Organizing principles for vegetation dynamics

Variations and trade-offs in leaf and culm functional traits among 77 woody bamboo species

BACKGROUND

Woody bamboos are the only diverse large perennial grasses in mesic-wet forests and are widely distributed in the understory and canopy. The functional trait variations and trade-offs in this taxon remain unclear due to woody bamboo syndromes (represented by lignified culm of composed internodes and nodes). Here, we examined the effects of heritable legacy and occurrence site climates on functional trait variations in leaf and culm across 77 woody bamboo species in a common garden. We explored the trade-offs among leaf functional traits, the connection between leaf nitrogen (N), phosphorus (P) concentrations and functional niche traits, and the correlation of functional traits between leaves and culms.

RESULTS

The Bayesian mixed models reveal that the combined effects of heritable legacy (phylogenetic distances and other evolutionary processes) and occurrence site climates accounted for 55.10-90.89% of the total variation among species for each studied trait. The standardized major axis analysis identified trade-offs among leaf functional traits in woody bamboo consistent with the global leaf economics spectrum; however, compared to non-bamboo species, the woody bamboo exhibited lower leaf mass per area but higher N, P concentrations and assimilation, dark respiration rates. The canonical correlation analysis demonstrated a positive correlation (ρ = 0.57, P-value < 0.001) between leaf N, P concentrations and morphophysiology traits. The phylogenetic principal components and trait network analyses indicated that leaf and culm traits were clustered separately, with leaf assimilation and respiration rates associated with culm ground diameter.

CONCLUSION

Our study confirms the applicability of the leaf economics spectrum and the biogeochemical niche in woody bamboo taxa, improves the understanding of woody bamboo leaf and culm functional trait variations and trade-offs, and broadens the taxonomic units considered in plant functional trait studies, which contributes to our comprehensive understanding of terrestrial forest ecosystems.

A neutral theory of plant carbon allocation

How plants use the carbon they gain from photosynthesis remains a key area of study among plant ecologists. Although numerous theories have been presented throughout the years, the field lacks a clear null model. To fill this gap, I have developed the first null model, or neutral theory, of plant carbon allocation using probability theory, plant biochemistry and graph theory at the level of a leaf. Neutral theories have been used to establish a null hypothesis in molecular evolution and community assembly to describe how much of an ecological phenomenon can be described by chance alone. Here, the aim of a neutral theory of plant carbon allocation is to ask: how is carbon partitioned between sinks if one assumes plants do not prioritize certain sinks over others? Using the biochemical network of plant carbon metabolism, I show that, if allocation was strictly random, carbon is more likely to be allocated to storage, defense, respiration and finally growth. This 'neutral hierarchy' suggests that a sink's biochemical distance from photosynthesis plays an important role in carbon allocation patterns, highlighting the potentially adaptive role of this biochemical network for plant survival in variable environments. A brief simulation underscores that our ability to measure the carbon allocation from photosynthesis to a given sink is unreliable due to simple probabilistic rules. While neutral theory may not explain all patterns of carbon allocation, its utility is in the minimal assumptions and role as a null model against which future data should be tested.

Amphistomy increases leaf photosynthesis more in coastal than montane plants of Hawaiian 'ilima (Sida fallax)

PREMISE

The adaptive significance of amphistomy (stomata on both upper and lower leaf surfaces) is unresolved. A widespread association between amphistomy and open, sunny habitats suggests the adaptive benefit of amphistomy may be greatest in these contexts, but this hypothesis has not been tested experimentally. Understanding amphistomy informs its potential as a target for crop improvement and paleoenvironment reconstruction.

METHODS

We developed a method to quantify "amphistomy advantage" (AA $\text{AA}$ ) as the log-ratio of photosynthesis in an amphistomatous leaf to that of the same leaf but with gas exchange blocked through the upper surface (pseudohypostomy). Humidity modulated stomatal conductance and thus enabled comparing photosynthesis at the same total stomatal conductance. We estimatedAA $\text{AA}$ and leaf traits in six coastal (open, sunny) and six montane (closed, shaded) populations of the indigenous Hawaiian species 'ilima (Sida fallax).

RESULTS

Coastal 'ilima leaves benefit 4.04 times more from amphistomy than montane leaves. Evidence was equivocal with respect to two hypotheses: (1) that coastal leaves benefit more because they are thicker and have lower CO2 conductance through the internal airspace and (2) that they benefit more because they have similar conductance on each surface, as opposed to most conductance being through the lower surface.

CONCLUSIONS

This is the first direct experimental evidence that amphistomy increases photosynthesis, consistent with the hypothesis that parallel pathways through upper and lower mesophyll increase CO2 supply to chloroplasts. The prevalence of amphistomatous leaves in open, sunny habitats can partially be explained by the increased benefit of amphistomy in "sun" leaves, but the mechanistic basis remains uncertain.

The carbon balance of plants: economics, optimization, and trait spectra in a historical perspective

Over fifty years have passed since the publication of Harold Mooney's formative paper, "The Carbon Balance of Plants" on pages 315-346 of Volume 3 (1972) of Annual Review of Ecology and Systematics. Arguably, the conceptual framework presented in that paper, and the work by Mooney and his students leading up to the paper, provided the foundational principles from which core disciplines emerged in plant economic theory, functional trait theory and, more generally, plant physiological ecology. Here, we revisit the primary impacts of those early discoveries to understand how researchers constructed major concepts in our understanding of plant adaptations, and where those concepts are likely to take us in the near future. The discipline of functional trait ecology, which is rooted in the principles of evolutionary and economic optimization, has captured the imagination of the plant physiological ecology research community, though its emphasis has shifted toward predicting species distributions and ecological roles across resource gradients. In the face of 'big-data' research pursuits that are revealing trait expression patterns at the cellular level and mass and energy exchange patterns at the planetary scale, an opportunity exists to reconnect the principles of plant carbon balance and evolutionary optimization with trait origins at the genetic and cellular scales and trait impacts at the global scale.

Wood-density has no effect on stomatal control of leaf-level water use efficiency in an Amazonian forest

Forest disturbances increase the proportion of fast-growing tree species compared to slow-growing ones. To understand their relative capacity for carbon uptake and their vulnerability to climate change, and to represent those differences in Earth system models, it is necessary to characterise the physiological differences in their leaf-level control of water use efficiency and carbon assimilation. We used wood density as a proxy for the fast-slow growth spectrum and tested the assumption that trees with a low wood density (LWD) have a lower water-use efficiency than trees with a high wood density (HWD). We selected 5 LWD tree species and 5 HWD tree species growing in the same location in an Amazonian tropical forest and measured in situ steady-state gas exchange on top-of-canopy leaves with parallel sampling and measurement of leaf mass area and leaf nitrogen content. We found that LWD species invested more nitrogen in photosynthetic capacity than HWD species, had higher photosynthetic rates and higher stomatal conductance. However, contrary to expectations, we showed that the stomatal control of the balance between transpiration and carbon assimilation was similar in LWD and HWD species and that they had the same dark respiration rates.

The hidden order of Turing patterns in arid and semi-arid vegetation ecosystems

Vegetation Turing patterns play a critical role in the ecological functioning of arid and semi-arid ecosystems. However, the long-range spatial features of these patterns have been neglected compared to short-range features like patch shape and spatial wavelength. Drawing inspiration from hyperuniform structures in material science, we find that the arid and semi-arid vegetation Turing pattern exhibits long-range dispersion similar to hyperuniformity. As the degree of hyperuniformity of the vegetation Turing pattern increases, so does the water-use efficiency of the vegetation. This finding supports previous studies that suggest that Turing patterns represent a spatially optimized self-organization of ecosystems for water acquisition. The degree of hyperuniformity of Turing-type ecosystems exhibits significant critical slowing down near the tipping point, indicating that these ecosystems have non-negligible transient dynamical behavior. Reduced rainfall not only decreases the resilience of the steady state of the ecosystem but also slows down the rate of spatial optimization of water-use efficiency in long transient regimes. We propose that the degree of hyperuniformity indicates the spatial resilience of Turing-type ecosystems after strong, short-term disturbances. Spatially heterogeneous disturbances that reduce hyperuniformity lead to longer recovery times than spatially homogeneous disturbances that maintain hyperuniformity.

Vegetation-environment interactions: plant species distribution and community assembly in mixed coniferous forests of Northwestern Himalayas

One of the main goals of ecological studies is to disentangle the dynamics that underlie the spatiotemporal distribution of biodiversity and further functions of the ecosystem. However, due to many ecological and geopolitical reasons, many remote areas with high plant species diversity have not been assessed using newly based analytical approaches for vegetation characterization. Here, we classified and characterized different vegetation types (i.e., major plant communities) based on indicator species and on the influence of different environmental gradients in the Himalayan mixed coniferous forest, Pakistan. For that, we addressed the following questions: Does the vegetation composition of the Himalayan mixed coniferous forest correlate with climatic, topographic, geographic, and edaphic variables? Is it possible to identify plant communities through indicator species in relation to environmental gradients using multivariate approaches? Can this multivariate be helpful for conservation planning? During four consecutive years we assessed the vegetation composition and environmental variables (21 variables divided in geographic, climatic, topographic, and edaphic groups) of 156 50 m-trasects between an elevation of 2000-4000 m. Using newly based analytical approaches for community characterization, we found a total of 218 plant species clustered into four plant communities with the influence of environmental gradients. The highest index of similarity was recorded between Pinus-Cedrus-Viburnum (PCV) and Viburnum-Pinus-Abies (VPA) communities, and the highest index of dissimilarity was recorded between PCV and Abies-Juniperus-Picea (AJP) communities. Among these four communities, highest number of plant species (156 species) was recorded in PCV, maximum alpha diversity (H' = 3.68) was reported in VPA, highest Simpson index (0.961) and Pielou's evenness (0.862) were reported in VPA and AJP. The edaphic gradients (i.e., organic matter, phosphorous, pH and soil texture) and climatic factors (temperature, humidity) were the strongest environmental gradients that were responsible for structuring and hosting the diverse plant communities in mixed coniferous forest. Finally, the Himalayan mixed coniferous structure is more influenced by the spatial turnover beta-diversity process (βsim) than by the species loss (nestedness-resultant, βsne). Our analysis of the vegetation structure along the environmental gradient in the Himalayan mixed coniferous forest supported by sophisticated analytical approaches reveled indicator species groups, which are associated to specific microclimatic zones (i.e., vegetation communities). Within this focus, we side with the view that these results can support conservation planning and management for similar and different areas providing mitigating and preventive measures to reduce potential negative impacts, such as anthropic and climatic.

Accounting for trait variability and coordination in predictions of drought-induced range shifts in woody plants

Functional traits offer a promising avenue to improve predictions of species range shifts under climate change, which will entail warmer and often drier conditions. Although the conceptual foundation linking traits with plant performance and range shifts appears solid, the predictive ability of individual traits remains generally low. In this review, we address this apparent paradox, emphasizing examples of woody plants and traits associated with drought responses at the species' rear edge. Low predictive ability reflects the fact not only that range dynamics tend to be complex and multifactorial, as well as uncertainty in the identification of relevant traits and limited data availability, but also that trait effects are scale- and context-dependent. The latter results from the complex interactions among traits (e.g. compensatory effects) and between them and the environment (e.g. exposure), which ultimately determine persistence and colonization capacity. To confront this complexity, a more balanced coverage of the main functional dimensions involved (stress tolerance, resource use, regeneration and dispersal) is needed, and modelling approaches must be developed that explicitly account for: trait coordination in a hierarchical context; trait variability in space and time and its relationship with exposure; and the effect of biotic interactions in an ecological community context.

Soil nitrogen fertilization reduces relative leaf nitrogen allocation to photosynthesis

The connection between soil nitrogen availability, leaf nitrogen, and photosynthetic capacity is not perfectly understood. Because these three components tend to be positively related over large spatial scales, some posit that soil nitrogen positively drives leaf nitrogen, which positively drives photosynthetic capacity. Alternatively, others posit that photosynthetic capacity is primarily driven by above-ground conditions. Here, we examined the physiological responses of a non-nitrogen-fixing plant (Gossypium hirsutum) and a nitrogen-fixing plant (Glycine max) in a fully factorial combination of light by soil nitrogen availability to help reconcile these competing hypotheses. Soil nitrogen stimulated leaf nitrogen in both species, but the relative proportion of leaf nitrogen used for photosynthetic processes was reduced under elevated soil nitrogen in all light availability treatments due to greater increases in leaf nitrogen content than chlorophyll and leaf biochemical process rates. Leaf nitrogen content and biochemical process rates in G. hirsutum were more responsive to changes in soil nitrogen than those in G. max, probably due to strong G. max investments in root nodulation under low soil nitrogen. Nonetheless, whole-plant growth was significantly enhanced by increased soil nitrogen in both species. Light availability consistently increased relative leaf nitrogen allocation to leaf photosynthesis and whole-plant growth, a pattern that was similar between species. These results suggest that the leaf nitrogen-photosynthesis relationship varies under different soil nitrogen levels and that these species preferentially allocated more nitrogen to plant growth and non-photosynthetic leaf processes, rather than photosynthesis, as soil nitrogen increased.

Optimal balancing of xylem efficiency and safety explains plant vulnerability to drought

In vast areas of the world, forests and vegetation are water limited and plant survival depends on the ability to avoid catastrophic hydraulic failure. Therefore, it is remarkable that plants take hydraulic risks by operating at water potentials (ψ) that induce partial failure of the water conduits (xylem). Here we present an eco-evolutionary optimality principle for xylem conduit design that explains this phenomenon based on the hypothesis that conductive efficiency and safety are optimally co-adapted to the environment. The model explains the relationship between the tolerance to negative water potential (ψ50 ) and the environmentally dependent minimum ψ (ψmin ) across a large number of species, and along the xylem pathway within individuals of two species studied. The wider hydraulic safety margin in gymnosperms compared to angiosperms can be explained as an adaptation to a higher susceptibility to accumulation of embolism. The model provides a novel optimality-based perspective on the relationship between xylem safety and efficiency.

Leaf-level coordination principles propagate to the ecosystem scale

Fundamental axes of variation in plant traits result from trade-offs between costs and benefits of resource-use strategies at the leaf scale. However, it is unclear whether similar trade-offs propagate to the ecosystem level. Here, we test whether trait correlation patterns predicted by three well-known leaf- and plant-level coordination theories - the leaf economics spectrum, the global spectrum of plant form and function, and the least-cost hypothesis - are also observed between community mean traits and ecosystem processes. We combined ecosystem functional properties from FLUXNET sites, vegetation properties, and community mean plant traits into three corresponding principal component analyses. We find that the leaf economics spectrum (90 sites), the global spectrum of plant form and function (89 sites), and the least-cost hypothesis (82 sites) all propagate at the ecosystem level. However, we also find evidence of additional scale-emergent properties. Evaluating the coordination of ecosystem functional properties may aid the development of more realistic global dynamic vegetation models with critical empirical data, reducing the uncertainty of climate change projections.

The effect of the vertical gradients of photosynthetic parameters on the CO2 assimilation and transpiration of a Panamanian tropical forest

Terrestrial biosphere models (TBMs) include the representation of vertical gradients in leaf traits associated with modeling photosynthesis, respiration, and stomatal conductance. However, model assumptions associated with these gradients have not been tested in complex tropical forest canopies. We compared TBM representation of the vertical gradients of key leaf traits with measurements made in a tropical forest in Panama and then quantified the impact of the observed gradients on simulated canopy-scale CO₂ and water fluxes. Comparison between observed and TBM trait gradients showed divergence that impacted canopy-scale simulations of water vapor and CO₂ exchange. Notably, the ratio between the dark respiration rate and the maximum carboxylation rate was lower near the ground than at the top-of-canopy, leaf-level water-use efficiency was markedly higher at the top-of-canopy, and the decrease in maximum carboxylation rate from the top-of-canopy to the ground was less than TBM assumptions. The representation of the gradients of leaf traits in TBMs is typically derived from measurements made within-individual plants, or, for some traits, assumed constant due to a lack of experimental data. Our work shows that these assumptions are not representative of the trait gradients observed in species-rich, complex tropical forests.

No carbon storage in growth-limited trees in a semi-arid woodland

Plant survival depends on a balance between carbon supply and demand. When carbon supply becomes limited, plants buffer demand by using stored carbohydrates (sugar and starch). During drought, NSCs (non-structural carbohydrates) may accumulate if growth stops before photosynthesis. This expectation is pervasive, yet few studies have combined simultaneous measurements of drought, photosynthesis, growth, and carbon storage to test this. Using a field experiment with mature trees in a semi-arid woodland, we show that growth and photosynthesis slow in parallel as [Formula: see text] declines, preventing carbon storage in two species of conifer (J. monosperma and P. edulis). During experimental drought, growth and photosynthesis were frequently co-limited. Our results point to an alternative perspective on how plants use carbon that views growth and photosynthesis as independent processes both regulated by water availability.

Do stomata optimize turgor-driven growth? A new framework for integrating stomata response with whole-plant hydraulics and carbon balance

Every existing optimal stomatal model uses photosynthetic carbon assimilation as a proxy for plant evolutionary fitness. However, assimilation and growth are often decoupled, making assimilation less ideal for representing fitness when optimizing stomatal conductance to water vapor and carbon dioxide. Instead, growth should be considered a closer proxy for fitness. We hypothesize stomata have evolved to maximize turgor-driven growth, instead of assimilation, over entire plants' lifetimes, improving their abilities to compete and reproduce. We develop a stomata model that dynamically maximizes whole-stem growth following principles from turgor-driven growth models. Stomata open to assimilate carbohydrates that supply growth and osmotically generate turgor, while stomata close to prevent losses of turgor and growth due to negative water potentials. In steady state, the growth optimization model captures realistic stomatal, growth, and carbohydrate responses to environmental cues, reconciles conflicting interpretations within existing stomatal optimization theories, and explains patterns of carbohydrate storage and xylem conductance observed during and after drought. Our growth optimization hypothesis introduces a new paradigm for stomatal optimization models, elevates the role of whole-plant carbon use and carbon storage in stomatal functioning, and has the potential to simultaneously predict gross productivity, net productivity, and plant mortality through a single, consistent modeling framework.

Atmospheric phosphorus deposition amplifies carbon sinks in simulations of a tropical forest in Central Africa

Spatial redistribution of nutrients by atmospheric transport and deposition could theoretically act as a continental-scale mechanism which counteracts declines in soil fertility caused by nutrient lock-up in accumulating biomass in tropical forests in Central Africa. However, to what extent it affects carbon sinks in forests remains elusive. Here we use a terrestrial biosphere model to quantify the impact of changes in atmospheric nitrogen and phosphorus deposition on plant nutrition and biomass carbon sink at a typical lowland forest site in Central Africa. We find that the increase in nutrient deposition since the 1980s could have contributed to the carbon sink over the past four decades up to an extent which is similar to that from the combined effects of increasing atmospheric carbon dioxide and climate change. Furthermore, we find that the modelled carbon sink responds to changes in phosphorus deposition, but less so to nitrogen deposition. The pronounced response of ecosystem productivity to changes in nutrient deposition illustrates a potential mechanism that could control carbon sinks in Central Africa. Monitoring the quantity and quality of nutrient deposition is needed in this region, given the changes in nutrient deposition due to human land use.

Transitions between dissipative localized structures in the simplified Gilad-Meron model for dryland plant ecology

Spatially extended patterns and multistability of possible different states are common in many ecosystems, and their combination has an important impact on their dynamical behaviors. One potential combination involves tristability between a patterned state and two different uniform states. Using a simplified version of the Gilad-Meron model for dryland ecosystems, we study the organization, in bifurcation terms, of the localized structures arising in tristable regimes. These states are generally related to the concept of wave front locking and appear in the form of spots and gaps of vegetation. We find that the coexistence of localized spots and gaps, within tristable configurations, yields the appearance of hybrid states. We also study the emergence of spatiotemporal localized states consisting of a portion of a periodic pattern embedded in a uniform Hopf-like oscillatory background in a subcritical Turing-Hopf dynamical regime.

Global patterns of water storage in the rooting zones of vegetation

The rooting-zone water-storage capacity-the amount of water accessible to plants-controls the sensitivity of land-atmosphere exchange of water and carbon during dry periods. How the rooting-zone water-storage capacity varies spatially is largely unknown and not directly observable. Here we estimate rooting-zone water-storage capacity globally from the relationship between remotely sensed vegetation activity, measured by combining evapotranspiration, sun-induced fluorescence and radiation estimates, and the cumulative water deficit calculated from daily time series of precipitation and evapotranspiration. Our findings indicate plant-available water stores that exceed the storage capacity of 2-m-deep soils across 37% of Earth's vegetated surface. We find that biome-level variations of rooting-zone water-storage capacities correlate with observed rooting-zone depth distributions and reflect the influence of hydroclimate, as measured by the magnitude of annual cumulative water-deficit extremes. Smaller-scale variations are linked to topography and land use. Our findings document large spatial variations in the effective root-zone water-storage capacity and illustrate a tight link among the climatology of water deficits, rooting depth of vegetation and its sensitivity to water stress.

Leaf economics fundamentals explained by optimality principles

The life span of leaves increases with their mass per unit area (LMA). It is unclear why. Here, we show that this empirical generalization (the foundation of the worldwide leaf economics spectrum) is a consequence of natural selection, maximizing average net carbon gain over the leaf life cycle. Analyzing two large leaf trait datasets, we show that evergreen and deciduous species with diverse construction costs (assumed proportional to LMA) are selected by light, temperature, and growing-season length in different, but predictable, ways. We quantitatively explain the observed divergent latitudinal trends in evergreen and deciduous LMA and show how local distributions of LMA arise by selection under different environmental conditions acting on the species pool. These results illustrate how optimality principles can underpin a new theory for plant geography and terrestrial carbon dynamics.

Optimality principles explaining divergent responses of alpine vegetation to environmental change

Recent increases in vegetation greenness over much of the world reflect increasing CO₂ globally and warming in cold areas. However, the strength of the response to both CO₂ and warming in those areas appears to be declining for unclear reasons, contributing to large uncertainties in predicting how vegetation will respond to future global changes. Here, we investigated the changes of satellite-observed peak season absorbed photosynthetically active radiation (F_max ) on the Tibetan Plateau between 1982 and 2016. Although climate trends are similar across the Plateau, we identified robust divergent responses (a greening of 0.31 ± 0.14% year^-1 in drier regions and a browning of 0.12 ± 0.08% year^-1 in wetter regions). Using an eco-evolutionary optimality (EEO) concept of plant acclimation/adaptation, we propose a parsimonious modelling framework that quantitatively explains these changes in terms of water and energy limitations. Our model captured the variations in F_max with a correlation coefficient (r) of .76 and a root mean squared error of .12 and predicted the divergent trends of greening (0.32 ± 0.19% year^-1 ) and browning (0.07 ± 0.06% year^-1 ). We also predicted the observed reduced sensitivities of F_max to precipitation and temperature. The model allows us to explain these changes: Enhanced growing season cumulative radiation has opposite effects on water use and energy uptake. Increased precipitation has an overwhelmingly positive effect in drier regions, whereas warming reduces F_max in wetter regions by increasing the cost of building and maintaining leaf area. Rising CO₂ stimulates vegetation growth by enhancing water-use efficiency, but its effect on photosynthesis saturates. The large decrease in the sensitivity of vegetation to climate reflects a shift from water to energy limitation. Our study demonstrates the potential of EEO approaches to reveal the mechanisms underlying recent trends in vegetation greenness and provides further insight into the response of alpine ecosystems to ongoing climate change.

Towards a unified theory of plant photosynthesis and hydraulics

The global carbon and water cycles are governed by the coupling of CO₂ and water vapour exchanges through the leaves of terrestrial plants, controlled by plant adaptations to balance carbon gains and hydraulic risks. We introduce a trait-based optimality theory that unifies the treatment of stomatal responses and biochemical acclimation of plants to environments changing on multiple timescales. Tested with experimental data from 18 species, our model successfully predicts the simultaneous decline in carbon assimilation rate, stomatal conductance and photosynthetic capacity during progressive soil drought. It also correctly predicts the dependencies of gas exchange on atmospheric vapour pressure deficit, temperature and CO₂. Model predictions are also consistent with widely observed empirical patterns, such as the distribution of hydraulic strategies. Our unified theory opens new avenues for reliably modelling the interactive effects of drying soil and rising atmospheric CO₂ on global photosynthesis and transpiration.

Leaf nitrogen from the perspective of optimal plant function

Leaf dry mass per unit area (LMA), carboxylation capacity (V _cmax) and leaf nitrogen per unit area (N_area) and mass (N_mass) are key traits for plant functional ecology and ecosystem modelling. There is however no consensus about how these traits are regulated, or how they should be modelled. Here we confirm that observed leaf nitrogen across species and sites can be estimated well from observed LMA and V _cmax at 25°C (V _cmax25). We then test the hypothesis that global variations of both quantities depend on climate variables in specific ways that are predicted by leaf-level optimality theory, thus allowing both N_area to be predicted as functions of the growth environment.A new global compilation of field measurements was used to quantify the empirical relationships of leaf N to V _cmax25 and LMA. Relationships of observed V _cmax25 and LMA to climate variables were estimated, and compared to independent theoretical predictions of these relationships. Soil effects were assessed by analysing biases in the theoretical predictions.LMA was the most important predictor of N_area (increasing) and N_mass (decreasing). About 60% of global variation across species and sites in observed N_area, and 31% in N_mass, could be explained by observed LMA and V _cmax25. These traits, in turn, were quantitatively related to climate variables, with significant partial relationships similar or indistinguishable from those predicted by optimality theory. Predicted trait values explained 21% of global variation in observed site-mean V _cmax25, 43% in LMA and 31% in N_area. Predicted V _cmax25 was biased low on clay-rich soils but predicted LMA was biased high, with compensating effects on N_area. N_area was overpredicted on organic soils. Synthesis. Global patterns of variation in observed site-mean N_area can be explained by climate-induced variations in optimal V _cmax25 and LMA. Leaf nitrogen should accordingly be modelled as a consequence (not a cause) of V _cmax25 and LMA, both being optimized to the environment. Nitrogen limitation of plant growth would then be modelled principally via whole-plant carbon allocation, rather than via leaf-level traits. Further research is required to better understand and model the terrestrial nitrogen and carbon cycles and their coupling.

Insights into source/sink controls on wood formation and photosynthesis from a stem chilling experiment in mature red maple

Whether sources or sinks control wood growth remains debated with a paucity of evidence from mature trees in natural settings. Here, we altered carbon supply rate in stems of mature red maples (Acer rubrum) within the growing season by restricting phloem transport using stem chilling; thereby increasing carbon supply above and decreasing carbon supply below the restrictions, respectively. Chilling successfully altered nonstructural carbon (NSC) concentrations in the phloem without detectable repercussions on bulk NSC in stems and roots. Ring width responded strongly to local variations in carbon supply with up to seven-fold differences along the stem of chilled trees; however, concurrent changes in the structural carbon were inconclusive at high carbon supply due to large local variability of wood growth. Above chilling-induced bottlenecks, we also observed higher leaf NSC concentrations, reduced photosynthetic capacity, and earlier leaf coloration and fall. Our results indicate that the cambial sink is affected by carbon supply, but within-tree feedbacks can downregulate source activity, when carbon supply exceeds demand. Such feedbacks have only been hypothesized in mature trees. Consequently, these findings constitute an important advance in understanding source-sink dynamics, suggesting that mature red maples operate close to both source- and sink-limitation in the early growing season.

The evolution, complexity and diversity of models of long-term forest dynamics

To assess the impacts of climate change on vegetation from stand to global scales, models of forest dynamics that include tree demography are needed. Such models are now available for 50 years, but the currently existing diversity of model formulations and its evolution over time are poorly documented. This hampers systematic assessments of structural uncertainties in model-based studies.We conducted a meta-analysis of 28 models, focusing on models that were used in the past five years for climate change studies. We defined 52 model attributes in five groups (basic assumptions, growth, regeneration, mortality and soil moisture) and characterized each model according to these attributes. Analyses of model complexity and diversity included hierarchical cluster analysis and redundancy analysis.Model complexity evolved considerably over the past 50 years. Increases in complexity were largest for growth processes, while complexity of modelled establishment processes increased only moderately. Model diversity was lowest at the global scale, and highest at the landscape scale. We identified five distinct clusters of models, ranging from very simple models to models where specific attribute groups are rendered in a complex manner and models that feature high complexity across all attributes.Most models in use today are not balanced in the level of complexity with which they represent different processes. This is the result of different model purposes, but also reflects legacies in model code, modelers' preferences, and the 'prevailing spirit of the epoch'. The lack of firm theories, laws and 'first principles' in ecology provides high degrees of freedom in model development, but also results in high responsibilities for model developers and the need for rigorous model evaluation. Synthesis. The currently available model diversity is beneficial: convergence in simulations of structurally different models indicates robust projections, while convergence of similar models may convey a false sense of certainty. The existing model diversity-with the exception of global models-can be exploited for improved projections based on multiple models. We strongly recommend balanced further developments of forest models that should particularly focus on establishment and mortality processes, in order to provide robust information for decisions in ecosystem management and policymaking.

Predicting resilience through the lens of competing adjustments to vegetation function

There is a pressing need to better understand ecosystem resilience to droughts and heatwaves. Eco-evolutionary optimization approaches have been proposed as means to build this understanding in land surface models and improve their predictive capability, but competing approaches are yet to be tested together. Here, we coupled approaches that optimize canopy gas exchange and leaf nitrogen investment, respectively, extending both approaches to account for hydraulic impairment. We assessed model predictions using observations from a native Eucalyptus woodland that experienced repeated droughts and heatwaves between 2013 and 2020, whilst exposed to an elevated [CO₂ ] treatment. Our combined approaches improved predictions of transpiration and enhanced the simulated magnitude of the CO₂ fertilization effect on gross primary productivity. The competing approaches also worked consistently along axes of change in soil moisture, leaf area, and [CO₂ ]. Despite predictions of a significant percentage loss of hydraulic conductivity due to embolism (PLC) in 2013, 2014, 2016, and 2017 (99th percentile PLC > 45%), simulated hydraulic legacy effects were small and short-lived (2 months). Our analysis suggests that leaf shedding and/or suppressed foliage growth formed a strategy to mitigate drought risk. Accounting for foliage responses to water availability has the potential to improve model predictions of ecosystem resilience.

Modeling Global Carbon Costs of Plant Nitrogen and Phosphorus Acquisition

Most Earth system models (ESMs) do not explicitly represent the carbon (C) costs of plant nutrient acquisition, which leads to uncertainty in predictions of the current and future constraints to the land C sink. We integrate a plant productivity-optimizing nitrogen (N) and phosphorus (P) acquisition model (fixation & uptake of nutrients, FUN) into the energy exascale Earth system (E3SM) land model (ELM). Global plant N and P uptake are dynamically simulated by ELM-FUN based on the C costs of nutrient acquisition from mycorrhizae, direct root uptake, retranslocation from senescing leaves, and biological N fixation. We benchmarked ELM-FUN with three classes of products: ILAMB, a remotely sensed nutrient limitation product, and CMIP6 models; we found significant improvements in C cycle variables, although the lack of more observed nutrient data prevents a comprehensive level of benchmarking. Overall, we found N and P co-limitation for 80% of land area, with the remaining 20% being either predominantly N or P limited. Globally, the new model predicts that plants invested 4.1 Pg C yr-1 to acquire 841.8 Tg N yr-1 and 48.1 Tg P yr-1 (1994-2005), leading to significant downregulation of global net primary production (NPP). Global NPP is reduced by 20% with C costs of N and 50% with C costs of NP. Modeled and observed nutrient limitation agreement increases when N and P are considered together (r 2 from 0.73 to 0.83).

Forest disturbances and climate constrain carbon allocation dynamics in trees

Forest disturbances such as drought, fire, and logging affect the forest carbon dynamics and the terrestrial carbon sink. Forest mortality after disturbances creates uncertainties that need to be accounted for to understand forest dynamics and their associated C-sink. We combined data from permanent resampling plots and biomass oriented dendroecological plots to estimate time series of annual woody biomass growth (ABI) in several forests. ABI time series were used to benchmark a vegetation model to analyze dynamics in forest productivity and carbon allocation forced by environmental variability. The model implements source and sink limitations explicitly by dynamically constraining carbon allocation of assimilated photosynthates as a function of temperature and moisture. Bias in tree-ring reconstructed ABI increased back in time from data collection and with increasing disturbance intensity. ABI bias ranged from zero, in open stands without recorded mortality, to over 100% in stands with major disturbances such as thinning or snowstorms. Stand leaf area was still lower than in control plots decades after heavy thinning. Disturbances, species life-history strategy and climatic variability affected carbon-partitioning patterns in trees. Resprouting broadleaves reached maximum biomass growth at earlier ages than nonresprouting conifers. Environmental variability and leaf area explained much variability in woody biomass allocation. Effects of stand competition on C-allocation were mediated by changes in stand leaf area except after major disturbances. Divergence between tree-ring estimated and simulated ABI were caused by unaccounted changes in allocation or misrepresentation of some functional process independently of the model calibration approach. Higher disturbance intensity produced greater modifications of the C-allocation pattern, increasing error in reconstructed biomass dynamics. Legacy effects from disturbances decreased model performance and reduce the potential use of ABI as a proxy to net primary productivity. Trait-based dynamics of C-allocation in response to environmental variability need to be refined in vegetation models.

Soil phosphorus drives plant trait variations in a mature subtropical forest

Earth system models are implementing soil phosphorus dynamic and plant functional traits to predict functional changes in global forests. However, the linkage between soil phosphorus and plant traits lacks empirical evidence, especially in mature forests. Here, we examined the soil phosphorus constraint on plant functional traits in a mature subtropical forest based on observations of 9943 individuals from 90 species in a 5-ha forest dynamic plot and 405 individuals from 15 species in an adjacent 10-year nutrient-addition experiment. We first confirmed a pervasive phosphorus limitation on subtropical tree growth based on leaf N:P ratios. Then, we found that soil phosphorus dominated multidimensional trait variations in the 5-ha forest dynamic plot. Soil phosphorus content explained 44% and 53% of the variance in the traits defining the main functional space across species and communities, respectively. Lastly, we found much stronger phosphorus effects on most plant functional traits than nitrogen at both species and community levels in the 10-year nutrient-addition experiment. This study provides evidence for the consistent pattern of soil phosphorus constraint on plant trait variations between the species and community levels in a mature evergreen broadleaf forest in the East Asian monsoon region. These findings shed light on the predominant role of soil phosphorus on plant functional trait variations in mature subtropical forests, providing new insights for models to incorporate soil phosphorus constraint in predicting future vegetation dynamics.

Increasing the spatial and temporal impact of ecological research: A roadmap for integrating a novel terrestrial process into an Earth system model

Terrestrial ecosystems regulate Earth's climate through water, energy, and biogeochemical transformations. Despite a key role in regulating the Earth system, terrestrial ecology has historically been underrepresented in the Earth system models (ESMs) that are used to understand and project global environmental change. Ecology and Earth system modeling must be integrated for scientists to fully comprehend the role of ecological systems in driving and responding to global change. Ecological insights can improve ESM realism and reduce process uncertainty, while ESMs offer ecologists an opportunity to broadly test ecological theory and increase the impact of their work by scaling concepts through time and space. Despite this mutualism, meaningfully integrating the two remains a persistent challenge, in part because of logistical obstacles in translating processes into mathematical formulas and identifying ways to integrate new theories and code into large, complex model structures. To help overcome this interdisciplinary challenge, we present a framework consisting of a series of interconnected stages for integrating a new ecological process or insight into an ESM. First, we highlight the multiple ways that ecological observations and modeling iteratively strengthen one another, dispelling the illusion that the ecologist's role ends with initial provision of data. Second, we show that many valuable insights, products, and theoretical developments are produced through sustained interdisciplinary collaborations between empiricists and modelers, regardless of eventual inclusion of a process in an ESM. Finally, we provide concrete actions and resources to facilitate learning and collaboration at every stage of data-model integration. This framework will create synergies that will transform our understanding of ecology within the Earth system, ultimately improving our understanding of global environmental change, and broadening the impact of ecological research.

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

Plant functional traits can predict community assembly and ecosystem functioning and are thus widely used in global models of vegetation dynamics and land-climate feedbacks. Still, we lack a global understanding of how land and climate affect plant traits. A previous global analysis of six traits observed two main axes of variation: (1) size variation at the organ and plant level and (2) leaf economics balancing leaf persistence against plant growth potential. The orthogonality of these two axes suggests they are differently influenced by environmental drivers. We find that these axes persist in a global dataset of 17 traits across more than 20,000 species. We find a dominant joint effect of climate and soil on trait variation. Additional independent climate effects are also observed across most traits, whereas independent soil effects are almost exclusively observed for economics traits. Variation in size traits correlates well with a latitudinal gradient related to water or energy limitation. In contrast, variation in economics traits is better explained by interactions of climate with soil fertility. These findings have the potential to improve our understanding of biodiversity patterns and our predictions of climate change impacts on biogeochemical cycles.

Coordination of plant hydraulic and photosynthetic traits: confronting optimality theory with field measurements

Close coupling between water loss and carbon dioxide uptake requires coordination of plant hydraulics and photosynthesis. However, there is still limited information on the quantitative relationships between hydraulic and photosynthetic traits. We propose a basis for these relationships based on optimality theory, and test its predictions by analysis of measurements on 107 species from 11 sites, distributed along a nearly 3000-m elevation gradient. Hydraulic and leaf economic traits were less plastic, and more closely associated with phylogeny, than photosynthetic traits. The two sets of traits were linked by the sapwood to leaf area ratio (Huber value, v_H ). The observed coordination between v_H and sapwood hydraulic conductivity (K_S ) and photosynthetic capacity (V_cmax ) conformed to the proposed quantitative theory. Substantial hydraulic diversity was related to the trade-off between K_S and v_H . Leaf drought tolerance (inferred from turgor loss point, -Ψ_tlp ) increased with wood density, but the trade-off between hydraulic efficiency (K_S ) and -Ψ_tlp was weak. Plant trait effects on v_H were dominated by variation in K_S , while effects of environment were dominated by variation in temperature. This research unifies hydraulics, photosynthesis and the leaf economics spectrum in a common theoretical framework, and suggests a route towards the integration of photosynthesis and hydraulics in land-surface models.

Integrating terrestrial laser scanning with functional-structural plant models to investigate ecological and evolutionary processes of forest communities

BACKGROUND

Woody plants (trees and shrubs) play an important role in terrestrial ecosystems, but their size and longevity make them difficult subjects for traditional experiments. In the last 20 years functional-structural plant models (FSPMs) have evolved: they consider the interplay between plant modular structure, the immediate environment and internal functioning. However, computational constraints and data deficiency have long been limiting factors in a broader application of FSPMs, particularly at the scale of forest communities. Recently, terrestrial laser scanning (TLS), has emerged as an invaluable tool for capturing the 3-D structure of forest communities, thus opening up exciting opportunities to explore and predict forest dynamics with FSPMs.

SCOPE

The potential synergies between TLS-derived data and FSPMs have yet to be fully explored. Here, we summarize recent developments in FSPM and TLS research, with a specific focus on woody plants. We then evaluate the emerging opportunities for applying FSPMs in an ecological and evolutionary context, in light of TLS-derived data, with particular consideration of the challenges posed by scaling up from individual trees to whole forests. Finally, we propose guidelines for incorporating TLS data into the FSPM workflow to encourage overlap of practice amongst researchers.

CONCLUSIONS

We conclude that TLS is a feasible tool to help shift FSPMs from an individual-level modelling technique to a community-level one. The ability to scan multiple trees, of multiple species, in a short amount of time, is paramount to gathering the detailed structural information required for parameterizing FSPMs for forest communities. Conventional techniques, such as repeated manual forest surveys, have their limitations in explaining the driving mechanisms behind observed patterns in 3-D forest structure and dynamics. Therefore, other techniques are valuable to explore how forests might respond to environmental change. A robust synthesis between TLS and FSPMs provides the opportunity to virtually explore the spatial and temporal dynamics of forest communities.

Eco-evolutionary optimality as a means to improve vegetation and land-surface models

Global vegetation and land-surface models embody interdisciplinary scientific understanding of the behaviour of plants and ecosystems, and are indispensable to project the impacts of environmental change on vegetation and the interactions between vegetation and climate. However, systematic errors and persistently large differences among carbon and water cycle projections by different models highlight the limitations of current process formulations. In this review, focusing on core plant functions in the terrestrial carbon and water cycles, we show how unifying hypotheses derived from eco-evolutionary optimality (EEO) principles can provide novel, parameter-sparse representations of plant and vegetation processes. We present case studies that demonstrate how EEO generates parsimonious representations of core, leaf-level processes that are individually testable and supported by evidence. EEO approaches to photosynthesis and primary production, dark respiration and stomatal behaviour are ripe for implementation in global models. EEO approaches to other important traits, including the leaf economics spectrum and applications of EEO at the community level are active research areas. Independently tested modules emerging from EEO studies could profitably be integrated into modelling frameworks that account for the multiple time scales on which plants and plant communities adjust to environmental change.

Modelling of land nutrient cycles: recent progress and future development

While widespread imitation of the productivity of the land biosphere by nutrients, like nitrogen and phosphorus, was demonstrated many decades ago, representation of nutrient cycles in global land models has been relatively recent. Over the last three years, significant progress has been made in understanding some of the key processes and their representation in global land models. They include the significance of plant–microbial interaction in affecting nutrient cycles, inorganic soil phosphorus transformation, and nitrogen release from rocks. As a result, our understanding of the linkages among geology, biology, and climate controlling nutrient cycles is improving. However, progress in modelling nutrient cycles at a global scale is still confronted with large uncertainties in representing key processes owing to lack of data at the relevant scales for evaluating coupled carbon and nutrient cycles. Here we recommend two approaches to advance modelling of land nutrient cycles: the application of machine learning techniques to bridge the gap between global modelling and scattered site-level information and the use of optimality principles to identify key mechanisms driving spatial and temporal patterns of nutrients.

Coupled whole-tree optimality and xylem hydraulics explain dynamic biomass partitioning

Trees partition biomass in response to resource limitation and physiological activity. It is presumed that these strategies evolved to optimize some measure of fitness. If the optimization criterion can be specified, then allometry can be modeled from first principles without prescribed parameterization. We present the Tree Hydraulics and Optimal Resource Partitioning (THORP) model, which optimizes allometry by estimating allocation fractions to organs as proportional to their ratio of marginal gain to marginal cost, where gain is net canopy photosynthesis rate, and costs are senescence rates. Root total biomass and profile shape are predicted simultaneously by a unified optimization. Optimal partitioning is solved by a numerically efficient analytical solution. THORP's predictions agree with reported tree biomass partitioning in response to size, water limitations, elevated CO₂ and pruning. Roots were sensitive to soil moisture profiles and grew down to the groundwater table when present. Groundwater buffered against water stress regardless of meteorology, stabilizing allometry and root profiles as deep as c. 30 m. Much of plant allometry can be explained by hydraulic considerations. However, nutrient limitations cannot be fully ignored. Rooting mass and profiles were synchronized with hydrological conditions and groundwater even at considerable depths, illustrating that the below ground shapes whole-tree allometry.

Mechanisms driving plant functional trait variation in a tropical forest

Plant functional trait variation in tropical forests results from taxonomic differences in phylogeny and associated genetic differences, as well as, phenotypic plastic responses to the environment. Accounting for the underlying mechanisms driving plant functional trait variation is important for understanding the potential rate of change of ecosystems since trait acclimation via phenotypic plasticity is very fast compared to shifts in community composition and genetic adaptation. We here applied a statistical technique to decompose the relative roles of phenotypic plasticity, genetic adaptation, and phylogenetic constraints. We examined typically obtained plant functional traits, such as wood density, plant height, specific leaf area, leaf area, leaf thickness, leaf dry mass content, leaf nitrogen content, and leaf phosphorus content. We assumed that genetic differences in plant functional traits between species and genotypes increase with environmental heterogeneity and geographic distance, whereas trait variation due to plastic acclimation to the local environment is independent of spatial distance between sampling sites. Results suggest that most of the observed trait variation could not be explained by the measured environmental variables, thus indicating a limited potential to predict individual plant traits from commonly assessed parameters. However, we found a difference in the response of plant functional traits, such that leaf traits varied in response to canopy-light regime and nutrient availability, whereas wood traits were related to topoedaphic factors and water availability. Our analysis furthermore revealed differences in the functional response of coexisting neotropical tree species, which suggests that endemic species with conservative ecological strategies might be especially prone to competitive exclusion under projected climate change.

Tackling unresolved questions in forest ecology: The past and future role of simulation models

Understanding the processes that shape forest functioning, structure, and diversity remains challenging, although data on forest systems are being collected at a rapid pace and across scales. Forest models have a long history in bridging data with ecological knowledge and can simulate forest dynamics over spatio-temporal scales unreachable by most empirical investigations.We describe the development that different forest modelling communities have followed to underpin the leverage that simulation models offer for advancing our understanding of forest ecosystems.Using three widely applied but contrasting approaches - species distribution models, individual-based forest models, and dynamic global vegetation models - as examples, we show how scientific and technical advances have led models to transgress their initial objectives and limitations. We provide an overview of recent model applications on current important ecological topics and pinpoint ten key questions that could, and should, be tackled with forest models in the next decade.Synthesis. This overview shows that forest models, due to their complementarity and mutual enrichment, represent an invaluable toolkit to address a wide range of fundamental and applied ecological questions, hence fostering a deeper understanding of forest dynamics in the context of global change.

Growth, death, and resource competition in sessile organisms

Population-level scaling in ecological systems arises from individual growth and death with competitive constraints. We build on a minimal dynamical model of metabolic growth where the tension between individual growth and mortality determines population size distribution. We then separately include resource competition based on shared capture area. By varying rates of growth, death, and competitive attrition, we connect regular and random spatial patterns across sessile organisms from forests to ants, termites, and fairy circles. Then, we consider transient temporal dynamics in the context of asymmetric competition, such as canopy shading or large colony dominance, whose effects primarily weaken the smaller of two competitors. When such competition couples slow timescales of growth to fast competitive death, it generates population shocks and demographic oscillations similar to those observed in forest data. Our minimal quantitative theory unifies spatiotemporal patterns across sessile organisms through local competition mediated by the laws of metabolic growth, which in turn, are the result of long-term evolutionary dynamics.

Global climate and nutrient controls of photosynthetic capacity

There is huge uncertainty about how global exchanges of carbon between the atmosphere and land will respond to continuing environmental change. A better representation of photosynthetic capacity is required for Earth System models to simulate carbon assimilation reliably. Here we use a global leaf-trait dataset to test whether photosynthetic capacity is quantitatively predictable from climate, based on optimality principles; and to explore how this prediction is modified by soil properties, including indices of nitrogen and phosphorus availability, measured in situ. The maximum rate of carboxylation standardized to 25 °C (Vcmax25) was found to be proportional to growing-season irradiance, and to increase-as predicted-towards both colder and drier climates. Individual species' departures from predicted Vcmax25 covaried with area-based leaf nitrogen (Narea) but community-mean Vcmax25 was unrelated to Narea, which in turn was unrelated to the soil C:N ratio. In contrast, leaves with low area-based phosphorus (Parea) had low Vcmax25 (both between and within communities), and Parea increased with total soil P. These findings do not support the assumption, adopted in some ecosystem and Earth System models, that leaf-level photosynthetic capacity depends on soil N supply. They do, however, support a previously-noted relationship between photosynthesis and soil P supply.

Integrating vegetation suitability in sustainable revegetation for the Loess Plateau, China

Revegetation is accelerating globally due to its benefits for ecosystem restoration, desertification prevention, and climate change mitigation. The Loess Plateau has suffered serious erosion in the past decades, and revegetation projects, such as those under the 'Grain for Green' program, have been conducted for soil erosion prevention. The irrational distribution of artificial plantations had negative consequences, including vegetation degradation, soil drying, and decreases in streamflow. Determining the suitable plant species is critical in guiding the design of revegetation programs and may help delimit the suitable boundaries for artificial plantations. In this study, we used an eco-hydrological model to quantify the suitability of two typical revegetation species (Robinia pseudoacacia and Stipa bungeana) using a developed vegetation suitability equation, which estimates the water use/water stress trade-off. The results showed that R. pseudoacacia was more sensitive to water stress than S. bungeana. The water use of both species varied along the precipitation gradient, and S. bungeana generally had a higher water use than R. pseudoacacia. Suitable areas for R. pseudoacacia were mainly located in the northeastern part of the plateau. By overlaying the suitable boundaries for R. pseudoacacia on the current land cover, we found that the area of forests distributed in unsuitable regions reached 7.31% of the entire Loess Plateau. Converting forests beyond the suitable boundary to grasslands would increase the water yield (0.51%-12.23%) and slightly decrease the soil retention capacity (0.01%-0.08%), resulting in a 'win-win' situation for sustainable plant-soil ecosystems and soil-water conservations. Additionally, the suitable area of R. pseudoacacia is predicted to shrink under projected future drying trends. In conclusion, vegetation suitability in the future planning and design of revegetation projects should be considered to effectively tackle the impacts of environmental degradation and climate change in the Loess Plateau.

The Net Effect of Functional Traits on Fitness

Generalizing the effect of traits on performance across species may be achievable if traits explain variation in population fitness. However, testing relationships between traits and vital rates to infer effects on fitness can be misleading. Demographic trade-offs can generate variation in vital rates that yield equal population growth rates, thereby obscuring the net effect of traits on fitness. To address this problem, we describe a diversity of approaches to quantify intrinsic growth rates of plant populations, including experiments beyond range boundaries, density-dependent population models built from long-term demographic data, theoretical models, and methods that leverage widely available monitoring data. Linking plant traits directly to intrinsic growth rates is a fundamental step toward rigorous predictions of population dynamics and community assembly.

Thermodynamics in Ecology-An Introductory Review

How to predict the evolution of ecosystems is one of the numerous questions asked of ecologists by managers and politicians. To answer this we will need to give a scientific definition to concepts like sustainability, integrity, resilience and ecosystem health. This is not an easy task, as modern ecosystem theory exemplifies. Ecosystems show a high degree of complexity, based upon a high number of compartments, interactions and regulations. The last two decades have offered proposals for interpretation of ecosystems within a framework of thermodynamics. The entrance point of such an understanding of ecosystems was delivered more than 50 years ago through Schrödinger’s and Prigogine’s interpretations of living systems as “negentropy feeders” and “dissipative structures”, respectively. Combining these views from the far from equilibrium thermodynamics to traditional classical thermodynamics, and ecology is obviously not going to happen without problems. There seems little reason to doubt that far from equilibrium systems, such as organisms or ecosystems, also have to obey fundamental physical principles such as mass conservation, first and second law of thermodynamics. Both have been applied in ecology since the 1950s and lately the concepts of exergy and entropy have been introduced. Exergy has recently been proposed, from several directions, as a useful indicator of the state, structure and function of the ecosystem. The proposals take two main directions, one concerned with the exergy stored in the ecosystem, the other with the exergy degraded and entropy formation. The implementation of exergy in ecology has often been explained as a translation of the Darwinian principle of “survival of the fittest” into thermodynamics. The fittest ecosystem, being the one able to use and store fluxes of energy and materials in the most efficient manner. The major problem in the transfer to ecology is that thermodynamic properties can only be calculated and not measured. Most of the supportive evidence comes from aquatic ecosystems. Results show that natural and culturally induced changes in the ecosystems, are accompanied by a variations in exergy. In brief, ecological succession is followed by an increase of exergy. This paper aims to describe the state-of-the-art in implementation of thermodynamics into ecology. This includes a brief outline of the history and the derivation of the thermodynamic functions used today. Examples of applications and results achieved up to now are given, and the importance to management laid out. Some suggestions for essential future research agendas of issues that needs resolution are given.