Molecular mechanisms of cell death: recommendations of the Nomenclature Committee on Cell Death 2018.

Over the past decade, the Nomenclature Committee on Cell Death (NCCD) has formulated guidelines for the definition and interpretation of cell death from morphological, biochemical, and functional perspectives. Since the field continues to expand and novel mechanisms that orchestrate multiple cell death pathways are unveiled, we propose an updated classification of cell death subroutines focusing on mechanistic and essential (as opposed to correlative and dispensable) aspects of the process. As we provide molecularly oriented definitions of terms including intrinsic apoptosis, extrinsic apoptosis, mitochondrial permeability transition (MPT)-driven necrosis, necroptosis, ferroptosis, pyroptosis, parthanatos, entotic cell death, NETotic cell death, lysosome-dependent cell death, autophagy-dependent cell death, immunogenic cell death, cellular senescence, and mitotic catastrophe, we discuss the utility of neologisms that refer to highly specialized instances of these processes. The mission of the NCCD is to provide a widely accepted nomenclature on cell death in support of the continued development of the field

sPlotOpen - An environmentally balanced, open-access, global dataset of vegetation plots

Motivation Assessing biodiversity status and trends in plant communities is critical for understanding, quantifying and predicting the effects of global change on ecosystems. Vegetation plots record the occurrence or abundance of all plant species co-occurring within delimited local areas. This allows species absences to be inferred, information seldom provided by existing global plant datasets. Although many vegetation plots have been recorded, most are not available to the global research community. A recent initiative, called 'sPlot', compiled the first global vegetation plot database, and continues to grow and curate it. The sPlot database, however, is extremely unbalanced spatially and environmentally, and is not open-access. Here, we address both these issues by (a) resampling the vegetation plots using several environmental variables as sampling strata and (b) securing permission from data holders of 105 local-to-regional datasets to openly release data. We thus present sPlotOpen, the largest open-access dataset of vegetation plots ever released. sPlotOpen can be used to explore global diversity at the plant community level, as ground truth data in remote sensing applications, or as a baseline for biodiversity monitoring. Main types of variable contained Vegetation plots (n = 95,104) recording cover or abundance of naturally co-occurring vascular plant species within delimited areas. sPlotOpen contains three partially overlapping resampled datasets (c. 50,000 plots each), to be used as replicates in global analyses. Besides geographical location, date, plot size, biome, elevation, slope, aspect, vegetation type, naturalness, coverage of various vegetation layers, and source dataset, plot-level data also include community-weighted means and variances of 18 plant functional traits from the TRY Plant Trait Database. Spatial location and grain Global, 0.01-40,000 m(2). Time period and grain 1888-2015, recording dates. Major taxa and level of measurement 42,677 vascular plant taxa, plot-level records. Software format Three main matrices (.csv), relationally linked

sPlotOpen – An environmentally-balanced, open-access, global dataset of vegetation plots

Motivation Assessing biodiversity status and trends in plant communities is critical for understanding, quantifying and predicting the effects of global change on ecosystems. Vegetation plots record the occurrence or abundance of all plant species co-occurring within delimited local areas. This allows species absences to be inferred, information seldom provided by existing global plant datasets. Although many vegetation plots have been recorded, most are not available to the global research community. A recent initiative, called ‘sPlot’, compiled the first global vegetation plot database, and continues to grow and curate it. The sPlot database, however, is extremely unbalanced spatially and environmentally, and is not open-access. Here, we address both these issues by (a) resampling the vegetation plots using several environmental variables as sampling strata and (b) securing permission from data holders of 105 local-to-regional datasets to openly release data. We thus present sPlotOpen, the largest open-access dataset of vegetation plots ever released. sPlotOpen can be used to explore global diversity at the plant community level, as ground truth data in remote sensing applications, or as a baseline for biodiversity monitoring. Main types of variable contained Vegetation plots (n = 95,104) recording cover or abundance of naturally co-occurring vascular plant species within delimited areas. sPlotOpen contains three partially overlapping resampled datasets (c. 50,000 plots each), to be used as replicates in global analyses. Besides geographical location, date, plot size, biome, elevation, slope, aspect, vegetation type, naturalness, coverage of various vegetation layers, and source dataset, plot-level data also include community-weighted means and variances of 18 plant functional traits from the TRY Plant Trait Database. Spatial location and grain Global, 0.01–40,000 m². Time period and grain 1888–2015, recording dates. Major taxa and level of measurement 42,677 vascular plant taxa, plot-level records. Software format Three main matrices (.csv), relationally linked

sPlotOpen – An environmentally balanced, open-access, global dataset of vegetation plots

Motivation Assessing biodiversity status and trends in plant communities is critical for understanding, quantifying and predicting the effects of global change on ecosystems. Vegetation plots record the occurrence or abundance of all plant species co-occurring within delimited local areas. This allows species absences to be inferred, information seldom provided by existing global plant datasets. Although many vegetation plots have been recorded, most are not available to the global research community. A recent initiative, called ‘sPlot’, compiled the first global vegetation plot database, and continues to grow and curate it. The sPlot database, however, is extremely unbalanced spatially and environmentally, and is not open-access. Here, we address both these issues by (a) resampling the vegetation plots using several environmental variables as sampling strata and (b) securing permission from data holders of 105 local-to-regional datasets to openly release data. We thus present sPlotOpen, the largest open-access dataset of vegetation plots ever released. sPlotOpen can be used to explore global diversity at the plant community level, as ground truth data in remote sensing applications, or as a baseline for biodiversity monitoring. Main types of variable contained Vegetation plots (n = 95,104) recording cover or abundance of naturally co-occurring vascular plant species within delimited areas. sPlotOpen contains three partially overlapping resampled datasets (c. 50,000 plots each), to be used as replicates in global analyses. Besides geographical location, date, plot size, biome, elevation, slope, aspect, vegetation type, naturalness, coverage of various vegetation layers, and source dataset, plot-level data also include community-weighted means and variances of 18 plant functional traits from the TRY Plant Trait Database. Spatial location and grain Global, 0.01–40,000 m². Time period and grain 1888–2015, recording dates. Major taxa and level of measurement 42,677 vascular plant taxa, plot-level records. Software format Three main matrices (.csv), relationally linked

sPlot - A new tool for global vegetation analyses

Dengler, Jurgen/0000-0003-3221-660X; Chytry, Milan/0000-0002-8122-3075; de Gasper, Andre Luis/0000-0002-1940-9581; Marceno, Corrado/0000-0003-4361-5200; Swacha, Grzegorz/0000-0002-6380-2954; He, Tianhua/0000-0002-0924-3637; Haider, Sylvia/0000-0002-2966-0534; Kuhn, Ingolf/0000-0003-1691-8249; Svenning, Jens-Christian/0000-0002-3415-0862; Jansen, Florian/0000-0002-0331-5185; Casella, Laura/0000-0003-2550-3010; Schmidt, Marco/0000-0001-6087-6117; Chepinoga, Victor/0000-0003-3809-7453; Petrik, Petr/0000-0001-8518-6737; Willner, Wolfgang/0000-0003-1591-8386; Jansen, Steven/0000-0002-4476-5334; De Sanctis, Michele/0000-0002-7280-6199; Niinemets, Ulo/0000-0002-3078-2192; Pauchard, Anibal/0000-0003-1284-3163; Vibrans, Alexander C./0000-0002-8789-5833; Biurrun, Idoia/0000-0002-1454-0433; De Patta Pillar, Valerio/0000-0001-6408-2891; Phillips, Oliver L/0000-0002-8993-6168; Sibik, Jozef/0000-0002-5949-862X; Lenoir, Jonathan/0000-0003-0638-9582; Venanzoni, Roberto/0000-0002-7768-0468; Gutierrez, Alvaro G./0000-0001-8928-3198; Cayuela, Luis/0000-0003-3562-2662; Nobis, Marcin/0000-0002-1594-2418; Agrillo, Emiliano/0000-0003-2346-8346; Manning, Peter/0000-0002-7940-2023; Venanzoni, Roberto/0000-0002-7768-0468; Virtanen, Risto/0000-0002-8295-8217; Higuchi, Pedro/0000-0002-3855-555X; Sopotlieva, Desislava/0000-0002-9281-7039; Kuzemko, Anna/0000-0002-9425-2756; Hatim, Mohamed/0000-0002-0872-5108; Mencuccini, Maurizio/0000-0003-0840-1477; Enquist, Brian J./0000-0002-6124-7096; De Bie, Els/0000-0001-7679-743X; Samimi, Cyrus/0000-0001-7001-7893; Nowak, Arkadiusz/0000-0001-8638-0208; Jimenez-Alfaro, Borja/0000-0001-6601-9597; Font, Xavier/0000-0002-7253-8905; Levesley, Aurora/0000-0002-7999-5519; Acic, Svetlana/0000-0001-6553-3797; Kattge, Jens/0000-0002-1022-8469; Silc, Urban/0000-0002-3052-699X; Arnst, Elise/0000-0003-2388-7428; Moretti, Marco/0000-0002-5845-3198; Kozub, Lukasz/0000-0002-6591-8045; Kacki, Zygmunt/0000-0002-2241-1631; Fagundez, Jaime/0000-0001-6605-7278; Purschke, Oliver/0000-0003-0444-0882; Martynenko, Vasiliy/0000-0002-9071-3789; Jandt, Ute/0000-0002-3177-3669; Peyre, Gwendolyn/0000-0002-1977-7181; SABATINI, FRANCESCO MARIA/0000-0002-7202-7697; Bruelheide, Helge/0000-0003-3135-0356; Wohlgemuth, Thomas/0000-0002-4623-0894; Onyshchenko, Viktor/0000-0001-9079-7241; Kuzmic, Filip/0000-0002-3894-7115; Ejrnaes, Rasmus/0000-0003-2538-8606; Jirousek, Martin/0000-0002-4293-478X; Noroozi, Jalil/0000-0003-4124-2359; Curran, Michael/0000-0002-1858-5612; Baraloto, Christopher/0000-0001-7322-8581; Ozinga, Wim/0000-0002-6369-7859WOS: 000466421500001Aims Vegetation-plot records provide information on the presence and cover or abundance of plants co-occurring in the same community. Vegetation-plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level. Results sPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected worldwide between 1885 and 2015. We complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g., biomes) from external sources, and by calculating community-weighted means and variances of traits using gap-filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots. We present the first maps of global patterns of community richness and community-weighted means of key traits. Conclusions The availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale.German Research FoundationGerman Research Foundation (DFG) [DFG FZT 118]; TRY initiative on plant traitsWe are grateful to thousands of vegetation scientists who sampled vegetation plots in the field or digitized them into regional, national or international databases. We also appreciate the support of the German Research Foundation for funding sPlot as one of the iDiv (DFG FZT 118) research platforms, and the organization of three workshops through the sDiv calls. We acknowledge this support with naming the database "sPlot", where the "s" refers to the sDiv synthesis workshops. The study was supported by the TRY initiative on plant traits (http://www.try-db.org). For all further acknowledgements see Appendix S10. We thank Meelis Partel for his very fast and constructive feedback on an earlier version of this manuscript

sPlotOpen – An environmentally balanced, open‐access, global dataset of vegetation plots

Abstract Motivation Assessing biodiversity status and trends in plant communities is critical for understanding, quantifying and predicting the effects of global change on ecosystems. Vegetation plots record the occurrence or abundance of all plant species co‐occurring within delimited local areas. This allows species absences to be inferred, information seldom provided by existing global plant datasets. Although many vegetation plots have been recorded, most are not available to the global research community. A recent initiative, called ‘sPlot’, compiled the first global vegetation plot database, and continues to grow and curate it. The sPlot database, however, is extremely unbalanced spatially and environmentally, and is not open‐access. Here, we address both these issues by (a) resampling the vegetation plots using several environmental variables as sampling strata and (b) securing permission from data holders of 105 local‐to‐regional datasets to openly release data. We thus present sPlotOpen, the largest open‐access dataset of vegetation plots ever released. sPlotOpen can be used to explore global diversity at the plant community level, as ground truth data in remote sensing applications, or as a baseline for biodiversity monitoring. Main types of variable contained Vegetation plots (n = 95,104) recording cover or abundance of naturally co‐occurring vascular plant species within delimited areas. sPlotOpen contains three partially overlapping resampled datasets (c. 50,000 plots each), to be used as replicates in global analyses. Besides geographical location, date, plot size, biome, elevation, slope, aspect, vegetation type, naturalness, coverage of various vegetation layers, and source dataset, plot‐level data also include community‐weighted means and variances of 18 plant functional traits from the TRY Plant Trait Database. Spatial location and grain Global, 0.01–40,000 m². Time period and grain 1888–2015, recording dates. Major taxa and level of measurement 42,677 vascular plant taxa, plot‐level records. Software format Three main matrices (.csv), relationally linked.Agence Nationale de la Recherche http://dx.doi.org/10.13039/501100001665H2020 European Research Council http://dx.doi.org/10.13039/100010663Villum Fonden http://dx.doi.org/10.13039/100008398Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659Narodowe Centrum Nauki http://dx.doi.org/10.13039/501100004281Latvia grantNSF http://dx.doi.org/10.13039/100003187Horizon 2020 Framework Programme http://dx.doi.org/10.13039/100010661U.S. National Science Foundation http://dx.doi.org/10.13039/100000001Grantová Agentura České Republiky http://dx.doi.org/10.13039/501100001824German Centre for Integrative Biodiversity Research http://dx.doi.org/10.13039/501100020056Fundación BBVA http://dx.doi.org/10.13039/100007406Akademie Věd České Republiky http://dx.doi.org/10.13039/501100004240Spanish Research Agency http://dx.doi.org/10.13039/501100011033National Research, Development and Innovation Office, Hungar http://dx.doi.org/10.13039/501100018818Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung http://dx.doi.org/10.13039/501100001711Basque Government http://dx.doi.org/10.13039/501100003086Russian Foundation for Basic Research http://dx.doi.org/10.13039/501100002261Brazil’s National Council of Scientific and Technological DevelopmentVolkswagen Foundation http://dx.doi.org/10.13039/50110000166

sPlot:a new tool for global vegetation analyses

Abstract Aims: Vegetation‐plot records provide information on the presence and cover or abundance of plants co‐occurring in the same community. Vegetation‐plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level. Results: sPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected worldwide between 1885 and 2015. We complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g., biomes) from external sources, and by calculating community‐weighted means and variances of traits using gap‐filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots. We present the first maps of global patterns of community richness and community‐weighted means of key traits. Conclusions: The availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale