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"bibliographic_citation": "Puumala, E., Pehkonen, S., Saarimäki, H., Akhundzadeh, R., Hokka, J., Suoranta, A. S., Maiche, K., Lefort, B., Sevik, E., Ristimäki, H.-L., Kolarzik, N., & Ajakainen, M. (2025). Coexistence and conflict in the age of complexity (EmergentCommunity). Tampere University, Yhteiskuntatieteiden tiedekunta. 8921b88e-69c6-4e0a-8297-24e659016a6b",
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"en": "The data addresses the dynamics of coexistence and conflict in increasingly diverse cities from a human-centred perspective. It was collected as part of the EU-funded project Coexistence and Conflict in the Age of Complexity (EmergentCommunity) in nine European cities in Finland, France, and Sweden. The dataset comprises of two parts: EmergentCommunityEthno (qualitative data) and EmergentCommunityVR (quantitative and qualitative data) that were collected during the project. In addition to these, desk research was conducted and these files have been included in the metadata description. \n\nEmergentCommunityEthno (dataset 1):\n\nAcross the nine cities, participants consisted of people above 15-years of age, living in the studied urban neighbourhoods or using their public spaces. In Finland, data were collected in the neighbourhoods of Peltolammi and Multisilta in Tampere, in Malmi in Helsinki, and in Martti and Paavola in Hyvinkää. In Tampere, part of the data (n=31 interviews) was collected in collaboration with the EKOS research project (this part of the data is described and archived in the Finnish Social Science Data Archive, DoI: https://doi.org/10.60686/t-fsd3816) The second part of the data was collected in Sweden. The data collection sites there were the neighborhoods of Möllevången and Nydala in Malmö, Farsta and Rågsved in Stockholm, and Fröslunda and Årby in Eskilstuna. The French data were collected in the La Plaine area in Marseille; in La-Chapelle-Saint-Luc, Saint-Andre-Les-Vergers and Les Chartreux in Troyes; and in Guillotière in Lyon.\n\nAcross these sites shared methods were used in data collection, consisting of thematic interviews, walking interviews, and observations. The dataset emphasizes the diversity of experiences and the manifestations of distinctions in diverse urban environments and examines the ways in which people form bonds in relation to each other, their neighborhoods, and the broader society.\n\nThe first set of participants were located through social media groups (Facebook), from the premises of associations organizing community activities in the areas, libraries, cafes, community events, and youth centers. After this, snowball sampling was used, in addition to which targeted recruitment was applied if a population group represented in the area was completely missing from the dataset. Ethnographic observations were conducted in public spaces, community centres, cafés, stations, and shopping centres that were selected as potentially interesting places based on extant scholarship on living with difference and urban encounters. Here, attention was paid at how people used these sites, who were there and who were absent, as well as how people moved in and across the sites. Notes were made of what kinds of encounters, patterns of behaviour, cooperations, and conflicts occurred. These observations were made at various times of the day, to capture potential temporal changes. This resulted in a rich collection of fieldnotes, sketches, photographs, and movement maps. The interview outline and ethnographic observation matrix are attached as part of the metadata.\n\nEmergentCommunityVR (dataset 2):\n\nData collection was conducted in Helsinki, Marseille, and Malmö. The data was collected using 360-degree videos based on the aforementioned ethnographic data as stimuli to which participants were exposed. A separate video was created for each city, using specifically the data collected therein. We put together a mobile laboratory set-up that travelled to each city and collaborated with local NGOs whose premises were used as our laboratory space. The equipment and software used are explained in the document \"EmergentCommunity mobile laboratory.pdf\".\n\nThe inclusion criteria for participation were: being a major, healthy, not having hearing or vision impairments, being a resident in the city that the video depicted, and knowledge of the local language in which the video was executed. During the viewing of the video stimulus, participants' physiological responses were measured and their eye movements were tracked. VR eye tracking was used as it enables the precise analysis of gaze behaviour – such as fixations and saccades – within immersive, ecologically valid environments. Regarding physiological signals, the focus was on the electrical activity of the heart using electrocardiography (ECG), the electrical activity of the facial muscles using facial electromyography (fEMG), and the electrical conductivity of the skin using galvanic skin response (GSR). To complement the physiological data, a multimodal setup was established to assess the affective content of the stimulus in terms of arousal/valence, avoidance/approach, and unpredictability. After viewing, the participants were asked to evaluate the intensity of their emotional experience and to name the emotional reactions elicited by the video using a questionnaire carried out with Gorilla Experiment Builder. The questionnaire also contained background questions, from basic participant information, such as age and gender, to aspects that relate to diversity and inequality in contemporary societies: language, income, housing, education, political activity, participation, as well as political opinions and social values. After completing the measurements and the questionnaire, participants were interviewed about their experience and the thoughts it provoked, and they were asked to share information regarding their daily lives.\n\nThe purpose of the dataset was to help understand the formation of emotional experiences and the significance and functioning of emotions in the everyday life of increasingly diverse and unequal cities. The call for participation was distributed in several thematic Facebook groups (related to e.g., urban development, multiculturalism, neighborhood, local NGOs and minority communities) and via Instagram, as well as through flyers/posters in libraries, local associations, shopping centers, cafes, and on the project's Facebook page and Instagram profile. In the case of Marseille and Malmö, local assistants were used to spread the invitation within their networks and distribute participation invitation leaflets on the streets. In each city, it was possible for already registered participants to invite additional participants as well. Overall, the goal was to ensure the representativeness of the data in terms of age, gender, and minority status. The content of the video stimuli, questionnaire, and interview outline have been attached as part of the metadata.\n\nPurpose of the data\n\nThe EmergentCommunity project aimed at producing knowledge about what community means and how it is formed in increasingly diverse societies, as well as the conflicts and tensions that everyday life brings out. The project empirically examined the concrete challenges that societal changes produce for cities and coexistence. The aim was to identify how peaceful coexistence could be supported and population relations promoted in urban everyday life. The project emphasized that community relations and everyday coexistence are affective, social, and spatial phenomena, which is why a wide range of research methods from ethnography and observation to psychophysiological measurements and interviews were applied. These approaches were brought into dialogue through virtual reality by utilizing ethnography-based 360-degree videos depicting everyday life in the latter part of the project (EmergentCommunityVR). Thus, the project created new understanding of emotions formed in everyday life and produced unique knowledge in the fields of psychological and sociological emotion research. Bringing these areas together enabled a critical examination of the concept of community and the identification of the practices and ways in which communities are produced in the everyday life of diverse and unequal cities (see CORDIS database for public description, results, and reporting: https://cordis.europa.eu/project/id/946012).\n\nThroughout the data collection, the research focused on everyday life and the forms, practices, and interpretations of everyday coexistence in public urban spaces in the selected research neighbourhoods. Participants were also asked to share their experiences, interpretations, and views on societal change and how the change has been visible in their own neighborhoods and what thoughts and feelings it evokes in them. The data was formed through non-probability sampling (self-formed sample).\n\nThese countries were selected by examining statistics, policy reports, and available data on demographic changes and diversity, income inequality, trends of residential and ethnic segregation in different countries and cities (desk research). We chose the countries and cities so that they would complement each other and that changes were observable in each selected context, although their forms, emphases, and manifestations might vary. After this extensive background review, we focused on the city level, complementing the available statistical data with news articles and reports and analyses related to urban areas and development. This allowed us to identify pockets of diversity and inequality within each city. Finally, study neighborhoods were selected based on them having undergone urban development projects, being targeted with anti-segregation measures, their residents' socio-economic backgrounds being diverse, and several dimensions of inequality (regarding education level, employment rate, income level) being present in the areas.\n\nThe total size of the data\n\nThe dataset consists of desk research data made up of 960 files (reports, news articles, anonymized social media discussions), amounting to 4Gb. The data were used to identify the research sites and set the collected data within the broader socio-political context.\n\nEmergentCommunityEthno data consists of 142 recorded interviews with 185 people that amount to 118 hours of talk, and 2214 pages of transcribed material (+ 31 interviews collected with the EKOS project, archived separately in FSD, ). In addition to the interviews, the data includes 338 pages of fieldnotes, 1974 photographs/videos, and 63 sketches/maps. \n\nEmergentCommunityVR data includes 3 ethnography-based 360-degree video stimuli (length approximately 7:30 minutes/video) and 198 recorded interviews with 200 participants amounting to 116 hours of talk, 2017 pages of transcribed data. The size of the physiological and eye-tracking data is 294 Gb, and ~30Mb for the questionnaire answers; this data was collected from 197 participants.",
"fi": "Tutkimuksessa kerätty aineisto käsittelee rinnakkaiselon ja konfliktien dynamiikkaa yhä monimuotoisemmissa kaupungeissa ihmiskeskeisestä näkökulmasta. Aineisto kerättiin osana EU-rahoitteista projektia \"Coexistence and Conflict in the Age of Complexity\" (EmergentCommunity) yhdeksässä Euroopan kaupungissa Suomessa, Ranskassa ja Ruotsissa. Aineisto koostuu kahdesta osasta: EmergentCommunityEthno (laadullinen aineisto) ja EmergentCommunityVR (määrällinen ja laadullinen aineisto). Lisäksi tehtiin kirjallisuuskatsaus (Desk research). Lista tutkimushankkeen aikana kerätiystä aineistoista löytyy Zenodosta (https://doi.org/10.5281/zenodo.15108328 ).\n\nTutkimuksen kohdemaat valittiin tarkastelemalla tilastoja, politiikkaraportteja ja saatavilla olevia tietoja väestönmuutoksista ja monimuotoisuudesta, tuloeroista, asuin- ja etnisen segregaation trendeistä eri maissa ja kaupungeissa (kirjallisuuskatsaus). Valitsimme maat ja kaupungit niin, että ne täydentäisivät toisiaan ja että muutokset olisivat havaittavissa kussakin valitussa kontekstissa, vaikka niiden muodot, painotukset ja ilmenemismuodot vaihtelisivat. Tämän laajan taustakatsauksen jälkeen keskityimme kaupunkitasoon, täydentäen saatavilla olevia tilastotietoja uutisartikkeleilla ja raporteilla sekä analyyseillä, jotka liittyvät kaupunkialueisiin ja kehitykseen. Tämä mahdollisti monimuotoisuuden ja eriarvoisuuden taskujen tunnistamisen kussakin kaupungissa. Lopuksi tutkimusnaapurustot valittiin sen perusteella, että niissä oli toteutettu kaupunkikehityshankkeita, niihin oli kohdistettu segregaation vastaisia toimenpiteitä, niiden asukkaiden sosioekonomiset taustat olivat monimuotoisia ja alueilla oli useita eriarvoisuuden ulottuvuuksia (koulutustaso, työllisyysaste, tulotaso).\n\nEmergentCommunity-projektin tavoitteena oli tuottaa tietoa siitä, mitä yhteisö tarkoittaa ja miten se muodostuu yhä monimuotoisemmissa yhteiskunnissa, sekä erilaisista arjen konflikteista ja jännitteistä. Projekti tutki empiirisesti yhteiskunnallisten muutosten tuomia konkreettisia haasteita kaupungeille ja rinnakkaiselolle. Tavoitteena oli tunnistaa, miten rauhanomaista rinnakkaiseloa voitaisiin tukea ja väestösuhteita edistää kaupunkien arjessa. Projekti korosti, että yhteisösuhteet ja arjen rinnakkaiselo ovat affektiivisia, sosiaalisia ja tilallisia ilmiöitä, minkä vuoksi hankkeessa sovellettiin laajaa valikoimaa tutkimusmenetelmiä etnografisesta havainnoinnista psykofysiologisiin mittauksiin ja haastatteluihin. Näitä lähestymistapoja tuotiin yhteen virtuaalitodellisuuden kautta hyödyntämällä etnografiaan perustuvia 360°-videoita. Näin projekti loi uutta ymmärrystä arjessa muodostuvista tunteista ja tuotti ainutlaatuista tietoa psykologiseen ja sosiologiseen tutkimukseen tunteista. Tällainen näkökulmien yhdistäminen mahdollisti kriittisen tarkastelun yhteisön käsitteestä sekä niiden käytäntöjen ja tapojen tunnistamisen, joilla yhteisöt muodostuvat monimuotoisten ja eriarvoisten kaupunkien arjessa (katso CORDIS-tietokanta julkista kuvausta, tuloksia ja raportointia varten: https://cordis.europa.eu/project/id/946012).\n\nKoko datankeruun ajan tutkimus keskittyi arkeen ja arjen rinnakkaiselon muotoihin, käytäntöihin ja tulkintoihin valittujen naapurustojen julkisissa kaupunkitiloissa. Osallistujia pyydettiin myös jakamaan kokemuksiaan, tulkintojaan ja näkemyksiään yhteiskunnallisesta muutoksesta sekä siitä, miten muutokset ovat näkyvissä heidän omissa naapurustoissaan ja mitä ajatuksia ja tunteita se herättää heissä. Data muodostettiin ei-satunnaisotannalla (itse muodostettu otos).\n\nEmergentCommunityEthno (aineisto 1):\nOsallistujat olivat yli 15-vuotiaita, tutkituilla kaupunkialueilla asuvia tai niiden julkisia tiloja käyttäviä henkilöitä. Suomessa data kerättiin Tampereen Peltolammin ja Multisillan kaupunginosissa, Helsingin Malmilla sekä Hyvinkään Martissa ja Paavolassa. Tampereella osa haastatteluaineistosta (31 haastattelua) kerättiin yhteistyössä EKOS-tutkimusprojektin kanssa (tämä osa datasta on kuvattu ja arkistoitu Tietoarkistossa, https://doi.org/10.60686/t-fsd3816) Toinen osa datasta kerättiin Ruotsissa. Datankeruupaikat siellä olivat Malmön Möllevången ja Nydala, Tukholman Farsta ja Rågsved sekä Eskilstunan Fröslunda ja Årby. Ranskassa data kerättiin Marseillen La Plaine -alueella, Troyes'n La-Chapelle-Saint-Luc, Saint-Andre-Les-Vergers ja Les Chartreux'ssa ja Lyonin Guillotièressä.\n\nAineistokeruussa käytettiin temaattisia haastatteluita, kävelyhaastatteluita ja havainnointia. Aineisto korostaa kokemusten monimuotoisuutta ja erojen ilmenemistä monimuotoisissa kaupunkiympäristöissä osoittamalla, miten ihmiset muodostavat siteitä toisiinsa, naapurustoihinsa ja laajempaan yhteiskuntaan.\n\nOsallistujajoukko löydettiin ensin sosiaalisen median ryhmistä (Facebook), alueilla toimivien yhdistysten tiloista, kirjastoista, kahviloista, yhteisötapahtumista ja nuorisokeskuksista. Tämän jälkeen käytettiin lumipallo-otantaa. Lisäksi sovellettiin kohdennettua rekrytointia, jos jokin alueella edustettu väestöryhmä puuttui kokonaan aineistosta. Etnografiset havainnot tehtiin julkisissa tiloissa, yhteisökeskuksissa, kahviloissa, asemilla ja ostoskeskuksissa, jotka valittiin potentiaalisesti kiinnostaviksi paikoiksi olemassa olevan tutkimuksen perusteella. Huomiota kiinnitettiin siihen, miten ihmiset käyttivät näitä paikkoja, ketkä olivat siellä ja ketkä puuttuivat. Lisäksi havainnoitiin ihmisten liikkumista paikoissa ja niiden välillä. Muistiinpanoja tehtiin kohtaamisista, käyttäytymismalleista, yhteistyöstä ja konflikteista. Havainnot tehtiin eri vuorokaudenaikoina, jotta mahdolliset ajalliset muutokset saatiin talteen. Tämä johti rikkaaseen kokoelmaan kenttämuistiinpanoja, luonnoksia, valokuvia ja liikkumiskarttoja. Haastattelurungot ja etnografinen havainnointimatriisi on liitetty osaksi metatietoja.\n\nEmergentCommunityVR (aineisto 2):\nAineistonkeruu tehtiin Helsingissä, Marseillessa ja Malmössä. Data kerättiin käyttämällä 360°-videoita, jotka perustuivat edellä mainittuun etnografiseen aineistoon, Videot toimivat osallistujia altistavina ärsykkeinä mahdollistaen osallistujien psykofysiologisten reaktioiden mittausten. Kussakin kaupungissa käytetiin kyseisessä kaupungissa kerättyä dataa ja siihen pohjautuvaa videota. Osallistumiskriteerit olivat: täysi-ikäisyys, terveydentila, ei kuulo- tai näkövammaa, asuminen videossa kuvatussa kaupungissa ja paikallisen kielen tuntemus.\n\nVideon katselun aikana mitattiin osallistujien fysiologisia reaktioita ja seurattiin heidän silmänliikkeitään. VR-lasien silmänliikeseurantaa käytettiin jäljittämään osallistujien katsekäyttäytymistä. Fysiologisten signaalien osalta keskityttiin sydämen sähköiseen toimintaan (elektrokardiografia, EKG), kasvojen lihasten sähkönjohtavuuteen (elektromyografia, fEMG) ja ihon sähkönjohtavuuteen (galvaninen ihoreaktio, GSR). Fysiologisen datan validioimiseksi luotiin multimodaalinen matriisi, jolla arvioitiin ärsykkeen affektiivista sisältöä virittyneisyyden/valenssin, välttämisen/lähestymisen ja ennakoimattomuuden osalta. Katselun jälkeen osallistujia pyydettiin arvioimaan emotionaalisen kokemuksensa intensiteettiä ja nimeämään videon herättämät emotionaaliset reaktiot kyselylomakkeella, joka toteutettiin Gorilla Experiment Builderilla. Kyselylomake sisälsi myös taustakysymyksiä osallistujan perustiedoista, kuten ikä ja sukupuoli, sekä monimuotoisuuteen ja eriarvoisuuteen liittyviä yhteiskunnallisia muuttuja (kieli, tulot, asuminen, koulutus, poliittinen toiminta, osallistuminen sekä poliittiset asenteet ja sosiaaliset arvot). Mittausten ja kyselylomakkeen täyttämisen jälkeen osallistujia haastateltiin heidän katselukokemuksestaan ja videon herättämistä ajatuksista. Lisäksi heitä pyydettiin jakamaan tietoa päivittäisestä elämästään.\n\nAineiston tarkoitus oli auttaa ymmärtämään emotionaalisten kokemusten muodostumista ja tunteiden merkitystä ja toimintaa yhä monimuotoisempien ja eriarvoisempien kaupunkien arjessa. Osallistumiskutsua jaettiin useissa Facebook-ryhmissä (liittyen esimerkiksi kaupunkikehitykseen, monikulttuurisuuteen, naapurustoon, paikallisiin kansalaisjärjestöihin ja vähemmistöyhteisöihin) ja Instagramissa, sekä lentolehtisten/julisteiden kautta kirjastoissa, paikallisissa yhdistyksissä, ostoskeskuksissa, kahviloissa ja projektin Facebook-sivulla ja Instagram-profiilissa. Marseillen ja Malmön tapauksessa käytettiin paikallisia avustajia kutsun levittämiseen heidän verkostoissaan ja osallistumiskutsujen jakamiseen kadulla. Jokaisessa kaupungissa oli mahdollista, että jo rekisteröityneet osallistujat kutsuivat lisää osallistujia. Tavoitteena oli varmistaa datan edustavuus iän, sukupuolen ja vähemmistöaseman suhteen. Videoiden, kyselylomakkeen ja haastattelurungon sisältö on liitetty osaksi metatietoja.\n\n\nAineiston kokonaiskoko\nAineisto koostuu kirjallisuuskatsauksen datasta, joka sisältää 960 tiedostoa (raportteja, uutisartikkeleita, anonymisoituja sosiaalisen median keskusteluja), yhteensä 4Gb. Dataa käytettiin tutkimuskohteiden tunnistamiseen ja kerätyn datan asettamiseen laajempaan yhteiskunnalliseen kontekstiin. EmergentCommunityEthno koostuu 142 nauhoitetusta haastattelusta, jotka sisältävät 118 tuntia puhetta ja 2214 sivua litteroitua materiaalia. Haastattelujen lisäksi data sisältää 338 sivua kenttämuistiinpanoja, 1974 valokuvaa/videota ja 63 luonnosta/karttaa. EmergentCommunityVR sisältää kolme etnografiaan perustuvaa 360' videota (kesto noin 7:30 minuuttia/video), jotka toimivat ärsykkeinä fysiologisissa mittauksissa. Fysiologisen datan ja silmänliikeseurantadatan koko on yhteensä 294Gb ja niihin liittyvät kyselyvastaukset noin 30 Mb. Mittausten jälkeen suoritetttin osallistujien haastattelut (197 kpl) yhteensä 200 osallistujan kanssa (116 tuntia puhetta, 2017 sivua litteroitua dataa)."
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],
"infrastructure": [],
"issued": "2025-03-11",
"keyword": [
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"human migration",
"social segration",
"cultural diversity",
"interdisciplinary studies",
"interdisciplinary research/methods",
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"en": "A dataset of images from a drone imaging missions in Brattnäsviken, Parainen, Finland by Turku University of Applied Sciences in 2025. The area was photographed in two parts due to weather conditions.\n\nThe dataset consists of a drone data table, an orthomosaic image and ODM Quality Report.\n\nThe drone data table includes information about the flight: shooting location, municipality, date, drone, shooting height, shooting direction, front overlap ratio, side overlap ratio, operator, processing in OpenDroneMap (yes/no), orthomosaic (yes/no), surface model (yes/no), 3D model (yes/no), GPS error (RMS), coordinate system, project, file location of aerial survey images, file location of the orthomosaic image and the ODM Quality Report, information whether the orthomosaic image has been clipped (yes/no) and project.\n\nThe orthomosaic image is based on aerial survey images and made with WebODM Drone Software.\n\nThe ODM Quality Report is a report on the processing of the aerial survey images."
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"title": {
"en": "Drone image dataset: Brattnäsviken 26.3.2025 and 30.3.2025"
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"name": "Katja Ikonen"
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"data_catalog": "urn:nbn:fi:att:data-catalog-att",
"description": {
"en": "Wildlife triangle data, winter census Species-specific annual snow-track counts and average snow-track abundance indices in 50 × 50 km grid cells. The snow-track abundance index for a wildlife triangle (a ~12 km line transect) is calculated as N / (km_counted × snow_days). Here N is the number of snow-tracks crossing the transect line. The denominator stands for counting effort, consisting of the kilometers counted (km_counted) multiplied with the number of days during which tracks have accumulated (snow_days). The snow days are counted from last snowfall, or from the timing of a pre-mapping of snow-tracks, which prevents from recounting the tracks during the actual survey. The presented index for a given species, year and grid cell is calculated as the arithmetic mean index over all triangles, whose point of gravity are within the focal grid cell. In addition to the species-specific average abundance indices, also the number of snow tracks recorded, and the number of triangles counted are reported. The grid is constructed according to the ETRS-TM35FIN -coordinate system and the grid cell locations are given using the lower left corner coordinates (“lon” and “lat”).\n\nCoverage basis: threatened and invasive mammal species in the winter track counts, excluding the large carnivores.\n\nData embargo period: 3 years\n\nData quality: Professional / professionally curated (monitoring scheme)\n\nMethods: Line-transect census of snow tracks. The transect is ca 12 km long, shaped as an equilateral triangle and located in boreal forest landscape. The survey is done during one day by volunteers, mainly local hunters, skiing or walking along the transect. The survey period starts the 15th January and ends on the 28th February in the southern and central parts of Finland. In the northern parts of Finland (Oulu region and Lapland) the period continues until 15th March.\n\nTaxonomic coverage: Siberian flying squirrel (Pteromys volans); http://tun.fi/MX.48243 Muskrat (Ondatra zibethicus); http://tun.fi/MX.48537 Raccoon dog (Nyctereutes procyonoides); http://tun.fi/MX.46564 American mink (Neovison vison); http://tun.fi/MX.47243 European polecat (Mustela putorius); http://tun.fi/MX.47240 White-tailed deer (Odocoileus virginianus); http://tun.fi/MX.47629",
"fi": "Luonnonvarakeskus (Luke) seuraa riistakantojen muutoksia metsämaastossa ympäri maata riistakolmioiden avulla sekä kesäisin että talvisin. Seuranta perustuu vapaaehtoisten tärkeään työpanokseen. Riistakolmiot ovat pysyviä metsäriistan runsauden seurantaa varten perustettuja laskentareittejä. Riistakolmio on tasasivuinen kolmio, jonka sivu on 4 km, ja siten laskentalinjan kokonaispituus on 12 km. Kolmiot säilyvät samoina vuodesta toiseen. Peltokolmioilla tehdään vain talvista lumijälkilaskentaa, soveltaen samaa menetelmällä kuin riistakolmioilla.\n\n## Riistakolmioiden kesälaskenta\nKesälaskennassa lasketaan kanalintujen (metso, teeri, riekko, pyy) tiheys, muutosprosentti edelliseen vuoteen, runsausindeksi, poikasosuus ja poikuekoko. Lisäksi kirjataan havainnot sepelkyyhkystä, lehtokurpasta ja metsäjäniksestä sekä kaikki karhua koskevat havainnot: näköhavainnot, jäljet, jätökset, kynsimiset, jne.\n\n## Kesälaskennan muuttujat\n\n### Tiheys (T)\nKanalinnut lasketaan 60 m leveältä pääkaistalta. Tiheys ilmaistaan lintujen lukumääränä metsämaan neliökilometriä kohti.\n\nT = N / 0,06 L\n\nN = havaittujen lintujen lukumäärä, L = laskentalinjan pituus (km), vakio 0,06 on laskentakaistan leveys (km)\n\nesim. 8 teertä: 8 teertä / (0,06 km * 12 km) = 11,11 teertä/km^2\n\n### Muutos (M) =Tiheyden prosenttinen muutos edellisvuodesta.\n\nM = 100 (T(v) – T(v-1)) / T(v-1)\n\nT(v) = kuluvan vuoden ja T(v-1) = edellisvuoden tiheys.\n\n### Runsausindeksi (I)\nVuoden runsausindeksi on tiheyden poikkeama kauden 1990-95 keskiarvosta, jolle on annettu arvo 100. Huomaa, että tämä tunnusluku poikkeaa vesilintulaskennassa käytetystä runsausindeksistä siten, että tässä vertailuluvun ”perustasoksi” on määritetty vuosien 1990-95 keskiarvo.\n\nI = 100 T(v) / TK\n\nT(v) = tarkasteltavan vuoden tiheysarvo ja TK tiheyden keskiarvo kaudelta 1990-95.\n\n### Poikasosuus\nPoikaslintujen prosenttiosuus kaikista havaituista linnuista.\n\n### Poikuekoko\nPoikasten keskimääräinen lukumäärä havaituissa poikueissa.\n\nKesälaskennassa kanalintutiheydet lasketaan suoraan laskentakaistan pinta-alan avulla. Tämä johtaa lievään aliarvioon, sillä kaikkia laskentahetkellä linjalla olevia yksilöitä ei havaita (linnut väistävät lähestyvää laskijarintamaa). Ruotsalaistutkimuksen mukaan aikuisista metsoista ja teeristä (koiraat, poikueettomat naaraat) havaitaan noin 60 %; poikueet emoineen löydetään paljon tehokkaammin, lähes 100 %:n todennäköisyydellä.\n\nKanalintulaskentatuloksen lievää aliarviota alueellisissa lintumäärissä kompensoi se, että riistakolmiot sijaitsevat lievästi keskimääräistä puustoisemmilla alueilla. Seurantaan nämä virhetekijät eivät vaikuta, sillä niiden voimakkuus lienee samansuuruinen vuodesta toiseen.\n\n\n## Riista- ja peltokolmioiden talvilaskenta\nTalvilaskennassa (riista- ja peltokolmioilla) lasketaan lumijälki-indeksi. Talvilaskennassa lasketaan kolmiolinjan ylittävien lumijälkien lukumäärä seuraavista lajeista: metsäjänis, rusakko, orava, liito-orava, majava, piisami, susi, kettu, naali, supikoira, karhu, kärppä, lumikko, minkki, hilleri, näätä, ahma, mäyrä, saukko, ilves, villisika, valkohäntäpeura, hirvi, metsäpeura ja metsäkauris. Lisäksi merkitään näköhavainnot metsosta, teerestä, pyystä, riekosta, peltopyystä, fasaanista, kanahaukasta ja korpista.\nIndeksi kolmiolle lasketaan seuraavasti: N / (km_laskettu × lumipäiviä). Tässä N on laskentalinjan ylittävien lumijälkien lukumäärä. Nimittäjässä suluissa on laskentapanostus, joka saadaan lasketun kilometrimäärän (km_laskettu) ja jälkien kertymäpäivien (lumipäiviä) tulona. Lumipäivät lasketaan edellisestä lumisateesta tai ns. esikierrosta, jolloin laskija on kartoittanut vahat lumijäljet, jotta ei laskisi niitä uudestaan varsinaisessa laskennassa. \n\n## Talvilaskennan muuttujat\n\n### Jälki-indeksi (J)\nJälki-indeksi mittaa eläinten jälkitiheyttä maastossa ja se kuvaa tietyin varauksin lajin runsautta. Jälki-indeksi on laskentalinjan ylittävien jälkien lukumäärä kymmentä kolmiolinjan kilometriä ja vuorokautta kohti.\n\nJ = 10 N / (L T)\n\nN = ylitysjälkien lukumäärä, L = laskentalinjan pituus (km), T = jälkien kertymäaika (vrk).\n\n### Muutos (M)\nJälki-indeksin prosenttinen muutos edellisvuodesta.\n\nM = 100 (J(v) – J(v -1)) / J(v-1)\n\nv = vuosi\n\n### Runsausindeksi (I)\nVuoden runsausindeksi on jälki-indeksin poikkeama kauden 1990-95 keskiarvosta, jolle on annettu arvo 100.\n\nI = 100 J(v) / JK\n\nJ(v) = tarkasteltavan vuoden jälki-indeksi ja JK = jälki-indeksien keskiarvo kaudelta 1990-95.\n\n### Lumijäljen muuttaminen tiheydeksi\nLaskentalinjan ylittävien jälkien määrän riippuvuus jälkimäärästä tietyllä alueella, tai yleisimmin linjaleikkausten määrän riippuvuus viivan kokonaispituudesta, on tunnettu kauan erilaisina sovelluksina monilla aloilla. Tässä yhteydessä, ylitysjälkien määrän suhteesta eläintiheyteen, on tärkeä erottaa ongelman matemaattinen ja biologinen osatekijä. Biologinen osa tehtävää on vastata kysymykseen, kuinka monta eläinyksilöä on jättänyt havaitun ylitysjälkimäärän.\n\nEntisessä Neuvostoliitossa on tutkittu jo 1930-luvulta lähtien eläintiheyden arviointia lumijälkimäärien pohjalta. Alun perin kokeilun kautta syntyi ratkaisu, joka nykyään tunnetaan muodossa T = 1,57 × S / (M × D), jossa S on ylitysjälkien lukumäärä vuorokaudessa, M laskentalinjan pituus ja D lajin keskimääräinen kulkumatka vuorokaudessa. Yhtälön vakio 1,57 on ”tilatekijä” eli π / 2.\n\nYhtälön ainoa muuttuja, jota ei saada suoraan laskentatapahtumasta on D, lajin keskimäärin vuorokaudessa kulkema matka. Mallin oletuksia ovat jälkikuvion satunnaisuus, ylitysten toisistaan riippumattomuus, kaikkien ylitysjälkien laskenta erikseen ja se, että vuorokausijäljen pituus mutkineen on mitattu oikein suhteessa eläimen kokoon. Vuorokausijäljen pituus on mitattava maastotyönä. Siihen vaikuttavat joukko tekijöitä, jotka usein ovat huonosti tunnettuja. \n\n### Runsauslaskelmat pienille alueille\nSiitä huolimatta, että riistakolmiolaskenta on mittava seurantajärjestelmä, aineistopohja jää usein puutteelliseksi, kun halutaan laskea riistan runsautta pienillä alueilla. Sattumanvaraisen vaihtelun hallitseminen edellyttää vähintään noin 100 km laskentalinjaa, mutta mieluummin yli 300 km laskentalinjaa. Tarvittava otoskoko riippuu myös lajin runsaudesta ja alueellisesta vaihtelusta. Riistakolmiotiheys on vain poikkeustapauksissa niin suuri, että esimerkiksi kunta- ja riistanhoitoyhdistystasolle olisi suoraan käytettävissä riittävä laskenta-aineisto.\n\nRiistakolmioaineistosta on voitu osoittaa, että riistakantojen vaihtelut lähialueilla usein ovat samankaltaisia. Tämä havainto on luonut edellytykset laskennallisesti esittää runsaustietoa myös sellaisille rajallisille alueille, joilla riistakolmiolaskentaa ei ole tehty. Esimerkiksi kanalintutiheyden laskeminen riistanhoitoyhdistyksille tapahtuu siten, että kolmiokohtaisia tiheyksiä kerätään 50 km:n säteellä alueen keskipisteestä. Kohdealueen kattavan ympyrän alalta kolmiokohtaisille tuloksille annetaan painoarvo 1 (ne tulevat aineistoon sellaisenaan), kun taas kauempana sijaitsevien kolmioiden painoarvoa pienennetään suoraviivaisesti 50 km:n säteeseen saakka siten, että niiden merkitys pienenee etäisyyden kasvaessa. Painotettu tiheys (T) lasketaan seuraavasti:\n\nT = Σ (T[i] P[i] ) / Σ P[i], missä T[i] on kolmion i tiheys ja P[i] kolmion i painokerroin."
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