Functional Type Level Research Articles

Changes in Community Composition Induced by Experimental Warming in an Alpine Meadow: Beyond Plant Functional Type

Climate warming exerts profound effects on plant community composition. However, responses to climate warming are often reported at the community and functional type levels, but not at the species level. To test whether warming-induced changes are consistent among community, functional type, and species levels, we examined the warming-induced changes at different levels in an alpine meadow from 2015 to 2018. The warming was achieved by deploying six (open top) chambers [including three non-warmed chambers and three warmed chambers; 15 × 15 × 2.5 m (height) for each] that resulted in a small increase in mean annual temperature (0.3–0.5°C, varying with years) with a higher increase during the non-growing season (0.4–0.6°C) than in the growing season (0.03–0.47°C). The results show that warming increased plant aboveground biomass but did not change species richness, or Shannon diversity and evenness at the community level. At the functional type level, warming increased the relative abundance of grasses from 3 to 16%, but decreased the relative abundance of forbs from 89 to 79%; relative abundances of sedges and legumes were unchanged. However, for a given functional type, warming could result in contrasting effects on the relative abundance among species, e.g., the abundances of the forb species Geranium pylzowianum, Potentilla anserine, Euphrasia pectinate, and the sedge species Carex atrofusca increased in the warmed (compared to the non-warmed) chambers. More importantly, the difference in species identity between warmed and non-warmed chambers revealed warming-induced species loss. Specifically, four forb species were lost in both types of chambers, one additional forb species (Angelica apaensis) was lost in the non-warmed chambers, and two additional species (one forb species Saussurea stella and one sedge species Blysmus sinocompressus) were lost in the warmed chambers. Consequently, changes at the species level could not be deduced from the results at the community or functional type levels. These data indicate that species-level responses to climate changes must be more intensively studied. This work also highlights the importance of examining species identity (and not only species number) to study changes of community composition in response to climate warming.

Accounting for forest age in the tile-based dynamic global vegetation model JSBACH4 (4.20p7; git feature/forests) – a land surface model for the ICON-ESM

Abstract. Natural and anthropogenic disturbances, in particular forest management, affect forest age structures all around the globe. Forest age structures in turn influence key land surface processes, such as photosynthesis and thus the carbon cycle. Yet, many dynamic global vegetation models (DGVMs), including those used as land surface models (LSMs) in Earth system models (ESMs), do not account for subgrid forest age structures, despite being used to investigate land-use effects on the global carbon budget or simulating biogeochemical responses to climate change. In this paper we present a new scheme to introduce forest age classes in hierarchical tile-based DGVMs combining benefits of recently applied approaches the first being a computationally efficient age-dependent simulation of all relevant processes, such as photosynthesis and respiration, using a restricted number of age classes and the second being the tracking of the exact forest age, which is a prerequisite for any implementation of age-based forest management. This combination is achieved by using the tile hierarchy to track the area fraction for each age on an aggregated plant functional type level, whilst simulating the relevant processes for a set of age classes. We describe how we implemented this scheme in JSBACH4, the LSM of the ICOsahedral Non-hydrostatic Earth system model (ICON-ESM). Subsequently, we compare simulation output to global observation-based products for gross primary production, leaf area index, and above-ground biomass to assess the ability of simulations with and without age classes to reproduce the annual cycle and large-scale spatial patterns of these variables. The comparisons show decreasing differences and increasing computation costs with an increasing number of distinguished age classes. The results demonstrate the benefit of the introduction of age classes, with the optimal number of age classes being a compromise between computation costs and error reduction.

Functional responses of the herbaceous plant community explain ecohydrological impacts of savanna shrub encroachment

Major drivers of savanna shrub encroachment are climatic conditions, CO2 and unsustainable grazing management including fire prevention. Although all drivers affect ecohydrological processes, and given that water is a seasonally scarce resource in savannas, it remains largely unclear how shrub encroachment itself affects hydrological conditions that feed back into water use and community assembly of the remaining plant community. Hence, understanding direct ecohydrological effects of shrubs that may limit the recovery of the perennial herbaceous vegetation in grazed areas and promote the establishment of shrub seedlings facilitates the identification of areas that are most sensitive to further encroachment.In our trait-based approach, we determined relationships among shrub cover, soil and plant trait characteristics sensitive to water limitation in 120 plots along a shrub cover gradient. We focused on two functional response traits indicating immediate drought stress and subsequent water use for drought stress recovery with associated competition for water (midday leaf/xylem water potential and diurnally recovery rate of leaf water potential), and three functional response traits indicating long-term stress adaptation and related resource use strategies (SLA, plant height and seed release height). To understand species assembly and the associated mechanisms of resource use, we calculated community weighted mean traits, intraspecific trait variability as a proxy for the mechanism of coexistence, and mean traits at plant functional type level including 2-year-old Acacia mellifera-saplings.We found a low intraspecific trait variability in drought stress recovery rate and height suggesting that competitive exclusion via active resource acquisition (i.e. water exploitation) played a minor role for community assembly in a shrub encroaching savanna. The dominant community assembly process was passive stress avoidance via resource conservation up to stress tolerance indicated by the high variability in SLA and midday leaf water potential. Correlations of traits with soil moisture suggest a rooting niche differentiation between annual and perennial grasses and that Acacia-shrub saplings within the first 50 cm of soil already escaped the highest drought stress. Interestingly, immediate drought stress for the herbaceous community was lowest on moderately shrub encroached sites and not on grass dominated sites.Since passive stress avoidance accompanied by a distinct stress tolerance in semi-arid savannas is more important than active competition, and assuming that the low drought stress of the herbaceous community at intermediate levels of shrub cover also applies to newly emerging shrub seedlings, these areas are likely to be most sensitive to further encroachment. As such, they should be considered as focal areas for prevention management.

Adaptation of Dominant Species to Drought in the Inner Mongolia Grassland - Species Level and Functional Type Level Analysis.

The adaptation of plants to drought through the adjustment of their leaf functional traits is a hot topic in plant ecology. However, while there is a good understanding of how individual species adapt to drought in this way, the way in which different functional types adapt to drought along a precipitation gradient remains poorly understood. In this study, we sampled 22 sites along a precipitation gradient in the Inner Mongolia grassland and measured eight leaf functional traits across 39 dominant species to determine the adaptive strategies of plant leaves to drought at the species and plant functional type levels. We found that leaf functional traits were mainly influenced by both aridity and phylogeny at the species level. There were four types of leaf adaptations to drought at the functional type level: adjusting the carbon-nitrogen ratio, the specific leaf area, the nitrogen content, and the specific leaf area and leaf nitrogen content simultaneously. These findings indicate that there is the trade-offs relationship between water and nitrogen acquisition as the level of drought increases, which is consistent with the worldwide leaf economics spectrum. In this study, we highlighted that the leaf economic spectrum can be adopted to reveal the adaptations of plants to drought in the Inner Mongolia grassland.

Evaluating and improving the Community Land Model's sensitivity to land cover

Abstract. Modeling studies have shown the importance of biogeophysical effects of deforestation on local climate conditions but have also highlighted the lack of agreement across different models. Recently, remote-sensing observations have been used to assess the contrast in albedo, evapotranspiration (ET), and land surface temperature (LST) between forest and nearby open land on a global scale. These observations provide an unprecedented opportunity to evaluate the ability of land surface models to simulate the biogeophysical effects of forests. Here, we evaluate the representation of the difference of forest minus open land (i.e., grassland and cropland) in albedo, ET, and LST in the Community Land Model version 4.5 (CLM4.5) using various remote-sensing and in situ data sources. To extract the local sensitivity to land cover, we analyze plant functional type level output from global CLM4.5 simulations, using a model configuration that attributes a separate soil column to each plant functional type. Using the separated soil column configuration, CLM4.5 is able to realistically reproduce the biogeophysical contrast between forest and open land in terms of albedo, daily mean LST, and daily maximum LST, while the effect on daily minimum LST is not well captured by the model. Furthermore, we identify that the ET contrast between forests and open land is underestimated in CLM4.5 compared to observation-based products and even reversed in sign for some regions, even when considering uncertainties in these products. We then show that these biases can be partly alleviated by modifying several model parameters, such as the root distribution, the formulation of plant water uptake, the light limitation of photosynthesis, and the maximum rate of carboxylation. Furthermore, the ET contrast between forest and open land needs to be better constrained by observations to foster convergence amongst different land surface models on the biogeophysical effects of forests. Overall, this study demonstrates the potential of comparing subgrid model output to local observations to improve current land surface models' ability to simulate land cover change effects, which is a promising approach to reduce uncertainties in future assessments of land use impacts on climate.

Phytoplankton traits from long-term oceanographic time-series

MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 576:11-25 (2017) - DOI: https://doi.org/10.3354/meps12220 Phytoplankton traits from long-term oceanographic time-series Crispin M. Mutshinda1, Zoe V. Finkel2, Claire E. Widdicombe3, Andrew J. Irwin1,* 1Mathematics & Computer Science, Mount Allison University, Sackville, NB E4L 1E6, Canada 2Environmental Science, Mount Allison University, Sackville, NB E4L 1A7, Canada 3Plymouth Marine Laboratory, Prospect Place, Plymouth PL1 3DH, UK *Corresponding author: airwin@mta.ca ABSTRACT: Trait values are usually extracted from laboratory studies of single phytoplankton species, which presents challenges for understanding the immense diversity of phytoplankton species and the wide range of dynamic ocean environments. Here we use a Bayesian approach and a trait-based model to extract trait values for 4 functional types and 10 diatom species from field data collected at Station L4 in the Western Channel Observatory, English Channel. We find differences in maximum net growth rate, temperature optimum and sensitivity, half-saturation constants for light and nitrogen, and density-dependent loss terms across the functional types. We find evidence of very high linear loss rates, suggesting that grazing may be even more important than commonly assumed and differences in density-dependent loss rates across functional types, indicating the presence of strong niche differentiation among functional types. Low half-saturation constants for nitrogen at the functional type level may indicate widespread mixotrophy. At the species level, we find a wide range of density-dependent effects, which may be a signal of diversity in grazing susceptibility or biotic interactions. This approach may be a way to obtain more realistic and better-constrained trait values for functional types to be used in ecosystem modeling. KEY WORDS: Phytoplankton · Time series · Traits · Growth rate · Grazing rate · English Channel Full text in pdf format Supplementary material PreviousNextCite this article as: Mutshinda CM, Finkel ZV, Widdicombe CE, Irwin AJ (2017) Phytoplankton traits from long-term oceanographic time-series. Mar Ecol Prog Ser 576:11-25. https://doi.org/10.3354/meps12220 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 576. Online publication date: August 03, 2017 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2017 Inter-Research.

Sagebrush, Greater Sage-Grouse, and the Occurrence and Importance of Forbs

Big sagebrush (Artemisia tridentata Nutt.) ecosystems provide habitat for sagebrush-obligate wildlife species such as the Greater Sage-Grouse (Centrocercus urophasianus). The understory of big sagebrush plant communities is composed of grasses and forbs that are important sources of cover and food for wildlife. The grass component is well described in the literature, but the composition, abundance, and habitat role of forbs in these communities is largely unknown. Our objective was to synthesize information about forbs and their importance to Greater Sage-Grouse diets and habitats, how rangeland management practices affect forbs, and how forbs respond to changes in temperature and precipitation. We also sought to identify research gaps and needs concerning forbs in big sagebrush plant communities. We searched for relevant literature including journal articles and state and federal agency reports. Our results indicated that in the spring and summer, Greater Sage-Grouse diets consist of forbs (particularly species in the Asteraceae family), arthropods, and lesser amounts of sagebrush. The diets transition to sagebrush in fall and winter. Forbs provide cover for Greater Sage-Grouse individuals at their lekking, nesting, and brood-rearing sites, and the species has a positive relationship with arthropod presence. The effect of grazing on native forbs may be compounded by invasion of nonnative species and differs depending on grazing intensity. The effect of fire on forbs varies greatly and may depend on time elapsed since burning. In addition, chemical and mechanical treatments affect annual and perennial forbs differently. Temperature and precipitation influence forb phenology, biomass, and abundance differently among species. Our review identified several uncertainties and research needs about forbs in big sagebrush ecosystems. First, in many cases the literature about forbs is reported only at the genus or functional type level. Second, information about forb composition and abundance near lekking sites is limited, despite the fact that lekking sites are an important center of Greater Sage-Grouse activity. Third, there is little published literature on the relationship between forbs and precipitation and between forbs and temperature, thereby limiting our ability to understand potential responses of forbs to climate change. While there is wide agreement among Greater Sage-Grouse biologists that forbs are an important habitat component, our knowledge about the distribution and environmental responses of forb species in big sagebrush plant communities is limited. Our work for the first time synthesizes the current knowledge regarding forbs in sagebrush ecosystems and their importance for Greater Sage-Grouse and identifies additional research needs for effective conservation and management.

Can digital image classification be used as a standardised method for surveying peatland vegetation cover?

The ability to carry out systematic, accurate and repeatable vegetation surveys is an essential part of long-term scientific studies into ecosystem biodiversity and functioning. However, current widely used traditional survey techniques such as destructive harvests, pin frame quadrats and visual cover estimates can be very time consuming and are prone to subjective variations. We investigated the use of digital image techniques as an alternative way of recording vegetation cover to plant functional type level on a peatland ecosystem. Using an established plant manipulation experimental site at Moor House NNR (an Environmental Change Network site), we compared visual cover estimates of peatland vegetation with cover estimates using digital image classification methods, from 0.5m×0.5m field plots. Our results show that digital image classification of photographs taken with a standard digital camera can be used successfully to estimate dwarf-shrub and graminoid vegetation cover at a comparable level to field visual cover estimates, although the methods were less effective for lower plants such as mosses and lichens. Our study illustrates the novel application of digital image techniques to provide a new way of measuring and monitoring peatland vegetation to the plant functional group level, which is less vulnerable to surveyor bias than are visual field surveys. Furthermore, as such digital techniques are highly repeatable, we suggest that they have potential for use in long-term monitoring studies, at both plot and landscape scales.

Foraging ecology of three sympatric ungulate species - Behavioural and resource maps indicate differences between chamois, ibex and red deer.

BackgroundThe spatial distribution of forage resources is a major driver of animal movement patterns. Understanding where animals forage is important for the conservation of multi-species communities, since interspecific competition can emerge if different species use the same depletable resources. However, determining forage resources in a spatially continuous fashion in alpine grasslands at high spatial resolution was challenging up to now, because terrain heterogeneity causes vegetation characteristics to vary at small spatial scales, and methods for detection of behavioural phases in animal movement patterns were not widely available. We delineated areas coupled to the foraging behaviour of three sympatric ungulate species (chamois, ibex, red deer) using Time Local Convex Hull (T-LoCoH), a non-parametric utilisation distribution method incorporating spatial and temporal autocorrelation structure of GPS data. We used resource maps of plant biomass and plant nitrogen content derived from high-resolution airborne imaging spectroscopy data, and multinomial logistic regression to compare the foraging areas of the three ungulate species.ResultsWe found significant differences in plant biomass and plant nitrogen content between the core foraging areas of chamois, ibex and red deer. Core foraging areas of chamois were characterised by low plant biomass and low to medium plant nitrogen content. Core foraging areas of ibex were, in contrast, characterised by high plant nitrogen content, but varied in plant biomass, and core foraging areas of red deer had high plant biomass, but varied in plant nitrogen content.ConclusionsPrevious studies carried out in the same study area found no difference in forage consumed by chamois, ibex and red deer. Methodologically, those studies were based on micro-histological analysis of plant fragments identifying them to plant family or functional type level. However, vegetation properties such as productivity (biomass) or plant nutrient content can vary within vegetation communities, especially in highly heterogeneous landscapes. Thus, the combination of high spatial resolution resource maps with a utilisation distribution method allowing to generate behavioural maps (T-LoCoH) provides new insights into the foraging ecology of the three sympatric species, important for their conservation and to monitor expected future changes.Electronic supplementary materialThe online version of this article (doi:10.1186/s40462-015-0033-x) contains supplementary material, which is available to authorized users.

Regeneration of Different Plant Functional Types in a Masson Pine Forest Following Pine Wilt Disease

Pine wilt disease is a severe threat to the native pine forests in East Asia. Understanding the natural regeneration of the forests disturbed by pine wilt disease is thus critical for the conservation of biodiversity in this realm. We studied the dynamics of composition and structure within different plant functional types (PFTs) in Masson pine forests affected by pine wilt disease (PWD). Based on plant traits, all species were assigned to four PFTs: evergreen woody species (PFT1), deciduous woody species (PFT2), herbs (PFT3), and ferns (PFT4). We analyzed the changes in these PFTs during the initial disturbance period and during post-disturbance regeneration. The species richness, abundance and basal area, as well as life-stage structure of the PFTs changed differently after pine wilt disease. The direction of plant community regeneration depended on the differential response of the PFTs. PFT1, which has a higher tolerance to disturbances, became dominant during the post-disturbance regeneration, and a young evergreen-broad-leaved forest developed quickly after PWD. Results also indicated that the impacts of PWD were dampened by the feedbacks between PFTs and the microclimate, in which PFT4 played an important ecological role. In conclusion, we propose management at the functional type level instead of at the population level as a promising approach in ecological restoration and biodiversity conservation.

Modelling Late Miocene vegetation in Europe: Results of the CARAIB model and comparison with palaeovegetation data

The CARAIB (CARbon Assimilation In the Biosphere) model is used to study the vegetation distribution during the Late Miocene (Tortonian). In this version, the plant classification is specifically adapted to best represent Miocene European vegetation. Compared to other plant classifications used in global models, this adapted classification is more refined, since it is specifically developed for European vegetation and it includes various thermophylous tree types, which were present in Europe during the Miocene. The corresponding climatic tolerance parameters are based on the study of Laurent et al. (Journal of Vegetation Science, 15, 739-746, 2004) for the tree types currently present in Europe and on the distribution of analogue species in southeastern Asia and North/Central America for the thermophylous (sub-tropical) trees. The same classification is used to characterize the palaeoflora at the available Late Miocene localities, allowing a model–data comparison at the plant functional type level, rather than at the biome level. The climatic inputs to CARAIB are obtained from the COSMOS atmosphere–ocean general circulation model. The climatic anomalies (Tortonian minus Present) derived from COSMOS are interpolated to a higher spatial resolution before being used in the vegetation model. These anomalies are combined with a modern climatology to produce climatic fields with high spatial resolution (10′ × 10′). This procedure has the advantage of making apparent relief features smaller than the grid cells of the climate model and, hence, makes easier the comparison with local vegetation data, although it does not really improve the quality of the Tortonian climate reconstruction. The new version of CARAIB was run over Europe at this higher spatial resolution. It calculates the potential distribution of 13 different classes of trees (including cold/cool/warm-temperate, sub-tropical and tropical types), together with their cover fractions, net primary productivities and biomasses. The resulting model vegetation distribution reconstructed for the Tortonian is compared to available palaeovegetation and pollen data. Before performing this comparison, the tree taxa present at the various data sites are assigned to one or several model classes, depending on the identification level of the taxa. If several classes are possible for a taxon, only those that can co-exist with the other tree classes identified at the site are retained. This methodology is similar to the co-existence approach used in palaeoclimatic reconstructions based on vegetation data. It narrows the range of tree types present at the various sites, by suppressing in the data the extreme types, such as the cold boreal/temperate and tropical trees. The method allows a comparison with the model simulation on a presence/absence basis. This comparison provides an overall agreement of 53% between the model and the data, when all sites and tree types are considered. The agreement is high (> 85%) for needle-leaved summergreen boreal/temperate cold trees ( Larix sp.) and for tropical trees, intermediate (> 40%) for other boreal/temperate cold trees and for needle-leaved evergreen temperate cool trees, broadleaved summergreen temperate cool trees and broadleaved evergreen warm-temperate trees, and poor (< 40%) for most temperate perhumid warm trees. In many cases, the model is shown to be better at predicting the absence than the presence, as observed for tropical trees. The modelled distributions of cold boreal/temperate trees tend to extend too much towards the south compared to the data. By contrast, model sub-tropical trees (temperate perhumid warm and needle-leaf summergreen temperate warm trees) appear to be restricted to some limited areas in southern Europe, while they are present in the data from central Europe up to at least 50°N. Consequently, modelled Late Miocene climate appears to remain too cold to produce assemblages of trees consistent with the data. The predicted modelled trends from the past to the present are in the right direction, but the amplitude remains too small. For the simulations to be in a better agreement with the data, higher CO 2 levels may be necessary in the climate simulations, or possibly other oceanic boundary conditions may be required, such as different bathymetry in the Panama seaway.

Simulating the dynamics of primary productivity of a Sonoran ecosystem: Model parameterization and validation

Modeling has played a crucial role in understanding the structural and functional dynamics of forest and grassland ecosystems in the past decades, but relatively few ecosystem models have been developed for deserts. Adapting an existing desert ecosystem model to new regions with different community components and environmental settings may testify to the generality of model applicability, further verify model structure and formulations, and provide new insight into understanding desert ecosystem functioning. In this paper, we use a desert ecosystem model that was originally developed for the Chihuahuan Desert, Patch Arid Land Simulator-Functional Types (PALS-FT), to estimate the aboveground annual net primary productivity (ANPP) of a creosotebush ( Larrea tridentata)-dominated Sonoran Desert ecosystem in the Phoenix metropolitan area, home to the Central Arizona-Phoenix Long-Term Ecological Research Project (CAP LTER). We modified and parameterized the model using meteorological data, ecophysiological parameters for different plant functional types, and site characteristic data from the CAP LTER study area and an independent test site in the San Simon Valley of southeastern Arizona. Model predictions were validated and calibrated using field observations from the San Simon Valley test site. The results showed that PALS-FT was able to simulate ANPP of this typical Sonoran Desert ecosystem reasonably well, with a relative error of ±2.4% at the ecosystem level and generally less than ±25% at the functional-type level. We then used the model to simulate ANPP and its seasonal and inter-annual dynamics for a similar ecosystem in the CAP LTER study area. The model predicted average annual ANPP of 72.3 g m −2 y −1, ranging from 11.3 g m −2 y −1 to 229.6 g m −2 y −1 in a 15-year simulation. The simulated average ANPP of the Sonoran Desert ecosystem is close to field observations in other areas of the Sonoran Desert, and the range of variation also is close to that reported by other researchers for arid and semiarid ecosystems. The dynamics of ecosystem ANPP in response to fluctuations in annual precipitation simulated by the model agreed well with the known relationship between ANPP and precipitation in arid and semiarid systems. A closer examination of this relationship at the level of plant functional types further revealed that seasonal distribution of rainfall significantly affected ANPP. A comparison between the PALS-FT model prediction and two regression models for North American warm deserts showed that both regression models underestimated the Larrea ecosystem ANPP, while the process-based PALS-FT model provided the most accurate prediction among the three models. This study provides a validation for use of the PALS-FT model to investigate Sonoran desert ecosystem responses to environmental changes.

Phytolith assemblages in grasses native to central Argentina.

Phytolith reference collections are a prerequisite for accurate interpretation of soil phytolith assemblages aimed at reconstructing past vegetation. In this study a phytolith reference collection has been developed for several grasses native to central Argentina: Poa ligularis, Piptochaetium napostaense, Stipa clarazii, Stipa tenuis, Stipa tenuissima, Stipa eriostachya, Stipa ambigua, Stipa brachychaeta, Pappophorum subbulbosum, Digitaria californica, Bothriochloa edwardsiana and Aristida subulata. For each species, phytoliths present in the leaf blades were classified into 47 morphotypes, and their relative frequency determined by observing 300-400 phytoliths per sample (n = 5). Data were analyzed by complete linkage cluster analysis, using the Morisita Index as measure of association. The results showed differentiation among phytolith assemblages at species level or at plant functional type level. Cluster analysis separated C3 from C4 species and palatable from non-palatable species. This study highlights the possibility of reconstructing past vegetation in central Argentina grasslands through the analysis of soil phytolith assemblages.

Chemistry and toughness predict leaf litter decomposition rates over a wide spectrum of functional types and taxa in central Argentina.

Litter decomposition, a major determinant of ecosystem functioning, is strongly influenced by the litter quality of different species. We aimed at (1) relating interspecific variation in leaf litter decomposition rate to the functional types different species belong to; and (2) understanding the chemical and/or physical basis for such variation and its robustness to environmental factors. We selected 52 Angiosperms from a climatic gradient in central-western Argentina, representing the widest range of functional types and habitats published so far. Ten litter samples of each species were simultaneously buried for 9 weeks during the 1996 summer in an experimental decomposition bed. Decomposition rate was defined as the percentage of dry mass loss after incubation. Chemical litter quality was measured as carbon (C) content, nitrogen (N) content, and C-to-N ratio. Since tensile strength of litter and living leaves were strongly correlated, the latter was chosen as an indicator of physical litter quality. A subset of 15 species representing different functional types was also incubated in England for 15 weeks, following a similar experimental procedure. Litter C-to-N and leaf tensile strength of the leaves showed the strongest negative associations with decomposition rate, both at the species and at the functional-type level. Decomposition rates of the same species in Argentina and in England were strongly correlated. This reinforces previous evidence that species rankings in terms of litter decomposition rates are robust to methodological and environmental factors. This paper has shown new evidence of plant control over the turnover of organic matter through litter quality, and confirms, over a broad spectrum of functional types, general models of resource allocation. The strong correlations between leaf tensile strength – a trait that is easy and quick to measure in a large number of species – decomposition rate, and C-to-N ratio indicate that leaf tensile strength can be useful in linking plant quality to decomposition patterns at the ecosystem level.