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Record W2617027240 · doi:10.1093/jxb/erx114

Warming puts the squeeze on photosynthesis – lessons from tropical trees

2017· article· en· W2617027240 on OpenAlexaff
Mirindi Eric Dusenge, Danielle A. Way

Bibliographic record

VenueJournal of Experimental Botany · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant responses to elevated CO2
Canadian institutionsWestern University
Fundersnot available
KeywordsPhotosynthesisTropical climateEnvironmental scienceBiologyEcologyBotany

Abstract

fetched live from OpenAlex

Tropical forests are regions of relative thermal stability and so, although equatorial regions are expected to experience less climate warming than the global average in coming years, tropical trees might be more vulnerable to change. But are they? In this issue of Journal of Experimental Botany, Slot and Winter (2017) provide one of the most comprehensive studies on thermal acclimation of tropical trees to date. Climate change will increase global temperatures by 2–4 °C in the next 85 years. While this represents an enormous shift in the Earth’s climate, warming is not expected to be uniform over the globe, with equatorial regions warming by ‘only’ 1–2 °C by 2050 (IPCC, 2013). This might lead to the conclusion that tropical forests are therefore less at risk from climate warming than other biomes (Sala et al., 2000). However, tropical forests are regions of thermal stability: on a geological timescale, they have avoided the repeated glaciations and associated climate extremes experienced by higher latitudes. On much shorter timescales, diurnal temperatures may fluctuate by only 5 °C, while monthly mean temperatures may differ by just 1–4 °C across the year (Trewin, 2014), an enormous contrast to the broad temperature swings that temperate and boreal trees experience on a daily and yearly basis. It has thus long been thought that tropical species may be adapted to a narrow thermal niche and that the ability to tolerate and acclimate to temperatures outside this temperature range may be much more limited than it is in higher latitude species (Janzen, 1967). If this is true, then the relatively small increases in temperatures expected in low latitudes may actually cause greater thermal stress in tropical forests than the larger degree of warming will in temperate and tropical trees. Indeed, increased growth temperatures decrease tree growth in tropical species in almost every study (Way and Oren, 2010). Given that tropical forests contain more than 50% of the carbon found in forests (Pan et al., 2011) and that the majority of the world’s biodiversity is in the tropics (Lewis, 2006), declines in the growth, carbon sequestration and survival of tropical tree species in a warmer world would have dire consequences. While we have considerable data on how temperate species respond to increased growth temperatures, there are only a handful of studies looking at the thermal acclimation capacity of tropical tree species, and this paucity of information impedes our ability to predict how low-latitude forests will respond to a future, warmer world. The new paper by Slot and Winter (2017) provides one of the most comprehensive studies on thermal acclimation of tropical trees to date. They grew seedlings of three common lowland tropical species at 25 °C, 30 °C and 35 °C and assessed how photosynthesis, respiration and growth were affected by the different temperature regimes. The good news is that all the species acclimated to the warmer temperatures: the thermal optimum of photosynthesis (Topt, the temperature at which carbon uptake is maximized) increased with increasing growth temperature, and respiration rates were lower in plants from warmer treatments (indicating a reduction in carbon losses). But there was also bad news. The shift in Topt was smaller than the shift in growth temperature, net photosynthetic rates at the growth temperature (Pgrowth, the most ecologically relevant measurement of CO2 uptake) were reduced in plants grown at the warmest temperature, and the photosynthetic capacity of leaves showed little plasticity to growth temperature. Most strikingly, one of the three species (Calophyllum longifolium) grew so poorly at 35 °C that Slot and Winter had to use a 33 °C treatment to provide enough leaves to collect their data. Even under this lower, ‘severe’ warming treatment, the late-successional C. longifolium showed substantial reductions in photosynthesis compared to seedlings grown at 25 and 30 °C, and also compared to the other species in the study, Ficus insipida and Ochroma pyramidale, which are both early-successional. Overall, the results indicate that while photosynthesis in the study species shows some plasticity to increasing temperatures, acclimation cannot keep pace with warming, and this failure to acclimate successfully may be worse in late-successional species, as also seen in Cheesman and Winter (2013). One of the most interesting parts of the work by Slot and Winter (2017) was their assessment of the high-temperature CO2 compensation point, the upper leaf temperature at which net CO2 assimilation rates were zero (Tmax; see Box 1). Recent work has explored how thermal acclimation affects photosynthetic traits such as Topt and Pgrowth, (Way and Yamori, 2014; Yamori et al., 2014). Also, Yamori et al. (2014) noted that the span of leaf temperatures that realizes 80% of the maximum photosynthetic rate was invariant with growth temperature, implying that the temperature response of net photosynthesis is not narrowed or broadened by warming. However, there is almost nothing known about how Tmax is affected by changes in growth temperature. In their study, Slot and Winter (2017) found that a 10 °C change in growth temperature had no effect on Tmax, but Tmax did vary between species: while Tmax was 45 °C in C. longifolium (the late-successional species with pronounced mortality at 35 °C), Tmax was 50 °C for both F. insipida and O. pyramidale. The combination of a shift in Topt without a corresponding shift in Tmax in plants grown at warmer temperatures resulted in a narrowing of the temperature-response curve of photosynthesis. The solid, blue line represents a cool-grown leaf and the dashed, red line represents a warm-grown leaf. Plants grown at higher temperatures usually exhibit an increased photosynthetic thermal optimum (Topt, shown as a point on each curve), but there is little data on how Tmax (the upper temperature at which net CO2 assimilation rates are zero, i.e. carbon gain balances carbon loss) responds to warming. If Topt increases but Tmax remains constant, as in Slot and Winter (2017), the temperature response of net photosynthesis is ‘squeezed’ and becomes narrower. To further explore the extent to which Tmax changes in response to an increase in growth temperature, we collated data from 34 published studies (Box 2; Table 1) that reported temperature-response curves of net photosynthesis for plants grown at two or more different thermal regimes. Only papers with measurements that included points of declining net CO2 assimilation rates above the Topt were used, ensuring a robust estimate of Tmax. We then estimated Tmax for both control and warm-grown plants for each reported species using a second-order polynomial fit to the temperature-response curve of net photosynthesis. Although there is considerable variation in the relationship between the degree of warming and the shift in Tmax, overall, a 1 °C increase in growth temperature led to a 0.4 °C increase in Tmax. Unfortunately, there is insufficient data to determine if there are significant differences in the thermal acclimation of Tmax between plant functional types, but in 25% of the cases assessed, Tmax actually decreased with increasing growth temperature (Box 2). Based on these findings, the inability of the tropical species investigated in Slot and Winter (2017) to shift their Tmax is uncommon, and may be related to the high values for Tmax, which are close to temperatures that can cause irreversible damage to leaves (Krause et al., 2010; 2015). Change in Tmax (∆ Tmax) of net CO2 assimilation rate as a function of the increase in growth temperature (∆ Tgrowth) in plant species from four plant functional types (see key). Each point plotted represents a comparison between cool and warm-grown plants from a single study (Table 1). The dotted line shows the regression for all data taken together (y=–1.29 + 0.40x; r2=0.13; P=0.0002). Species/functional types used in the high-temperature CO2compensation point analysis Although Slot and Winter (2017) provide critical data on how carbon fluxes in tropical species acclimate to warming, there is a pressing need to move beyond gas exchange measurements in these types of studies. Many papers on thermal acclimation measure traits such as leaf nitrogen concentrations and specific leaf area, but future studies should delve more deeply into the biochemical and physiological mechanisms underlying photosynthetic (and respiratory) acclimation. Recent studies in tropical tree species have highlighted the importance of within-leaf N allocation as a strong determinant of variation in photosynthetic capacity (Coste et al., 2005; Dusenge et al., 2015). Specifically, Scafaro et al. (2016) demonstrated that accounting for changes in N allocation to the CO2-fixing enzyme Rubisco in response to growth temperature explained the measured variation in photosynthetic capacity in a range of temperate and tropical species. Shifts in N allocation between the Calvin cycle and electron transport may represent a major theme for thermal acclimation of carbon gain (Hikosaka et al., 2006), but we still lack a predictive model of photosynthetic acclimation to temperature that could explain the variation we see between plant functional types (as described in Yamori et al., 2014, and Way and Yamori, 2014). While this is not a problem unique to tropical systems, building such a model will require a much more extensive understanding of how changes in temperature affect photosynthesis in a broad range of species and ecosystems. This represents a significant challenge, but it would be an important step forward for predicting future carbon fluxes in vegetation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.203
Threshold uncertainty score0.521

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.036
GPT teacher head0.281
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations12
Published2017
Admission routes1
Has abstractyes

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