Spatial variability of soil respiration (R<inf>s</inf>) and its controls are subjected to strong seasonality in an even-aged European beech (Fagus sylvatica L.) stand

Uncertainties arising from the so-far poorly explained spatial variability of soil respiration (Rs) remain large. This is partly due to the limited understanding about how spatially variable Rs actually is, but also on how environmental controls determine Rs's spatial variability and how these controls vary in time (e.g., seasonally). Our study was designed to look more deeply into the complexity of Rs's spatial variability in a European beech even-aged stand, covering both phenologically and climatically contrasting periods (spring, summer, autumn and winter). Although we studied a relatively homogeneous stand, we found a large spatial variability of Rs (coefficients of variation &gt; 30%) characterized by strong seasonality. This large spatial variability of Rs suggests that even in relatively homogeneous stands there is a large potential source of error when estimating Rs. This was also reflected by the sampling effort needed to obtain seasonally robust estimates of Rs, which may actually require a number of samples above that used in Rs studies. We further postulate that the effect of seasonality on the spatial variability and environmental controls of Rs was determined by the seasonal shifts of its microclimatic controls: during winter, low temperatures constrain plant and soil metabolic activities and hence reduce Rs variability (temperature-controlled processes), whereas during summer, water demand by vegetation and changes in water availability due to the microtopography of the terrain (i.e., slope) increase Rs variability (water-controlled processes). This study provides novel information on the spatiotemporal variability of Rs and looks more deeply into the seasonality of its environmental controls and the architecture of their causal-effect relationships controlling Rs's spatial variability. Our study further shows that improving current estimates of Rs at local and regional levels might be necessary in order to reduce uncertainties and improve CO2 estimates at larger spatial scales. Highlights: The spatial variability of soil respiration (Rs) and its environmental controls vary seasonally. Seasonal shifts from temperature- to water-controlled processes determine Rs's spatial variability. Besides microclimate, slope and grass cover explain the spatiotemporal variability of Rs. An intense sampling effort is needed to obtain robust Rs estimates even in homogeneous forests. © 2021 British Society of Soil Science.This research was supported by the Forest GHG Management (PN‐II‐ID‐PCE‐2011‐3‐0781), TREEMORIS (PN‐II‐RU‐TE‐2014‐4‐0791), BIOCARB (PN‐III‐P1‐1.1‐TE‐2016‐1508), NATIvE (PN‐III‐P1‐1.1‐PD‐2016‐0583) and REASONING (PN‐III‐P1‐1.1‐TE‐2019‐1099) projects, all financed by the Romanian Ministry of Education and Research through UEFISCDI ( link ). This research was also supported by the IBERYCA (CGL2017‐84723‐P) project and by the BC3 María de Maeztu excellence accreditation 2018‐2022 (Ref. MDM‐2017‐0714), both financed by the Spanish Ministry of Science, Innovation and Universities. The Basque Government also supported this research through the BERC 2018‐2021 programme

Legacies of past forest management determine current responses to severe drought events of conifer species in the Romanian Carpathians

Worldwide increases in droughts- and heat-waves-associated tree mortality events are destabilizing the future of many forests and the ecosystem services they provide. Along with climate, understanding the impact of the legacies of past forest management is key to better explain current responses of different tree species to climate change. We studied tree mortality events that peaked in 2012 affecting one native (silver fir; growing within its natural distribution range) and two introduced (black pine and Scots; growing outside their natural distribution range) conifer species from the Romanian Carpathians. The three conifers were compared in terms of mortality events, growth trends, growth resilience to severe drought events, climate-growth relationships, and regeneration patterns. The mortality rates of the three species were found to be associated with severe drought events. Nevertheless, the native silver fir seems to undergo a self-thinning process, while the future of the remaining living black pine and Scots pine trees is uncertain as they register significant negative growth trends. Overall, the native silver fir showed a higher resilience to severe drought events than the two introduced pine species. Furthermore, and unlike the native silver fir, black pine and Scots pine species do not successfully regenerate. A high diversity of native broadleaf species sprouts and develops instead under them suggesting that we might be witnessing a process of ecological succession, with broadleaves recovering their habitats. As native species seem to perform better in terms of resilience and regeneration than introduced species, the overall effect of the black pine and Scots pine mortality might be compensated. Legacies of past forest management should be taken into account in order to better understand current responses of different tree species to ongoing climate change. © 2020 Elsevier B.V.We thank the Forest District staff of Sacele, Kronstadt, Rasnov, Teliu, Codlea, and Intorsura Buzaului for all their support and for giving us access to the Forest Management Plans. This work was financed by the NATIvE ( PN-III-P1-1.1-PD-2016-0583 ) and TreeMoris ( PN-II-RU-TE-2014-4-0791 ) projects through UEFISCDI (link; Romanian Ministry of Education and Research ) and supported by the BERC 2018-2021 ( Basque Government ), and BC3 María de Maeztu Excellence Accreditation 2018-2022, Ref. MDM-2017-0714 ( Spanish Ministry of Science, Innovation and Universities ). We also thank Antonio Gazol for interesting discussions on the study and Ionela-Mirela Medrea, Andrei Apafaian, Maria Băluţ, and Florin Dinulică for assistance during field and laboratory campaigns. Silver fir, black pine, and Scots pine figures included in the graphical abstract are reproduced with the authorization of the designer Luiza Anamaria Pop (©2020) who drew the three conifer species and processed the drawings in Adobe Illustrator® CS5 (v. 15.0.0)

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

No systematic effects of sampling direction on climate-growth relationships in a large-scale, multi-species tree-ring data set

Ring-width series are important for diverse fields of research such as the study of past climate, forest ecology, forest genetics, and the determination of origin (dendro-provenancing) or dating of archaeological objects. Recent research suggests diverging climate-growth relationships in tree-rings due to the cardinal direction of extracting the tree cores (i.e. direction-specific effect). This presents an understudied source of bias that potentially affects many data sets in tree-ring research. In this study, we investigated possible direction-specific growth variability based on an international (10 countries), multi-species (8 species) tree-ring width network encompassing 22 sites. To estimate the effect of direction-specific growth variability on climate-growth relationships, we applied a combination of three methods: An analysis of signal strength differences, a Principal Component Gradient Analysis and a test on the direction-specific differences in correlations between indexed ring-widths series and climate variables. We found no evidence for systematic direction-specific effects on tree radial growth variability in high-pass filtered ring-width series. In addition, direction-specific growth showed only marginal effects on climate-growth correlations. These findings therefore indicate that there is no consistent bias caused by coring direction in data sets used for diverse dendrochronological applications on relatively mesic sites within forests in flat terrain, as were studied here. However, in extremely dry, warm or cold environments, or on steep slopes, and for different life-forms such as shrubs, further research is advisable.</p

TRY plant trait database - enhanced coverage and open access

This article has 730 authors, of which I have only listed the lead author and myself as a representative of University of HelsinkiPlant 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.Peer reviewe

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

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

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

The stationary and non-stationary character of the silver fir, black pine and Scots pine tree-growth-climate relationships

Tree-growth-climate relationships are usually assumed to have a stationary character, i.e., continuous and/or time-independent, along the lifetime of the trees. The fact that non-stationarity, i.e., discontinuous and/or time-variable, is more likely to actually be their general rule, has been often neglected in dendrochronology. Nine silver fir, black pine and Scots pine residual ring-width index chronologies (RWIresidual) and five precipitation- and temperature-derived seasonal climatic variables, covering the 20th century and the beginning of the 21st one, were used in this study. Heat map analyses based on rolling window correlations, using corrected p-values in order to deal with the type I errors (i.e., the multiple testing or comparison problem) and reduce them, were conducted to evaluate the evolution and stability of tree-growth-climate relationships along the lifetime of the trees, i.e., their stationary and/or non-stationary character. The obtained results showed that stationary tree-growth-climate relationships were well conserved within trees belonging to a given genus: positive effects, both at young and mature stages, of Twinter (winter temperature) on the Abies trees and of Psprsum(t) (spring-summer precipitation of the current-to-growth year) on the Pinus trees. Non-stationary tree-growth-climate relationships were instead species- and site-dependent and stopped in the 1970s/1980s/1990s. Growth decoupling from seasonal climatic variables was linked in many cases with climatic anomalies but the obtained results did not yield a general rule in this regard. Heat map analyses based on rolling window correlations proved to be a powerful statistical tool in disentangling between the stationary and/or non-stationary character of the tree-growth-climate relationships. Summarizing, this study puts into perspective the critical aspect of looking at the stationary and/or non-stationary character of the tree-growth-climate relationships if we want to better predict the impact of climate change on the future forest tree growth and dynamics based on past tree-growth-climate relationshipsWe thank the Forest District staff of Sacele, Kronstadt, Rasnov, Teliu, Codlea and Intorsura Buzaului for all their support during the fieldwork and for allowing us to access their Forest Management Plans. This work was supported by different projects granted by the Romanian Ministry of Research, Innovation and Digitization, CNCS/CCCDI – UEFISCDI: PN-II-RU-TE-2014-4-0791 (TREEMORIS), PN-III-P1-1.1-PD-2016-0583 (NATIvE), PN-III-P1-1.1-TE-2019-1099 (REASONING) and PN-III-P4-ID-PCE-2020-2696 (DeWooD). This work was also supported by the BERC 2018-2021 (Basque Government) and by the BC3 María de Maeztu Excellence Accreditation 2018-2022, Ref. MDM-2017-0714 (Spanish Ministry of Science, Innovation and Universities). JMPM acknowledges funding support from the SEPE (Spanish National Employment Service), the Junta de Castilla y León and the European Regional Development Fund (grant CLU-2019-03). We very much appreciate all the critical help that we received during the field and laboratory campaigns from Ionela-Mirela Medrea, Andrei Apafaian, Cosmin Zgremţia, Maria Băluţ and Florin Dinulică. The designer Luiza Anamaria Pop (©2020) drew the silver fir, black pine and Scots pine figures that appear in the graphical abstract and processed them in Adobe Illustrator® CS5 (v. 15.0.0). These figures are reproduced with her permission. We thank the Forest District staff of Sacele, Kronstadt, Rasnov, Teliu, Codlea and Intorsura Buzaului for all their support during the fieldwork and for allowing us to access their Forest Management Plans. This work was supported by different projects granted by the Romanian Ministry of Research, Innovation and Digitization, CNCS/CCCDI – UEFISCDI: PN-II-RU-TE-2014-4-0791 (TREEMORIS), PN-III-P1-1.1-PD-2016-0583 (NATIvE), PN-III-P1-1.1-TE-2019-1099 (REASONING) and PN-III-P4-ID-PCE-2020-2696 (DeWooD). This work was also supported by the BERC 2018-2021 (Basque Government) and by the BC3 María de Maeztu Excellence Accreditation 2018-2022, Ref. MDM-2017-0714 (Spanish Ministry of Science, Innovation and Universities). JMPM acknowledges funding support from the SEPE (Spanish National Employment Service), the Junta de Castilla y León and the European Regional Development Fund (grant CLU-2019-03). We very much appreciate all the critical help that we received during the field and laboratory campaigns from Ionela-Mirela Medrea, Andrei Apafaian, Cosmin Zgremţia, Maria Băluţ and Florin Dinulică. The designer Luiza Anamaria Pop (©2020) drew the silver fir, black pine and Scots pine figures that appear in the graphical abstract and processed them in Adobe Illustrator® CS5 (v. 15.0.0). These figures are reproduced with her permission