October 2024
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32 Reads
Botany Letters
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October 2024
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32 Reads
Botany Letters
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.
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.
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.
October 2024
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546 Reads
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.
October 2024
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11 Reads
Comptes Rendus Biologies
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.
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.
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.
July 2024
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255 Reads
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1 Citation
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... 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 . ...
October 2024
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). ...
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. ...
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]. ...
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. ...
March 2024
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). ...
March 2024
... 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. ...
February 2024
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. ...
February 2024
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 . ...
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. ...
January 2024
Nature Ecology & Evolution