Using climate-driven leaf phenology and growth to improve predictions of gross primary productivity in North American forests

Long-term species-level observations indicate the critical role of soil moisture in regulating China's grassland productivity relative to phenological and climatic factors

As a sensitive indicator of climate change and a key variable in ecosystem surface-atmosphere interaction, vegetation phenology, and the growing season length, as well as climatic factors (i.e., temperature, precipitation, and sunshine duration) are widely recognized as key factors influencing vegetation productivity. Recent studies have highlighted the importance of soil moisture in regulating grassland productivity. However, the relative importance of phenology, climatic factors, and soil moisture to plant species-level productivity across China's grasslands remains poorly understood. Here, we use nearly four decades (1981 to 2018) of in situ species-level observations from 17 stations distributed across grasslands in China to examine the key mechanisms that control grassland productivity. The results reveal that soil moisture is the strongest determinant of the interannual variability in grassland productivity. In contrast, the spring/autumn phenology, the length of vegetation growing season, and climate factors have relatively minor impacts. Generally, annual aboveground biomass increases by 3.9 to 25.3 g∙m2 (dry weight) with a 1 % increase in growing season mean soil moisture across the stations. Specifically, the sensitivity of productivity to moisture in wetter and colder environments (e.g., alpine meadows) is significantly higher than that in drier and warmer environments (e.g., temperate desert steppes). In contrast, the sensitivity to the precipitation of the latter is greater than the former. The effect of soil moisture is the most pronounced during summer. Dominant herb productivity is more sensitive to soil moisture than the others. Moreover, multivariate regression analyses show that the primary climatic factors and their attributions to variations in soil moisture differ among the stations, indicating the interaction between climate and soil moisture is very complex. Our study highlights the interspecific difference in the soil moisture dependence of grassland productivity and provides guidance to climate change impact assessments in grassland ecosystems.

Climate-driven shifts in leaf senescence are greater for boreal species than temperate species in the Acadian Forest region in contrast to leaf emergence shifts

The Acadian Forest Region is a temperate-boreal transitional zone in eastern North America which provides a unique opportunity for understanding the potential effects of climate change on both forest types. Leaf phenology, the timing of leaf life cycle changes, is an important indicator of the biological effects of climate change, which can be observed with stationary timelapse cameras known as phenocams. Using four growing seasons of observations for the species Acer rubrum (red maple), Betula papyrifera (paper/white birch) and Abies balsamea (balsam fir) from the Acadian Phenocam Network as well as multiple growing season observations from the North American PhenoCam Network we parameterized eight leaf emergence and six leaf senescence models for each species which span a range in process and driver representation. With climate models from the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5) we simulated future leaf emergence, senescence and season length (senescence minus emergence) for these species at sites within the Acadian Phenocam Network. Model performances were similar across models and leaf emergence model RMSE ranged from about 1 to 2 weeks across species and models, while leaf senescence model RMSE ranged from about 2 to 4 weeks. The simulations suggest that by the late 21st century, leaf senescence may become continuously delayed for boreal species like Betula papyrifera and Abies balsamea, though remain relatively stable for temperate species like Acer rubrum. In contrast, the projected advancement in leaf emergence was similar across boreal and temperate species. This has important implications for carbon uptake, nutrient resorption, ecology and ecotourism for the Acadian Forest Region. More work is needed to improve predictions of leaf phenology for the Acadian Forest Region, especially with respect to senescence. Phenocams have the potential to rapidly advance process-based model development and predictions of leaf phenology in the context of climate change.

Vegetation photosynthetic phenology dataset in northern terrestrial ecosystems

Vegetation phenology can profoundly modulate the climate-biosphere interactions and thus plays a crucial role in regulating the terrestrial carbon cycle and the climate. However, most previous phenology studies rely on traditional vegetation indices, which are inadequate to characterize the seasonal activity of photosynthesis. Here, we generated an annual vegetation photosynthetic phenology dataset with a spatial resolution of 0.05 degrees from 2001 to 2020, using the latest gross primary productivity product based on solar-induced chlorophyll fluorescence (GOSIF-GPP). We combined smoothing splines with multiple change-point detection to retrieve the phenology metrics: start of the growing season (SOS), end of the growing season (EOS), and length of growing season (LOS) for terrestrial ecosystems above 30° N latitude (Northern Biomes). Our phenology product can be used to validate and develop phenology or carbon cycle models and monitor the climate change impacts on terrestrial ecosystems.

Increasing temperature regulates the advance of peak photosynthesis timing in the boreal ecosystem

The shift in vegetation phenology is an essential indicator of global climate change. Numerous researches based on reflectance-based vegetation index data have explored the changes in the start (SOS) and end (EOS) of vegetation life events at long time scales, while a huge discrepancy existed between the phenological metrics of vegetation structure and function. The peak photosynthesis timing (PPT), which is crucial in regulating terrestrial ecosystem carbon balance, has not received much attention. Using two global reconstructed solar-induced chlorophyll fluorescence data (CSIF and GOSIF) directly associated with vegetation photosynthesis, the spatio-temporal dynamics in PPT as well as the key environmental controls across the boreal ecosystem during 2001-2019 were systematically explored. Multi-year mean pattern showed that PPT mainly appeared in the first half of July. Compared to the northern Eurasia, later PPT appeared in the northern North America continent for about 4-5 days. Meanwhile, spatial trend in PPT exhibited an advanced trend during the last two decades. Especially, shrubland and grassland were obvious among all biomes. Spatial partial correlation analysis revealed that preseason temperature was the dominant environmental driver of PPT trends, occupying 81.32% and 78.04% of the total pixels of PPT_CSIF and PPT_GOSIF, respectively. Attribution analysis by ridge regression again emphasized the largest contribution of temperature to PPT dynamics in the boreal ecosystem by 52.22% (PPT_CSIF) and 46.59% (PPT_GOSIF), followed by radiation (PPT_CSIF: 24.44%; PPT_GOSIF: 28.66%) and precipitation (PPT_CSIF: 23.34%; PPT_GOSIF: 24.75%). These results have significant implications for deepening our understanding between vegetation photosynthetic phenology and carbon cycling with respect to future climate change in the boreal ecosystem.

Integrating multiple plant functional traits to predict ecosystem productivity

Quantifying and predicting variation in gross primary productivity (GPP) is important for accurate assessment of the ecosystem carbon budget under global change. Scaling traits to community scales for predicting ecosystem functions (i.e., GPP) remain challenging, while it is promising and well appreciated with the rapid development of trait-based ecology. In this study, we aim to integrate multiple plant traits with the recently developed trait-based productivity (TBP) theory, verify it via Bayesian structural equation modeling (SEM) and complementary independent effect analysis. We further distinguish the relative importance of different traits in explaining the variation in GPP. We apply the TBP theory based on plant community traits to a multi-trait dataset containing more than 13,000 measurements of approximately 2,500 species in Chinese forest and grassland systems. Remarkably, our SEM accurately predicts variation in annual and monthly GPP across China (R² values of 0.87 and 0.73, respectively). Plant community traits play a key role. This study shows that integrating multiple plant functional traits into the TBP theory strengthens the quantification of ecosystem primary productivity variability and further advances understanding of the trait-productivity relationship. Our findings facilitate integration of the growing plant trait data into future ecological models.

Early flowering changes robusta coffee yield responses to climate stress and management

A shift towards earlier flowering is a widely noted consequence of climate change for the world's plants. However, whether early flowering changes the way in which plants respond to climate stress, and in turn plant yield, remains largely unexplored. Using 10 years of flowering time and yield observations (Total N = 5580) from 558 robusta coffee (Coffea canephora) farms across Vietnam we used structural equation modelling (SEM) to examine the drivers of flowering day anomalies and the consequent effects of this on coffee climate stress sensitivity and management responses (i.e. irrigation and fertilization). SEM allowed us to model the cascading and interacting effects of differences in flowering time, growing season length and climate stress. Warm nights were the main driver of early flowering (i.e. flowering day anomalies <0), which in turn corresponded to longer growing seasons. Early flowering was linked to greater sensitivity of yield to temperature during flowering (i.e. early in the season). In contrast, when late flowering occurred yield was most sensitive to temperature and rainfall later in the growing season, after flowering and fruit development. The positive effects of tree age and fertilizer on yield, apparent under late flowering conditions, were absent when flowering occurred early. Late flowering models predicted yields under early flowering conditions poorly (a 50 % reduction in cross-validated R² of 0.54 to 0.27). Likewise, models based on early flowering were unable to predict yields well under late flowering conditions (a 75 % reduction in cross-validated R², from 0.58 to 0.14). Our results show that early flowering changes the sensitivity of coffee production to climate stress and management and in turn our ability to predict yield. Our results indicate that changes in plant phenology need to be taken into account in order to more accurately assess climate risk and management impacts on plant performance and crop yield.

Warming and spring precipitation addition change plant growth pattern but have minor effects on growing season mean gross ecosystem productivity in an alpine meadow

Gross ecosystem productivity (GEP) plays an important role in global carbon cycling. However, how plant phenology and growth rate regulate GEP under climate change is unclear. Based on an in situ manipulative experiment using open top chambers from 2015 to 2018, we measured whole year warming and spring precipitation addition effects on plant phenology, plant growth rate and GEP. Our results showed that warming delayed plant green up (4 days) and withering (5 days), while spring precipitation addition advanced green up 13 days and did not change withering. Warming delayed the timing of the fast-growing phase 7 days, shortened length of the fast-growing phase 7 days and marginally increased the growth rate. Spring precipitation addition advanced the timing of the fast-growing phase 6 days, but did not change the length of the fast-growing phase or the growth rate. Both whole year warming and spring precipitation addition have not significantly affected growing season mean GEP. GEP is positively correlated with plant growth rate and negatively correlated with the length of the fast-growing phase. We provide an evidence that although warming did not change growing season mean productivity, it delayed plant fast-growing phase. Our findings suggest that management approaches for increasing water availability before the fast-growing phase should be intensified to increase ecosystem carbon uptake and grass supply for animal husbandry in spring.

Climatic regulation of leaf and cambial phenology in Quercus pubescens: Their interlinkage and impact on xylem and phloem conduits

Increased frequency and severity of stressful events affects the growth patterns and functioning of trees which adjust their phenology to given conditions. Here, we analysed environmental effects (temperature, precipitation, VPD and SWC) on the timing of leaf phenology, seasonal stem radial growth patterns, and xylem and phloem anatomy of Quercus pubescens in the sub-Mediterranean in the period 2014-2019, when various adverse weather events occurred, i.e. spring drought in 2015, summer fire in 2016 and summer drought in 2017. Results showed that the timings of leaf and cambium phenology do not occur simultaneously in Q. pubescens, reflecting different environmental and internal constraints. Although year-to-year variability in the timings of leaf and cambial phenology exists, their chronological sequence is fairly fixed. Different effects of weather conditions on different stages of leaf development in spring were observed. Common climatic drivers (i.e., negative effect of hot and dry summers and a positive effect of increasing moisture availability in winter and summer) were found to affect the widths of xylem and phloem increments with more pronounced effect on late formed parts. A legacy effect of the timing of leaf and cambial phenology of the previous growing season on the timing of phenology of the following spring was confirmed. Rarely available phloem data permitted a comprehensive insight into the interlinkage of the timing of cambium and leaf phenology and adjustment strategies of vascular tissues in Mediterranean pubescent oak to various environmental constraints, including frequent extreme events (drought, fire). Our results suggest that predicted changes in autumn/winter and spring climatic conditions for this area could affect the timings of leaf and stem cambial phenology of Q. pubescens in the coming years, which would affect stem xylem and phloem structure and hydraulic properties, and ultimately its performance.

When Water Availability Is Low, Two Mediterranean Salvia Species Rely on Root Hydraulics

Increase in severity and frequency of drought events is altering plant community composition, exposing biomes to a higher risk of biodiversity losses. This is exacerbated in the most fragile areas as Mediterranean biome. Thus, identifying plant traits for forecasting species with a high risk of drought-driven mortality is particularly urgent. In the present study, we investigated the drought resistance strategy of two Mediterranean native species: Salvia ceratophylloides Ard. (Sc) and Salvia officinalis L. (So) by considering the impact of drought-driven water content decline on plant hydraulics. Well-watered samples of Sc displayed higher leaf and stemsaturated water content and lower shoot biomass than So samples, but similar root biomass. In response to drought, Sc showed a conservative water use strategy, as the prompt stomatal closure and leaves shedding suggested. A drought-tolerant mechanism was confirmed in So samples. Nevertheless, Sc and So showed similar drought-driven plant hydraulic conductance (Kplant) recover ability. Root hydraulic traits played a key role to reach this goal. Relative water content as well as loss of cell rehydration capability and membrane damages, especially of stem and root, were good proxies of drought-driven Kplant decline.

Too dry to survive: Leaf hydraulic failure in two Salvia species can be predicted on the basis of water content

Global warming is exposing plants to increased risks of drought-driven mortality. Recent advances suggest that hydraulic failure is a key process leading to plant death, and the identification of simple and reliable proxies of species-specific risk of irreversible hydraulic damage is urgently required. We assessed the predictive power of leaf water content and shrinkage for monitoring leaf hydraulic failure in two Mediterranean native species, Salvia ceratophylloides (Sc) and S. officinalis (So). The study species showed significant differences in relative water content (RWC) thresholds inducing loss of rehydration capacity, as well as leaf hydraulic conductance (K_L) impairment. Sc turned out to be more resistant to drought than So. However, Sc and So showed different leaf saturated water content values, so that different RWC values actually corresponded to similar absolute leaf water content. Our findings suggest that absolute leaf water content and leaf water potential, but not RWC, are reliable parameters for predicting the risk of leaf hydraulic impairment of two Salvia species, and their potential risk of irreversible damage under severe drought. Moreover, the lack of any K_L decline until the turgor loss point in Sc, coupled to consistent leaf shrinkage, rejects the hypothesis to use leaf shrinkage as a proxy to predict K_L vulnerability, at least in species with high leaf capacitance. Robust linear correlations between K_L decline and electrolyte leakage measurements suggested a role of membrane damage in driving leaf hydraulic collapse.