Warming induces divergent stomatal dynamics in co-occurring boreal trees.

Climate warming will alter photosynthesis and respiration not only via direct temperature effects on leaf biochemistry but also by increasing atmospheric dryness, thereby reducing stomatal conductance and suppressing photosynthesis. Our knowledge on how climate warming affects these processes is mainly derived from seedlings grown under highly controlled conditions. However, little is known regarding temperature responses of trees growing under field settings. We exposed mature tamarack and black spruce trees growing in a peatland ecosystem to whole-ecosystem warming of up to +9°C above ambient air temperatures in an ongoing long-term experiment (SPRUCE: Spruce and Peatland Responses Under Changing Environments). Here, we report the responses of leaf gas exchange after the first two years of warming. We show that the two species exhibit divergent stomatal responses to warming and vapor pressure deficit. Warming of up to 9°C increased leaf N in both spruce and tamarack. However, higher leaf N in the warmer plots translate into higher photosynthesis in tamarack but not in spruce, with photosynthesis being more constrained by stomatal limitations in spruce than in tamarack under warm conditions. Surprisingly, dark respiration did not acclimate to warming in spruce, and thermal acclimation of respiration was only seen in tamarack once changes in leaf N were considered. Our results highlight how warming can lead to differing stomatal responses to warming in co-occurring species, with consequent effects on both vegetation carbon and water dynamics.

Divergent species-specific impacts of whole ecosystem warming and elevated CO2 on vegetation water relations in an ombrotrophic peatland.

Boreal peatland forests have relatively low species diversity and thus impacts of climate change on one or more dominant species could shift ecosystem function. Despite abundant soil water availability, shallowly rooted vascular plants within peatlands may not be able to meet foliar demand for water under drought or heat events that increase vapor pressure deficits while reducing near surface water availability, although concurrent increases in atmospheric CO2 could buffer resultant hydraulic stress. We assessed plant water relations of co-occurring shrub (primarily Rhododendron groenlandicum and Chamaedaphne calyculata) and tree (Picea mariana and Larix laricina) species prior to, and in response to whole ecosystem warming (0 to +9°C) and elevated CO2 using 12.8-m diameter open-top enclosures installed within an ombrotrophic bog. Water relations (water potential [Ψ], turgor loss point, foliar and root hydraulic conductivity) were assessed prior to treatment initiation, then Ψ and peak sap flow (trees only) assessed after 1 or 2 years of treatments. Under the higher temperature treatments, L. laricina Ψ exceeded its turgor loss point, increased its peak sap flow, and was not able to recover Ψ overnight. In contrast, P. mariana operated below its turgor loss point and maintained constant Ψ and sap flow across warming treatments. Similarly, C. calyculata Ψ stress increased with temperature while R. groenlandicum Ψ remained at pretreatment levels. The more anisohydric behavior of L. laricina and C. calyculata may provide greater net C uptake with warming, while the more conservative P. mariana and R. groenlandicum maintained greater hydraulic safety. These latter species also responded to elevated CO2 by reduced Ψ stress, which may also help limit hydraulic failure during periods of extreme drought or heat in the future. Along with Sphagnum moss, the species-specific responses of peatland vascular communities to drier or hotter conditions will shape boreal peatland composition and function in the future.

Correction to: Diel rewiring and positive selection of ancient plant proteins enabled evolution of CAM photosynthesis in Agave.

Following publication of the original article.

Terrestrial biosphere models may overestimate Arctic CO2 assimilation if they do not account for decreased quantum yield and convexity at low temperature.

How terrestrial biosphere models (TBMs) represent leaf photosynthesis and its sensitivity to temperature are two critical components of understanding and predicting the response of the Arctic carbon cycle to global change. We measured the effect of temperature on the response of photosynthesis to irradiance in six Arctic plant species and determined the quantum yield of CO2 fixation ( ϕCO2 ) and the convexity factor (θ). We also determined leaf absorptance (α) from measured reflectance to calculate ϕCO2 on an absorbed light basis ( ϕCO2.a ) and enabled comparison with nine TBMs. The mean ϕCO2.a was 0.045 mol CO2  mol-1 absorbed quanta at 25°C and closely agreed with the mean TBM parameterisation (0.044), but as temperature decreased measured ϕCO2.a diverged from TBMs. At 5°C measured ϕCO2.a was markedly reduced (0.025) and 60% lower than TBM estimates. The θ also showed a significant reduction between 25°C and 5°C. At 5°C θ was 38% lower than the common model parameterisation of 0.7. These data show that TBMs are not accounting for observed reductions in ϕCO2.a and θ that can occur at low temperature. Ignoring these reductions in ϕCO2.a and θ could lead to a marked (45%) overestimation of CO2 assimilation at subsaturating irradiance and low temperature.

Diel rewiring and positive selection of ancient plant proteins enabled evolution of CAM photosynthesis in Agave.

BACKGROUND: Crassulacean acid metabolism (CAM) enhances plant water-use efficiency through an inverse day/night pattern of stomatal closure/opening that facilitates nocturnal CO2 uptake. CAM has evolved independently in over 35 plant lineages, accounting for ~ 6% of all higher plants. Agave species are highly heat- and drought-tolerant, and have been domesticated as model CAM crops for beverage, fiber, and biofuel production in semi-arid and arid regions. However, the genomic basis of evolutionary innovation of CAM in genus Agave is largely unknown. RESULTS: Using an approach that integrated genomics, gene co-expression networks, comparative genomics and protein structure analyses, we investigated the molecular evolution of CAM as exemplified in Agave. Comparative genomics analyses among C3, C4 and CAM species revealed that core metabolic components required for CAM have ancient genomic origins traceable to non-vascular plants while regulatory proteins required for diel re-programming of metabolism have a more recent origin shared among C3, C4 and CAM species. We showed that accelerated evolution of key functional domains in proteins responsible for primary metabolism and signaling, together with a diel re-programming of the transcription of genes involved in carbon fixation, carbohydrate processing, redox homeostasis, and circadian control is required for the evolution of CAM in Agave. Furthermore, we highlighted the potential candidates contributing to the adaptation of CAM functional modules. CONCLUSIONS: This work provides evidence of adaptive evolution of CAM related pathways. We showed that the core metabolic components required for CAM are shared by non-vascular plants, but regulatory proteins involved in re-reprogramming of carbon fixation and metabolite transportation appeared more recently. We propose that the accelerated evolution of key proteins together with a diel re-programming of gene expression were required for CAM evolution from C3 ancestors in Agave.

Molecular Insights into Arctic Soil Organic Matter Degradation under Warming.

Molecular composition of the Arctic soil organic carbon (SOC) and its susceptibility to microbial degradation are uncertain due to heterogeneity and unknown SOC compositions. Using ultrahigh-resolution mass spectrometry, we determined the susceptibility and compositional changes of extractable dissolved organic matter (EDOM) in an anoxic warming incubation experiment (up to 122 days) with a tundra soil from Alaska (United States). EDOM was extracted with 10 mM NH4HCO3 from both the organic- and mineral-layer soils during incubation at both -2 and 8 °C. Based on their O:C and H:C ratios, EDOM molecular formulas were qualitatively grouped into nine biochemical classes of compounds, among which lignin-like compounds dominated both the organic and the mineral soils and were the most stable, whereas amino sugars, peptides, and carbohydrate-like compounds were the most biologically labile. These results corresponded with shifts in EDOM elemental composition in which the ratios of O:C and N:C decreased, while the average C content in EDOM, molecular mass, and aromaticity increased after 122 days of incubation. This research demonstrates that certain EDOM components, such as amino sugars, peptides, and carbohydrate-like compounds, are disproportionately more susceptible to microbial degradation than others in the soil, and these results should be considered in SOC degradation models to improve predictions of Arctic climate feedbacks.

Terrestrial biosphere models underestimate photosynthetic capacity and CO2 assimilation in the Arctic.

Terrestrial biosphere models (TBMs) are highly sensitive to model representation of photosynthesis, in particular the parameters maximum carboxylation rate and maximum electron transport rate at 25°C (Vc,max.25 and Jmax.25 , respectively). Many TBMs do not include representation of Arctic plants, and those that do rely on understanding and parameterization from temperate species. We measured photosynthetic CO2 response curves and leaf nitrogen (N) content in species representing the dominant vascular plant functional types found on the coastal tundra near Barrow, Alaska. The activation energies associated with the temperature response functions of Vc,max and Jmax were 17% lower than commonly used values. When scaled to 25°C, Vc,max.25 and Jmax.25 were two- to five-fold higher than the values used to parameterize current TBMs. This high photosynthetic capacity was attributable to a high leaf N content and the high fraction of N invested in Rubisco. Leaf-level modeling demonstrated that current parameterization of TBMs resulted in a two-fold underestimation of the capacity for leaf-level CO2 assimilation in Arctic vegetation. This study highlights the poor representation of Arctic photosynthesis in TBMs, and provides the critical data necessary to improve our ability to project the response of the Arctic to global environmental change.

Root structural and functional dynamics in terrestrial biosphere models--evaluation and recommendations.

There is wide breadth of root function within ecosystems that should be considered when modeling the terrestrial biosphere. Root structure and function are closely associated with control of plant water and nutrient uptake from the soil, plant carbon (C) assimilation, partitioning and release to the soils, and control of biogeochemical cycles through interactions within the rhizosphere. Root function is extremely dynamic and dependent on internal plant signals, root traits and morphology, and the physical, chemical and biotic soil environment. While plant roots have significant structural and functional plasticity to changing environmental conditions, their dynamics are noticeably absent from the land component of process-based Earth system models used to simulate global biogeochemical cycling. Their dynamic representation in large-scale models should improve model veracity. Here, we describe current root inclusion in models across scales, ranging from mechanistic processes of single roots to parameterized root processes operating at the landscape scale. With this foundation we discuss how existing and future root functional knowledge, new data compilation efforts, and novel modeling platforms can be leveraged to enhance root functionality in large-scale terrestrial biosphere models by improving parameterization within models, and introducing new components such as dynamic root distribution and root functional traits linked to resource extraction.

The unseen iceberg: plant roots in arctic tundra.

Plant roots play a critical role in ecosystem function in arctic tundra, but root dynamics in these ecosystems are poorly understood. To address this knowledge gap, we synthesized available literature on tundra roots, including their distribution, dynamics and contribution to ecosystem carbon and nutrient fluxes, and highlighted key aspects of their representation in terrestrial biosphere models. Across all tundra ecosystems, belowground plant biomass exceeded aboveground biomass, with the exception of polar desert tundra. Roots were shallowly distributed in the thin layer of soil that thaws annually, and were often found in surface organic soil horizons. Root traits - including distribution, chemistry, anatomy and resource partitioning - play an important role in controlling plant species competition, and therefore ecosystem carbon and nutrient fluxes, under changing climatic conditions, but have only been quantified for a small fraction of tundra plants. Further, the annual production and mortality of fine roots are key components of ecosystem processes in tundra, but extant data are sparse. Tundra root traits and dynamics should be the focus of future research efforts. Better representation of the dynamics and characteristics of tundra roots will improve the utility of models for the evaluation of the responses of tundra ecosystems to changing environmental conditions.

A roadmap for research on crassulacean acid metabolism (CAM) to enhance sustainable food and bioenergy production in a hotter, drier world.

Crassulacean acid metabolism (CAM) is a specialized mode of photosynthesis that features nocturnal CO2 uptake, facilitates increased water-use efficiency (WUE), and enables CAM plants to inhabit water-limited environments such as semi-arid deserts or seasonally dry forests. Human population growth and global climate change now present challenges for agricultural production systems to increase food, feed, forage, fiber, and fuel production. One approach to meet these challenges is to increase reliance on CAM crops, such as Agave and Opuntia, for biomass production on semi-arid, abandoned, marginal, or degraded agricultural lands. Major research efforts are now underway to assess the productivity of CAM crop species and to harness the WUE of CAM by engineering this pathway into existing food, feed, and bioenergy crops. An improved understanding of CAM has potential for high returns on research investment. To exploit the potential of CAM crops and CAM bioengineering, it will be necessary to elucidate the evolution, genomic features, and regulatory mechanisms of CAM. Field trials and predictive models will be required to assess the productivity of CAM crops, while new synthetic biology approaches need to be developed for CAM engineering. Infrastructure will be needed for CAM model systems, field trials, mutant collections, and data management.

Genomics in a changing arctic: critical questions await the molecular ecologist.

Molecular ecology is poised to tackle a host of interesting questions in the coming years. The Arctic provides a unique and rapidly changing environment with a suite of emerging research needs that can be addressed through genetics and genomics. Here we highlight recent research on boreal and tundra ecosystems and put forth a series of questions related to plant and microbial responses to climate change that can benefit from technologies and analytical approaches contained within the molecular ecologist's toolbox. These questions include understanding (i) the mechanisms of plant acquisition and uptake of N in cold soils, (ii) how these processes are mediated by root traits, (iii) the role played by the plant microbiome in cycling C and nutrients within high-latitude ecosystems and (iv) plant adaptation to extreme Arctic climates. We highlight how contributions can be made in these areas through studies that target model and nonmodel organisms and emphasize that the sequencing of the Populus and Salix genomes provides a valuable resource for scientific discoveries related to the plant microbiome and plant adaptation in the Arctic. Moreover, there exists an exciting role to play in model development, including incorporating genetic and evolutionary knowledge into ecosystem and Earth System Models. In this regard, the molecular ecologist provides a valuable perspective on plant genetics as a driver for community biodiversity, and how ecological and evolutionary forces govern community dynamics in a rapidly changing climate.

Climate-resilient agroforestry: physiological responses to climate change and engineering of crassulacean acid metabolism (CAM) as a mitigation strategy.

Global climate change threatens the sustainability of agriculture and agroforestry worldwide through increased heat, drought, surface evaporation and associated soil drying. Exposure of crops and forests to warmer and drier environments will increase leaf:air water vapour-pressure deficits (VPD), and will result in increased drought susceptibility and reduced productivity, not only in arid regions but also in tropical regions with seasonal dry periods. Fast-growing, short-rotation forestry (SRF) bioenergy crops such as poplar (Populus spp.) and willow (Salix spp.) are particularly susceptible to hydraulic failure following drought stress due to their isohydric nature and relatively high stomatal conductance. One approach to sustaining plant productivity is to improve water-use efficiency (WUE) by engineering crassulacean acid metabolism (CAM) into C3 crops. CAM improves WUE by shifting stomatal opening and primary CO2 uptake and fixation to the night-time when leaf:air VPD is low. CAM members of the tree genus Clusia exemplify the compatibility of CAM performance within tree species and highlight CAM as a mechanism to conserve water and maintain carbon uptake during drought conditions. The introduction of bioengineered CAM into SRF bioenergy trees is a potentially viable path to sustaining agroforestry production systems in the face of a globally changing climate.

Sphagnum physiology in the context of changing climate: emergent influences of genomics, modelling and host-microbiome interactions on understanding ecosystem function.

Peatlands harbour more than one-third of terrestrial carbon leading to the argument that the bryophytes, as major components of peatland ecosystems, store more organic carbon in soils than any other collective plant taxa. Plants of the genus Sphagnum are important components of peatland ecosystems and are potentially vulnerable to changing climatic conditions. However, the response of Sphagnum to rising temperatures, elevated CO2 and shifts in local hydrology have yet to be fully characterized. In this review, we examine Sphagnum biology and ecology and explore the role of this group of keystone species and its associated microbiome in carbon and nitrogen cycling using literature review and model simulations. Several issues are highlighted including the consequences of a variable environment on plant-microbiome interactions, uncertainty associated with CO2 diffusion resistances and the relationship between fixed N and that partitioned to the photosynthetic apparatus. We note that the Sphagnum fallax genome is currently being sequenced and outline potential applications of population-level genomics and corresponding plant photosynthesis and microbial metabolic modelling techniques. We highlight Sphagnum as a model organism to explore ecosystem response to a changing climate and to define the role that Sphagnum can play at the intersection of physiology, genetics and functional genomics.

Stoichiometry and temperature sensitivity of methanogenesis and CO2 production from saturated polygonal tundra in Barrow, Alaska.

Arctic permafrost ecosystems store ~50% of global belowground carbon (C) that is vulnerable to increased microbial degradation with warmer active layer temperatures and thawing of the near surface permafrost. We used anoxic laboratory incubations to estimate anaerobic CO2 production and methanogenesis in active layer (organic and mineral soil horizons) and permafrost samples from center, ridge and trough positions of water-saturated low-centered polygon in Barrow Environmental Observatory, Barrow AK, USA. Methane (CH4 ) and CO2 production rates and concentrations were determined at -2, +4, or +8 °C for 60 day incubation period. Temporal dynamics of CO2 production and methanogenesis at -2 °C showed evidence of fundamentally different mechanisms of substrate limitation and inhibited microbial growth at soil water freezing points compared to warmer temperatures. Nonlinear regression better modeled the initial rates and estimates of Q10 values for CO2 that showed higher sensitivity in the organic-rich soils of polygon center and trough than the relatively drier ridge soils. Methanogenesis generally exhibited a lag phase in the mineral soils that was significantly longer at -2 °C in all horizons. Such discontinuity in CH4 production between -2 °C and the elevated temperatures (+4 and +8 °C) indicated the insufficient representation of methanogenesis on the basis of Q10 values estimated from both linear and nonlinear models. Production rates for both CH4 and CO2 were substantially higher in organic horizons (20% to 40% wt. C) at all temperatures relative to mineral horizons (<20% wt. C). Permafrost horizon (~12% wt. C) produced ~5-fold less CO2 than the active layer and negligible CH4 . High concentrations of initial exchangeable Fe(II) and increasing accumulation rates signified the role of iron as terminal electron acceptors for anaerobic C degradation in the mineral horizons.

Needle age and season influence photosynthetic temperature response and total annual carbon uptake in mature Picea mariana trees.

BACKGROUND AND AIMS: The carbon (C) balance of boreal terrestrial ecosystems is sensitive to increasing temperature, but the direction and thresholds of responses are uncertain. Annual C uptake in Picea and other evergreen boreal conifers is dependent on seasonal- and cohort-specific photosynthetic and respiratory temperature response functions, so this study examined the physiological significance of maintaining multiple foliar cohorts for Picea mariana trees within an ombrotrophic bog ecosystem in Minnesota, USA. METHODS: Measurements were taken on multiple cohorts of needles for photosynthetic capacity, foliar respiration (Rd) and leaf biochemistry and morphology of mature trees from April to October over 4 years. The results were applied to a simple model of canopy photosynthesis in order to simulate annual C uptake by cohort age under ambient and elevated temperature scenarios. KEY RESULTS: Temperature responses of key photosynthetic parameters [i.e. light-saturated rate of CO2 assimilation (Asat), rate of Rubisco carboxylation (Vcmax) and electron transport rate (Jmax)] were dependent on season and generally less responsive in the developing current-year (Y0) needles compared with 1-year-old (Y1) or 2-year-old (Y2) foliage. Temperature optimums ranged from 18·7 to 23·7, 31·3 to 38·3 and 28·7 to 36·7 °C for Asat, Vcmax and Jmax, respectively. Foliar cohorts differed in their morphology and photosynthetic capacity, which resulted in 64 % of modelled annual stand C uptake from Y1&2 cohorts (LAI 0·67 m(2 )m(-2)) and just 36 % from Y0 cohorts (LAI 0·52 m(2 )m(-2)). Under warmer climate change scenarios, the contribution of Y0 cohorts was even less; e.g. 31 % of annual C uptake for a modelled 9 °C rise in mean summer temperatures. Results suggest that net annual C uptake by P. mariana could increase under elevated temperature, and become more dependent on older foliar cohorts. CONCLUSIONS: Collectively, this study illustrates the physiological and ecological significance of different foliar cohorts, and indicates the need for seasonal- and cohort-specific model parameterization when estimating C uptake capacity of boreal forest ecosystems under ambient or future temperature scenarios.

Global-scale environmental control of plant photosynthetic capacity.

Photosynthetic capacity, determined by light harvesting and carboxylation reactions, is a key plant trait that determines the rate of photosynthesis; however, in Earth System Models (ESMs) at a reference temperature, it is either a fixed value for a given plant functional type or derived from a linear function of leaf nitrogen content. In this study, we conducted a comprehensive analysis that considered correlations of environmental factors with photosynthetic capacity as determined by maximum carboxylation (V(cm)) rate scaled to 25 degrees C (i.e., V(c),25; µmol CO2 x m(-2)x s(-1)) and maximum electron transport rate (J(max)) scaled to 25 degrees C (i.e., J25; µmol electron x m(-2) x s(-1)) at the global scale. Our results showed that the percentage of variation in observed V(c),25 and J25 explained jointly by the environmental factors (i.e., day length, radiation, temperature, and humidity) were 2-2.5 times and 6-9 times of that explained by area-based leaf nitrogen content, respectively. Environmental factors influenced photosynthetic capacity mainly through photosynthetic nitrogen use efficiency, rather than through leaf nitrogen content. The combination of leaf nitrogen content and environmental factors was able to explain -56% and -66% of the variation in V(c),25 and J25 at the global scale, respectively. Our analyses suggest that model projections of plant photosynthetic capacity and hence land-atmosphere exchange under changing climatic conditions could be substantially improved if environmental factors are incorporated into algorithms used to parameterize photosynthetic capacity in ESMs.

Plant functional types in Earth system models: past experiences and future directions for application of dynamic vegetation models in high-latitude ecosystems.

BACKGROUND: Earth system models describe the physical, chemical and biological processes that govern our global climate. While it is difficult to single out one component as being more important than another in these sophisticated models, terrestrial vegetation is a critical player in the biogeochemical and biophysical dynamics of the Earth system. There is much debate, however, as to how plant diversity and function should be represented in these models. SCOPE: Plant functional types (PFTs) have been adopted by modellers to represent broad groupings of plant species that share similar characteristics (e.g. growth form) and roles (e.g. photosynthetic pathway) in ecosystem function. In this review, the PFT concept is traced from its origin in the early 1800s to its current use in regional and global dynamic vegetation models (DVMs). Special attention is given to the representation and parameterization of PFTs and to validation and benchmarking of predicted patterns of vegetation distribution in high-latitude ecosystems. These ecosystems are sensitive to changing climate and thus provide a useful test case for model-based simulations of past, current and future distribution of vegetation. CONCLUSIONS: Models that incorporate the PFT concept predict many of the emerging patterns of vegetation change in tundra and boreal forests, given known processes of tree mortality, treeline migration and shrub expansion. However, representation of above- and especially below-ground traits for specific PFTs continues to be problematic. Potential solutions include developing trait databases and replacing fixed parameters for PFTs with formulations based on trait co-variance and empirical trait-environment relationships. Surprisingly, despite being important to land-atmosphere interactions of carbon, water and energy, PFTs such as moss and lichen are largely absent from DVMs. Close collaboration among those involved in modelling with the disciplines of taxonomy, biogeography, ecology and remote sensing will be required if we are to overcome these and other shortcomings.

Extrapolating active layer thickness measurements across Arctic polygonal terrain using LiDAR and NDVI data sets.

Landscape attributes that vary with microtopography, such as active layer thickness (ALT), are labor intensive and difficult to document effectively through in situ methods at kilometer spatial extents, thus rendering remotely sensed methods desirable. Spatially explicit estimates of ALT can provide critically needed data for parameterization, initialization, and evaluation of Arctic terrestrial models. In this work, we demonstrate a new approach using high-resolution remotely sensed data for estimating centimeter-scale ALT in a 5 km2 area of ice-wedge polygon terrain in Barrow, Alaska. We use a simple regression-based, machine learning data-fusion algorithm that uses topographic and spectral metrics derived from multisensor data (LiDAR and WorldView-2) to estimate ALT (2 m spatial resolution) across the study area. Comparison of the ALT estimates with ground-based measurements, indicates the accuracy (r2 = 0.76, RMSE ±4.4 cm) of the approach. While it is generally accepted that broad climatic variability associated with increasing air temperature will govern the regional averages of ALT, consistent with prior studies, our findings using high-resolution LiDAR and WorldView-2 data, show that smaller-scale variability in ALT is controlled by local eco-hydro-geomorphic factors. This work demonstrates a path forward for mapping ALT at high spatial resolution and across sufficiently large regions for improved understanding and predictions of coupled dynamics among permafrost, hydrology, and land-surface processes from readily available remote sensing data.

Extending the Arabidopsis flowering paradigm to a mass flowering phenomenon in the tropics.

Flowering time is a critical life history trait, one that is shaped by evolution to maximize fecundity, reproductive success and fitness (Amasino 2010). This is especially true of annual plants where the cycle of floral initiation, pollination and seed production occur at regular intervals to ensure the survival of the species. In long-lived perennials, however, flowering can be an intermittent phenomenon and thus a challenge to understand. In this issue of Molecular Ecology, Kobayashi et al. (2013) tackle this particular challenge by applying modern-day molecular techniques to the 'spectacular and mysterious' mass flowering that takes places in mixed dipterocarp forests of South-East Asia. Here, amidst an almost unimaginable diversity of forbs, shrubs and trees, these authors used next-generation sequencing technology to characterize what they refer to as the 'ecological transcriptome' in an attempt to glimpse into the functional genomic reprogramming of Shorea beccariana at pre- and postflowering developmental transitions. They encountered many of the challenges that are often underappreciated yet typical for tropical ecological research including sample collection within a ~40-m high tree canopy, unpredictable flowering intervals and determining the most appropriate preflowering state for sampling. Despite these challenges, the authors were able to integrate gene ontology relationships with gene-clustering algorithms and environmental data to support the hypothesis that drought is a key trigger for flowering in S. beccariana. The cloning and transgenic expression of selected S. beccariana genes to corroborate presumed protein function is a key feature of their work and seldom applied within an ecological framework. As illustrated by Kobayashi et al. (2013), the inclusion of molecular biology, genomics and bioinformatics has the potential to shed light on long-standing questions of ecological concern.