Cascading effects associated with climate-change-induced conifer mortality in mountain temperate forests result in hot-spots of soil CO 2 emissions

Climate change-induced tree mortality is occurring worldwide, at increasingly larger scales and with increasing frequency. How climate change-induced tree mortality could affect the ecology and carbon (C) sink capacity of soils remains unknown. This study investigated regional-scale drought-induced tree mortality, based on events that occurred after a very dry year (2012) in the Carpathians mountain range (Romania), which caused mortality in three common conifer species: Scots pine, Black pine, and Silver fir. This resulted in hot-spots of biogenic soil CO 2 emissions (soil respiration; Rs). Four to five years after the main mortality event, Rs-related soil CO 2 emissions under dead trees were, on average, 21% (ranging from 18 to 35%) higher than CO 2 emissions under living trees. Total (Rs) and heterotrophic (R H )-related soil CO 2 emissions were strongly related to alterations in the soil environment following tree mortality (e.g. changes in quantity and quality of soil organic matter, microclimate, pH or fine root demography). Moreover, the massive mortality event of 2012 resulted in greater presence of successional vegetation (broadleaf seedlings, shrubland and grasses), which may control the environmental factors that either directly or indirectly affected biotic soil fluxes (Rs and R H ). Besides the well-known direct effects of climate change on soil CO 2 emissions, the cascading effects triggered by climate change-induced tree mortality could also exert a strong indirect impact on soil CO 2 emissions. Overall, climate change-induced tree mortality alters the magnitude of environmental controls on Rs and hence determines how the ecosystem C budget responds to climate change. © 2019 Elsevier LtdThis work was supported by the Spanish Ministry of Economy and Competitiveness (MINECO) with the projects VERONICA ( CGL2013-42271-P ) and the project IBERYCA ( CGL2017-84723-P ), and by the Romanian Ministry of Education and Scientific Research through UEFISCDI with the projects TREEMORIS ( PN-II-RU-TE-2014-4-0791 ), NATIvE ( PN-III-P1-1.1-PD-2016-0583 ), and BIOCARB ( PN-III-P1-1.1-TE-2016-1508 ). This research was also supported by the Basque Government through the BERC 2018-2021 program, and by the Spanish Ministry of Economy and Competitiveness (MINECO) through the BC3 María de Maeztu excellence accreditation ( MDM-2017-0714 ). I.C. Petritan was partially funded by the H2020/ERA-NET/ERA-GAS (Project 82/2017, Mobilizing and monitoring climate positive efforts in forests and forestry, FORCLIMIT ). Many thanks to Cosmin Zgremtia, Ionela Medrea, Andrei Apafaian, Raluca Enescu and Marta Ramos for their valuable help during field campaigns and laboratory work

The impact of insect herbivory on biogeochemical cycling in broadleaved forests varies with temperature

Herbivorous insects alter biogeochemical cycling within forests, but the magnitude of these impacts, their global variation, and drivers of this variation remain poorly understood. To address this knowledge gap and help improve biogeochemical models, we established a global network of 74 plots within 40 mature, undisturbed broadleaved forests. We analyzed freshly senesced and green leaves for carbon, nitrogen, phosphorus and silica concentrations, foliar production and herbivory, and stand-level nutrient fluxes. We show more nutrient release by insect herbivores at non-outbreak levels in tropical forests than temperate and boreal forests, that these fluxes increase strongly with mean annual temperature, and that they exceed atmospheric deposition inputs in some localities. Thus, background levels of insect herbivory are sufficiently large to both alter ecosystem element cycling and influence terrestrial carbon cycling. Further, climate can affect interactions between natural populations of plants and herbivores with important consequences for global biogeochemical cycles across broadleaved forests

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Deadwood density, C stocks and their controlling factors in a beech-silver fir mixed virgin European forest

Deadwood is a fundamental structural and functional component of forests, with a crucial role in supporting forest biodiversity, nutrient and carbon cycling. Precise deadwood density estimates and its relation to environmental factors are necessary to evaluate the biomass and carbon stocked in this component. In this study, we estimated dry deadwood density for two different tree species, silver fir (Abies alba) and European beech (Fagus sylvatica) and for three snags and five logs decomposition classes in a virgin mixed beech-fir forest in the Southern Carpathians. The goal was to assess how deadwood density is influenced by different abiotic (moisture, elevation, slope, aspect) and wood-related factors (rottenness, position along the piece, contact with the soil). For snags, the mean dry density showed a reduced variability within decomposition classes (484–326 kg.m−3 for beech and 374–319 kg.m−3 for fir), compared to the logs (486–139 kg.m−3 for beech and 359–161 kg.m−3 for fir). While the mass moisture varied slowly in the first three decay classes (around 60–80 %), it increased sharply in the last two decay classes of logs (>140 % in the fourth class and > 350 % in the last one). The rottenness increased with the decay class in a similar way for both species. The contact of logs with the soil influenced positively the moisture, but the position of the sampling within the piece did not play any significant role in the variability of density. Based on density estimates per decay classes we estimated that the carbon (C) stored in deadwood varied greatly among the 21 plots from 0.36 to 41.16 MgC ha−1, with a mean value of 15.96 ± 2.36 (±SE) MgC ha−1. Our study suggests that volume-based calculations might yield biased quantitative estimates of C stored in deadwood unless a local estimate of dead wood density corrected per species and decomposition class is applied. Moreover, the use of an averaged value of dry density instead of value for each decay class may result in an overestimation of 22% on the estimation of C stock. Thus, our study emphasises the importance of considering decay class-specific values in future inventories of C stocks in other forests and for other species. Furthermore, it could serve as a methodological basis for more specific research designed to uncover the potential influence of different forest management practices on dry deadwood density.Deadwood is a fundamental structural and functional component of forests, with a crucial role in supporting forest biodiversity, nutrient and carbon cycling. Precise deadwood density estimates and its relation to environmental factors are necessary to evaluate the biomass and carbon stocked in this component. In this study, we estimated dry deadwood density for two different tree species, silver fir (Abies alba) and European beech (Fagus sylvatica) and for three snags and five logs decomposition classes in a virgin mixed beech-fir forest in the Southern Carpathians. The goal was to assess how deadwood density is influenced by different abiotic (moisture, elevation, slope, aspect) and wood-related factors (rottenness, position along the piece, contact with the soil). For snags, the mean dry density showed a reduced variability within decomposition classes (484–326 kg.m−3 for beech and 374–319 kg.m−3 for fir), compared to the logs (486–139 kg.m−3 for beech and 359–161 kg.m−3 for fir). While the mass moisture varied slowly in the first three decay classes (around 60–80 %), it increased sharply in the last two decay classes of logs (>140 % in the fourth class and > 350 % in the last one). The rottenness increased with the decay class in a similar way for both species. The contact of logs with the soil influenced positively the moisture, but the position of the sampling within the piece did not play any significant role in the variability of density. Based on density estimates per decay classes we estimated that the carbon (C) stored in deadwood varied greatly among the 21 plots from 0.36 to 41.16 MgC ha−1, with a mean value of 15.96 ± 2.36 (±SE) MgC ha−1. Our study suggests that volume-based calculations might yield biased quantitative estimates of C stored in deadwood unless a local estimate of dead wood density corrected per species and decomposition class is applied. Moreover, the use of an averaged value of dry density instead of value for each decay class may result in an overestimation of 22% on the estimation of C stock. Thus, our study emphasises the importance of considering decay class-specific values in future inventories of C stocks in other forests and for other species. Furthermore, it could serve as a methodological basis for more specific research designed to uncover the potential influence of different forest management practices on dry deadwood density

Litterfall production and leaf area index in a virgin European beech (Fagus sylvatica L.) – Silver fir (Abies alba Mill.) forest

Because of their role in carbon and nutrient exchange, litterfall and leaf area have been increas- ingly studied in the last few decades. However, most existing information comes from managed forests, while comparable data for virgin forests is scarce. To address this scarcity, we investigated a mixed beech – silver fir virgin forest located in the Southern Carpathian Mountains, using 78 litter traps to measure the annual litterfall production, litter composition and leaf area index (LAI). The LAI was calculated in two ways: directly, by using litter traps, and indirectly, based on hemispherical photographs. Furthermore, we investigated the influence of different stand and environmental characteristics on litter production, total foliar mass and LAIs. Annual litter productivity ranged from 1.8 to 8.3 t ha−1 with a mean of 3.5 t ha−1. Litter was composed mainly of beech leaves (66%) along with a lower percentage of silver fir needles (16%). The total foliar dry mass (sum of beech leaves and silver fir needles) increased significantly with the proportion of beeches and decreased with the median stand age. The LAI determined by using litter traps had a mean value of 5.06 m2 m−2, ranging from 3.52 to 8.22, and was characterised by a higher variability than the LAI estimated indirectly using the hemispherical approach (which had a mean value of 3.65 and a range of 2.30–5.28). The two indices did not correlate with each other. We found no significant relation between the LAIs and any stand or environmental variables. We conclude that in the more complex forests, such as the virgin beech – silver fir mixed forest we studied, annual foliar dry mass is more closely related to stand characteristics than is LAI. We also note significant limitations of both LAI estimation methods, which indicate that a more elaborate approach to estimating LAI is needed

Jet stream position explains regional anomalies in European beech forest productivity and tree growth

The mechanistic pathways connecting ocean-atmosphere variability and terrestrial productivity are well-established theoretically, but remain challenging to quantify empirically. Such quantification will greatly improve the assessment and prediction of changes in terrestrial carbon sequestration in response to dynamically induced climatic extremes. The jet stream latitude (JSL) over the North Atlantic-European domain provides a synthetic and robust physical framework that integrates climate variability not accounted for by atmospheric circulation patterns alone. Surface climate impacts of north-south summer JSL displacements are not uniform across Europe, but rather create a northwestern-southeastern dipole in forest productivity and radial-growth anomalies. Summer JSL variability over the eastern North Atlantic-European domain (5-40E) exerts the strongest impact on European beech, inducing anomalies of up to 30% in modelled gross primary productivity and 50% in radial tree growth. The net effects of JSL movements on terrestrial carbon fluxes depend on forest density, carbon stocks, and productivity imbalances across biogeographic regions. © 2022, The Author(s).Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

TRY plant trait database, enhanced coverage and open access

Plant traits-the morphological, ahawnatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives