Jérôme Chave’s research while affiliated with Paul Sabatier University - Toulouse III and other places


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Publications (447)


Evidence for a Miocene pulse of diversification of the tropical American clade of the Brazil nut family (Lecythidaceae)
  • Article

October 2024

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32 Reads

Botany Letters

Jérôme Chave

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Uxue Suescun

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TROLL 4.0: representing water and carbon fluxes, leaf phenology and intraspecific trait variation in a mixed-species individual-based forest dynamics model – Part 1: Model description
  • Preprint
  • File available

October 2024

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45 Reads

TROLL 4.0 is an individual-based forest dynamics model that is capable of jointly simulating forest structure, diversity and ecosystem functioning, including the ecosystem water balance and productivity, leaf area dynamics and the tree community functional and taxonomic composition. It represents ecosystem flux processes in a manner similar to dynamic global vegetation models, while adopting a representation of plant community structure and diversity at a resolution consistent with that used by field ecologists. Specifically, trees are modeled as three-dimensional individuals with a metric-scale spatial representation, providing a detailed description of ecological processes such as competition for resources and tree demography. Carbon assimilation and plant water loss are explicitly represented at tree level using coupled photosynthesis and stomatal conductance models, depending on the micro-environmental conditions experienced by trees. Soil water uptake by trees is also modelled. Physiological and demographic processes are parameterized using plant functional traits measured in the field. Here we provide a detailed description and discussion of the implementation of TROLL 4.0. An evaluation of the model at two tropical forest sites is provided in a companion paper (Schmitt et al., submitted companion paper). TROLL 4.0’s representation of processes reflects the state of the art, and we discuss possible developments to improve its predictive capability and its capacity to address challenges in forest monitoring, forest dynamics and carbon cycle research.

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TROLL 4.0: representing water and carbon fluxes, leaf phenology, and intraspecific trait variation in a mixed-species individual-based forest dynamics model – Part 2: Model evaluation for two Amazonian sites

October 2024

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25 Reads

TROLL 4.0 is an individual-based forest dynamics model that jointly simulates the structure, diversity and functioning of tropical forests, including their water balance, carbon fluxes and leaf phenology, while accounting for intraspecific trait variation for a large number of species. In a companion paper, we describe how the model represents the physiological and demographic processes that control the tree life cycle in a one-metre-resolution spatially-explicit scene and uses plant functional traits measurable in the field to parameterize such processes across species and individuals (Maréchaux et al., submitted companion paper). Here we evaluate the performance of TROLL 4.0 for two Amazonian sites with contrasting soil and climate properties. We assessed the model's ability to represent forest structure and composition using lidar-derived canopy height distributions and forest inventories combined with information on plant functional traits. We also evaluated the model's ability to represent carbon and water fluxes, as well as leaf area variation, at daily and fortnightly resolution over a decade, using detailed information from on-site eddy covariance towers, satellite data and ground-based or air-borne lidar data. We finally compared the responses of carbon and water fluxes to environmental drivers between simulated and observed data. Overall, TROLL 4.0 provided a realistic representation of forests at both sites. The simulated canopy height distribution showed a high correlation coefficient (CC) with observed aerial and satellite data (CC>0.92), while the species and functional composition were well represented (CC>0.75). TROLL 4.0 also realistically simulated the seasonal variability of carbon and water fluxes (CC>0.46) and their responses to environmental drivers, while capturing temporal variations in leaf area (CC>0.76) and its partitioning in leaf age cohorts. However, TROLL 4.0 overestimated annual gross primary productivity at both sites (mean RMSEP=0.94 kgC m-2 yr-1) and evapotranspiration at one site (mean RMSEP=0.75 mm day-1), likely due to an underestimation of the soil water depletion and stomatal control during the dry season. This evaluation highlights the potential of TROLL 4.0 to represent ecosystem fluxes and the structure and diversity of plant communities at a fine resolution, paving the way for model predictions of the effects of climate change, fragmentation and forest management on forest structure and dynamics.


Design and performance of the Climate Change Initiative Biomass global retrieval algorithm

October 2024

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201 Reads

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2 Citations

Science of Remote Sensing

The increase in Earth observations from space in recent years supports improved quantification of carbon storage by terrestrial vegetation and fosters studies that relate satellite measurements to biomass retrieval algorithms. However, satellite observations are only indirectly related to the carbon stored by vegetation. While ground surveys provide biomass stock measurements to act as reference for training the models, they are sparsely distributed. Here, we addressed this problem by designing an algorithm that harnesses the interplay of satellite observations, modeling frameworks and field measurements, and generated global estimates of above-ground biomass (AGB) density that meet the requirements of the scientific community in terms of accuracy, spatial and temporal resolution. The design was adapted to the amount, type and spatial distribution of satellite data available around the year 2020. The retrieval algorithm estimated AGB annually by merging estimates derived from C-and L-band Synthetic Aperture Radar (SAR) backscatter observations with a Water Cloud type of model and does not rely on AGB reference data at the same spatial scale as the SAR data. This model is integrated with functions relating to forest structural variables that were trained on spaceborne LiDAR observations and sub-national AGB statistics. The yearly estimates of AGB were successively harmonized using a cost function that minimizes spurious fluctuations arising from the moderate-to-weak sensitivity of the SAR backscatter to AGB. The spatial distribution of the AGB estimates was correctly reproduced when the retrieval model was correctly set. Over-predictions occasionally occurred in the low AGB range (<50 Mg ha − 1) and under-predictions in the high AGB range (>300 Mg ha − 1). These errors were a consequence of sometimes too strong generalizations made within the modeling framework to allow reliable retrieval worldwide at the expense of accuracy. The precision of the estimates was mostly between 30% and 80% relative to the estimated value. While the framework is well founded, it could be improved by incorporating additional satellite observations that capture structural properties of vegetation (e.g., from SAR interferometry, low-frequency SAR, or high-resolution observations), a dense network of regularly monitored high-quality forest biomass reference sites, and spatially more detailed characterization of all model parameters estimates to better reflect regional differences.


Hypothesised association between maturation size (dmat$$ {d}_{\mathrm{mat}} $$) and maximum size (dmax$$ {d}_{\mathrm{max}} $$) (a) and the relative size at maturation (drel=dmat/dmax$$ {d}_{\mathrm{rel}}={d}_{\mathrm{mat}}/{d}_{\mathrm{max}} $$) (b) (Equation (1)). To highlight the effects of size (parameter βd$$ {\beta}_{\mathrm{d}} $$), values of parameter α$$ \alpha $$ are selected to yield an equivalent diameter at dmax = 60 cm. Two ‘baseline’ hypotheses (dashed lines) are independence between dmat$$ {d}_{\mathrm{mat}} $$ and dmax$$ {d}_{\mathrm{max}} $$ (black dotted) and proportionate delay (red dotted), the latter is expected if increased size incurs the same maturation delay at all size classes. Two alternative hypotheses are increasing (purple—accelerating risk model) or decreasing (blue—diminishing risk model) maturation delays in the largest size classes.
Three elements of the analysis include (a) an individual‐scale analysis (blue) to estimate maturation status each year and to parameterise relationships that control maturation. This fitted model is the basis for species‐level prediction of maturation size (red). (b) Species‐level expected maturation size based on the proportionate risk model, controlling for species' differences in their climate domains. (c) Analysis of species‐level trait relationships with maturation size.
Tree maturation size (a, b), and relative size at maturation (c, d) for 486 species. Each dot represents one species. Alternative models are dashed lines, black for independence between maturation size and maximum size (βd=0$$ {\beta}_{\mathrm{d}}=0 $$), and red for the proportional cost model (βd=1$$ {\beta}_{\mathrm{d}}=1 $$). The best fitting model (blue with 95%CI) supports the diminishing risk model (βd<1$$ {\beta}_{\mathrm{d}}<1 $$, Table 1). Panels b and d are predictions from the fitted model with an interaction between continuous dmax$$ {d}_{\mathrm{max}} $$ and temperature (Line 1 of Table 1). This model gives a continuous surface plot of maturation size as a function of maximum size and temperature (see Figure S4). However, for clarity, we represent only the prediction at cold (8°C, purple) and warm temperatures (25°C, green) spanning observed diameter ranges.
Conditional parameter estimates for the direct effect of traits on tree size at maturation diameter (dmat$$ {d}_{\mathrm{mat}} $$) while accounting for trait covariance, climate, and phylogeny. Conditional parameters are evaluated on a standardised scale (predictors are centred and standardised) making trait effects on dmat$$ {d}_{\mathrm{mat}} $$ respective to their variation in the data set. Shown are posterior means and 95% credible intervals. Blue and red represent positive and negative associations where 95% of the posterior does not include zero. SLA = specific leaf area.
The Relationship Between Maturation Size and Maximum Tree Size From Tropical to Boreal Climates

Ecology Letters

The fundamental trade‐off between current and future reproduction has long been considered to result in a tendency for species that can grow large to begin reproduction at a larger size. Due to the prolonged time required to reach maturity, estimates of tree maturation size remain very rare and we lack a global view on the generality and the shape of this trade‐off. Using seed production from five continents, we estimate tree maturation sizes for 486 tree species spanning tropical to boreal climates. Results show that a species' maturation size increases with maximum size, but in a non‐proportional way: the largest species begin reproduction at smaller sizes than would be expected if maturation were simply proportional to maximum size. Furthermore, the decrease in relative maturation size is steepest in cold climates. These findings on maturation size drivers are key to accurately represent forests' responses to disturbance and climate change.



Variation in composition and relative abundance of 5188 tree species in 2023 forest-inventory plots (1 ha) across Amazonian forests
Ordination biplots showing the two first principal components with inventory plots coloured by (a) ecological forest categories based on hydrology and soil characteristics and (b) geographic regions. a Ecological categories: VA, Várzea forests; SW, swamp forests; IG, igapó forests; PZ, white-sand (podzol) forests; TFGS, terra-firme on the Guiana Shield; TFBS terra-firme on the Brazilian Shield, TFPB terra-firme on the Pebas sedimentary basin. b Geographical regions: CA Central Amazonia, EA Eastern Amazonia, SA Southern Amazonia, GS Guiana Shield, NWA Northwestern Amazonia, SWA Southwestern Amazonia. Arrows indicate vectors constructed with envfit()⁸¹ for 14 environmental predictors: Flooded flooding vs. non-flooding terrains, WTD water table depth, Temp_avg average annual temperature, MCWD maximum climatological water deficit), Annal_ppt Annual Rainfall, Podzol White Sand vs. Clay-Silt terrains, ALOS_MTPI Multiscale Topographic Position Index, TopoDiver Topographic Diversity Index, Ppt_sea precipitation seasonality, ALOS_3D elevation, Temp_range temperature range, Temp_seas temperature seasonality, pH soil pH, SB soil sum of bases.
Variation in interpolated composition and relative abundance of 5,188 tree species in 47,441 grid cells (0.1-degree squares) across Amazonian forests
Ordination biplots showing the two first DCA axes with grid cells coloured by geographic region: CA Central Amazonia, EA Eastern Amazonia, GS Guiana Shield, NWA Northwestern Amazonia, SWA Southwestern Amazonia, SA Southern Amazonia. Black marks show the average position for the abundance distribution of the 20 tree species with the highest interpolated total abundance. The distributions of these species in geographical and ordination space are shown in Supplementary Figs. 5–24.
Maps of the broad-scale spatial variation of tree species composition across Amazonia
Scores of (a) DCA Axis 1, (b) DCA Axis2 (both from Fig. 2). In both maps, grey lines are the isolines linking equal levels of DCA scores, with the spatial distance between consecutive isolines being inversely related to the rate of compositional change across space and used to mark sharp compositional turnover zones (if closer together) or smoother compositional turnover (consecutive isolines further apart). In (a), the blue isoline corresponds to DCA score of 1.0 and the red isoline to soil pH = 5 (west of that line having a soil pH >5). In (b), the red isoline corresponds to maximum climatological water deficit (MCWD) = − 275 mm (south of that line having MCWD < −275), and the blue isoline to MCWD = −100 (west that line having MCWD > −100). The dark green line delimits the Amazonian tropical forests⁹⁵, with white areas within these limits corresponding to montane areas (above 500 m elevation) and non-forested habitats such as savannas. Major river courses are shown in blue. Base map source for countries: https://www.naturalearthdata.com/; rivers⁶¹. Maps created with custom R⁸⁸ script.
Niche positions and niche breadths of 5188 tree species along environmental and compositional gradients in Amazonia as calculated with data from 2023 1-ha forest-inventory plots
Gradients along the x axis: (a) Annual rainfall (mm); (b) maximum climatological water deficit (mm); (c) log(soil sum of bases (Ca+Mg+K)); (d) soil acidity (pH); (e) DCA1 scores from Fig. 2; and (f) DCA2 scores from Fig. 2. The black dots mark the mean niche position or optimum (weighted average value) for each species and the grey lines depict the niche breadths or tolerance (±standard deviation for the variable in sites where the species was observed). The red lines show the mean niche breadth (determined by loess regression). Coloured lines correspond to the lines also visible in Fig. 3 (DCA1, DCA2, pH, MCWD). Species are shown from bottom to top in the order of increasing niche position. (See supplementary data 1 for the niche breadth and position values of all tree species).
The associations of species niche positions on compositional and environmental gradients
In the first row the species niche positions on the DCA1 scores gradient in relation to edaphic niche position gradients: (a) Soil sum of bases, (b) Soil pH. The second row shows the species niche positions along the DCA2 scores gradient in relation to climatic gradients: (c) Annual Rainfall, (d) Maximum climatological water deficit. Plot colours correspond to colours in Fig. 3. Coloured lines correspond to the lines (DCA1, pH, MCWD) also visible in Fig. 3.
The biogeography of the Amazonian tree flora

October 2024

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994 Reads

Communications Biology

We describe the geographical variation in tree species composition across Amazonian forests and show how environmental conditions are associated with species turnover. Our analyses are based on 2023 forest inventory plots (1 ha) that provide abundance data for a total of 5188 tree species. Within-plot species composition reflected both local environmental conditions (especially soil nutrients and hydrology) and geographical regions. A broader-scale view of species turnover was obtained by interpolating the relative tree species abundances over Amazonia into 47,441 0.1-degree grid cells. Two main dimensions of spatial change in tree species composition were identified. The first was a gradient between western Amazonia at the Andean forelands (with young geology and relatively nutrient-rich soils) and central–eastern Amazonia associated with the Guiana and Brazilian Shields (with more ancient geology and poor soils). The second gradient was between the wet forests of the northwest and the drier forests in southern Amazonia. Isolines linking cells of similar composition crossed major Amazonian rivers, suggesting that tree species distributions are not limited by rivers. Even though some areas of relatively sharp species turnover were identified, mostly the tree species composition changed gradually over large extents, which does not support delimiting clear discrete biogeographic regions within Amazonia.


Tall Bornean forests experience higher canopy disturbance rates than those in the eastern Amazon or Guiana shield

September 2024

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55 Reads

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2 Citations

Global Change Biology

The future of tropical forests hinges on the balance between disturbance rates, which are expected to increase with climate change, and tree growth. Whereas tree growth is a slow process, disturbance events occur sporadically and tend to be short‐lived. This difference challenges forest monitoring to achieve sufficient resolution to capture tree growth, while covering the necessary scale to characterize disturbance rates. Airborne LiDAR time series can address this challenge by measuring landscape scale changes in canopy height at 1 m resolution. In this study, we present a robust framework for analysing disturbance and recovery processes in LiDAR time series data. We apply this framework to 8000 ha of old‐growth tropical forests over a 4–5‐year time frame, comparing growth and disturbance rates between Borneo, the eastern Amazon and the Guiana shield. Our findings reveal that disturbance was balanced by growth in eastern Amazonia and the Guiana shield, resulting in a relatively stable mean canopy height. In contrast, tall Bornean forests experienced a decrease in canopy height due to numerous small‐scale (<0.1 ha) disturbance events outweighing the gains due to growth. Within sites, we found that disturbance rates were weakly related to topography, but significantly increased with maximum canopy height. This could be because taller trees were particularly vulnerable to disturbance agents such as drought, wind and lightning. Consequently, we anticipate that tall forests, which contain substantial carbon stocks, will be disproportionately affected by the increasing severity of extreme weather events driven by climate change.


New tree height allometries derived from terrestrial laser scanning reveal substantial discrepancies with forest inventory methods in tropical rainforests

August 2024

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204 Reads

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1 Citation

Global Change Biology

Tree allometric models, essential for monitoring and predicting terrestrial carbon stocks, are traditionally built on global databases with forest inventory measurements of stem diameter (D) and tree height (H). However, these databases often combine H measurements obtained through various measurement methods, each with distinct error patterns, affecting the resulting H:D allometries. In recent decades, terrestrial laser scanning (TLS) has emerged as a widely accepted method for accurate, non‐destructive tree structural measurements. This study used TLS data to evaluate the prediction accuracy of forest inventory‐based H:D allometries and to develop more accurate pantropical allometries. We considered 19 tropical rainforest plots across four continents. Eleven plots had forest inventory and RIEGL VZ‐400(i) TLS‐based D and H data, allowing accuracy assessment of local forest inventory‐based H:D allometries. Additionally, TLS‐based data from 1951 trees from all 19 plots were used to create new pantropical H:D allometries for tropical rainforests. Our findings reveal that in most plots, forest inventory‐based H:D allometries underestimated H compared with TLS‐based allometries. For 30‐metre‐tall trees, these underestimations varied from −1.6 m (−5.3%) to −7.5 m (−25.4%). In the Malaysian plot with trees reaching up to 77 m in height, the underestimation was as much as −31.7 m (−41.3%). We propose a TLS‐based pantropical H:D allometry, incorporating maximum climatological water deficit for site effects, with a mean uncertainty of 19.1% and a mean bias of −4.8%. While the mean uncertainty is roughly 2.3% greater than that of the Chave2014 model, this model demonstrates more consistent uncertainties across tree size and delivers less biased estimates of H (with a reduction of 8.23%). In summary, recognizing the errors in H measurements from forest inventory methods is vital, as they can propagate into the allometries they inform. This study underscores the potential of TLS for accurate H and D measurements in tropical rainforests, essential for refining tree allometries.



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Citations (71)


... The precision of an AGBD estimate was quantified by an standard error, obtained by propagating individual errors of the SAR backscatter measurements and the retrieval model parameters throughout the retrieval approach. Few studies have assessed the CCI map accuracy to AGBD estimates from a global collection of National Forest Inventories and research plots, highlighting that networks of regularly monitored forest biomass reference sites may better reflect regional performance 38,39 . ...

Reference:

Intergovernmental Panel on Climate Change (IPCC) Tier 1 forest biomass estimates from Earth Observation
Design and performance of the Climate Change Initiative Biomass global retrieval algorithm

Science of Remote Sensing

... Even when we do correctly identify trees in ALS scans, there is still the issue accurately measuring their vertical and horizontal growth rates. Differences in sampling density and flight configuration across ALS scans can severely affect the retrieval of canopy attributes , although we can effectively mitigate these sources of uncertainty by using robust CHM algorithms and statistically correcting for differences in sampling density across ALS scans Jackson et al., 2024), as we have done here. Finally, if we want to convert changes in tree height and crown size into units of biomass, we need to rely on allometric equations that relate a tree's crown dimensions to its mass (Jucker et al., 2017). ...

Tall Bornean forests experience higher canopy disturbance rates than those in the eastern Amazon or Guiana shield
  • Citing Article
  • September 2024

Global Change Biology

... Finally, if we want to convert changes in tree height and crown size into units of biomass, we need to rely on allometric equations that relate a tree's crown dimensions to its mass (Jucker et al., 2017). Not only do these equations carry larger uncertainty than traditional biomass models based on stem diameters, but the field data used to calibrate them may also systematically differ from ALS-based estimates of tree height and crown size (Terryn et al., 2024). All these sources of error are minimised when working in open canopy systems with flat terrain dominated by relatively large, single-stemmed trees (Brandt et al., 2020) which is a key reason why we chose the GWW for our study. ...

New tree height allometries derived from terrestrial laser scanning reveal substantial discrepancies with forest inventory methods in tropical rainforests
  • Citing Article
  • August 2024

Global Change Biology

... Saumitou-Laprade et al. [18] suggest that this topic merits some investigations. In this regard, very recently Raimondeau et al. [46] have found heteromorphic SSI in the family Oleaceae and reported that the same SI determinants operating in DSI control distyly in Jasminum. The role of exceptional male olive trees (female sterile), reputed as very good pollinizers but at risk of disappearance [43], has not been considered by any author to explain the evolution of the olive reproductive system as it was in Phillyrea angustifolia [30]. ...

A hemizygous supergene controls homomorphic and heteromorphic self-incompatibility systems in Oleaceae
  • Citing Article
  • May 2024

Current Biology

... Examples include regions such as Northwest China, the Western United States, Central Western Australia, Southern India, Russia, and parts of Africa (Qureshi et al. 2007;Jones et al. 2007;Sisto 2009;Pang and Sun 2014). In these areas, significant conflicts exist between ecological and production water use in oases, forests, and other natural eco-systems (Householder et al. 2024). Therefore, this model can be applied not only to regions facing similar challenges in global rivers but also to water resource allocation for the restoration of natural ecosystems, such as oases. ...

One sixth of Amazonian tree diversity is dependent on river floodplains

Nature Ecology & Evolution

... Large land areas with an abundance of individual trees outside of forests can be mapped in India and elsewhere. Beyond forests alone, these poorly documented and underrepresented landscapes (Mugabowindekwe et al 2024) can also be introduced into policies for climate change mitigation, using agroforestry, small scale plantations and other Nature-based Solutions (NbS) (Terasaki Hart et al 2023). This analysis also demonstrates the potential of mapping and measuring the carbon stocks of trees outside of forests, which could be important for generating new types of carbon removals are not part of national forest inventories (Chapman et al 2020). ...

Trees on smallholder farms and forest restoration are critical for Rwanda to achieve net zero emissions
Communications Earth & Environment

... Multiple studies have analysed genomic mosaicism within individual plants and discussed various aspects of somatic mutations like mutation rates, allelic frequencies, genome-wide distribution, and distribution across branches [14][15][16][17][18][19][20][21][22]. However, most analyses were limited to bulked samples where cells from all layers were sequenced and analysed together. ...

Low-frequency somatic mutations are heritable in tropical trees Dicorynia guianensis and Sextonia rubra

Proceedings of the National Academy of Sciences

... ref. 45). However, quantitative tests of the biogeographical pattern of Amazonian tree communities are scarce and based on incomplete presence/absence data 44,48 or on genus-level identifications and very coarse spatial resolution 29 ; but see Luize et al. 49 , unveiling the role of dispersal and phylogenetic niche conservatism on phylogenetic compositional changes over Amazonia. ...

Geography and ecology shape the phylogenetic composition of Amazonian tree communities

Journal of Biogeography

... Beyond global forest age distribution changes (Fig. 1b), we identified contrasted local and regional forest age transitions (Fig. 1c, Fig. S3, and (Table S3). This trend is primarily attributed to increasing stand-replacing disturbances and mortality 31,32 , indicating a shift towards younger forest stands and the replacement of old-growth forests. Traditional activities such as slash-and-burn agriculture also contributed to this trend in the Amazon Basin 33 . ...

Central African biomass carbon losses and gains during 2010–2019
  • Citing Article
  • February 2024

One Earth

... However, we did not observe such a strong link between leaf nitrogen content and photosynthesis in the seedlings of our studied species. Nitrogen may not be a limiting factor among the studied seedlings because the seeds came from the HKK plot, which has one of the most fertile soils in the tropics (Medina-Vega et al., 2024). These seeds were germinated in the nursery conditions in the fertile soil to ensure survival and most likely not limited by how much nitrogen they could allocate into the leaf content. ...

Tropical tree ectomycorrhiza are distributed independently of soil nutrients

Nature Ecology & Evolution