SwePub - search: WFRF:(Pugh Thomas A.M.)

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1.	Wayman, Joseph P., et al. (author) Assessing taxonomic and functional change in British breeding bird assemblages over time 2022 In: Global Ecology and Biogeography. - : Wiley. - 1466-822X .- 1466-8238. ; 31:5, s. 925-939 Journal article (peer-reviewed)abstract Aim: The aim was to identify the primary drivers of compositional change in breeding bird assemblages over a 40-year period. Location: Britain. Time period: From 1970 to 2010. Major taxa studied: Birds. Methods: Using morphological trait measurements and a dataset of presence–absence data for British breeding birds surveyed in 10 km × 10 km hectads during two time periods, we calculated temporal taxonomic and functional beta diversity for each hectad alongside the change in species richness, mean nearest taxon distance (MNTD) and mean pairwise distance (MPD). We also estimated potential drivers of beta diversity, including climatic and land-use and land-cover (LULC) change variables, elevation and assemblage species richness in 1970 (1970rich). We used random forest regressions to test which variables best explained compositional change in the assemblages. We also assessed spatial taxonomic and functional change by analysing multiple-site beta diversity and pairwise dissimilarities between time periods. Results: Initial (1970) species richness was the most important predictor (highest importance score) across all models, with areas characterized by higher initial richness experiencing less assemblage change overall. The coordinates included to capture spatial autocorrelation in the data were also important predictors of change. Most climate and LULC variables had relatively low explanatory power; elevation and average temperature were the most influential. All metrics increased slightly with increasing elevation, except for species richness change and MPD, which decreased. Main conclusions: The composition of British breeding bird assemblages changed substantially between 1970 and 2010. Spatial heterogeneity increased, both taxonomically and functionally. We show evidence that hectads with larger assemblages have been buffered from temporal diversity change and that those at higher elevations changed more in composition than those at lower elevations. Overall, coarse-resolution climate and LULC explained only small to moderate amounts of variation, suggesting that stochastic assembly change or finer-scale drivers might be drivers of temporal changes in assemblage composition.
2.	Wayman, Joseph P., et al. (author) Identifying the Drivers of Spatial Taxonomic and Functional Beta-Diversity of British Breeding Birds 2021 In: Frontiers in Ecology and Evolution. - : Frontiers Media SA. - 2296-701X. ; 9 Journal article (peer-reviewed)abstract Spatial variation in community composition may be driven by a variety of processes, including environmental filtering and dispersal limitation. While work has been conducted on the relative importance of these processes on various taxa and at varying resolutions, tests using high-resolution empirical data across large spatial extents are sparse. Here, we use a dataset on the presence/absence of breeding bird species collected at the 10 km × 10 km scale across the whole of Britain. Pairwise spatial taxonomic and functional beta diversity, and the constituent components of each (turnover and nestedness/richness loss or gain), were calculated alongside two other measures of functional change (mean nearest taxon distance and mean pairwise distance). Predictor variables included climate and land use measures, as well as a measure of elevation, human influence, and habitat diversity. Generalized dissimilarity modeling was used to analyze the contribution of each predictor variable to variation in the different beta diversity metrics. Overall, we found that there was a moderate and unique proportion of the variance explained by geographical distance per se, which could highlight the role of dispersal limitation in community dissimilarity. Climate, land use, and human influence all also contributed to the observed patterns, but a large proportion of the explained variance in beta diversity was shared between these variables and geographical distance. However, both taxonomic nestedness and functional nestedness were uniquely predicted by a combination of land use, human influence, elevation, and climate variables, indicating a key role for environmental filtering. These findings may have important conservation implications in the face of a warming climate and future land use change.
3.	Asuk, Sijeh A., et al. (author) Impact of human foraging on tree diversity, composition, and abundance in a tropical rainforest 2023 In: Biotropica. - : Wiley. - 0006-3606 .- 1744-7429. ; 55:1, s. 232-245 Journal article (peer-reviewed)abstract Tropical forest tree communities are structured by a range of large-scale drivers including elevation, certain high-impact anthropogenic activities (e.g., deforestation), and fires. However, low-impact human activities such as foraging may also be subtly but notably altering the composition of tropical forest tree communities. The study assessed the (i) differences in species diversity, patterns of relative abundance, and pairwise beta diversity between trees with edible and inedible fruits and seeds along an elevation gradient, and (ii) impact of human foraging on the forest tree communities in Oban Division of Cross River National Park, Nigeria. Fifteen permanent 40 by 40 m plots were established along an elevational gradient (120–460 m above mean sea level). All trees of 0.1 m diameter at breast height (dbh) and above were measured, identified, and, with the aid of structured questionnaires, classified into those with edible and inedible fruits/seeds. A total of 35 edible species with density of 128 stems/hectare and basal area of 11.99 m2/hectare, and 109 inedible species with density of 364 stems/hectare and basal area of 22.42 m2/hectare were sampled. However, the evenness of edible and inedible species was similar at pooled and plot levels. For inedible species, there was a positive relationship between pairwise beta diversity and elevation, and this was driven mainly by turnover. In contrast, edible species exhibited a non-significant trend between elevation and beta diversity. Thus, the study showed that human foraging of edible fruits may have subtly influenced patterns of species diversity and community structure in this tropical forest.
4.	Papastefanou, Phillip, et al. (author) A Dynamic Model for Strategies and Dynamics of Plant Water-Potential Regulation Under Drought Conditions 2020 In: Frontiers in Plant Science. - : Frontiers Media SA. - 1664-462X. ; 11 Journal article (peer-reviewed)abstract Vegetation responds to drought through a complex interplay of plant hydraulic mechanisms, posing challenges for model development and parameterization. We present a mathematical model that describes the dynamics of leaf water-potential over time while considering different strategies by which plant species regulate their water-potentials. The model has two parameters: the parameter λ describing the adjustment of the leaf water potential to changes in soil water potential, and the parameter Δψww describing the typical ‘well-watered’ leaf water potentials at non-stressed (near-zero) levels of soil water potential. Our model was tested and calibrated on 110 time-series datasets containing the leaf- and soil water potentials of 66 species under drought and non-drought conditions. Our model successfully reproduces the measured leaf water potentials over time based on three different regulation strategies under drought. We found that three parameter sets derived from the measurement data reproduced the dynamics of 53% of an drought dataset, and 52% of a control dataset [root mean square error (RMSE) < 0.5 MPa)]. We conclude that, instead of quantifying water-potential-regulation of different plant species by complex modeling approaches, a small set of parameters may be sufficient to describe the water potential regulation behavior for large-scale modeling. Thus, our approach paves the way for a parsimonious representation of the full spectrum of plant hydraulic responses to drought in dynamic vegetation models.
5.	Pugh, Thomas A.M., et al. (author) Understanding the uncertainty in global forest carbon turnover 2020 In: Biogeosciences. - : Copernicus GmbH. - 1726-4170 .- 1726-4189. ; 17:15, s. 3961-3989 Journal article (peer-reviewed)abstract The length of time that carbon remains in forest biomass is one of the largest uncertainties in the global carbon cycle, with both recent historical baselines and future responses to environmental change poorly constrained by available observations. In the absence of large-scale observations, models used for global assessments tend to fall back on simplified assumptions of the turnover rates of biomass and soil carbon pools. In this study, the biomass carbon turnover times calculated by an ensemble of contemporary terrestrial biosphere models (TBMs) are analysed to assess their current capability to accurately estimate biomass carbon turnover times in forests and how these times are anticipated to change in the future. Modelled baseline 1985-2014 global average forest biomass turnover times vary from 12.2 to 23.5 years between TBMs. TBM differences in phenological processes, which control allocation to, and turnover rate of, leaves and fine roots, are as important as tree mortality with regard to explaining the variation in total turnover among TBMs. The different governing mechanisms exhibited by each TBM result in a wide range of plausible turnover time projections for the end of the century. Based on these simulations, it is not possible to draw robust conclusions regarding likely future changes in turnover time, and thus biomass change, for different regions. Both spatial and temporal uncertainty in turnover time are strongly linked to model assumptions concerning plant functional type distributions and their controls. Thirteen model-based hypotheses of controls on turnover time are identified, along with recommendations for pragmatic steps to test them using existing and novel observations. Efforts to resolve uncertainty in turnover time, and thus its impacts on the future evolution of biomass carbon stocks across the world's forests, will need to address both mortality and establishment components of forest demography, as well as allocation of carbon to woody versus non-woody biomass growth.
6.	Wartenburger, Richard, et al. (author) Evapotranspiration simulations in ISIMIP2a-Evaluation of spatio-temporal characteristics with a comprehensive ensemble of independent datasets 2018 In: Environmental Research Letters. - : IOP Publishing. - 1748-9326. ; 13:7 Journal article (peer-reviewed)abstract Actual land evapotranspiration (ET) is a key component of the global hydrological cycle and an essential variable determining the evolution of hydrological extreme events under different climate change scenarios. However, recently available ET products show persistent uncertainties that are impeding a precise attribution of human-induced climate change. Here, we aim at comparing a range of independent global monthly land ET estimates with historical model simulations from the global water, agriculture, and biomes sectors participating in the second phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2a). Among the independent estimates, we use the EartH2Observe Tier-1 dataset (E2O), two commonly used reanalyses, a pre-compiled ensemble product (LandFlux-EVAL), and an updated collection of recently published datasets that algorithmically derive ET from observations or observations-based estimates (diagnostic datasets). A cluster analysis is applied in order to identify spatio-temporal differences among all datasets and to thus identify factors that dominate overall uncertainties. The clustering is controlled by several factors including the model choice, the meteorological forcing used to drive the assessed models, the data category (models participating in the different sectors of ISIMIP2a, E2O models, diagnostic estimates, reanalysis-based estimates or composite products), the ET scheme, and the number of soil layers in the models. By using these factors to explain spatial and spatio-temporal variabilities in ET, we find that the model choice mostly dominates (24%-40% of variance explained), except for spatio-temporal patterns of total ET, where the forcing explains the largest fraction of the variance (29%). The most dominant clusters of datasets are further compared with individual diagnostic and reanalysis-based estimates to assess their representation of selected heat waves and droughts in the Great Plains, Central Europe and western Russia. Although most of the ET estimates capture these extreme events, the generally large spread among the entire ensemble indicates substantial uncertainties.
7.	Anderegg, William R L, et al. (author) A climate risk analysis of Earth's forests in the 21st century 2022 In: Science (New York, N.Y.). - : American Association for the Advancement of Science (AAAS). - 1095-9203 .- 0036-8075. ; 377:6610, s. 1099-1103 Journal article (peer-reviewed)abstract Earth's forests harbor extensive biodiversity and are currently a major carbon sink. Forest conservation and restoration can help mitigate climate change; however, climate change could fundamentally imperil forests in many regions and undermine their ability to provide such mitigation. The extent of climate risks facing forests has not been synthesized globally nor have different approaches to quantifying forest climate risks been systematically compared. We combine outputs from multiple mechanistic and empirical approaches to modeling carbon, biodiversity, and disturbance risks to conduct a synthetic climate risk analysis for Earth's forests in the 21st century. Despite large uncertainty in most regions we find that some forests are consistently at higher risk, including southern boreal forests and those in western North America and parts of the Amazon.
8.	Araza, Arnan, et al. (author) Past decade above-ground biomass change comparisons from four multi-temporal global maps 2023 In: International Journal of Applied Earth Observation and Geoinformation. - 1569-8432. ; 118 Journal article (peer-reviewed)abstract Above-ground biomass (AGB) is considered an essential climate variable that underpins our knowledge and information about the role of forests in mitigating climate change. The availability of satellite-based AGB and AGB change (ΔAGB) products has increased in recent years. Here we assessed the past decade net ΔAGB derived from four recent global multi-date AGB maps: ESA-CCI maps, WRI-Flux model, JPL time series, and SMOS-LVOD time series. Our assessments explore and use different reference data sources with biomass re-measurements within the past decade. The reference data comprise National Forest Inventory (NFI) plot data, local ΔAGB maps from airborne LiDAR, and selected Forest Resource Assessment country data from countries with well-developed monitoring capacities. Map to reference data comparisons were performed at levels ranging from 100 m to 25 km spatial scale. The comparisons revealed that LiDAR data compared most reasonably with the maps, while the comparisons using NFI only showed some agreements at aggregation levels <10 km. Regardless of the aggregation level, AGB losses and gains according to the map comparisons were consistently smaller than the reference data. Map-map comparisons at 25 km highlighted that the maps consistently captured AGB losses in known deforestation hotspots. The comparisons also identified several carbon sink regions consistently detected by all maps. However, disagreement between maps is still large in key forest regions such as the Amazon basin. The overall ΔAGB map cross-correlation between maps varied in the range 0.11–0.29 (r). Reported ΔAGB magnitudes were largest in the high-resolution datasets including the CCI map differencing (stock change) and Flux model (gain-loss) methods, while they were smallest according to the coarser-resolution LVOD and JPL time series products, especially for AGB gains. Our results suggest that ΔAGB assessed from current maps can be biased and any use of the estimates should take that into account. Currently, ΔAGB reference data are sparse especially in the tropics but that deficit can be alleviated by upcoming LiDAR data networks in the context of Supersites and GEO-Trees.
9.	Camargo-Alvarez, Hector, et al. (author) Modelling crop yield and harvest index : the role of carbon assimilation and allocation parameters 2023 In: Modeling Earth Systems and Environment. - : Springer Science and Business Media LLC. - 2363-6203 .- 2363-6211. ; 9:2, s. 2617-2635 Journal article (peer-reviewed)abstract Crop yield improvement during the last decades has relied on increasing the ratio of the economic organ to the total aboveground biomass, known as the harvest index (HI). In most crop models, HI is set as a parameter; this empirical approach does not consider that HI not only depends on plant genotype, but is also affected by the environment. An alternative is to simulate allocation mechanistically, as in the LPJ-GUESS crop model, which simulates HI based on daily growing conditions and the crop development stage. Simulated HI is critical for agricultural research due to its economic importance, but it also can validate the robust representation of production processes. However, there is a challenge to constrain parameter values globally for the allocation processes. Therefore, this paper aims to evaluate the sensitivity of yield and HI of wheat and maize simulated with LPJ-GUESS to eight production allocation-related parameters and identify the most suitable parameter values for global simulations. The nitrogen demand reduction after anthesis, the minimum leaf carbon to nitrogen ratio (C:N) and the range of leaf C:N strongly affected carbon assimilation and yield, while the retranslocation of labile stem carbon to grains and the retranslocation rate of nitrogen and carbon from vegetative organs to grains after anthesis mainly influenced HI. A global database of observed HI for both crops was compiled for reference to constrain simulations before calibrating parameters for yield against reference data. Two high- and low-yielding maize cultivars emerged from the calibration, whilst spring and winter cultivars were found appropriate for wheat. The calibrated version of LPJ-GUESS improved the simulation of yield and HI at the global scale for both crops, providing a basis for future studies exploring crop production under different climate and management scenarios.
10.	Deryng, Delphine, et al. (author) Regional disparities in the beneficial effects of rising CO2 concentrations on crop water productivity 2016 In: Nature Climate Change. - : Springer Science and Business Media LLC. - 1758-678X .- 1758-6798. ; 6:8, s. 786-790 Journal article (peer-reviewed)abstract Rising atmospheric CO2 concentrations ([CO2 ]) are expected to enhance photosynthesis and reduce crop water use. However, there is high uncertainty about the global implications of these effects for future crop production and agricultural water requirements under climate change. Here we combine results from networks of field experiments and global crop models to present a spatially explicit global perspective on crop water productivity (CWP, the ratio of crop yield to evapotranspiration) for wheat, maize, rice and soybean under elevated [CO2 ] and associated climate change projected for a high-end greenhouse gas emissions scenario. We find CO2 effects increase global CWP by 10[0;47]%-27[7;37]% (median[interquartile range] across the model ensemble) by the 2080s depending on crop types, with particularly large increases in arid regions (by up to 48[25;56]% for rainfed wheat). If realized in the fields, the effects of elevated [CO2 ] could considerably mitigate global yield losses whilst reducing agricultural consumptive water use (4-17%). We identify regional disparities driven by differences in growing conditions across agro-ecosystems that could have implications for increasing food production without compromising water security. Finally, our results demonstrate the need to expand field experiments and encourage greater consistency in modelling the effects of rising [CO2 ] across crop and hydrological modelling communities.
11.	Folberth, Christian, et al. (author) Parameterization-induced uncertainties and impacts of crop management harmonization in a global gridded crop model ensemble 2019 In: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 14:9 Journal article (peer-reviewed)abstract Global gridded crop models (GGCMs) combine agronomic or plant growth models with gridded spatial input data to estimate spatially explicit crop yields and agricultural externalities at the global scale. Differences in GGCM outputs arise from the use of different biophysical models, setups, and input data. GGCM ensembles are frequently employed to bracket uncertainties in impact studies without investigating the causes of divergence in outputs. This study explores differences in maize yield estimates from five GGCMs based on the public domain field-scale model Environmental Policy Integrated Climate (EPIC) that participate in the AgMIP Global Gridded Crop Model Intercomparison initiative. Albeit using the same crop model, the GGCMs differ in model version, input data, management assumptions, parameterization, and selection of subroutines affecting crop yield estimates via cultivar distributions, soil attributes, and hydrology among others. The analyses reveal inter-annual yield variability and absolute yield levels in the EPIC-based GGCMs to be highly sensitive to soil parameterization and crop management. All GGCMs show an intermediate performance in reproducing reported yields with a higher skill if a static soil profile is assumed or sufficient plant nutrients are supplied. An in-depth comparison of setup domains for two EPIC-based GGCMs shows that GGCM performance and plant stress responses depend substantially on soil parameters and soil process parameterization, i.e. hydrology and nutrient turnover, indicating that these often neglected domains deserve more scrutiny. For agricultural impact assessments, employing a GGCM ensemble with its widely varying assumptions in setups appears the best solution for coping with uncertainties from lack of comprehensive global data on crop management, cultivar distributions and coefficients for agro-environmental processes. However, the underlying assumptions require systematic specifications to cover representative agricultural systems and environmental conditions. Furthermore, the interlinkage of parameter sensitivity from various domains such as soil parameters, nutrient turnover coefficients, and cultivar specifications highlights that global sensitivity analyses and calibration need to be performed in an integrated manner to avoid bias resulting from disregarded core model domains. Finally, relating evaluations of the EPIC-based GGCMs to a wider ensemble based on individual core models shows that structural differences outweigh in general differences in configurations of GGCMs based on the same model, and that the ensemble mean gains higher skill from the inclusion of structurally different GGCMs. Although the members of the wider ensemble herein do not consider crop-soil-management interactions, their sensitivity to nutrient supply indicates that findings for the EPIC-based sub-ensemble will likely become relevant for other GGCMs with the progressing inclusion of such processes.
12.	Franke, James A, et al. (author) Agricultural breadbaskets shift poleward given adaptive farmer behavior under climate change 2022 In: Global Change Biology. - : Wiley. - 1354-1013 .- 1365-2486. ; 28:1, s. 167-181 Journal article (peer-reviewed)abstract Modern food production is spatially concentrated in global "breadbaskets". A major unresolved question is whether these peak production regions will shift poleward as the climate warms, allowing some recovery of potential climaterelated losses. While agricultural impacts studies to date have focused on currently cultivated land, the Global Gridded Crop Model Intercomparison Project (GGCMI) Phase 2 experiment allows us to assess changes in both yields and the location of peak productivity regions under warming. We examine crop responses under projected end-of-century warming using 7 process-based models simulating 5 major crops (maize, rice, soybeans, and spring and winter wheat) with a variety of adaptation strategies. We find that in no-adaptation cases, when planting date and cultivar choices are held fixed, regions of peak production remain stationary and yield losses can be severe, since growing seasons contract strongly with warming. When adaptations in management practices are allowed (cultivars that retain growing season length under warming and modified planting dates), peak productivity zones shift poleward and yield losses are largely recovered. While most growing-zone shifts are ultimately limited by geography, breadbaskets studied here move poleward over 600 km on average by end of the century under RCP8.5. These results suggest that agricultural impacts assessments can be strongly biased if restricted in spatial area or in the scope of adaptive behavior considered. Accurate evaluation of food security under climate change requires global modeling and careful treatment of adaptation strategies.
13.	Franke, James A., et al. (author) The GGCMI Phase 2 emulators : Global gridded crop model responses to changes in CO2, temperature, water, and nitrogen (version 1.0) 2020 In: Geoscientific Model Development. - : Copernicus GmbH. - 1991-959X .- 1991-9603. ; 13:9, s. 3995-4018 Journal article (peer-reviewed)abstract Statistical emulation allows combining advantageous features of statistical and process-based crop models for understanding the effects of future climate changes on crop yields. We describe here the development of emulators for nine process-based crop models and five crops using output from the Global Gridded Model Intercomparison Project (GGCMI) Phase 2. The GGCMI Phase 2 experiment is designed with the explicit goal of producing a structured training dataset for emulator development that samples across four dimensions relevant to crop yields: Atmospheric carbon dioxide (CO2) concentrations, temperature, water supply, and nitrogen inputs (CTWN). Simulations are run under two different adaptation assumptions: That growing seasons shorten in warmer climates, and that cultivar choice allows growing seasons to remain fixed. The dataset allows emulating the climatological-mean yield response of all models with a simple polynomial in mean growing-season values. Climatological-mean yields are a central metric in climate change impact analysis; we show here that they can be captured without relying on interannual variations. In general, emulation errors are negligible relative to differences across crop models or even across climate model scenarios; errors become significant only in some marginal lands where crops are not currently grown. We demonstrate that the resulting GGCMI emulators can reproduce yields under realistic future climate simulations, even though the GGCMI Phase 2 dataset is constructed with uniform CTWN offsets, suggesting that the effects of changes in temperature and precipitation distributions are small relative to those of changing means. The resulting emulators therefore capture relevant crop model responses in a lightweight, computationally tractable form, providing a tool that can facilitate model comparison, diagnosis of interacting factors affecting yields, and integrated assessment of climate impacts.
14.	Franke, James A., et al. (author) The GGCMI Phase 2 experiment : Global gridded crop model simulations under uniform changes in CO2, temperature, water, and nitrogen levels (protocol version 1.0) 2020 In: Geoscientific Model Development. - : Copernicus GmbH. - 1991-959X .- 1991-9603. ; 13:5, s. 2315-2336 Journal article (peer-reviewed)abstract Concerns about food security under climate change motivate efforts to better understand future changes in crop yields. Process-based crop models, which represent plant physiological and soil processes, are necessary tools for this purpose since they allow representing future climate and management conditions not sampled in the historical record and new locations to which cultivation may shift. However, process-based crop models differ in many critical details, and their responses to different interacting factors remain only poorly understood. The Global Gridded Crop Model Intercomparison (GGCMI) Phase 2 experiment, an activity of the Agricultural Model Intercomparison and Improvement Project (AgMIP), is designed to provide a systematic parameter sweep focused on climate change factors and their interaction with overall soil fertility, to allow both evaluating model behavior and emulating model responses in impact assessment tools. In this paper we describe the GGCMI Phase 2 experimental protocol and its simulation data archive. A total of 12 crop models simulate five crops with systematic uniform perturbations of historical climate, varying CO2, temperature, water supply, and applied nitrogen ("CTWN") for rainfed and irrigated agriculture, and a second set of simulations represents a type of adaptation by allowing the adjustment of growing season length. We present some crop yield results to illustrate general characteristics of the simulations and potential uses of the GGCMI Phase 2 archive. For example, in cases without adaptation, modeled yields show robust decreases to warmer temperatures in almost all regions, with a nonlinear dependence that means yields in warmer baseline locations have greater temperature sensitivity. Inter-model uncertainty is qualitatively similar across all the four input dimensions but is largest in high-latitude regions where crops may be grown in the future.
15.	Gärtner, Antje, et al. (author) Temperature and Tree Size Explain the Mean Time to Fall of Dead Standing Trees across Large Scales 2023 In: Forests. - : MDPI. - 1999-4907. ; 14:5 Journal article (peer-reviewed)abstract AbstractDead standing trees (DSTs) generally decompose slower than wood in contact with the forest floor. In many regions, DSTs are being created at an increasing rate due to accelerating tree mortality caused by climate change. Therefore, factors determining DST fall are crucial for predicting dead wood turnover time but remain poorly constrained. Here, we conduct a re-analysis of published DST fall data to provide standardized information on the mean time to fall (MTF) of DSTs across biomes. We used multiple linear regression to test covariates considered important for DST fall, while controlling for mortality and management effects. DSTs of species killed by fire, insects and other causes stood on average for 48, 13 and 19 years, but MTF calculations were sensitive to how tree size was accounted for. Species’ MTFs differed significantly between DSTs killed by fire and other causes, between coniferous and broadleaved plant functional types (PFTs) and between managed and unmanaged sites, but management did not explain MTFs when we distinguished by mortality cause. Mean annual temperature (MAT) negatively affected MTFs, whereas larger tree size or being coniferous caused DSTs to stand longer. The most important explanatory variables were MAT and tree size, with minor contributions of management and plant functional type depending on mortality cause. Our results provide a basis to improve the representation of dead wood decomposition in carbon cycle assessments.
16.	Hartmann, Henrik, et al. (author) Climate Change Risks to Global Forest Health : Emergence of Unexpected Events of Elevated Tree Mortality Worldwide 2022 In: Annual Review of Plant Biology. - : Annual Reviews. - 1543-5008 .- 1545-2123. ; 73, s. 673-702 Research review (peer-reviewed)abstract Recent observations of elevated tree mortality following climate extremes, like heat and drought, raise concerns about climate change risks to global forest health. We currently lack both sufficient data and understanding to identify whether these observations represent a global trend toward increasing tree mortality. Here, we document events of sudden and unexpected elevated tree mortality following heat and drought events in ecosystems that previously were considered tolerant or not at risk of exposure. These events underscore the fact that climate change may affect forests with unexpected force in the future. We use the events as examples to highlight current difficulties and challenges for realistically predicting such tree mortality events and the uncertainties about future forest condition. Advances in remote sensing technology and greater availably of high-resolution data, from both field assessments and satellites, are needed to improve both understanding and prediction of forest responses to future climate change.
17.	Kondo, Masayuki, et al. (author) Are Land-Use Change Emissions in Southeast Asia Decreasing or Increasing? 2022 In: Global Biogeochemical Cycles. - 0886-6236. ; 36:1 Journal article (peer-reviewed)abstract Southeast Asia is a region known for active land-use changes (LUC) over the past 60 years; yet, how trends in net CO2 uptake and release resulting from LUC activities (net LUC flux) have changed through past decades remains uncertain. The level of uncertainty in net LUC flux from process-based models is so high that it cannot be concluded that newer estimates are necessarily more reliable than older ones. Here, we examined net LUC flux estimates of Southeast Asia for the 1980s−2010s from older and newer sets of Dynamic Global Vegetation Model simulations (TRENDY v2 and v7, respectively), and forcing data used for running those simulations, along with two book-keeping estimates (H&N and BLUE). These estimates yielded two contrasting historical LUC transitions, such that TRENDY v2 and H&N showed a transition from increased emissions from the 1980s to 1990s to declining emissions in the 2000s, while TRENDY v7 and BLUE showed the opposite transition. We found that these contrasting transitions originated in the update of LUC forcing data, which reduced the loss of forest area during the 1990s. Further evaluation of remote sensing studies, atmospheric inversions, and the history of forestry and environmental policies in Southeast Asia supported the occurrence of peak emissions in the 1990s and declining thereafter. However, whether LUC emissions continue to decline in Southeast Asia remains uncertain as key processes in recent years, such as conversion of peat forest to oil-palm plantation, are yet to be represented in the forcing data, suggesting a need for further revision.
18.	Kondo, Masayuki, et al. (author) State of science in carbon budget assessments for temperate forests and grasslands 2022 In: Balancing Greenhouse Gas Budgets : Accounting for Natural and Anthropogenic Flows of CO2 and other Trace Gases - Accounting for Natural and Anthropogenic Flows of CO2 and other Trace Gases. - 9780128149522 - 9780128149539 ; , s. 237-270 Book chapter (peer-reviewed)abstract With the abundance of observations and advancement in modeling, temperate regions allow for a comprehensive comparison of the data-driven and process-based methods of carbon budget estimation. This chapter presents a review of the latest methodologies for carbon budget and component flux estimation, and the key components in the temperate carbon budget, such as forest regrowth, and summarizes uncertainties in the current carbon budget of temperate ecosystems that the research community needs to resolve. Lastly, we describe the key progress made in the carbon budget assessment in past decades, and how it should be further advanced to be useful for policy decision-making.
19.	Krause, Andreas, et al. (author) Impacts of land-use history on the recovery of ecosystems after agricultural abandonment 2016 In: Earth System Dynamics. - : Copernicus GmbH. - 2190-4979 .- 2190-4987. ; 7:3, s. 745-766 Journal article (peer-reviewed)abstract Land-use changes have been shown to have large effects on climate and biogeochemical cycles, but so far most studies have focused on the effects of conversion of natural vegetation to croplands and pastures. By contrast, relatively little is known about the long-term influence of past agriculture on vegetation regrowth and carbon sequestration following land abandonment. We used the LPJ-GUESS dynamic vegetation model to study the legacy effects of different land-use histories (in terms of type and duration) across a range of ecosystems. To this end, we performed six idealized simulations for Europe and Africa in which we made a transition from natural vegetation to either pasture or cropland, followed by a transition back to natural vegetation after 20, 60 or 100 years. The simulations identified substantial differences in recovery trajectories of four key variables (vegetation composition, vegetation carbon, soil carbon, net biome productivity) after agricultural cessation. Vegetation carbon and composition typically recovered faster than soil carbon in subtropical, temperate and boreal regions, and vice versa in the tropics. While the effects of different land-use histories on recovery periods of soil carbon stocks often differed by centuries across our simulations, differences in recovery times across simulations were typically small for net biome productivity (a few decades) and modest for vegetation carbon and composition (several decades). Spatially, we found the greatest sensitivity of recovery times to prior land use in boreal forests and subtropical grasslands, where post-agricultural productivity was strongly affected by prior land management. Our results suggest that land-use history is a relevant factor affecting ecosystems long after agricultural cessation, and it should be considered not only when assessing historical or future changes in simulations of the terrestrial carbon cycle but also when establishing long-term monitoring networks and interpreting data derived therefrom, including analysis of a broad range of ecosystem properties or local climate effects related to land cover changes.
20.	Krause, Andreas, et al. (author) Large uncertainty in carbon uptake potential of land-based climate-change mitigation efforts 2018 In: Global Change Biology. - : Wiley. - 1354-1013. ; 24:7, s. 3025-3038 Journal article (peer-reviewed)abstract Most climate mitigation scenarios involve negative emissions, especially those that aim to limit global temperature increase to 2°C or less. However, the carbon uptake potential in land-based climate change mitigation efforts is highly uncertain. Here, we address this uncertainty by using two land-based mitigation scenarios from two land-use models (IMAGE and MAgPIE) as input to four dynamic global vegetation models (DGVMs; LPJ-GUESS, ORCHIDEE, JULES, LPJmL). Each of the four combinations of land-use models and mitigation scenarios aimed for a cumulative carbon uptake of ~130 GtC by the end of the century, achieved either via the cultivation of bioenergy crops combined with carbon capture and storage (BECCS) or avoided deforestation and afforestation (ADAFF). Results suggest large uncertainty in simulated future land demand and carbon uptake rates, depending on the assumptions related to land use and land management in the models. Total cumulative carbon uptake in the DGVMs is highly variable across mitigation scenarios, ranging between 19 and 130 GtC by year 2099. Only one out of the 16 combinations of mitigation scenarios and DGVMs achieves an equivalent or higher carbon uptake than achieved in the land-use models. The large differences in carbon uptake between the DGVMs and their discrepancy against the carbon uptake in IMAGE and MAgPIE are mainly due to different model assumptions regarding bioenergy crop yields and due to the simulation of soil carbon response to land-use change. Differences between land-use models and DGVMs regarding forest biomass and the rate of forest regrowth also have an impact, albeit smaller, on the results. Given the low confidence in simulated carbon uptake for a given land-based mitigation scenario, and that negative emissions simulated by the DGVMs are typically lower than assumed in scenarios consistent with the 2°C target, relying on negative emissions to mitigate climate change is a highly uncertain strategy.
21.	Lee, Heera, et al. (author) Three billion new trees in the EU’s biodiversity strategy : low ambition, but better environmental outcomes? 2023 In: Environmental Research Letters. - : IOP Publishing. - 1748-9318 .- 1748-9326. ; 18:3 Journal article (peer-reviewed)abstract The EU Biodiversity strategy aims to plant 3 billion trees by 2030, in order to improve ecosystem restoration and biodiversity. Here, we compute the land area that would be required to support this number of newly planted trees by taking account of different tree species and planting regimes across the EU member states. We find that 3 billion trees would require a total land area of between 0.81 and 1.37 Mha (avg. 1.02 Mha). The historic forest expansion in the EU since 2010 was 2.44 Mha, meaning that despite 3 billion trees sounding like a large number this target is considerably lower than historic afforestation rates within the EU, i.e. only 40% of the past trend. Abandoned agricultural land is often proposed as providing capacity for afforestation. We estimate agricultural abandoned land areas from the HIstoric Land Dynamics Assessment+ database using two time thresholds (abandonment since 2009 or 2014) to identify potential areas for tree planting. The area of agricultural abandoned land was 2.6 Mha (potentially accommodating 7.2 billion trees) since 2009 and 0.2 Mha (potentially accommodating 741 million trees) since 2014. Our study highlights that sufficient space could be available to meet the 3 billion tree planting target from abandoned land. However, large-scale afforestation beyond abandoned land could have displacement effects elsewhere in the world because of the embodied deforestation in the import of agricultural crops and livestock. This would negate the expected benefits of EU afforestation. Hence, the EU’s relatively low ambition on tree planting may actually be better in terms of avoiding such displacement effects. We suggest that tree planting targets should be set at a level that considers physical ecosystem dynamics as well as socio-economic conditions.
22.	Li, Wei, et al. (author) Land-use and land-cover change carbon emissions between 1901 and 2012 constrained by biomass observations 2017 In: Biogeosciences. - : Copernicus GmbH. - 1726-4170 .- 1726-4189. ; 14:22, s. 5053-5067 Journal article (peer-reviewed)abstract The use of dynamic global vegetation models (DGVMs) to estimate CO2 emissions from land-use and land-cover change (LULCC) offers a new window to account for spatial and temporal details of emissions and for ecosystem processes affected by LULCC. One drawback of LULCC emissions from DGVMs, however, is lack of observation constraint. Here, we propose a new method of using satellite-and inventory-based biomass observations to constrain historical cumulative LULCC emissions (E-LUC(c)) from an ensemble of nine DGVMs based on emerging relationships between simulated vegetation biomass and E-LUC(c). This method is applicable on the global and regional scale. The original DGVM estimates of E-LUC(c) range from 94 to 273 PgC during 1901-2012. After constraining by current biomass observations, we derive a best estimate of 155 +/- 50 PgC (1 sigma Gaussian error). The constrained LULCC emissions are higher than prior DGVM values in tropical regions but significantly lower in North America. Our emergent constraint approach independently verifies the median model estimate by biomass observations, giving support to the use of this estimate in carbon budget assessments. The uncertainty in the constrained Ec LUC is still relatively large because of the uncertainty in the biomass observations, and thus reduced uncertainty in addition to increased accuracy in biomass observations in the future will help improve the constraint. This constraint method can also be applied to evaluate the impact of land-based mitigation activities.
23.	Liu, Daijun, et al. (author) Delayed and altered post-fire recovery pathways of Mediterranean shrubland under 20-year drought manipulation 2022 In: Forest Ecology and Management. - : Elsevier BV. - 0378-1127. ; 506 Journal article (peer-reviewed)abstract Increasing water deficits and severe droughts are expected to alter the dynamics of vegetation post-disturbance recovery by decreasing new recruitment and limiting growth in semi-arid Mediterranean ecosystems in future. However, which vegetation metrics will be shifted and how they respond over time are not clear, and the experimental evidence is still limited. Here we assessed the impacts of a long-term (20 years) experimental drought (−30% rainfall) on the pathways of vegetation metrics related to species richness, community composition and abundance dynamics for an early-successional Mediterranean shrubland. The results indicate that the pathways of vegetation metrics were differently affected by experimental drought. The abundance of Globularia alypum follows pathway 1 (altered mature state). Simpson diversity and abundance of Erica multiflora follow pathway 2 (delayed succession) while species richness, community abundance and shrub abundance follow pathway 3 (alternative stable state). There were no significances for the resilience to extremely dry years (the ratio between the performance after and before severe events) between control and drought treatment for all vegetation metric. But, their resilience for the metrics (except Simpson diversity) to extremely dry years in 2016–17 were significantly lower than that of 2001 and of 2006–07, possibly caused by the severe water deficits in 2016–17 at mature successional stage. Principal component analysis (PCA) shows that the first two principal components explained 72.3 % of the variance in vegetation metrics. The first axis was mainly related to the changes in community abundance, shrub abundance and species richness while the second axis was related to Simpson diversity and abundance of G. alypum and E. multiflora. Principal component scores along PC1 between control and drought treatment were significantly decreased by long-term experimental drought, but the scores along PC2 were not affected. Further research should focus on successional pathways in more water-deficit conditions in Mediterranean ecosystems and the consequences of changes in vegetation recovery pathways on ecosystem functions such as biomass accumulation and soil properties.
24.	Liu, Daijun, et al. (author) Increasing climatic sensitivity of global grassland vegetation biomass and species diversity correlates with water availability 2021 In: New Phytologist. - : Wiley. - 1469-8137 .- 0028-646X. ; 230:5, s. 1761-1771 Research review (peer-reviewed)abstract Grasslands are key repositories of biodiversity and carbon storage and are heavily impacted by effects of global warming and changes in precipitation regimes. Patterns of grassland dynamics associated with variability in future climate conditions across spatiotemporal scales are yet to be adequately quantified. Here, we performed a global meta-analysis of year and growing season sensitivities of vegetation aboveground biomass (AGB), aboveground net primary productivity (ANPP), and species richness (SR) and diversity (Shannon index, H) to experimental climate warming and precipitation shifts. All four variables were sensitive to climate change. Their sensitivities to shifts in precipitation were correlated with local background water availability, such as mean annual precipitation (MAP) and aridity, and AGB and ANPP sensitivities were greater in dry habitats than in non-water limited habitats. There was no effect of duration of experiment (short vs long-term) on sensitivities. Temporal trends in ANPP and SR sensitivity depended on local water availability; ANPP sensitivity to warming increased over time and SR sensitivity to irrigation decreased over time. Our results provide a global overview of the sensitivities of grassland function and diversity to climate change that will improve understanding of ecological responses across spatiotemporal scales and inform policies for conservation in dry climates.
25.	Minoli, Sara, et al. (author) Global Response Patterns of Major Rainfed Crops to Adaptation by Maintaining Current Growing Periods and Irrigation 2019 In: Earth's Future. - 2328-4277. ; 7:12, s. 1464-1480 Journal article (peer-reviewed)abstract Increasing temperature trends are expected to impact yields of major field crops by affecting various plant processes, such as phenology, growth, and evapotranspiration. However, future projections typically do not consider the effects of agronomic adaptation in farming practices. We use an ensemble of seven Global Gridded Crop Models to quantify the impacts and adaptation potential of field crops under increasing temperature up to 6 K, accounting for model uncertainty. We find that without adaptation, the dominant effect of temperature increase is to shorten the growing period and to reduce grain yields and production. We then test the potential of two agronomic measures to combat warming-induced yield reduction: (i) use of cultivars with adjusted phenology to regain the reference growing period duration and (ii) conversion of rainfed systems to irrigated ones in order to alleviate the negative temperature effects that are mediated by crop evapotranspiration. We find that cultivar adaptation can fully compensate global production losses up to 2 K of temperature increase, with larger potentials in continental and temperate regions. Irrigation could also compensate production losses, but its potential is highest in arid regions, where irrigation expansion would be constrained by water scarcity. Moreover, we discuss that irrigation is not a true adaptation measure but rather an intensification strategy, as it equally increases production under any temperature level. In the tropics, even when introducing both adapted cultivars and irrigation, crop production declines already at moderate warming, making adaptation particularly challenging in these areas.

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