Plant species phenology differs between climate and land-use scenarios and relates to plant functional traits.

Phenological shifts due to changing climate are often highly species and context specific. Land-use practices such as mowing or grazing directly affect the phenology of grassland species, but it is unclear if plants are similarly affected by climate change in differently managed grassland systems such as meadows and pastures. Functional traits have a high potential to explain phenological shifts and might help to understand species-specific and land-use-specific phenological responses to changes in climate. In the large-scale field experiment Global Change Experimental Facility (GCEF), we monitored the first flowering day, last flowering day, flowering duration, and day of peak flowering, of 17 herbaceous grassland species under ambient and future climate conditions, comparing meadows and pastures. Both climate and land use impacted the flowering phenology of plant species in species-specific ways. We did not find evidence for interacting effects of climate and land-use type on plant phenology. However, the data indicate that microclimatic and microsite conditions on meadows and pastures were differently affected by future climate, making differential effects on meadows and pastures likely. Functional traits, including the phenological niche and grassland utilization indicator values, explained species-specific phenological climate responses. Late flowering species and species with a low mowing tolerance advanced their flowering more strongly under future climate. Long flowering species and species following an acquisitive strategy (high specific leaf area, high mowing tolerance, and high forage value) advanced their flowering end more strongly and thus more strongly shortened their flowering under future climate. We associated these trait-response relationships primarily with a phenological drought escape during summer. Our results provide novel insights on how climate and land use impact the flowering phenology of grassland species and we highlight the role of functional traits in mediating phenological responses to climate.

Using near-infrared spectroscopy to predict nitrogen and phosphorus concentrations of herbarium specimens under different storage conditions.

BACKGROUND: Herbaria are becoming increasingly important as archives of biodiversity, and play a central role in taxonomic and biogeographic studies. There is also an ongoing interest in functional traits and the way they mediate interactions between a plant species and its environment. Herbarium specimens allow tracking trait values over time, and thus, capturing consequences of anthropogenic activities such as eutrophication. Here, we present an open, reproducible, non-destructive workflow to collect leaf trait data from herbarium specimens using near-infrared spectroscopy (NIRS), and a proof of concept for the reliability of this approach. RESULTS: We carried out three experiments to test the suitability of non-destructive NIRS methods to predict leaf traits both for fresh and dried leaves: (1) With a fertilization experiment, we studied whether NIRS was able to capture changes in leaf N and leaf P during a fertilization experiment and we compared contents predicted by NIRS with results obtained from regular wet lab methods. Calibration models for leaf nitrogen and phosphorus contents had a quality of R2 = 0.7 and 0.5, respectively. We fitted calibration models for NIRS readings on fresh and dried leaf samples, both of which produced equally precise predictions compared to results from wet lab analyses. (2) We tested the effect of herbarium conservation on NIRS readings by simulating them through the application of six treatments combining freezing, drying and pesticide spraying in a factorial scheme and comparing these with untreated samples. No consistent changes were observed in the spectra quality before and after the simulated herbarium conditions. (3) Finally, we studied the effect of specimen storage duration using specimens from a 2018 study which were re-analyzed and compared with spectra obtained in 2021. No consistent changes in spectra were observed after the storage period. CONCLUSIONS: The results demonstrate the reliability of NIRS to measure leaf N and P on herbarium samples. Together with the calibration method and dataset presented here, they provide a toolset allowing researchers to study the development of leaf traits and their response to environmental changes over decades and even centuries in a fast and non-destructive manner.

Spatial variability in herbaceous plant phenology is mostly explained by variability in temperature but also by photoperiod and functional traits.

Whereas temporal variability of plant phenology in response to climate change has already been well studied, the spatial variability of phenology is not well understood. Given that phenological shifts may affect biotic interactions, there is a need to investigate how the variability in environmental factors relates to the spatial variability in herbaceous species' phenology by at the same time considering their functional traits to predict their general and species-specific responses to future climate change. In this project, we analysed phenology records of 148 herbaceous species, which were observed for a single year by the PhenObs network in 15 botanical gardens. For each species, we characterised the spatial variability in six different phenological stages across gardens. We used boosted regression trees to link these variabilities in phenology to the variability in environmental parameters (temperature, latitude and local habitat conditions) as well as species traits (seed mass, vegetative height, specific leaf area and temporal niche) hypothesised to be related to phenology variability. We found that spatial variability in the phenology of herbaceous species was mainly driven by the variability in temperature but also photoperiod was an important driving factor for some phenological stages. In addition, we found that early-flowering and less competitive species characterised by small specific leaf area and vegetative height were more variable in their phenology. Our findings contribute to the field of phenology by showing that besides temperature, photoperiod and functional traits are important to be included when spatial variability of herbaceous species is investigated.

Bridging the gap: how to adopt opportunistic plant observations for phenology monitoring.

Plant phenology plays a vital role in assessing climate change. To monitor this, individual plants are traditionally visited and observed by trained volunteers organized in national or international networks - in Germany, for example, by the German Weather Service, DWD. However, their number of observers is continuously decreasing. In this study, we explore the feasibility of using opportunistically captured plant observations, collected via the plant identification app Flora Incognita to determine the onset of flowering and, based on that, create interpolation maps comparable to those of the DWD. Therefore, the opportunistic observations of 17 species collected in 2020 and 2021 were assigned to "Flora Incognita stations" based on location and altitude in order to mimic the network of stations forming the data basis for the interpolation conducted by the DWD. From the distribution of observations, the percentile representing onset of flowering date was calculated using a parametric bootstrapping approach and then interpolated following the same process as applied by the DWD. Our results show that for frequently observed, herbaceous and conspicuous species, the patterns of onset of flowering were similar and comparable between both data sources. We argue that a prominent flowering stage is crucial for accurately determining the onset of flowering from opportunistic plant observations, and we discuss additional factors, such as species distribution, location bias and societal events contributing to the differences among species and phenology data. In conclusion, our study demonstrates that the phenological monitoring of certain species can benefit from incorporating opportunistic plant observations. Furthermore, we highlight the potential to expand the taxonomic range of monitored species for phenological stage assessment through opportunistic plant observation data.

Artificial light at night decreases plant diversity and performance in experimental grassland communities.

Artificial light at night (ALAN) affects many areas of the world and is increasing globally. To date, there has been limited and inconsistent evidence regarding the consequences of ALAN for plant communities, as well as for the fitness of their constituent species. ALAN could be beneficial for plants as they need light as energy source, but they also need darkness for regeneration and growth. We created model communities composed of 16 plant species sown, exposed to a gradient of ALAN ranging from 'moonlight only' to conditions like situations typically found directly underneath a streetlamp. We measured plant community composition and its production (biomass), as well as functional traits of three plant species from different functional groups (grasses, herbs, legumes) in two separate harvests. We found that biomass was reduced by 33% in the highest ALAN treatment compared to the control, Shannon diversity decreased by 43% and evenness by 34% in the first harvest. Some species failed to establish in the second harvest. Specific leaf area, leaf dry matter content and leaf hairiness responded to ALAN. These responses suggest that plant communities will be sensitive to increasing ALAN, and they flag a need for plant conservation activities that consider impending ALAN scenarios. This article is part of the theme issue 'Light pollution in complex ecological systems'.

Ecosystem consequences of invertebrate decline.

Human activities cause substantial changes in biodiversity.1,2 Despite ongoing concern about the implications of invertebrate decline,3,4,5,6,7 few empirical studies have examined the ecosystem consequences of invertebrate biomass loss. Here, we test the responses of six ecosystem services informed by 30 above- and belowground ecosystem variables to three levels of aboveground (i.e., vegetation associated) invertebrate community biomass (100%, 36%, and 0% of ambient biomass) in experimental grassland mesocosms in a controlled Ecotron facility. In line with recent reports on invertebrate biomass loss over the last decade, our 36% biomass treatment also represented a decrease in invertebrate abundance (-70%) and richness (-44%). Moreover, we simulated the pronounced change in invertebrate biomass and turnover in community composition across the season. We found that the loss of invertebrate biomass decreases ecosystem multifunctionality, including two critical ecosystem services, aboveground pest control and belowground decomposition, while harvested plant biomass increases, likely because less energy was channeled up the food chain. Moreover, communities and ecosystem functions become decoupled with a lower biomass of invertebrates. Our study shows that invertebrate loss threatens the integrity of grasslands by decoupling ecosystem processes and decreasing ecosystem-service supply.

Population size affected by environmental variability impacts genetics, traits, and plant performance in Trifolium montanum L.

Population size, genetic diversity, and performance have fundamental importance for ecology, evolution, and nature conservation of plant species. Despite well-studied relationships among environmental, genetic, and intraspecific trait variation (ITV), the influence of population size on these aspects is less understood. To assess the sources of population size variation, but also its impact on genetic, functional trait, and performance aspects, we conducted detailed population size estimations, assessed 23 abiotic and biotic environmental habitat factors, performed population genetic analyses using nine microsatellite markers, and recorded nine functional traits based on 260 Trifolium montanum individuals from 13 semi-dry grassland locations of Central Europe. Modern statistical analyses based on a multivariate framework (path analysis) with preselected linear regression models revealed that the variation of abiotic factors (in contrast to factors per se) almost completely, significantly explained fluctuations in population size (R 2 = .93). In general, abiotic habitat variation (heterogeneity) was not affected by habitat area. Population size significantly explained genetic diversity (N A: R 2 = .42, H o: R 2 = .67, H e: R 2 = .43, and I: R 2 = .59), inbreeding (F IS: R 2 = .35), and differentiation (G ST: R 2 = .20). We also found that iFDCV (ITV) was significantly explained by abiotic habitat heterogeneity, and to a lesser extent by genetic diversity H e (R 2 = .81). Nevertheless, habitat heterogeneity did not statistically affect genetic diversity. This may be due to the use of selectively neutral microsatellite markers, and possibly by insufficient abiotic selective pressures on habitats examined. Small T. montanum populations in nonoptimal habitats were characterized by reduced genetic and functional trait diversity, and elevated genetic inbreeding and differentiation. This indicates reduced adaptability to current and future environmental changes. The long-term survival of small populations with reduced genetic diversity and beginning inbreeding will be highly dependent on habitat protection and adequate land-use actions.

Functional rarity of plants in German hay meadows - Patterns on the species level and mismatches with community species richness.

Functional rarity (FR) - a feature combining a species' rarity with the distinctiveness of its traits - is a promising tool to better understand the ecological importance of rare species and consequently to protect functional diversity more efficiently. However, we lack a systematic understanding of FR on both the species level (which species are functionally rare and why) and the community level (how is FR associated with biodiversity and environmental conditions). Here, we quantify FR for 218 plant species from German hay meadows on a local, regional, and national scale by combining data from 6500 vegetation relevés and 15 ecologically relevant traits. We investigate the association between rarity and trait distinctiveness on different spatial scales via correlation measures and show which traits lead to low or high trait distinctiveness via distance-based redundancy analysis. We test how species richness and FR are correlated, and use boosted regression trees to determine environmental conditions that are driving species richness and FR. On the local scale, only rare species showed high trait distinctiveness while on larger spatial scales rare and common species showed high trait distinctiveness. As infrequent trait attributes (e.g., legumes, low clonality) led to higher trait distinctiveness, we argue that functionally rare species are either specialists or transients. While specialists occupy a particular niche in hay meadows leading to lower rarity on larger spatial scales, transients display distinct but maladaptive traits resulting in high rarity across all spatial scales. More functionally rare species than expected by chance occurred in species-poor communities indicating that they prefer environmental conditions differing from characteristic conditions of species-rich hay meadows. Finally, we argue that functionally rare species are not necessarily relevant for nature conservation because many were transients from surrounding habitats. However, FR can facilitate our understanding of why species are rare in a habitat and under which conditions these species occur.

The potential of multispectral imaging flow cytometry for environmental monitoring.

Environmental monitoring involves the quantification of microscopic cells and particles such as algae, plant cells, pollen, or fungal spores. Traditional methods using conventional microscopy require expert knowledge, are time-intensive and not well-suited for automated high throughput. Multispectral imaging flow cytometry (MIFC) allows measurement of up to 5000 particles per second from a fluid suspension and can simultaneously capture up to 12 images of every single particle for brightfield and different spectral ranges, with up to 60x magnification. The high throughput of MIFC has high potential for increasing the amount and accuracy of environmental monitoring, such as for plant-pollinator interactions, fossil samples, air, water or food quality that currently rely on manual microscopic methods. Automated recognition of particles and cells is also possible, when MIFC is combined with deep-learning computational techniques. Furthermore, various fluorescence dyes can be used to stain specific parts of the cell to highlight physiological and chemical features including: vitality of pollen or algae, allergen content of individual pollen, surface chemical composition (carbohydrate coating) of cells, DNA- or enzyme-activity staining. Here, we outline the great potential for MIFC in environmental research for a variety of research fields and focal organisms. In addition, we provide best practice recommendations.

Functional traits influence patterns in vegetative and reproductive plant phenology - a multi-botanical garden study.

Phenology has emerged as key indicator of the biological impacts of climate change, yet the role of functional traits constraining variation in herbaceous species' phenology has received little attention. Botanical gardens are ideal places in which to investigate large numbers of species growing under common climate conditions. We ask whether interspecific variation in plant phenology is influenced by differences in functional traits. We recorded onset, end, duration and intensity of initial growth, leafing out, leaf senescence, flowering and fruiting for 212 species across five botanical gardens in Germany. We measured functional traits, including plant height, absolute and specific leaf area, leaf dry matter content, leaf carbon and nitrogen content and seed mass and accounted for species' relatedness. Closely related species showed greater similarities in timing of phenological events than expected by chance, but species' traits had a high degree of explanatory power, pointing to paramount importance of species' life-history strategies. Taller plants showed later timing of initial growth, and flowered, fruited and underwent leaf senescence later. Large-leaved species had shorter flowering and fruiting durations. Taller, large-leaved species differ in their phenology and are more competitive than smaller, small-leaved species. We assume climate warming will change plant communities' competitive hierarchies with consequences for biodiversity.

Climatic and soil factors explain the two-dimensional spectrum of global plant trait variation.

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.

Starch and lipid storage strategies in tropical trees relate to growth and mortality.

Non-structural carbon (NSC) storage (i.e. starch, soluble sugras and lipids) in tree stems play important roles in metabolism and growth. Their spatial distribution in wood may explain species-specific differences in carbon storage dynamics, growth and survival. However, quantitative information on the spatial distribution of starch and lipids in wood is sparse due to methodological limitations. Here we assessed differences in wood NSC and lipid storage between tropical tree species with different growth and mortality rates and contrasting functional types. We measured starch and soluble sugars in wood cores up to 4 cm deep into the stem using standard chemical quantification methods and histological slices stained with Lugol's iodine. We also detected neutral lipids using histological slices stained with Oil-Red-O. The histological method allowed us to group individuals into two categories according to their starch storage strategy: fiber-storing trees and parenchyma-storing trees. The first group had a bigger starch pool, slower growth and lower mortality rates than the second group. Lipid storage was found in wood parenchyma in five species and was related to low mortality rates. The quantification of the spatial distribution of starch and lipids in wood improves our understanding of NSC dynamics in trees and reveals additional dimensions of tree growth and survival strategies.

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.

Invertebrate Decline Leads to Shifts in Plant Species Abundance and Phenology.

Climate and land-use change lead to decreasing invertebrate biomass and alter invertebrate communities. These biotic changes may affect plant species abundance and phenology. Using 24 controlled experimental units in the iDiv Ecotron, we assessed the effects of invertebrate decline on an artificial grassland community formed by 12 herbaceous plant species. More specifically, we used Malaise traps and sweep nets to collect invertebrates from a local tall oatgrass meadow and included them in our Ecotron units at two different invertebrate densities: 100% (no invertebrate decline) and 25% (invertebrate decline of 75%). Another eight EcoUnits received no fauna and served as a control. Plant species abundance and flowering phenology was observed weekly over a period of 18 weeks. Our results showed that invertebrate densities affected the abundance and phenology of plant species. We observed a distinct species abundance shift with respect to the invertebrate treatment. Notably, this shift included a reduction in the abundance of the dominant plant species, Trifolium pratense, when invertebrates were present. Additionally, we found that the species shifted their flowering phenology as a response to the different invertebrate treatments, e.g. with decreasing invertebrate biomass Lotus corniculatus showed a later peak flowering time. We demonstrated that in addition to already well-studied abiotic drivers, biotic components may also drive phenological changes in plant communities. This study clearly suggests that invertebrate decline may contribute to already observed mismatches between plants and animals, with potential negative consequences for ecosystem services like food provision and pollination success. This deterioration of ecosystem function could enhance the loss of insects and plant biodiversity.

Plant intraspecific functional trait variation is related to within-habitat heterogeneity and genetic diversity in Trifolium montanum L.

Intraspecific trait variation (ITV), based on available genetic diversity, is one of the major means plant populations can respond to environmental variability. The study of functional trait variation and diversity has become popular in ecological research, for example, as a proxy for plant performance influencing fitness. Up to now, it is unclear which aspects of intraspecific functional trait variation (iFDCV) can be attributed to the environment or genetics under natural conditions. Here, we examined 260 individuals from 13 locations of the rare (semi-)dry calcareous grassland species Trifolium montanum L. in terms of iFDCV, within-habitat heterogeneity, and genetic diversity. The iFDCV was assessed by measuring functional traits (releasing height, biomass, leaf area, specific leaf area, leaf dry matter content, Fv/Fm, performance index, stomatal pore surface, and stomatal pore area index). Abiotic within-habitat heterogeneity was derived from altitude, slope exposure, slope, leaf area index, soil depth, and further soil factors. Based on microsatellites, we calculated expected heterozygosity (He) because it best-explained, among other indices, iFDCV. We performed multiple linear regression models quantifying relationships among iFDCV, abiotic within-habitat heterogeneity and genetic diversity, and also between separate functional traits and abiotic within-habitat heterogeneity or genetic diversity. We found that abiotic within-habitat heterogeneity influenced iFDCV twice as strong compared to genetic diversity. Both aspects together explained 77% of variation in iFDCV ( R adj 2  = .77, F 2, 10 = 21.66, p < .001). The majority of functional traits (releasing height, biomass, specific leaf area, leaf dry matter content, Fv/Fm, and performance index) were related to abiotic habitat conditions indicating responses to environmental heterogeneity. In contrast, only morphology-related functional traits (releasing height, biomass, and leaf area) were related to genetics. Our results suggest that both within-habitat heterogeneity and genetic diversity affect iFDCV and are thus crucial to consider when aiming to understand or predict changes of plant species performance under changing environmental conditions.

Nutrients and water availability constrain the seasonality of vegetation activity in a Mediterranean ecosystem.

Anthropogenic nitrogen (N) deposition and resulting differences in ecosystem N and phosphorus (P) ratios are expected to impact photosynthetic capacity, that is, maximum gross primary productivity (GPPmax ). However, the interplay between N and P availability with other critical resources on seasonal dynamics of ecosystem productivity remains largely unknown. In a Mediterranean tree-grass ecosystem, we established three landscape-level (24 ha) nutrient addition treatments: N addition (NT), N and P addition (NPT), and a control site (CT). We analyzed the response of ecosystem to altered nutrient stoichiometry using eddy covariance fluxes measurements, satellite observations, and digital repeat photography. A set of metrics, including phenological transition dates (PTDs; timing of green-up and dry-down), slopes during green-up and dry-down period, and seasonal amplitude, were extracted from time series of GPPmax and used to represent the seasonality of vegetation activity. The seasonal amplitude of GPPmax was higher for NT and NPT than CT, which was attributed to changes in structure and physiology induced by fertilization. PTDs were mainly driven by rainfall and exhibited no significant differences among treatments during the green-up period. Yet, both fertilized sites senesced earlier during the dry-down period (17-19 days), which was more pronounced in the NT due to larger evapotranspiration and water usage. Fertilization also resulted in a faster increase in GPPmax during the green-up period and a sharper decline in GPPmax during the dry-down period, with less prominent decline response in NPT. Overall, we demonstrated seasonality of vegetation activity was altered after fertilization and the importance of nutrient-water interaction in such water-limited ecosystems. With the projected warming-drying trend, the positive effects of N fertilization induced by N deposition on GPPmax may be counteracted by an earlier and faster dry-down in particular in areas where the N:P ratio increases, with potential impact on the carbon cycle of water-limited ecosystems.

Grazing effects on intraspecific trait variability vary with changing precipitation patterns in Mongolian rangelands.

Functional traits are proxies for plant physiology and performance, which do not only differ between species but also within species. In this work, we hypothesized that (a) with increasing precipitation, the percentage of focal species which significantly respond to changes in grazing intensity increases, while under dry conditions, climate-induced stress is so high that plant species hardly respond to any changes in grazing intensity and that (b) the magnitude with which species change their trait values in response to grazing, reflected by coefficients of variation (CVs), increases with increasing precipitation. Chosen plant traits were canopy height, plant width, specific leaf area (SLA), chlorophyll fluorescence, performance index, stomatal pore area index (SPI), and individual aboveground biomass of 15 species along a precipitation gradient with different grazing intensities in Mongolian rangelands. We used linear models for each trait to assess whether the percentage of species that respond to grazing changes along the precipitation gradient. To test the second hypothesis, we assessed the magnitude of intraspecific trait variability (ITV) response to grazing, per species, trait, and precipitation level by calculating CVs across the different grazing intensities. ITV was most prominent for SLA and SPI under highest precipitation, confirming our first hypothesis. Accordingly, CVs of canopy height, SPI, and SLA increased with increasing precipitation, partly confirming our second hypothesis. CVs of the species over all traits increased with increasing precipitation only for three species. This study shows that it remains challenging to predict how plant performance will shift under changing environmental conditions based on their traits alone. In this context, the implications for the use of community-weighted mean trait values are discussed, as not only species abundances change in response to changing environmental conditions, but also values of traits considerably change. Including this aspect in further studies will improve our understanding of processes acting within and among communities.

Probability distributions of nonstructural carbon ages and transit times provide insights into carbon allocation dynamics of mature trees.

●In trees, the use of nonstructural carbon (NSC) under limiting conditions impacts the age structure of the NSC pools. We compared model predictions of NSC ages and transit times for Pinus halepensis, Acer rubrum and Pinus taeda, to understand differences in carbon (C) storage dynamics in species with different leaf phenology and growth environments. ●We used two C allocation models from the literature to estimate the NSC age and transit time distributions, to simulate C limitation, and to evaluate the sensitivity of the mean ages to changes in allocation fluxes. ●Differences in allocation resulted in different NSC age and transit time distributions. The simulated starvation flattened the NSC age distribution and increased the mean NSC transit time, which can be used to estimate the age of the NSC available and the time it would take to exhaust the reserves. Mean NSC ages and transit times were sensitive to C fluxes in roots and allocation of C from wood storage. ●Our results demonstrate how trees with different storage traits are expected to react differently to starvation. They also provide a probabilistic explanation for the 'last-in, first-out' pattern of NSC mobilization from well-mixed C pools.

Traits and climate are associated with first flowering day in herbaceous species along elevational gradients.

Phenological responses to changing temperatures are known as "fingerprints of climate change," yet these reactions are highly species specific. To assess whether different plant characteristics are related to these species-specific responses in flowering phenology, we observed the first flowering day (FFD) of ten herbaceous species along two elevational gradients, representing temperature gradients. On the same populations, we measured traits being associated with (1) plant performance (specific leaf area), (2) leaf biochemistry (leaf C, N, P, K, and Mg content), and (3) water-use efficiency (stomatal pore area index and stable carbon isotopes concentration). We found that as elevation increased, FFD was delayed for all species with a highly species-specific rate. Populations at higher elevations needed less temperature accumulation to start flowering than populations of the same species at lower elevations. Surprisingly, traits explained a higher proportion of variance in the phenological data than elevation. Earlier flowering was associated with higher water-use efficiency, higher leaf C, and lower leaf P content. In addition to that, the intensity of shifts in FFD was related to leaf N and K. These results propose that traits have a high potential in explaining phenological variations, which even surpassed the effect of temperature changes in our study. Therefore, they have a high potential to be included in future analyses studying the effects of climate change and will help to improve predictions of vegetation changes.

Interactive effects of landscape history and current management on dispersal trait diversity in grassland plant communities.

Plant communities and their ecosystem functions are expected to be more resilient to future habitat fragmentation and deterioration if the species comprising the communities have a wide range of dispersal and persistence strategies. However, the extent to which the diversity of dispersal and persistence traits in plant communities is determined by the current and historical characteristics of sites and their surrounding landscape has yet to be explored.Using quantitative information on long-distance seed dispersal potential by wind and animals (dispersal in space) and on species' persistence/longevity (dispersal in time), we (i) compared levels of dispersal and persistence trait diversity (functional richness, FRic, and functional divergence, FDiv) in seminatural grassland plant communities with those expected by chance, and (ii) quantified the extent to which trait diversity was explained by current and historical landscape structure and local management history - taking into account spatial and phylogenetic autocorrel.Null model analysis revealed that more grassland communities than expected had a level of trait diversity that was lower or higher than predicted, given the level of species richness. Both the range (FRic) and divergence (FDiv) of dispersal and persistence trait values increased with grassland age. FDiv was mainly explained by the interaction between current grazing intensity and the amount of grassland habitat in the surrounding landscape in 1938.Synthesis. The study suggests that the variability of dispersal and persistence traits in grassland plant communities is driven by deterministic assembly processes, with both history and current management (and their interactions), playing a major role as determinants of trait diversity. While a long continuity of grazing management is likely to have promoted the diversity of dispersal and persistence traits in present-day grasslands, communities in sites that are well grazed at the present day, and were also surrounded by large amounts of grassland in the past, showed the highest diversity of dispersal and persistence strategies. Our results indicate that the historical context of a site within a landscape will influence the extent to which current grazing management is able to maintain a diversity of dispersal and persistence strategies and buffer communities (and their associated functions) against continuing habitat fragmentation.