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publicSep 2015View details →

Data from: Mapping wood production in European forests

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publicFeb 2018View details →

Data from: Ecosystem-scale impacts of non-timber forest product harvesting: effects on soil nutrients

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publicMay 2024View details →

Data from: Climate interacts with the functional trait structure of tree communities to influence forest productivity

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publicNov 2019View details →

Effect of participation in commercial production of medicinal plants through community-based conservation groups on farm income at Kakamega forest, Kenya

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publicSep 2021View details →

Legacies of historic charcoal production affect the forest flora in a Swedish mining district: survey data

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publicApr 2019View details →

Data from: Effects of stand age, richness and density on productivity in subtropical forests in China

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publicJun 2019View details →

Data from: Global patterns of tree stem growth and stand aboveground wood production in mangrove forests

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publicOct 2018View details →

Data from: Impacts of species richness on productivity in a large-scale subtropical forest experiment

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opencc-by-4.0Jun 2020View details →

Data products for "Constraining the second half of reionization with the Lyman-β forest"

Data products for the paper "Constraining the second half of reionization with the Lyman-beta forest" (https://arxiv.org/abs/1912.05582)

opencc-zeroJan 2021View details →

Data from: Intraspecific variations in leaf traits, productivity, and resource use efficiencies in the dominant species of subalpine evergreen coniferous and deciduous broad-leaved forests along the altitudinal gradient

Many studies have reported intraspecific variations in leaf functional traits, but their contribution to plant performance and ecosystem function are poorly understood. We studied altitudinal gradients of intraspecific variations in leaf traits, productivity, and resource use efficiency in the dominant species of subalpine evergreen coniferous and deciduous broad-leaved forests in Japan. We addressed three hypotheses, which are exclusive to each other. 1) Leaf traits vary along the leaf economics spectrum (LES). Plants that grow at lower and higher altitudes have fast- and slow-return strategies, respectively, which improve productivity or resource use efficiency in the respective habitat. 2) Leaf trait variations are not consistent with the LES, but they contribute to improving productivity or resource use efficiency in the respective habitat. 3) Leaf trait variations do not contribute to improving productivity or resource use efficiency at higher altitudes. On the studied mountain range, Fagus crenata, a deciduous broad-leaved tree, and Abies mariesii, an evergreen conifer, are the dominant species at lower and higher altitudes, respectively. In F. crenata, leaf mass per area (LMA) and nitrogen concentrations were higher at higher altitudes. The net assimilation rate and light use efficiency during the growing season were greater at higher altitudes, which compensated for the shorter growing season in terms of annual productivity. In A. mariesii, the LMA was lower and the leaf life span was unchanged at higher altitudes. Productivity and resource use efficiency decreased with altitude. We conclude that F. crenata improves its productivity and resource use efficiency at higher altitudes by altering its leaf functional traits (Hypothesis 2), whereas alterations to leaf traits in A. mariesii are not associated with any improvement at higher altitudes (Hypothesis 3), which may result from the negative impact of environmental stress. Hence, the ecological significance of altitude to leaf trait variations depends on species and environment.

opencc-zeroDec 2015View details →

Data from: Tree genetics strongly affect forest productivity, but intraspecific diversity-productivity relationships do not

Numerous studies have demonstrated biodiversity–productivity relationships in plant communities, and analogous genetic diversity–productivity studies using genotype mixtures of single species may show similar patterns. Alternatively, competing individuals among genotypes within a species are less likely to exhibit resource-use complementarity, even when they exhibit large differences in their effects on ecosystem function. In this study, we test the impact of genotype diversity and genetic identity on ecosystem function using an ecosystem-scale common garden experiment. Distinct tree genotypes were collected across the entire natural range of the riparian tree Populus fremontii in the USA, and grown in 1–16 genotype combination forest stands. Due to the warm climate and irrigation of the planting location along the Colorado River (AZ, USA), mature forest physiognomy with trees up to 19 m tall was achieved in just five years. Several key patterns emerged: (i) genotype richness did not predict forest productivity, suggesting a lack of net biodiversity effects; (ii) we found differences among genotype monoculture stands comparable to differences in average productivity across all forest biomes on Earth; (iii) productivity was predicted based on genetic marker similarity in trees; (iv) genetic-based differences in leaf phenology (early leaf-on and late leaf-fall timing) were correlated with >80% of the variation in tree and forest productivity irrespective of home-site conditions. Large differences in productivity among genotypes can result in dramatic differences in forest productivity without resulting in diversity–productivity relationships that are present in species-scale biodiversity studies.

opencc-zeroDec 2018View details →

Data from: Tree species diversity promotes litterfall productivity through crown complementarity in subtropical forests

1. The role of niche complementarity for driving the positive biodiversity-ecosystem productivity relationship has been widely recognized, but there is scant evidence regarding the role of tree canopy structure on this relationship. Litterfall productivity is proportional to forest net primary productivity in natural forests, and we hypothesized that litterfall productivity would increase with tree species diversity via increased tree crown complementarity. 2. We investigated annual litterfall productivity, species diversity, tree crown architecture, soil moisture content, soil carbon content, and stand age across 28 subtropical forest plots in eastern Zhejiang province, China. Simple linear regression was used to examine bivariate relationships among rarified species richness, crown complementarity, total crown volume, soil moisture content, soil carbon content, stand age, and litterfall productivity. Structural equation modeling was employed to quantify the direct and indirect effects of species richness on litterfall productivity through tree crown complementarity. 3. Litterfall productivity increased with rarefied species richness via increasing crown complementarity rather than total crown volume. Species richness, crown complementarity, and litterfall productivity increased with soil moisture content, while crown complementarity and litterfall productivity increased with soil carbon content. Neither species richness nor crown complementarity increased with stand age, even though litterfall productivity increased with stand age. 4. Synthesis. Our study provides evidence for a strong role of tree crown assembly in shaping ecosystem function in complex natural forests. Our findings suggest that crown spatial complementarity among trees operates mechanistically to drive the positive tree species diversity-litterfall productivity relationship in subtropical forests. We argue that community and/or ecosystem ecology would benefit from more attention to crown variability among coexisting tree species.

restrictedcc-by-4.0Dec 2019View details →

Forest production efficiency increases with growth temperature - dataset

The present dataset belongs the manuscript "Forest production efficiency increases with growth temperature" published in Nature Communications: Collalti, A., Ibrom, A., Stockmarr, A. et al. Forest production efficiency increases with growth temperature. Nat Commun 11, 5322 (2020). https://doi.org/10.1038/s41467-020-19187-w    The data are freely available upon request to Alessio Collalti: alessio.collalti@cnr.it Alessio Collalti

opencc-by-4.0Feb 2024View details →

TimberTracer: A Comprehensive Framework for the Evaluation of Carbon Sequestration by Forest Management and Substitution of Harvested Wood Products.

Background Harvested wood products (HWPs) have a pivotal role in climate change mitigation, a recognition solidified in many Nationally Determined Contributions (NDCs) under the Paris Agreement. Integrating HWPs' greenhouse gas (GHG) emissions and removals into accounting requirements relies on typical decision-oriented tools known as wood product models (WPMs). The study introduces the 'TimberTracer' (TT) framework, designed to simulate HWP carbon stock, substitution effects, and emissions from wood decay and bioenergy.   Results Coupled with the 3D-CMCC-FEM forest growth model, TimberTracer was applied to Laricio Pine (Pinus nigra subsp. laricio) in Italy's Bonis watershed, evaluating three forest management practices (clearcut, selective thinning, and shelterwood) and four wood-use scenarios (business as usual, increased recycling rate, extended average lifespan, and a simultaneous increase in both the recycling rate and the average lifespan) over a 140-year planning horizon, to assess the overall carbon balance of HWPs. Furthermore, this study evaluates the consequences of disregarding landfill methane emissions and relying on static substitution factors, assessing their impact on the mitigation potential of various options. This investigation, covering HWPs stock, carbon (C) emissions, and the substitution effect, revealed that selective thinning emerged as the optimal forest management scenario. Additionally, the simultaneous increase in both the recycling rate and the half-life time proved to be the optimal wood-use scenario. Finally, the analysis shows that failing to account for landfill methane emissions and the use of dynamic substitution can significantly overestimate the mitigation potential of various forest management and wood-use options, which underscores the critical importance of a comprehensive accounting in climate mitigation strategies involving HWPs. Conclusion Our study highlights the critical role of harvested wood products (HWPs) in climate change mitigation, as endorsed by multiple Nationally Determined Contributions (NDCs) under the Paris Agreement. Utilizing the 'TimberTracer' framework coupled with the 3D-CMCC-FEM forest growth model, we identified selective thinning as the optimal forest management practice. Additionally, enhancing recycling rates and extending product lifespans effectively bolstered the carbon balance. Moreover, this study emphasizes the necessity of accounting for landfill methane emissions and dynamic product substitution, as failing to do so may significantly overestimate the mitigation potential of implemented projects. These findings offer actionable insights to optimize forest management strategies and advance climate change mitigation efforts.

opencc-zeroApr 2022View details →

Productivity of riparian Populus forests: satellite assessment along a prairie river with an environmental flow regime

In semi-arid regions, the growth and survival of cottonwoods (riparian Populus species) depend on river water supplementing the limited precipitation. Indicators of growth and productivity are needed to assess how altered streamflow regimes on regulated rivers impact cottonwood trees and the riparian forest ecosystems they support. Satellite imagery from the Landsat program was used to make historical assessments of ecosystem productivity in a riparian cottonwood forest along a regulated prairie river in southern Alberta, Canada from 1984 to 2020, with an environmental flow regime that increased the minimum flows implemented in 1993. A version of the near-infrared reflectance of vegetation scaled with incoming sunlight (NIRvP) was calculated from Landsat images to provide a proxy for primary production. NIRvP was validated against gross primary production measurements from eddy covariance and cottonwood basal area increment measurements from tree ring analyses. Streamflow and weather data were used to assess what environmental conditions drive year-to-year variations in NIRvP.

opencc-by-4.0Aug 2024View details →

A global gross primary productivity dataset of sunlit and shaded leaves via combining two-leaf light use efficiency model with random forest from 2002 to 2020

The TL-CRF model generated a global 0.05´0.05° product for eight-day gross primary productivity (GPP) of sunlit and shaded canopies from 2002 to 2020 by embedding the random forest (RF) submodule into the two-leaf light use efficiency (TL-LUE) model while considering the seasonal differences in the clumping index. The RF technique was used to integrate various environmental stress factors including meteorological, hydrological, soil properties, and elevation, thereby improving the overall scale of the complex environmental conditions to the maximum LUE. Eight-day GPP was then aggregated into monthly, seasonal, and annual GPP. This novel GPP product could support further research on spatial and temporal patterns of the carbon cycle and its association with climate change.

opencc-zeroDec 2016View details →

Data from: Estimation of aboveground net primary productivity in secondary tropical dry forests using the Carnegie–Ames–Stanford approach (CASA) model

Although tropical dry forests (TDFs) cover roughly 42% of all tropical ecosystems, extensive deforestation and habitat fragmentation pose important limitations for their conservation and restoration worldwide. In order to develop conservation policies for this endangered ecosystem, it is necessary to quantify their provision of ecosystems services such as carbon sequestration and primary production. In this paper we explore the potential of the Carnegie–Ames–Stanford approach (CASA) for estimating aboveground net primary productivity (ANPP) in a secondary TDF located at the Santa Rosa National Park (SRNP), Costa Rica. We calculated ANPP using the CASA model (ANPPCASA) in three successional stages (early, intermediate, and late). Each stage has a stand age of 21 years, 32 years, and 50+ years, respectively, estimated as the age since land abandonment. Our results showed that the ANPPCASA for early, intermediate, and late successional stages were 3.22 Mg C ha−1 yr−1, 8.90 Mg C ha−1 yr−1, and 7.59 Mg C ha−1 yr−1, respectively, which are comparable with rates of carbon uptake in other TDFs. Our results indicate that key variables that influence ANPP in our dry forest site were stand age and precipitation seasonality. Incident photosynthetically active radiation and temperature were not dominant in the ANPPCASA. The results of this study highlight the potential of the use of remote sensing techniques and the importance of incorporating successional stage in accurate regional TDF ANPP estimation.

publicApr 2022View details →

Productivity of riparian Populus forests: satellite assessment along a prairie river with an environmental flow regime

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publicAug 2017View details →

Data from: Tree genetics strongly affect forest productivity, but intraspecific diversity-productivity relationships do not

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