract Intraspecific trait variation can influence plant performance in different environments and may thereby determine the ability of individual plants to respond to climate change. However, our understanding of its patterns and environmental drivers across different spatial scales is incomplete, especially in understudied regions like the Arctic.To fill this knowledge gap, we examined above‐ground and below‐ground traits from three shrub taxa expanding across the tundra biome and evaluated their relationships with multiple microenvironmental and macroclimatic factors. The traits reflected plant size and structure (plant height, leaf area and root to shoot ratio), leaf economics (specific leaf area, nitrogen content), and root economics and collaboration with mycorrhizal fungi (specific root length, root tissue density, nitrogen content, and ectomycorrhizal colonisation intensity). We also measured leaf and root δ15N and leaf δ13C to characterise nitrogen source and acquisition pathways and plant water stress. Traits were measured in replicated plots (N = 135) varying in soil microclimate, thaw depth and organic layer thickness established across five sites spanning a macroclimate gradient in northern Alaska. This hierarchical design allowed us to disentangle the independent and combined effects of fine‐scale and broad‐scale factors on intraspecific trait variation.We found substantial intraspecific variation at fine spatial scales for most traits and less variation along the macroclimate gradient and between shrub taxa. Consistent with these patterns, microenvironmental factors, mainly soil moisture and thaw depth, interacted with macroclimate, mainly climatic water deficit, to structure size‐structural and leaf trait variation. In contrast, most root traits responded additively to thaw depth and macroclimate.Synthesis. Our results demonstrate that above‐ground and below‐ground tundra shrub traits respond differently to microenvironmental and macroclimatic variation. These differing responses contribute to substantial trait variation at fine spatial scales and may decouple above‐ground and below‐ground trait responses to climate change.more » « less
-
null (Ed.)Abstract The leaf economics spectrum 1,2 and the global spectrum of plant forms and functions 3 revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species 2 . Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities 4 . However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability 4,5 . Here we derive a set of ecosystem functions 6 from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range of responses to environmental changes in carbon, water and energy cycling in terrestrial ecosystems 7,8 .more » « less
-
Abstract Plant functional traits can predict community assembly and ecosystem functioning and are thus widely used in global models of vegetation dynamics and land–climate feedbacks. Still, we lack a global understanding of how land and climate affect plant traits. A previous global analysis of six traits observed two main axes of variation: (1) size variation at the organ and plant level and (2) leaf economics balancing leaf persistence against plant growth potential. The orthogonality of these two axes suggests they are differently influenced by environmental drivers. We find that these axes persist in a global dataset of 17 traits across more than 20,000 species. We find a dominant joint effect of climate and soil on trait variation. Additional independent climate effects are also observed across most traits, whereas independent soil effects are almost exclusively observed for economics traits. Variation in size traits correlates well with a latitudinal gradient related to water or energy limitation. In contrast, variation in economics traits is better explained by interactions of climate with soil fertility. These findings have the potential to improve our understanding of biodiversity patterns and our predictions of climate change impacts on biogeochemical cycles.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1111/ecog.06586
