Plant Functional Type Composition Research Articles

Large Divergence of Projected High Latitude Vegetation Composition and Productivity Due To Functional Trait Uncertainty

AbstractVegetation distribution and composition are expected to change in northern high latitudes under rapid warming, which regulates ecosystem functions but remains challenging to predict. Vegetation change arises from the interplay of chronic climate trends such as warming and transient demographic processes of recruitment, growth, competition, and mortality. Most predictive models overlooked the role of demographic dynamics controlled by plant traits. Here, we simulate vegetation dynamics at the Kougarok Hillslope site in Alaska under historical and future climates using the E3SM Land Model coupled to the Functionally Assembled Terrestrial Simulator (ELM‐FATES). To evaluate the roles of plant traits, we parameterize the model with 5,265 trait configurations representing diverse physiological and demographic strategies. Results show current modeled biomass, composition, and productivity are most sensitive to traits controlling photosynthetic capacity, carbon allocation, allometry, and phenology. Among all trait configurations, ∼5% reproduce in situ biomass and plant functional type (PFT) composition measured in 2016, that are indistinguishable from these two observed ecosystem states. Notably, these same trait configurations produce diverging biomass, composition, and productivity under future climate, where the uncertainty attributable to traits is twice the change attributable to climate change. The variation of projected productivity arises from emerging PFT composition under novel climate regimes, primarily explained by traits controlling cold‐induced mortality, recruitment, and allometry. Our findings highlight the importance and uncertainty of demographic dynamics and its interaction with climate change in shaping Arctic vegetation change. Improved model predictions will likely benefit from explicit consideration of vegetation demography and better constraints of critical traits.

Edaphic conditions affect plant life‐history trait syndromes in a tropical ancient biodiverse ecosystem

AbstractA functional approach to understand natural plant communities helps elucidate the dynamics of environmental filters and community assembly. Species classification into functional groups allows the translation of ecological complexity into simplified and applicable knowledge. Here, we developed a plant functional type (PFT) system to investigate whether functional structure (PFT composition and abundance) of plant communities varies between substrate types and plant physiognomies in an old climatically buffered infertile landscape (OCBIL), namely Brazilian campo rupestre. We sampled the herbaceous and shrubby vegetation and collected soil variables in four different plant physiognomies growing in quartzitic and ferruginous substrates. We classified the sampled species according to life‐history traits related to species persistence, reproduction, and biological interactions. Functional dissimilarity among plant physiognomies and the two substrate types and the role of soil factors affecting the dissimilarities were assessed. Pollination and seed dispersal syndromes, mycorrhizal association, and reproductive phenology were the main traits defining the PFTs. We found distinct functional structure between plant communities of different substrates and physiognomies, with a marked influence of chemical and physical soil factors. Also, we defined main PFTs profiles for each physiognomy, identifying core PFTs with basic combinations of traits, common to all or almost all physiognomies. The functional perspective proposed by this study provides applicable knowledge to the restoration and conservation of campo rupestre ecosystem, reinforcing the importance of habitat heterogeneity for maintaining its functioning.

Water level drawdown makes boreal peatland vegetation more responsive to weather conditions.

Climate warming and projected increase in summer droughts puts northern peatlands under pressure by subjecting them to a combination of gradual drying and extreme weather events. The combined effect of those on peatland functions is poorly known. Here, we studied the impact of long-term water level drawdown (WLD) and contrasting weather conditions on leaf phenology and biomass production of ground level vegetation in boreal peatlands. Data were collected during two contrasting growing seasons from a WLD experiment including a rich and a poor fen and an ombrotrophic bog. Results showed that WLD had a strong effect on both leaf area development and biomass production, and these responses differed between peatland types. In the poor fen and the bog, WLD increased plant growth, while in the rich fen, WLD reduced the growth of ground level vegetation. Plant groups differed in their response, as WLD reduced the growth of graminoids, while shrubs and tree seedlings benefited from it. In addition, the vegetation adjusted to the lower WTs, was more responsive to short-term climatic variations. The warmer summer resulted in a greater maximum and earlier peaking of leaf area index, and greater biomass production by vascular plants and Sphagnum mosses at WLD sites. In particular, graminoids benefitted from the warmer conditions. The change towards greater production in the WLD sites in general and during the warmer weather in particular, was related to the observed transition in plant functional type composition towards arboreal vegetation.

A 29-year time series of annual 300 m resolution plant-functional-type maps for climate models

Abstract. The existing medium-resolution land cover time series produced under the European Space Agency's Climate Change Initiative provides 29 years (1992–2020) of annual land cover maps at 300 m resolution, allowing for a detailed study of land change dynamics over the contemporary era. Because models need two-dimensional parameters rather than two-dimensional land cover information, the land cover classes must be converted into model-appropriate plant functional types (PFTs) to apply this time series to Earth system and land surface models. The first-generation cross-walking table that was presented with the land cover product prescribed pixel-level PFT fractional compositions that varied by land cover class but that lacked spatial variability. Here we describe a new ready-to-use data product for climate modelling: spatially explicit annual maps of PFT fractional composition at 300 m resolution for 1992–2020, created by fusing the 300 m medium-resolution land cover product with several existing high-resolution datasets using a globally consistent method. In the resulting data product, which has 14 layers for each of the 29 years, pixel values at 300 m resolution indicate the percentage cover (0 %–100 %) for each of 14 PFTs, with pixel-level PFT composition exhibiting significant intra-class spatial variability at the global scale. We additionally present an updated version of the user tool that allows users to modify the baseline product (e.g. re-mapping, re-projection, PFT conversion, and spatial sub-setting) to meet individual needs. Finally, these new PFT maps have been used in two land surface models – Organising Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) and the Joint UK Land Environment Simulator (JULES) – to demonstrate their benefit over the conventional maps based on a generic cross-walking table. Regional changes in the fractions of trees, short vegetation, and bare-soil cover induce changes in surface properties, such as the albedo, leading to significant changes in surface turbulent fluxes, temperature, and vegetation carbon stocks. The dataset is accessible at https://doi.org/10.5285/26a0f46c95ee4c29b5c650b129aab788 (Harper et al., 2023).

Small effects of livestock grazing intensification on diversity, abundance, and composition in a dryland plant community.

Livestock grazing is a globally important land use and has the potential to significantly influence plant community structure and ecosystem function, yet several critical knowledge gaps remain on the direction and magnitude of grazing impacts. Furthermore, much of our understanding of the long-term effects on plant community composition and structure are based on grazer exclusion experiments, which explicitly avoid characterizing effects along grazing intensity gradients. We sampled big sagebrush plant communities using 68 plots located along grazing intensity gradients to determine how grazing intensity influences multiple aspects of plant community structure over time. This was accomplished by sampling plant communities at different distances from 17 artificial watering sources, using distance from water and cow dung density as proxies for grazing intensity at individual plots. Total vegetation cover and total grass cover were negatively related to grazing intensity, and cover of annual forbs, exotic cover, and exotic richness were positively related to grazing intensity. In contrast, species richness and composition, bunchgrass biomass, shrub density and size, percentage cover of bare ground, litter, and biological soil crusts did not vary along our grazing intensity gradients, in spite of our expectations to the contrary. Our results suggest that the effects of livestock grazing over multiple decades (mean=46 years) in our sites are relatively small, especially for native perennial species, and that the big sagebrush plant communities we sampled are somewhat resistant to livestock grazing. Collectively, our findings are consistent with existing evidence that indicates the stability of the big sagebrush plant functional type composition under current grazing management regimes.

The impact of hurricane disturbances on a tropical forest: implementing a palm plant functional type and hurricane disturbance module in ED2-HuDi V1.0

Abstract. Hurricanes commonly disturb and damage tropical forests. Hurricane frequency and intensity are predicted to change under the changing climate. The short-term impacts of hurricane disturbances to tropical forests have been widely studied, but the long-term impacts are rarely investigated. Modeling is critical to investigate the potential response of forests to future disturbances, particularly if the nature of the disturbances is changing with climate. Unfortunately, existing models of forest dynamics are not presently able to account for hurricane disturbances. Therefore, we implement the Hurricane Disturbance in the Ecosystem Demography model (ED2) (ED2-HuDi). The hurricane disturbance includes hurricane-induced immediate mortality and subsequent recovery modules. The parameterizations are based on observations at the Bisley Experimental Watersheds (BEW) in the Luquillo Experimental Forest in Puerto Rico. We add one new plant functional type (PFT) to the model – Palm, as palms cannot be categorized into one of the current existing PFTs and are known to be an abundant component of tropical forests worldwide. The model is calibrated with observations at BEW using the generalized likelihood uncertainty estimation (GLUE) approach. The optimal simulation obtained from GLUE has a mean relative error of −21 %, −12 %, and −15 % for stem density, basal area, and aboveground biomass, respectively. The optimal simulation also agrees well with the observation in terms of PFT composition (+1 %, −8 %, −2 %, and +9 % differences in the percentages of “Early”, “Mid”, “Late”, and “Palm” PFTs, respectively) and size structure of the forest (+0.8 % differences in the percentage of large stems). Lastly, using the optimal parameter set, we study the impact of forest initial condition on the recovery of the forest from a single hurricane disturbance. The results indicate that, compared to a no-hurricane scenario, a single hurricane disturbance has little impact on forest structure (+1 % change in the percentage of large stems) and composition (<1 % change in the percentage of each of the four PFTs) but leads to 5 % higher aboveground biomass after 80 years of succession. The assumption of a less severe hurricane disturbance leads to a 4 % increase in aboveground biomass.

Holocene wildfire regimes in western Siberia: interaction between peatland moisture conditions and the composition of plant functional types

Abstract. Wildfire is the most common disturbance type in boreal forests and can trigger significant changes in forest composition. Waterlogging in peatlands determines the degree of tree cover and the depth of the burnt horizon associated with wildfires. However, interactions between peatland moisture, vegetation composition and flammability, and fire regime in forest and forested peatland in Eurasia remain largely unexplored, despite their huge extent in boreal regions. To address this knowledge gap, we reconstructed the Holocene fire regime, vegetation composition, and peatland hydrology at two sites located in predominantly light taiga (Pinus sylvestris Betula) with interspersed dark taiga communities (Pinus sibirica, Picea obovata, Abies sibirica) in western Siberia in the Tomsk Oblast, Russia. We found marked shifts in past water levels over the Holocene. The probability of fire occurrence and the intensification of fire frequency and severity increased at times of low water table (drier conditions), enhanced fuel dryness, and an intermediate dark-to-light taiga ratio. High water level, and thus wet peat surface conditions, prevented fires from spreading on peatland and surrounding forests. Deciduous trees (i.e. Betula) and Sphagnum were more abundant under wetter peatland conditions, and conifers and denser forests were more prevalent under drier peatland conditions. On a Holocene scale, severe fires were recorded between 7.5 and 4.5 ka with an increased proportion of dark taiga and fire avoiders (Pinus sibirica at Rybnaya and Abies sibirica at Ulukh–Chayakh) in a predominantly light taiga and fire-resister community characterised by Pinus sylvestris and lower local water level. Severe fires also occurred over the last 1.5 kyr and were associated with a declining abundance of dark taiga and fire avoiders, an expansion of fire invaders (Betula), and fluctuating water tables. These findings suggest that frequent, high-severity fires can lead to compositional and structural changes in forests when trees fail to reach reproductive maturity between fire events or where extensive forest gaps limit seed dispersal. This study also shows prolonged periods of synchronous fire activity across the sites, particularly during the early to mid-Holocene, suggesting a regional imprint of centennial- to millennial-scale Holocene climate variability on wildfire activity. Humans may have affected vegetation and fire from the Neolithic; however, increasing human presence in the region, particularly at the Ulukh–Chayakh Mire over the last 4 centuries, drastically enhanced ignitions compared to natural background levels. Frequent warm and dry spells predicted by climate change scenarios for Siberia in the future will enhance peatland drying and may convey a competitive advantage to conifer taxa. However, dry conditions will probably exacerbate the frequency and severity of wildfire, disrupt conifers' successional pathway, and accelerate shifts towards deciduous broadleaf tree cover. Furthermore, climate–disturbance–fire feedbacks will accelerate changes in the carbon balance of boreal peatlands and affect their overall future resilience to climate change.

Disturbance alters relationships between soil carbon pools and aboveground vegetation attributes in an anthropogenic peatland in Patagonia.

Anthropogenic‐based disturbances may alter peatland soil–plant causal associations and their ability to sequester carbon. Likewise, it is unclear how the vegetation attributes are linked with different soil C decomposition‐based pools (i.e., live moss, debris, and poorly‐ to highly‐decomposed peat) under grassing and harvesting conditions. Therefore, we aimed to assess the relationships between aboveground vegetation attributes and belowground C pools in a Northern Patagonian peatland of Sphagnum magellanicum with disturbed and undisturbed areas. We used ordination to depict the main C pool and floristic gradients and structural equation modeling (SEM) to explore the direct and indirect relationships among these variables. In addition, we evaluated whether attributes derived from plant functional types (PFTs) are better suited to predict soil C pools than attributes derived from species gradients. We found that the floristic composition of the peatland can be classified into three categories that follow the C pool gradient. These categories correspond to (1) woody species, such as Baccharis patagonica, (2) water‐logged species like Juncus procerus, and (3) grasslands. We depicted that these classes are reliable indicators of soil C decomposition stages. However, the relationships change between management. We found a clear statistical trend showing a decrease of live moss, debris, and poorly‐decomposed C pools in the disturbed area. We also depicted that plant diversity, plant height, and PFT composition were reliable indicators of C decomposition only under undisturbed conditions, while the species‐based attributes consistently yielded better overall results predicting soil C pools than PFT‐based attributes. Our results imply that managed peatlands of Northern Patagonia with active grassing and harvesting activities, even if small‐scaled, will significantly alter their future C sequestration capacities by decreasing their live and poorly‐decomposed components. Finally, aboveground vegetation attributes cannot be used as proxies of soil C decomposition in disturbed peatlands as they no longer relate to decomposition stages.

Sensitivity of ecosystem-protected permafrost under changing boreal forest structures

Boreal forests efficiently insulate underlying permafrost. The magnitude of this insulation effect is dependent on forest density and composition. A change therein modifies the energy and water fluxes within and below the canopy. The direct influence of climatic change on forests and the indirect effect through a change in permafrost dynamics lead to extensive ecosystem shifts such as a change in composition or density, which will, in turn, affect permafrost persistence. We derive future scenarios of forest density and plant functional type composition by analyzing future projections provided by the dynamic global vegetation model (LPJ-GUESS) under global warming scenarios. We apply a detailed permafrost-multilayer canopy model to study the spatial impact-variability of simulated future scenarios of forest densities and compositions for study sites throughout eastern Siberia. Our results show that a change in forest density has a clear effect on the ground surface temperatures (GST) and the maximum active layer thickness (ALT) at all sites, but the direction depends on local climate conditions. At two sites, higher forest density leads to a significant decrease in GSTs in the snow-free period, while leading to an increase at the warmest site. Complete forest loss leads to a deepening of the ALT up to 0.33 m and higher GSTs of over 8 ∘C independently of local climatic conditions. Forest loss can induce both, active layer wetting up to four times or drying by 50%, depending on precipitation and soil type. Deciduous-dominated canopies reveal lower GSTs compared to evergreen stands, which will play an important factor in the spreading of evergreen taxa and permafrost persistence under warming conditions. Our study highlights that changing density and composition will significantly modify the thermal and hydrological state of the underlying permafrost. The induced soil changes will likely affect key forest functions such as the carbon pools and related feedback mechanisms such as swamping, droughts, fires, or forest loss.

Landscape-scale characterization of Arctic tundra vegetation composition, structure, and function with a multi-sensor unoccupied aerial system

The Arctic is experiencing some of the most rapid climate change on Earth, with strong impacts on tundra ecosystems that are characterized by high land-surface and vegetation heterogeneity. Previous studies have explored this complexity using satellite remote sensing, however these typically coarse spatial resolution data have generally missed sub-pixel heterogeneity, leaving critical gaps in our understanding of tundra vegetation dynamics from the community to landscape scales. To address these gaps, we collected very high-resolution (1–5 cm) optical, structural, and thermal data at three low-Arctic tundra sites on the Seward Peninsula, Alaska, using a multi-sensor unoccupied aerial system (UAS). We examined the application of these data to studying tundra vegetation dynamics, by quantifying (a) canopy height and thermoregulation (leaf–air temperature) of representative plant functional types (PFTs), (b) fine-scale patterns of vegetation composition across landscapes, and (c) impacts of fine-scale vegetation composition on landscape-scale variation of canopy height and thermoregulation. Our results show that deciduous tall shrubs (those that can potentially grow >2 m) had a strong cooling effect, with canopy temperatures significantly lower than local air temperatures and other PFTs. Increased cover of tall shrubs also had the potential to reduce the cover of low-stature PFTs across the landscape, potentially associated with their closed canopy (i.e. increased light competition) and strong thermoregulation. To understand the connections between fine-scale vegetation composition and large-scale ecosystem processes, we produced a random forest model which showed that fine-scale PFT composition accounted for 86.8% and 74.2% of the landscape-scale variation in canopy height and thermoregulation, respectively. These findings highlight the importance of spatially detailed characterization of tundra PFTs to improve our ecological understanding and model representation of tundra vegetation, also transcend our study to show the need for continued collection of similar datasets to better understand the impacts of surface heterogeneity on the mapping and modeling of tundra ecosystem dynamics, as well as assist with conservation management and biodiversity monitoring strategies.

Plant Functional Diversity, Climate and Grazer Type Regulate Soil Activity in Natural Grasslands

Global change modifies vegetation composition in grasslands with shifts in plant functional types (PFT). Although changes in plant community composition imply changes in soil function, this relationship is not well understood. We investigated the relative importance of environmental (climatic, management and soil) variables and plant functional diversity (PFT composition and interactions) on soil activity and fertility along a climatic gradient. We collected samples of soil and PFT biomass (grasses, legumes, and non-legume forbs) in six extensively managed grasslands along a climatic gradient in the Northern Iberian Peninsula. Variation Partitioning Analysis showed that abiotic and management variables explained most of the global variability (96.5%) in soil activity and fertility; soil moisture and grazer type being the best predictors. PFT diversity accounted for 27% of the total variability, mostly in interaction with environmental factors. Diversity-Interaction models applied on each response variable revealed that PFT-evenness and pairwise interactions affected particularly the nitrogen cycle, enhancing microbial biomass nitrogen, dissolved organic nitrogen, total nitrogen, urease, phosphatase, and nitrification potential. Thus, soil activity and fertility were not only regulated by environmental variables, but also enhanced by PFT diversity. We underline that climate change-induced shifts in vegetation composition can alter greenhouse gas—related soil processes and eventually the feedback of the soil to the atmosphere.

Methods for tracking sagebrush‐steppe community trajectories and quantifying resilience in relation to disturbance and restoration

Understanding how plant community dynamics are impacted by altered disturbance regimes is a pressing challenge for restoration ecology. Most assessments of community dynamics involve computationally intensive statistical techniques, while management often defers to derived, qualitative “state‐and‐transition” models. Here, we demonstrate an intermediate approach to track and predict community resilience, diversifying the tools available to assess ecosystem change. First, we develop indices of sagebrush‐steppe community structure in permanent monitoring plots based on plant functional types and our conceptual understanding of the ecosystem. The indices define a bivariate space within which the trajectories of permanent monitoring plots can be tracked. Second, we quantify two metrics of community resilience: resistance (overall change during the time period) and stability (average amount of movement per monitoring period). Plots dominated by obligate seeder shrubs displayed low resilience relative to those dominated by grasses and forbs or resprouting shrubs. Resilience was strongly related to initial plant functional type composition and elevation. Our results suggest restoration objectives should consider how plant traits control ecosystem responses to disturbance. We suggest that the approach developed here can help assess longer‐term resilience, evaluate restoration success, and identify communities at risk of state transitions.

Soil texture and precipitation seasonality influence plant community structure in North American temperate shrub steppe.

In drylands, the coexistence of grasses and woody plants has been attributed to soil-water resource partitioning. Soil texture and precipitation seasonality can influence the amount and distribution of water in the soil, and their interaction may play an important role in determining the relative importance of grasses and woody plants. We investigated the influence of this interaction on plant functional types across a broad range of precipitation regimes and soil textures in western North America by analyzing plant-cover data collected at 2,084 plots that included the widespread shrub big sagebrush (Artemisia tridentata Nutt.). We characterized how the significance of the inverse-texture effect varies across soil conditions by quantifying relationships between precipitation and foliar cover on finer- vs. coarser-textured soils across a range of potential texture divisions represented by sand content. We found evidence of the inverse-texture effect for every plant functional type (except for cheatgrass) that we examined with at least one component of precipitation (annual, warm, or cold season), and provide the first evidence for this effect in locations with cold-season-dominated precipitation regimes. The texture and precipitation combinations that exhibited the inverse-texture effect varied with plant functional type, presumably because of effects of soil texture on water availability at different soil depths with season. Furthermore, we found an inverse-texture effect that was remarkably similar for shrub cover with cold-season precipitation and grass cover with warm-season precipitation. These results provide new insight into how the inverse-texture effect interacts with precipitation seasonality to influence plant functional type composition in drylands, and further suggest that quantifying the soil-texture division at which the inverse-texture effect is relevant under a given set of environmental conditions may provide support for the effect across dryland plant communities.

Phenology Dynamics of Dryland Ecosystems Along the North Australian Tropical Transect Revealed by Satellite Solar‐Induced Chlorophyll Fluorescence

AbstractAccurate phenological characterization of dryland ecosystems has remained a challenge due to the complex composition of plant functional types, each having distinct phenological dynamics, sensitivity to climate, and disturbance. Solar‐Induced chlorophyll Fluorescence (SIF), a proxy for photosynthesis, offers potential to alleviate such challenge. We here explore this potential using dryland systems along the North Australian Tropical Transect with SIF derived from Orbiting Carbon Observatory‐2. SIF identified the seasonal onset and senescence of Gross Primary Production at eddy covariance sites with improved accuracy over Enhanced Vegetation Index and Near‐Infrared Reflectance of terrestrial Vegetation from Moderate Resolution Imaging Spectroradiometer, especially at inland xeric shrublands. At regional scale, SIF depicted both earlier onset and senescence across North Australian Tropical Transect. We hypothesized that SIF outperformed Enhanced Vegetation Index and Near‐Infrared Reflectance of terrestrial Vegetation mainly because, unlike reflectance, it is not contaminated by background soil, and its total signal is contributed by mixed plant species in additive way.

Imaging spectrometry-derived estimates of regional ecosystem composition for the Sierra Nevada, California

The composition of the plant canopy is a key attribute of terrestrial ecosystems, influencing the fluxes of carbon, water, and energy between the land surface and the atmosphere. Terrestrial ecosystem and biosphere models, which are used to predict how ecosystems are expected to respond to changes in climate, atmospheric CO2, and land-use change, require accurate representations of plant canopy composition at large spatial scales. The ability to accurately specify plant canopy composition is important because it determines the physiological and ecological properties of plants (such as leaf photosynthetic capacity, patterns of plant carbon allocation and tissue turnover, and the resulting dynamics of plant demography) that govern the biophysical and biogeochemical functioning of ecosystems. Traditionally, plant canopy composition has been represented in a coarse-grained manner within terrestrial biosphere models, with ecosystems being comprised of a single plant functional type (PFT). However, models are increasingly seeking to represent fine-scale spatial variation in plant functional diversity. In this study, we show how imaging spectrometry measurements can provide spatially-comprehensive estimates of within-biome heterogeneity in PFT composition across a functionally diverse and topographically heterogeneous ~710 km2 area in the Southern Sierra Mountains of California. AVIRIS (Airborne Visible Infrared Imaging Spectrometer) data at 18 m resolution from the recent HyspIRI Preparatory Mission (Hyperspectral InfraRed Imager) were used to estimate the sub-pixel fractions of seven PFTs represented in the ED2 terrestrial biosphere model: Shrub, Oak, Western Hardwood, Western Pine, Cedar/Fir, and High-elevation Pine, plus a Grass/NPV (Non-Photosynthetic Vegetation) fraction using Multiple Endmember Spectral Mixture Analysis (MESMA). ED2 is an individual-based terrestrial biosphere model capable of representing fine-scale sub-pixel ecosystem heterogeneity. Our results show that this methodology captures important elevation-related shifts in canopy composition that occur within the study area that are not resolved by existing multi-spectral land-cover products. These estimates modestly improved when the putative PFT endmembers considered in the mixture analysis were constrained using available geospatial data about the presence and absence of the PFTs in particular areas: the average RMSEs (root-mean-square errors) with the geospatially-constrained versus conventional method were 11.3% and 11.9% respectively, with larger reductions in the bias (i.e. mean error) in the abundances of Oak, Cedar/Fir, and Western Hardwood PFTs (ranging from 2.0% to 7.8%). At the hectare scale around four flux towers in the Southern Sierra Mountains, the overall composition improved from an RMSE of 18.2% (5.0–24.2% for individual PFTs) to an RMSE of 9.5% (3.3–13.2% for individual PFTs). Downgrading AVIRIS to 30 m resolution resulted in a reduction in accuracy of the constrained method to an RMSE of 12.7% (0–23.7%) with <1% change in the bias for all tree and shrub PFTs. Our results demonstrate that imaging spectrometry measurements from planned satellite missions such as HyspIRI, EnMAP (Environmental Mapping and Analysis Program), and HISUI (Hyper-spectral Imager SUIte) can provide important and much-needed information about fine-scale heterogeneity in the composition of plant canopies for constraining and improving terrestrial ecosystem and biosphere model simulations of regional- and global-scale vegetation dynamics and function.

Predicting aboveground biomass in Arctic landscapes using very high spatial resolution satellite imagery and field sampling

ABSTRACTRemote sensing based biomass estimates in Arctic areas are usually produced using coarse spatial resolution satellite imagery, which is incapable of capturing the fragmented nature of tundra vegetation communities. We mapped aboveground biomass using field sampling and very high spatial resolution (VHSR) satellite images (QuickBird, WorldView-2 and WorldView-3) in four different Arctic tundra or peatland sites with low vegetation located in Russia, Canada, and Finland. We compared site-specific and cross-site empirical regressions. First, we classified species into plant functional types and estimated biomass using easy, non-destructive field measurements (cover, height). Second, we used the cover/height-based biomass as the response variable and used combinations of single bands and vegetation indices in predicting total biomass. We found that plant functional type biomass could be predicted reasonably well in most cases using cover and height as the explanatory variables (adjusted R2 0.21–0.92), and there was considerable variation in the model fit when the total biomass was predicted with satellite spectra (adjusted R2 0.33–0.75). There were dissimilarities between cross-site and site-specific regression estimates in satellite spectra based regressions suggesting that the same regression should be used only in areas with similar kinds of vegetation. We discuss the considerable variation in biomass and plant functional type composition within and between different Arctic landscapes and how well this variation can be reproduced using VHSR satellite images. Overall, the usage of VHSR images creates new possibilities but to utilize them to full potential requires similarly more detailed in-situ data related to biomass inventories and other ecosystem change studies and modelling.

Plant functional diversity affects climate–vegetation interaction

Abstract. We present how variations in plant functional diversity affect climate–vegetation interaction towards the end of the African Humid Period (AHP) in coupled land–atmosphere simulations using the Max Planck Institute Earth system model (MPI-ESM). In experiments with AHP boundary conditions, the extent of the “green” Sahara varies considerably with changes in plant functional diversity. Differences in vegetation cover extent and plant functional type (PFT) composition translate into significantly different land surface parameters, water cycling, and surface energy budgets. These changes have not only regional consequences but considerably alter large-scale atmospheric circulation patterns and the position of the tropical rain belt. Towards the end of the AHP, simulations with the standard PFT set in MPI-ESM depict a gradual decrease of precipitation and vegetation cover over time, while simulations with modified PFT composition show either a sharp decline of both variables or an even slower retreat. Thus, not the quantitative but the qualitative PFT composition determines climate–vegetation interaction and the climate–vegetation system response to external forcing. The sensitivity of simulated system states to changes in PFT composition raises the question how realistically Earth system models can actually represent climate–vegetation interaction, considering the poor representation of plant diversity in the current generation of land surface models.

Predicting the abundance of forest types across the eastern United States through inverse modelling of tree demography.

Global environmental change is expected to induce widespread changes in the geographic distribution and biomass of forest communities. Impacts have been projected from both empirical (statistical) and mechanistic (physiology-based) modelling approaches, but there remains an important gap in accurately predicting abundance across species' ranges from spatial variation in individual-level demographic processes. We address this issue by using a cohort-based forest dynamics model (CAIN) to predict spatial variation in the abundance of six plant functional types (PFTs) across the eastern United States. The model simulates tree-level growth, mortality, and recruitment, which we parameterized from data on both individual-level demographic rates and population-level abundance using Bayesian inverse modelling. Across a set of 1° grid cells, we calibrated local growth, mortality, and recruitment rates for each PFT to obtain a close match between predicted age-specific PFT basal area in forest stands and that observed in 46,603 Forest Inventory and Analysis plots. The resulting models produced a strong fit to PFT basal area across the region (R2 =0.66-0.87), captured successional changes in PFT composition with stand age, and predicted the overall stem diameter distribution well. The mortality rates needed to accurately predict basal area were consistently higher than observed mortality, possibly because sampling effects led to biased individual-level mortality estimates across spatially heterogeneous plots. Growth and recruitment rates did not show consistent directional changes from observed values. Relative basal area was most strongly influenced by recruitment processes, but the effects of growth and mortality tended to increase as stands matured. Our study illustrates how both top-down (population-level) and bottom-up (individual-level) data can be combined to predict variation in abundance from size, environmental, and competitive effects on tree demography. Evidence for how demographic processes influence variation in abundance, as provided by our model, can help in understanding how these forests may respond to future environmental change.

Disentangling grazing effects: trampling, defoliation and urine deposition

AbstractQuestionsDo the effects of grazing components on vegetation structure differ in their relative importance? Do components interact in their effect on vegetation?LocationSan Jose department, Southern Campos, Uruguay.MethodsIn a manipulative field experiment we simulated three different grazing components: trampling, defoliation and urine deposition, over 3 yr in a natural grassland. Defoliation was analysed through two intensity levels and two procedures: uniform and selective cutting. We evaluated the effects of grazing components on species diversity and composition, and frequency of plant functional types.ResultsAll simulated grazing components had at least some effect on vegetation structure. Additionally, both individual and interactive effects on vegetation attributes were detected. Our study indicates that the relative influence of each grazing component varied according to the attribute considered. N addition was the only treatment that affected plant diversity. Plant functional type composition, in turn, was affected mainly by trampling. N addition and trampling were the component that affected the frequency of the largest number of species. Defoliation selectivity showed effects both in terms of plant functional type and species composition. Exclosure treatment and defoliation intensity had slight effects on grassland structure.ConclusionsThis study provides insight on the underlying mechanisms of some observed patterns of grazing on the Campos grasslands. Our results lead us to conclude that all grazing components have to be taken into account to understand vegetation dynamics subjected to grazing. Prevention of woody encroachment by grazing can be attributed to direct and indirect effects of trampling. Trampling should be taken into account to explain increaser species responses. However, mechanisms responsible for other general patterns remain less clear. The importance of selective defoliation in species replacement induced by grazing in these grasslands has yet to be clarified.

Major forest changes and land cover transitions based on plant functional types derived from the ESA CCI Land Cover product

Land use and land cover change are of prime concern due to their impacts on CO2 emissions, climate change and ecological services. New global land cover products at 300m resolution from the European Space Agency (ESA) Climate Change Initiative Land Cover (CCI LC) project for epochs centered around 2000, 2005 and 2010 were analyzed to investigate forest area change and land cover transitions. Plant functional types (PFTs) fractions were derived from these land cover products according to a conversion table. The gross global forest loss between 2000 and 2010 is 172,171km2, accounting for 0.6% of the global forest area in year 2000. The forest changes are mainly distributed in tropical areas such as Brazil and Indonesia. Forest gains were only observed between 2005 and 2010 with a global area of 9844km2, mostly from crops in Southeast Asia and South America. The predominant PFT transition is deforestation from forest to crop, accounting for four-fifths of the total increase of cropland area between 2000 and 2010. The transitions from forest to bare soil, shrub, and grass also contributed strongly to the total areal change in PFTs. Different PFT transition matrices and composition patterns were found in different regions. The highest fractions of forest to bare soil transitions were found in the United States and Canada, reflecting forest management practices. Most of the degradation from grassland and shrubland to bare soil occurred in boreal regions. The areal percentage of forest loss and land cover transitions generally decreased from 2000–2005 to 2005–2010. Different data sources and uncertainty in the conversion factors (converting from original LC classes to PFTs) contribute to the discrepancy in the values of change in absolute forest area.