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Leaf Economic and Hydraulic Traits Signal Disparate Climate Adaptation Patterns in Two Co-Occurring Woodland Eucalypts.

ABSTRACT: With climate change impacting trees worldwide, enhancing adaptation capacity has become an important goal of provenance translocation strategies for forestry, ecological renovation, and biodiversity conservation. Given that not every species can be studied in detail, it is important to understand the extent to which climate adaptation patterns can be generalised across species, in terms of the selective agents and traits involved. We here compare patterns of genetic-based population (co)variation in leaf economic and hydraulic traits, climate-trait associations, and genomic differentiation of two widespread tree species (Eucalyptus pauciflora and E. ovata). We studied 2-year-old trees growing in a common-garden trial established with progeny from populations of both species, pair-sampled from 22 localities across their overlapping native distribution in Tasmania, Australia. Despite originating from the same climatic gradients, the species differed in their levels of population variance and trait covariance, patterns of population variation within each species were uncorrelated, and the species had different climate-trait associations. Further, the pattern of genomic differentiation among populations was uncorrelated between species, and population differentiation in leaf traits was mostly uncorrelated with genomic differentiation. We discuss hypotheses to explain this decoupling of patterns and propose that the choice of seed provenances for climate-based plantings needs to account for multiple dimensions of climate change unless species-specific information is available.

SUBMITTER: Prober SM

PROVIDER: S-EPMC9320154 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Global climate change is already impacting species and ecosystems across the planet. Trees, although long-lived, are sensitive to changes in climate, including climate extremes. Shifts in tree species' distributions will influence biodiversity and ecosystem function at scales ranging from local to landscape; dry and hot regions will be especially vulnerable. The Australian continent has been especially susceptible to climate change with extreme heat waves, droughts, and flooding in recent years, and this climate trajectory is expected to continue. We sought to understand how climate change may impact Australian ecosystems by modeling distributional changes in eucalypt species, which dominate or codominate most forested ecosystems across Australia. We modeled a representative sample of Eucalyptus and Corymbia species (n = 108, or 14% of all species) using newly available Representative Concentration Pathway (RCP) scenarios developed for the 5th Assessment Report of the IPCC, and bioclimatic and substrate predictor variables. We compared current, 2025, 2055, and 2085 distributions. Overall, Eucalyptus and Corymbia species in the central desert and open woodland regions will be the most affected, losing 20% of their climate space under the mid-range climate scenario and twice that under the extreme scenario. The least affected species, in eastern Australia, are likely to lose 10% of their climate space under the mid-range climate scenario and twice that under the extreme scenario. Range shifts will be lateral as well as polewards, and these east-west transitions will be more significant, reflecting the strong influence of precipitation rather than temperature changes in subtropical and midlatitudes. These net losses, and the direction of shifts and contractions in range, suggest that many species in the eastern and southern seaboards will be pushed toward the continental limit and that large tracts of currently treed landscapes, especially in the continental interior, will change dramatically in terms of species composition and ecosystem structure.

Project description:The leaf economics spectrum (LES) is the leading theory of plant ecological strategies based on functional traits, which explains the trade-off between dry matter investment in leaf structure and the potential rate of resource return, revealing general patterns of leaf economic traits investment for different plant growth types, functional types, or biomes. Prior work has revealed the moderating role of different environmental factors on the LES, but whether the leaf trait bivariate relationships are shifted across climate regions or across continental scales requires further verification. Here we use the Köppen-Geiger climate classification, a very widely used and robust criterion, as a basis for classifying climate regions to explore climatic differences in leaf trait relationships. We compiled five leaf economic traits from a global dataset, including leaf dry matter content (LDMC), specific leaf area (SLA), photosynthesis per unit of leaf dry mass (Amass), leaf nitrogen concentration (Nmass), and leaf phosphorus concentration (Pmass). Moreover, we primarily used the standardized major axis (SMA) analysis to establish leaf trait bivariate relationships and to explore differences in trait relationships across climate regions as well as intercontinental differences within the same climate type. Leaf trait relationships were significantly correlated across almost all subgroups (P < 0.001). However, there was no common slope among different climate zones or climate types and the slopes of the groups fluctuated sharply up and down from the global estimates. The range of variation in the SMA slope of each leaf relationship was as follows: LDMC-SLA relationships (from -0.84 to -0.41); Amass-SLA relationships (from 0.83 to 1.97); Amass-Nmass relationships (from 1.33 to 2.25); Nmass-Pmass relationships (from 0.57 to 1.02). In addition, there was significant slope heterogeneity among continents within the Steppe climate (BS) or the Temperate humid climate (Cf). The shifts of leaf trait relationships in different climate regions provide evidence for environmentally driven differential plant investment in leaf economic traits. Understanding these differences helps to better calibrate various plant-climate models and reminds us that smaller-scale studies may need to be carefully compared with global studies.

Project description:Drought can occur at different times during the grassland growing season, likely having contrasting effects on forage production when happening early or later in the season. However, knowledge about the interacting effects of the timing of drought and the development stage of the vegetation during the growing season is still scarce, thus limiting our ability to accurately predict forage quantity losses. To investigate plant community responses to drought seasonality (early- vs. late-season), we established a drought experiment in two permanent grasslands of the Swiss Jura Mountains that are used for forage production. We measured three plant functional traits, including two leaf traits related to plant economics (specific leaf area, SLA; leaf dry matter content, LDMC) and one hydraulic trait related to physiological function (predicted percentage loss of hydraulic conductance, PLCp), of the most abundant species, and plant above-ground biomass production. Plant species composition was also determined to calculate community-weighted mean (CWM) traits. First, we observed that CWM trait values strongly varied during the growing season. Second, we found that late-season drought had stronger effects on CWM trait values than early-season drought and that the plant hydraulic trait was the most variable functional trait. Using a structural equation model, we also showed that reduction in soil moisture had no direct impacts on above-ground biomass production. Instead, we observed that the drought-induced decrease in above-ground biomass production was mediated by a higher CWM PLCp (i.e. higher risk of hydraulic failure) and lower CWM SLA under drought. Change in CWM SLA in response to drought was the best predictor of community above-ground biomass production. Our findings reveal the importance of drought timing together with the plant trait responses to assess drought impacts on grassland biomass production and suggest that incorporating these factors into mechanistic models could considerably improve predictions of climate change impacts.

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Leaf Economic and Hydraulic Traits Signal Disparate Climate Adaptation Patterns in Two Co-Occurring Woodland Eucalypts.

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