Functional diversity is critical for ecosystem dynamics, stability and productivity. However, dynamic global vegetation models (DGVMs) which are increasingly used to simulate ecosystem functions ...under global change, condense functional diversity to plant functional types (PFTs) with constant parameters. Here, we develop an individual‐ and trait‐based version of the DGVM LPJmL (Lund‐Potsdam‐Jena managed Land) called LPJmL‐ flexible individual traits (LPJmL‐FIT) with flexible individual traits) which we apply to generate plant trait maps for the Amazon basin. LPJmL‐FIT incorporates empirical ranges of five traits of tropical trees extracted from the TRY global plant trait database, namely specific leaf area (SLA), leaf longevity (LL), leaf nitrogen content (Nₐᵣₑₐ), the maximum carboxylation rate of Rubisco per leaf area (vcmaxarea), and wood density (WD). To scale the individual growth performance of trees, the leaf traits are linked by trade‐offs based on the leaf economics spectrum, whereas wood density is linked to tree mortality. No preselection of growth strategies is taking place, because individuals with unique trait combinations are uniformly distributed at tree establishment. We validate the modeled trait distributions by empirical trait data and the modeled biomass by a remote sensing product along a climatic gradient. Including trait variability and trade‐offs successfully predicts natural trait distributions and achieves a more realistic representation of functional diversity at the local to regional scale. As sites of high climatic variability, the fringes of the Amazon promote trait divergence and the coexistence of multiple tree growth strategies, while lower plant trait diversity is found in the species‐rich center of the region with relatively low climatic variability. LPJmL‐FIT enables to test hypotheses on the effects of functional biodiversity on ecosystem functioning and to apply the DGVM to current challenges in ecosystem management from local to global scales, that is, deforestation and climate change effects.
Extreme droughts, heat waves, frosts, precipitation, wind storms and other climate extremes may impact the structure, composition and functioning of terrestrial ecosystems, and thus carbon cycling ...and its feedbacks to the climate system. Yet, the interconnected avenues through which climate extremes drive ecological and physiological processes and alter the carbon balance are poorly understood. Here, we review the literature on carbon cycle relevant responses of ecosystems to extreme climatic events. Given that impacts of climate extremes are considered disturbances, we assume the respective general disturbance‐induced mechanisms and processes to also operate in an extreme context. The paucity of well‐defined studies currently renders a quantitative meta‐analysis impossible, but permits us to develop a deductive framework for identifying the main mechanisms (and coupling thereof) through which climate extremes may act on the carbon cycle. We find that ecosystem responses can exceed the duration of the climate impacts via lagged effects on the carbon cycle. The expected regional impacts of future climate extremes will depend on changes in the probability and severity of their occurrence, on the compound effects and timing of different climate extremes, and on the vulnerability of each land‐cover type modulated by management. Although processes and sensitivities differ among biomes, based on expert opinion, we expect forests to exhibit the largest net effect of extremes due to their large carbon pools and fluxes, potentially large indirect and lagged impacts, and long recovery time to regain previous stocks. At the global scale, we presume that droughts have the strongest and most widespread effects on terrestrial carbon cycling. Comparing impacts of climate extremes identified via remote sensing vs. ground‐based observational case studies reveals that many regions in the (sub‐)tropics are understudied. Hence, regional investigations are needed to allow a global upscaling of the impacts of climate extremes on global carbon–climate feedbacks.
This planetary boundaries framework update finds that six of the nine boundaries are transgressed, suggesting that Earth is now well outside of the safe operating space for humanity. Ocean ...acidification is close to being breached, while aerosol loading regionally exceeds the boundary. Stratospheric ozone levels have slightly recovered. The transgression level has increased for all boundaries earlier identified as overstepped. As primary production drives Earth system biosphere functions, human appropriation of net primary production is proposed as a control variable for functional biosphere integrity. This boundary is also transgressed. Earth system modeling of different levels of the transgression of the climate and land system change boundaries illustrates that these anthropogenic impacts on Earth system must be considered in a systemic context.
Transgression of planetary boundaries by human activities have now brought humanity well beyond a “safe operating space.”
Fires are a fundamental part of the Earth System. In the last decades, they have been altering ecosystem structure, biogeochemical cycles and atmospheric composition with unprecedented rapidity. In ...this study, we implement a complex networks-based methodology to track individual fires over space and time. We focus on extreme fires—the 5% most intense fires—in the tropical forests of the Brazilian Legal Amazon over the period 2002–2019. We analyse the interannual variability in the number and spatial patterns of extreme forest fires in years with diverse climatic conditions and anthropogenic pressure to examine potential synergies between climate and anthropogenic drivers. We observe that major droughts, that increase forest flammability, co-occur with high extreme fire years but also that it is fundamental to consider anthropogenic activities to understand the distribution of extreme fires. Deforestation fires, fires escaping from managed lands, and other types of forest degradation and fragmentation provide the ignition sources for fires to ignite in the forests. We find that all extreme forest fires identified are located within a 0.5-km distance from forest edges, and up to 56% of them are within a 1-km distance from roads (which increases to 73% within 5 km), showing a strong correlation that defines spatial patterns of extreme fires.
This paper shows recent progress in our understanding of climate variability and trends in the Amazon region, and how these interact with land use change. The review includes an overview of ...up-to-date information on climate and hydrological variability, and on warming trends in Amazonia, which reached 0.6–0.7°C over the last 40 years, with 2016 as the warmest year since at least 1950 (0.9°C + 0.3°C). We focus on local and remote drivers of climate variability and change. We review the impacts of these drivers on the length of dry season, the role of the forest in climate and carbon cycles, the resilience of the forest, the risk of fires and biomass burning, and the potential “die back” of the Amazon forests if surpassing a “tipping point”. The role of the Amazon in moisture recycling and transport is also investigated, and a review of model development for climate change projections in the region is included. In sum, future sustainability of the Amazonian forests and its many services requires management strategies that consider the likelihood of multi-year droughts superimposed on a continued warming trend. Science has assembled enough knowledge to underline the global and regional importance of an intact Amazon region that can support policymaking and to keep this sensitive ecosystem functioning. This major challenge requires substantial resources and strategic cross-national planning, and a unique blend of expertise and capacities established in Amazon countries and from international collaboration. This also highlights the role of deforestation control in support of policy for mitigation options as established in the Paris Agreement of 2015.
Global Water Models (GWMs), which include Global Hydrological, Land Surface, and Dynamic Global Vegetation Models, present valuable tools for quantifying climate change impacts on hydrological ...processes in the data scarce high latitudes. Here we performed a systematic model performance evaluation in six major Pan-Arctic watersheds for different hydrological indicators (monthly and seasonal discharge, extremes, trends (or lack of), and snow water equivalent (SWE)) via a novel Aggregated Performance Index (API) that is based on commonly used statistical evaluation metrics. The machine learning Boruta feature selection algorithm was used to evaluate the explanatory power of the API attributes. Our results show that the majority of the nine GWMs included in the study exhibit considerable difficulties in realistically representing Pan-Arctic hydrological processes. Average API
discharge
(monthly and seasonal discharge) over nine GWMs is > 50% only in the Kolyma basin (55%), as low as 30% in the Yukon basin and averaged over all watersheds API
discharge
is 43%. WATERGAP2 and MATSIRO present the highest (API
discharge
> 55%) while ORCHIDEE and JULES-W1 the lowest (API
discharge
≤ 25%) performing GWMs over all watersheds. For the high and low flows, average API
extreme
is 35% and 26%, respectively, and over six GWMs API
SWE
is 57%. The Boruta algorithm suggests that using different observation-based climate data sets does not influence the total score of the APIs in all watersheds. Ultimately, only satisfactory to good performing GWMs that effectively represent cold-region hydrological processes (including snow-related processes, permafrost) should be included in multi-model climate change impact assessments in Pan-Arctic watersheds.
Climate change heavily threatens forest ecosystems worldwide and there is urgent need to understand what controls tree survival and forests stability. There is evidence that biodiversity can enhance ...ecosystem stability (Loreau and de Mazancourt in Ecol Lett 16:106-115, 2013; McCann in Nature 405:228-233, 2000), however it remains largely unclear whether this also holds for climate change and what aspects of biodiversity might be most important. Here we apply machine learning to outputs of a flexible-trait Dynamic Global Vegetation Model to unravel the effects of enhanced functional tree trait diversity and its sub-components on climate-change resistance of temperate forests ( http://www.pik-potsdam.de/~billing/video/Forest_Resistance_LPJmLFIT.mp4 ). We find that functional tree trait diversity enhances forest resistance. We explain this with 1. stronger complementarity effects (~ 25% importance) especially improving the survival of trees in the understorey of up to + 16.8% (± 1.6%) and 2. environmental and competitive filtering of trees better adapted to future climate (40-87% importance). We conclude that forests containing functionally diverse trees better resist and adapt to future conditions. In this context, we especially highlight the role of functionally diverse understorey trees as they provide the fundament for better survival of young trees and filtering of resistant tree individuals in the future.
The first generation of forest free‐air CO₂ enrichment (FACE) experiments has successfully provided deeper understanding about how forests respond to an increasing CO₂ concentration in the ...atmosphere. Located in aggrading stands in the temperate zone, they have provided a strong foundation for testing critical assumptions in terrestrial biosphere models that are being used to project future interactions between forest productivity and the atmosphere, despite the limited inference space of these experiments with regards to the range of global ecosystems. Now, a new generation of FACE experiments in mature forests in different biomes and over a wide range of climate space and biodiversity will significantly expand the inference space. These new experiments are: EucFACE in a mature Eucalyptus stand on highly weathered soil in subtropical Australia; AmazonFACE in a highly diverse, primary rainforest in Brazil; BIFoR‐FACE in a 150‐yr‐old deciduous woodland stand in central England; and SwedFACE proposed in a hemiboreal, Pinus sylvestris stand in Sweden. We now have a unique opportunity to initiate a model–data interaction as an integral part of experimental design and to address a set of cross‐site science questions on topics including responses of mature forests; interactions with temperature, water stress, and phosphorus limitation; and the influence of biodiversity.
The length of time that carbon remains in forest biomass
is one of the largest uncertainties in the global carbon cycle, with both
recent historical baselines and future responses to environmental ...change
poorly constrained by available observations. In the absence of large-scale
observations, models used for global assessments tend to fall back on
simplified assumptions of the turnover rates of biomass and soil carbon
pools. In this study, the biomass carbon turnover times calculated by an
ensemble of contemporary terrestrial biosphere models (TBMs) are analysed to
assess their current capability to accurately estimate biomass carbon
turnover times in forests and how these times are anticipated to change in
the future. Modelled baseline 1985–2014 global average forest biomass
turnover times vary from 12.2 to 23.5 years between TBMs. TBM differences in
phenological processes, which control allocation to, and turnover rate of,
leaves and fine roots, are as important as tree mortality with regard to
explaining the variation in total turnover among TBMs. The different
governing mechanisms exhibited by each TBM result in a wide range of
plausible turnover time projections for the end of the century. Based on
these simulations, it is not possible to draw robust conclusions regarding
likely future changes in turnover time, and thus biomass change, for
different regions. Both spatial and temporal uncertainty in turnover time
are strongly linked to model assumptions concerning plant functional type
distributions and their controls. Thirteen model-based hypotheses of
controls on turnover time are identified, along with recommendations for
pragmatic steps to test them using existing and novel observations. Efforts
to resolve uncertainty in turnover time, and thus its impacts on the future
evolution of biomass carbon stocks across the world's forests, will need to
address both mortality and establishment components of forest demography, as
well as allocation of carbon to woody versus non-woody biomass growth.
Ecosystems respond in various ways to disturbances. Quantifying ecological stability therefore requires inspecting multiple stability properties, such as resistance, recovery, persistence and ...invariability. Correlations among these properties can reduce the dimensionality of stability, simplifying the study of environmental effects on ecosystems. A key question is how the kind of disturbance affects these correlations. We here investigated the effect of three disturbance types (random, species‐specific, local) applied at four intensity levels, on the dimensionality of stability at the population and community level. We used previously parameterized models that represent five natural communities, varying in species richness and the number of trophic levels. We found that disturbance type but not intensity affected the dimensionality of stability and only at the population level. The dimensionality of stability also varied greatly among species and communities. Therefore, studying stability cannot be simplified to using a single metric and multi‐dimensional assessments are still to be recommended.
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