Chronicles of Nature Calendar: A long-term and large-scale multitaxon database on phenology

• Main Authors: Ovaskainen, Otso, Meyke, Evgeniy, Lo, Coong, Tikhonov, Gleb, Delgado, Maria, Roslin, Tomas, Gurarie, Eliezer, Abadonova, Marina, Abduraimov, Ozodbek, Adrianova, Olga, Akkiev, Muzhigit, Ananin, Aleksandr, Andreeva, Elena, Andriychuk, Natalia, Antipin, Maxim, Arzamascev, Konstantin, Babina, Svetlana, Babushkin, Miroslav, Bakin, Oleg, Basilskaja, Inna, Belova, Nina, Belyaeva, Natalia, Beshkarev, Aleksandr, Bespalova, Tatjana, Bisikalova, Evgeniya, Bobretsov, Anatoly, Bobrov, Vladimir, Bobrovskyi, Vadim, Bochkareva, Elena, Bogdanov, Gennady, Bondarchuk, Svetlana, Bukharova, Evgeniya, Butunina, Alena, Buyvolov, Yuri, Buyvolova, Anna, Bykov, Yuri, Chakhireva, Elena, Chashchina, Olga, Cherenkova, Nadezhda, Chervova, Lybov, Chistjakov, Sergej, Chuhontseva, Svetlana, Davydov, Evgeniy A, Demchenko, Viktor, Diadicheva, Elena, Dobrolyubov, Aleksandr, Dostoyevskaya, Ludmila, Drovnina, Svetlana, Drozdova, Zoya, Dubanaev, Akynaly, Dubrovsky, Yuriy, Elsukov, Sergey, Epova, Lidia, Ermakova, Olga S, Ermakova, Olga, Esengeldenova, Aleksandra, Esipov, Aleksandr, Evstigneev, Oleg, Fedchenko, Irina, Fedotova, Violetta, Filatova, Tatiana, Gashev, Sergey, Gavrilov, Anatoliy, Gaydysh, Irina, Golovcov, Dmitrij, Goncharova, Nadezhda, Gorbunova, Elena, Gordeeva, Tatyana, Grishchenko, Vitaly, Gromyko, Ludmila, Hohryakov, Vladimir, Hritankov, Alexander, Ignatenko, Elena, Igosheva, Svetlana, Ivanova, Uliya, Ivanova, Natalya, Kalinkin, Yury, Kaygorodova, Evgeniya, Kazansky, Fedor, Kiseleva, Darya, Knorre, Anastasia, Kolpashikov, Leonid, Korobov, Evgenii, Korolyova, Helen, Kosenkov, Gennadiy, Kossenko, Sergey, Kotlugalyamova, Elvira, Kozlovsky, Evgeny, Kozsheechkin, Vladimir, Kozurak, Alla, Kozyr, Irina, Krasnopevtseva, Aleksandra, Kruglikov, Sergey, Kuberskaya, Olga, Kudryavtsev, Aleksey, Kulebyakina, Elena, Kulsha, Yuliia, Kupriyanova, Margarita, Kurakina, Irina, Kurbanbagamaev, Murad, Kutenkov, Anatoliy, Kutenkova, Nadezhda, Kuyantseva, Nadezhda, Kuznetsov, Andrey, Larin, Evgeniy, Lebedev, Pavel, Litvinov, Kirill, Luzhkova, Natalia, Mahmudov, Azizbek, Makovkina, Lidiya, Mamontov, Viktor, Mayorova, Svetlana, Megalinskaja, Irina, Meydus, Artur, Minin, Aleksandr, Mitrofanov, Oleg, Motruk, Mykhailo, Myslenkov, Aleksandr, Nasonova, Nina, Nemtseva, Natalia, Nesterova, Irina, Nezdoliy, Tamara, Novikova, Tatiana, Panicheva, Darya, Pavlov, Alexey, Pavlova, Klara, Petrenko, Polina, Podolski, Sergei, Polikarpova, Natalja, Polyanskaya, Tatiana, Pospelov, Igor, Pospelova, Elena, Prokhorov, Ilya, Prokosheva, Irina, Puchnina, Lyudmila, Raiskaya, Julia, Romanova, Elena, Rozhkov, Yuri, Rozhkova, Olga, Rudenko, Marina, Rybnikova, Irina, Rykova, Svetlana, Sahnevich, Miroslava, Samoylov, Alexander, Sanko, Valeri, Sapelnikova, Inna, Sazonov, Sergei, Selyunina, Zoya, Shalaeva, Ksenia, Shashkov, Maksim, Shcherbakov, Anatoliy, Shevchyk, Vasyl, Shirshova, Natalia, Shubin, Sergej, Shujskaja, Elena, Sibgatullin, Rustam, Sikkila, Natalia, Sitnikova, Elena, Sivkov, Andrei, Skorokhodova, Svetlana, Smirnova, Elena, Sokolova, Galina, Sopin, Vladimir, Spasovski, Yurii, Stepanov, Sergei, Strekalovskaya, Violetta, Sukhov, Alexander, Suleymanova, Guzalya, Sultangareeva, Lilija, Teleganova, Viktorija, Teplov, Viktor, Teplova, Valentina, Tertitsa, Tatiana, Timoshkin, Vladislav, Tirski, Dmitry, Tomilin, Aleksey, Tselishcheva, Ludmila, Turgunov, Mirabdulla, Van, Vladimir, Vargot, Elena, Vasin, Aleksander, Vasina, Aleksandra, Vekliuk, Anatoliy, Vetchinnikova, Lidia, Vinogradov, Vladislav, Volodchenkov, Nikolay, Voloshina, Inna, Xoliqov, Tura, Yablonovska-Grishchenko, Eugenia, Yakovlev, Vladimir, Yakovleva, Marina, Yantser, Oksana, Zahvatov, Andrey, Zakharov, Valery, Zelenetskiy, Nicolay, Zheltukhin, Anatolii, Zubina, Tatyana, Kurhinen, Juri
• Format: Dataset
• Language: English
• Published: Zenodo 2018
• Subjects: Listvyanka; Stolby; karelia*; karelian
• Online Access: https://dx.doi.org/10.5281/zenodo.3595436; https://zenodo.org/record/3595436

We present an extensive, large-scale, long-term and multitaxon database on phenological and climatic variation, involving 506,186 observation dates acquired in 471 localities in Russian Federation, Ukraine, Uzbekistan, Belarus and Kyrgyzstan. The data cover the period 1890-2018, with 96% of the data being from 1960 onwards. The database is rich in plants, birds and climatic events, but also includes insects, amphibians, reptiles and fungi. The database includes multiple events per species, such as the onset days of leaf unfolding and leaf fall for plants, and the days for first spring and last autumn occurrences for birds. The data were acquired using standardized methods by permanent staff of national parks and nature reserves (87% of the data) and members of a phenological observation network (13% of the data). The database is valuable for exploring how species respond in their phenology to climate change. Large-scale analyses of spatial variation in phenological response can help to better predict the consequences of species and community responses to climate change. The recording scheme implemented at nature reserves offers unique opportunities for addressing community-level change across replicate local communities. These data have been systematically collected not as independent monitoring efforts, but using a shared and carefully standardized protocol adapted for each local community. Thus, variability in observation effort is of much less concern than in most other distributed cross-taxon phenological monitoring schemes. To enable analyses of higher-level taxonomical groups, we have included taxonomic classifications for the species in the database. The compilation of the data in a common database was initiated in the context of the project “Linking environmental change to biodiversity change: long-term and large-scale data on European boreal forest biodiversity” (EBFB), funded for 2011-2015 by the Academy of Finland, and continued with the help of other funding to OO since 2016. We organized a series of project meetings that were essential for data acquisition, digitalization and unification. These meetings were organized in Ekaterinburg (Russia) by the Institute of Plant and Animal Ecology, Ural Branch of RAS (Russian Academy of Sciences) in 2011; in Petrozavodsk (Russia) by the Forest Research Institute, at the Karelian Research Center, RAS in 2013; in Miass (Russia) by the Ilmen Nature Reserve in 2014; in Krasnoyarsk (Russia) by the Stolby Nature Reserve in 2014; in Artybash (Russia) by the Altaisky Nature Reserve in 2015; in Listvyanka, Lake Baikal (Russia) by the Zapovednoe Pribajkalje Nature Reserve in 2016; in Roztochja (Ukraine) by the Ministry of Natural Resources of Ukraine in 2016; in Puschino (Russia) by the Prioksko-Terrasnyj Nature Reserve in 2017, in Vyshinino (Russia) by the Kenozero National Park in 2018, and in St Petersburg (Russia) by the Komarov Botanical Institute of the Russian Academy of Sciences in 2019. The compilation of the data into a common database was conducted by the database coordinators (EM and CL) in Helsinki (Finland). Those participants that already held the data in digital format submitted it in the original format, and those that had the data only in paper format digitized it using Excel-based templates developed in the project meetings. Submitted data were processed by the database coordinators according to the following steps: The data were formatted so that each observation (the phenological date of a particular event in a particular locality and year) formed one row in the data table (e.g. un-pivoting tables that involved several years as the columns). The phenological event names were split into event type (e.g. “first occurrence“) and species name. The event type names (provided originally typically in Russian) were translated into English and the species names (usually provided in Russian) were identified to scientific names, using dictionaries that were partly developed and verified in the project meetings. All scientific names were periodically verified by mapping them to the Global Biodiversity Information Facility (GBIF) backbone taxonomy. We associated each data record with the following set of information fields: (1) project name, i.e. the source organization, (2) dataset name, (3) locality name, (4) unique taxon identifier, (5) scientific taxon name, and (6) event type. We imported the data records in the main database (maintained as an EarthCape database at https://ecn.ecdb.io). During the import, the taxonomic names, locality names, and dataset names were matched against already existing records.