Consistent Grime’s CSR Strategy of Daisy Fleabane Erigeron annuus (L.) Pers. despite Its High Morphological Variability—A Case Study from Zagreb and Medvednica Mt., Croatia

Alongside the direct destruction of natural habitats and changes in land use, invasive species are considered one of the greatest threats to global biodiversity. Daisy fleabane Erigeron annuus (L.) Pers. is among the most widespread invasive plants in Croatia. Invasions of E. annuus may be aided by morphological variability, which this study investigates. The variability of life traits (stem height, fresh and dry leaf mass, length, width and leaf area, specific leaf area, and leaf dry matter content) was examined among 18 locations throughout Zagreb and Medvednica Mt. Overall, 87 plant specimens and 435 leaves were measured and analysed using univariate and multivariate statistics. Viable populations were recorded in diverse habitat types, mostly with marked human impact. We determined Grime’s CR plant life strategies for all, except for two localities with C/CR plant strategies. Two populations with a more pronounced competitive strategy had high leaf dry matter content, with smaller leaves and medium height stems. Significant differences between the localities were found, with the specific leaf area (SLA) and plant height being the most diverse. Despite its high morphological variability, daisy fleabane had a consistent CSR strategy, which likely enables its widespread invasions across variable habitats.

Leaf functional traits differentiation in relation to covering materials of urban tree pits

Background Understanding the ecological strategies of urban trees to the urban environment is crucial to the selection and management of urban trees. However, it is still unclear whether urban tree pit cover will affect plant functional traits. Here, we study the response of urban trees to different tree pit covers, analyzed the effects of different cover types on soil properties and their trade-off strategies based on leaf functional traits. Results We found that there were obvious differences in the physical properties of the soil in different tree pit covers. Under the different tree pit cover types, soil bulk density and soil porosity reached the maximum under cement cover and turf cover, respectively. We found that tree pit cover significantly affected the leaf properties of urban trees. Leaf thickness, chlorophyll content index and stomatal density were mainly affected by soil bulk density and non-capillary porosity in a positive direction, and were affected by soil total porosity and capillary porosity in a negative direction. Leaf dry matter content and stomata area were mainly negatively affected by soil bulk density and non-capillary porosity, and positively affected by soil total porosity and capillary porosity. Covering materials of tree pits promoted the functional adjustment of plants and form the best combination of functions. Conclusion Under the influence of tree pit cover, plant have low specific leaf area, stomata density, high leaf thickness, chlorophyll content index, leaf dry matter content, leaf tissue density and stomata area, which belong to “quick investment-return” type in the leaf economics spectrum.

Leaf Functional Traits Differentiation and Its Trade-off Strategies of Urban Plant are Related to Atmospheric Particulate Pollution

Background: Functional trait-based ecological research has been instrumental in advancing our understanding of understanding of environmental changes. It is still, however, unclear how the functional traits of urban plants respond to atmospheric particulate pollution, and what trade-off strategies are shown. In order to explore the variation of plant functional traits with urban atmospheric particulate pollution gradient, we divided atmospheric particulate pollution into three levels according to road distance, and measured the variation of six key leaf functional traits and their trade-off strategies. Results: Here, we show that the functional traits of plants can be used as predictors or indicators of the response of plant to urban atmospheric particulate pollution. Within studies, there was a positive correlation between leaf thickness, leaf dry matter content, leaf tissue density, stomata density and leaf dust deposition. While chlorophyll content index and specific leaf area were negatively correlated with the leaf dust deposition. Plants improve the efficiency of gas exchange by optimizing the spatial distribution of stomata of leaves. Dust deposition promotes the regular distribution of stomata. Due to the pressure of atmospheric particles, urban plant shows a trade-off relationship of economics spectrum traits at the leaf level. Taken together, these results indicate that urban atmospheric particulate pollution is the main factor causing the variation of plant functional traits. Conclusion：Under the influence of urban atmospheric particulate matter, plant show a "slow investment-return" type in the global leaf economics spectrum, with lower specific leaf area, lower chlorophyll content, larger leaf thickness, higher leaf dry matter content, higher leaf tissue density and higher stomatal density. This finding provides a new perspective for understanding the resource trades-off strategy of plants adapting to air pollution environment.

Contrasting patterns of intraspecific trait variability in native and non-native plant species along an elevational gradient on Tenerife, Canary Islands

Background and Aims Non-native plant species are not restricted to lowlands, but increasingly are invading high elevations. While for both native and non-native species we expected variability of plant functional traits due to the changing environmental conditions along elevational gradients, we additionally assumed that non-native species are characterized by a more acquisitive growth strategy, as traits reflecting such a strategy have been found to correlate with invasion success. Furthermore, the typical lowland introduction of non-native species coming from multiple origins should lead to higher trait variability within populations of non-native species specifically at low elevations, and they might therefore occupy a larger total trait space. Methods Along an elevational gradient ranging from 55 to 1925 m a.s.l. on Tenerife, we collected leaves from eight replicate individuals in eight evenly distributed populations of five native and six non-native forb species. In each population, we measured ten eco-morphological and leaf biochemical traits and calculated trait variability within each population and the total trait space occupied by native and non-native species. Key Results We found both positive (e.g. leaf dry matter content) and negative (e.g. leaf N) correlations with elevation for native species, but only few responses for non-native species. For non-native species, within-population variability of leaf dry matter content and specific leaf area decreased with elevation, but increased for native species. The total trait space occupied by all non-native species was smaller than and a subset of that of native species. Conclusions We found little evidence that intraspecific trait variability is associated with the success of non-native species to spread towards higher elevations. Instead, for non-native species, our results indicate that intermediate trait values that meet the requirements of various conditions are favourable across the changing environmental conditions along elevational gradients. As a consequence, this might prevent non-native species from overcoming abruptly changing environmental conditions, such as when crossing the treeline.

Reliability of leaf functional traits after delayed measurements

In this study, the effect of temporary storage (at 4°C) on measurement of leaf traits was tested. We collected leaf samples from 25 species, which represented different functional types in the high altitude vegetation of western Himalaya, to measure leaf area (LA), leaf rehydration, specific leaf area (SLA) and leaf dry matter content (LDMC). Repeated trait measurements were performed for up to 7 days. We found that in all the species, LA increased in initial 24 h of rehydration and thereafter remained stable. Leaf rehydration was found to be sensitive to delayed measurements and changed significantly for up to 7 days. For SLA and LDMC, the effect of storage time was significant only for a few species. On the basis of our findings, we recommend that, for samples stored in dark at 4°C, LA, SLA and LDMC can reliably be estimated after a delay of up to 7 days. Further, these key leaf traits should be estimated only after 24 h of rehydration. Also, trait measurements after prolonged rehydration of leaves should be avoided. Outcomes of this study will be beneficial when a large number of samples are collected from locations far away from laboratory and temporary storage is necessitated before trait measurements.

Alleviation of Plant Stress Precedes Termination of Rich Fen Stages in Peat Profiles of Lowland Mires

Mesotrophic rich fens, that is, groundwater-fed mires, may be long-lasting, as well as transient ecosystems, displaced in time by poor fens, bogs, forests or eutrophic reeds. We hypothesized that fen stability is controlled by plant stress caused by waterlogging with calcium-rich and nutrient-poor groundwater, which limits expansion of hummock mosses, tussock sedges and trees. We analysed 32 European Holocene macrofossil profiles of rich fens using plant functional traits (PFTs) which indicate the level of plant stress in the environment: canopy height, clonal spread, diaspore mass, specific leaf area, leaf dry matter content, Ellenberg moisture value, hummock-forming ability, mycorrhizal status and plant functional groups. Six PFTs, which formed long-term significant trends during mire development, were compiled as rich fen stress indicator (RFSI). We found that RFSI values at the start of fen development were correlated with the thickness of subsequently accumulated rich fen peat. RFSI declined in fens approaching change into another mire type, regardless whether it was shifting into bog, forest or eutrophic reeds. RFSI remained comparatively high and stable in three rich fens, which have not terminated naturally until present times. By applying PFT analysis to macrofossil data, we demonstrated that fens may undergo a gradual autogenic process, which lowers the ecosystem’s resistance and enhances shifts to other mire types. Long-lasting rich fens, documented by deep peat deposits, are rare. Because autogenic processes tend to alleviate stress in fens, high levels of stress are needed at initial stages of rich fen development to enable its long persistence and continuous peat accumulation.

Validating the Predictive Power of Statistical Models in Retrieving Leaf Dry Matter Content of a Coastal Wetland from a Sentinel-2 Image

Leaf dry matter content (LDMC), the ratio of leaf dry mass to its fresh mass, is a key plant trait, which is an indicator for many critical aspects of plant growth and survival. Accurate and fast detection of the spatiotemporal dynamics of LDMC would help understanding plants’ carbon assimilation and relative growth rate, and may then be used as an input for vegetation process models to monitor ecosystems. Satellite remote sensing is an effective tool for predicting such plant traits non-destructively. However, studies on the applicability of remote sensing for LDMC retrieval are scarce. Only a few studies have looked into the practicality of using remotely sensed data for the prediction of LDMC in a forest ecosystem. In this study, we assessed the performance of partial least squares regression (PLSR) plus 11 widely used vegetation indices (VIs), calculated based on different combinations of Sentinel-2 bands, in predicting LDMC in a coastal wetland. The accuracy of the selected methods was validated using LDMC, destructively measured in 50 randomly distributed sample plots at the study site in Schiermonnikoog, the Netherlands. The PLSR applied to canopy reflectance of Sentinel-2 bands resulted in accurate prediction of LDMC (coefficient of determination (R2) = 0.71, RMSE = 0.033). PLSR applied to the studied VIs provided an R2 of 0.70 and RMSE of 0.033. Four vegetation indices (enhanced vegetation index(EVI), specific leaf area vegetation index (SLAVI), simple ratio vegetation index (SRVI), and visible atmospherically resistant index (VARI)) computed using band 3 (green) and band 11 of the Sentinel-2 performed equally well and achieved a good measure of accuracy (R2 = 0.67, RMSE = 0.034). Our findings demonstrate the feasibility of using Sentinel-2 surface reflectance data to map LDMC in a coastal wetland.