Measured and modelled leaf and stand-scale productivity across a soil moisture gradient and a severe drought

Improving global gross primary productivity estimation by fusing multi-source data products

A reliable estimate of the gross primary productivity (GPP) of terrestrial vegetation is essential for both making decisions to address global climate change and understanding the global carbon balance. The lack of consistency in global terrestrial GPP estimates across various products leads to great uncertainty. In this study, we improve the quantification of global gross primary productivity by integrating multiple source GPP products without using any prior knowledge through the Bayesian-based Three-Cornered Hat (BTCH) method to generate a new weighted GPP data set. The fusion results demonstrate the superiority of weighted GPP, which greatly reduces the random error of individual datasets and fully takes advantage of the characteristics of multi-source data products. The weighted dataset can largely reproduce the interannual variation of regional GPP. Overall, the merging scheme based on the BTCH method can effectively generate a new GPP dataset that integrates information from multiple products and provides new ideas for GPP estimation on a global scale.

Does economic optimisation explain LAI and leaf trait distributions across an Amazon soil moisture gradient?

Leaf area index (LAI) underpins terrestrial ecosystem functioning, yet our ability to predict LAI remains limited. Across Amazon forests, mean LAI, LAI seasonal dynamics and leaf traits vary with soil moisture stress. We hypothesise that LAI variation can be predicted via an optimality-based approach, using net canopy C export (NCE, photosynthesis minus the C cost of leaf growth and maintenance) as a fitness proxy. We applied a process-based terrestrial ecosystem model to seven plots across a moisture stress gradient with detailed in situ measurements, to determine nominal plant C budgets. For each plot, we then compared observations and simulations of the nominal (i.e. observed) C budget to simulations of alternative, experimental budgets. Experimental budgets were generated by forcing the model with synthetic LAI timeseries (across a range of mean LAI and LAI seasonality) and different leaf trait combinations (leaf mass per unit area, lifespan, photosynthetic capacity and respiration rate) operating along the leaf economic spectrum. Observed mean LAI and LAI seasonality across the soil moisture stress gradient maximised NCE, and were therefore consistent with optimality-based predictions. Yet, the predictive power of an optimality-based approach was limited due to the asymptotic response of simulated NCE to mean LAI and LAI seasonality. Leaf traits fundamentally shaped the C budget, determining simulated optimal LAI and total NCE. Long-lived leaves with lower maximum photosynthetic capacity maximised simulated NCE under aseasonal high mean LAI, with the reverse found for short-lived leaves and higher maximum photosynthetic capacity. The simulated leaf trait LAI trade-offs were consistent with observed distributions. We suggest that a range of LAI strategies could be equally economically viable at local level, though we note several ecological limitations to this interpretation (e.g. between-plant competition). In addition, we show how leaf trait trade-offs enable divergence in canopy strategies. Our results also allow an assessment of the usefulness of optimality-based approaches in simulating primary tropical forest functioning, evaluated against in situ data.

Mean annual precipitation predicts primary production resistance and resilience to extreme drought

Extreme drought is increasing in frequency and intensity in many regions globally, with uncertain consequences for the resistance and resilience of ecosystem functions, including primary production. Primary production resistance, the capacity to withstand change during extreme drought, and resilience, the degree to which production recovers, vary among and within ecosystem types, obscuring generalized patterns of ecological stability. Theory and many observations suggest forest production is more resistant but less resilient than grassland production to extreme drought; however, studies of production sensitivity to precipitation variability indicate that the processes controlling resistance and resilience may be influenced more by mean annual precipitation (MAP) than ecosystem type. Here, we conducted a global meta-analysis to investigate primary production resistance and resilience to extreme drought in 64 forests and grasslands across a broad MAP gradient. We found resistance to extreme drought was predicted by MAP; however, grasslands (positive) and forests (negative) exhibited opposing resilience relationships with MAP. Our findings indicate that common plant physiological mechanisms may determine grassland and forest resistance to extreme drought, whereas differences among plant residents in turnover time, plant architecture, and drought adaptive strategies likely underlie divergent resilience patterns. The low resistance and resilience of dry grasslands suggests that these ecosystems are the most vulnerable to extreme drought - a vulnerability that is expected to compound as extreme drought frequency increases in the future.

Water- and Nitrogen-Use Efficiencies of Hemp (Cannabis sativa L.) Based on Whole-Canopy Measurements and Modeling

Interest in hemp (Cannabis sativa L.) as a crop for the biobased economy is growing worldwide because hemp produces a high and valuable biomass while requiring low inputs. To understand the physiological basis of hemp's resource-use efficiency, canopy gas exchange was assessed using a chamber technique on canopies exposed to a range of nitrogen (N) and water levels. Since canopy transpiration and carbon assimilation were very sensitive to variations in microclimate among canopy chambers, observations were adjusted for microclimatic differences using a physiological canopy model, with leaf-level parameters estimated for hemp from our previous study. Canopy photosynthetic water-use efficiency (PWUEc), defined as the ratio of gross canopy photosynthesis to canopy transpiration, ranged from 4.0 mmol CO2 (mol H2O)-1 to 7.5 mmol CO2 (mol H2O)-1. Canopy photosynthetic nitrogen-use efficiency (PNUEc), the ratio of the gross canopy photosynthesis to canopy leaf-N content, ranged from 0.3 mol CO2 d-1 (g N)-1 to 0.7 mol CO2 d-1 (g N)-1. The effect of N-input levels on PWUEc and PNUEc was largely determined by the N effect on canopy size or leaf area index (LAI), whereas the effect of water-input levels differed between short- and long-term stresses. The effect of short-term water stress was reflected by stomatal regulation. The long-term stress increased leaf senescence, decreased LAI but retained total canopy N content; however, the increased average leaf-N could not compensate for the lost LAI, leading to a decreased PNUEc. Although hemp is known as a resource-use efficient crop, its final biomass yield and nitrogen use efficiency may be restricted by water limitation during growth. Our results also suggest that crop models should take stress-induced senescence into account in addition to stomatal effects if crops experience a prolonged water stress during growth.

How resilient are African woodlands to disturbance from shifting cultivation?

Large parts of sub-Saharan Africa are experiencing rapid changes in land use and land cover, driven largely by the expansion of small-scale shifting cultivation. This practice creates complex mosaic landscapes with active agricultural fields and patches of mature woodland, interspersed with remnant patches in various stages of regrowth. Our objective here was to examine the rate and extent to which carbon stocks in trees and soils recover after cultivation, and detail how this disturbance and regrowth affect patterns in tree species composition and diversity over 40 years of succession in a miombo woodland landscape in southeast Tanzania. We sampled 67 areas, including plots previously cleared for cultivation, active fields, and mature woodlands for reference purposes. Sites were further stratified by soil texture to test for associated effects. Tree carbon stocks accumulated at an average rate of 0.83 ± 0.10 Mg C x ha(-1) x yr(-1), with soil texture having no clear impact on accumulation rates. Bulk soil carbon stocks on both soil types appeared unaffected by both the initial land clearance and the subsequent regrowth, which resulted in no significant changes over time. Tree species diversity in regrowing plots developed rapidly and within -10 years was equivalent to that of mature woodland. Many of the species found in mature woodlands reappeared relatively quickly after abandonment, although species composition is expected to take considerably longer to recover, with at least 60-80 years required for the compositional similarity between regrowing and mature woodlands to reach levels similar to that among nearby mature woodlands. Through impacts on β-diversity, disturbance was also found to increase the total number of tree species present in the landscape, with many of the recorded species only found in regrowing woodlands. Our results are of relevance to carbon sequestration projects by helping to inform the potential future carbon and biodiversity benefits of restoring disturbed habitats (REDD+). At a time where the use of shifting cultivation is threatened by shifts to larger-scale, commercial agriculture, we show that secondary woodland habitats can retain considerable biodiversity value, and act as carbon sinks.

Arctic canopy photosynthetic efficiency enhanced under diffuse light, linked to a reduction in the fraction of the canopy in deep shade

We investigated how radiation conditions within a tundra canopy were linked to canopy photosynthesis, and how this linkage explained photosynthetic sensitivity to sky conditions, that is total radiation and its diffuse fraction. We measured within canopy radiation at leaf scales and net CO2 exchanges at canopy scales, under varied total irradiance and diffuse fraction, in Alaskan shrub tundra. Normalised mean radiation profiles within canopies showed no significant differences with varied diffuse fractions. However, radiation density distribution was non-normal, being more unimodal under diffuse conditions and distinctly bimodal under direct sunlight. There was a nearly three-fold increase in the proportion of the canopy in deep shade under direct illumination, compared to diffuse conditions. Under diffuse conditions the canopy had higher light-use efficiency (LUE), resulting in up to 17% greater photosynthesis. The enhancement in LUE under diffuse illumination was not related to differences in the mean light profiles, but instead was due to significant shifts in the density distribution of light at leaf scales, in particular a reduced fraction of the canopy in deep shade under diffuse illumination. These results provide unique information for testing radiative transfer schemes in canopy models, and for better understanding canopy structure and trait variation within plant canopies.

Cyclic occurrence of fire and its role in carbon dynamics along an edaphic moisture gradient in longleaf pine ecosystems

Fire regulates the structure and function of savanna ecosystems, yet we lack understanding of how cyclic fire affects savanna carbon dynamics. Furthermore, it is largely unknown how predicted changes in climate may impact the interaction between fire and carbon cycling in these ecosystems. This study utilizes a novel combination of prescribed fire, eddy covariance (EC) and statistical techniques to investigate carbon dynamics in frequently burned longleaf pine savannas along a gradient of soil moisture availability (mesic, intermediate and xeric). This research approach allowed us to investigate the complex interactions between carbon exchange and cyclic fire along the ecological amplitude of longleaf pine. Over three years of EC measurement of net ecosystem exchange (NEE) show that the mesic site was a net carbon sink (NEE = −2.48 tonnes C ha⁻¹), while intermediate and xeric sites were net carbon sources (NEE = 1.57 and 1.46 tonnes C ha⁻¹, respectively), but when carbon losses due to fuel consumption were taken into account, all three sites were carbon sources (10.78, 7.95 and 9.69 tonnes C ha⁻¹ at the mesic, intermediate and xeric sites, respectively). Nonetheless, rates of NEE returned to pre-fire levels 1–2 months following fire. Consumption of leaf area by prescribed fire was associated with reduction in NEE post-fire, and the system quickly recovered its carbon uptake capacity 30–60 days post fire. While losses due to fire affected carbon balances on short time scales (instantaneous to a few months), drought conditions over the final two years of the study were a more important driver of net carbon loss on yearly to multi-year time scales. However, longer-term observations over greater environmental variability and additional fire cycles would help to more precisely examine interactions between fire and climate and make future predictions about carbon dynamics in these systems.