Browsing by Subject "GIS"
Now showing items 1-4 of 4
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(2015)Suomesta tavataan kaksi majavalajia: alkuperäinen euroopanmajava (Castor fiber) ja vieraslaji amerikanmajava (Castor canadensis). Euroopanmajava metsästettiin sukupuuttoon 1800–luvulla ja viimeinen euroopanmajava ammuttiin tiettävästi Sallan Eniönjoesta vuonna 1868. Vuonna 1935 aloitettiin majavien uudelleenistutukset 17 Norjasta tuodulla euroopanmajavalla. Vuonna 1937 Suomen majavakantaa vahvistettiin seitsemällä Amerikasta tuodulla amerikanmajavalla. Tahallisesta vieraslajin tuomisesta ei kuitenkaan ollut kyse, vaan vasta vuonna 1973 todettiin Castor-suvun koostuvan kahdesta eri lajista. Alueilla, joille istutettiin molempia lajeja, on jäljellä ainoastaan amerikanmajava. Syyt ovat edelleen epäselviä. Molempien lajien kannat ovat edelleen keskittyneet alkuperäisten istutusalueiden läheisyyteen, ja amerikanmajavakanta on muutamia poikkeuksia lukuun ottamatta saanut kasvaa ilman euroopanmajavan kilpailun vaikutusta. Jos lajien elinympäristövaatimukset ovat samat, eivät lajit voi esiintyä rinnakkain. Näin ollen on tärkeää tuntea molempien lajien elinympäristön käyttö mahdollisemman tarkkaan aluekohtaisesti ja ennakoida, johtaako majavalajien kohtaaminen kahden lajin rauhaisaan yhteiseloon vai mahdollisesti euroopanmajavan häviämiseen läntisestä Suomesta. Tutkimuksen tarkoituksena oli vertailla lajien elinympäristön vaatimuksia ja sitä kautta tuoda lisätietoa euroopanmajavan suojeluun. Tutkimusalueeksi valikoitui keskinen Pirkanmaan alue, missä lajien välinen etäisyys on ainoastaan 11 kilometriä linnuntietä. Aineisto koostuu vuoden 2013 Luonnonvarakeskuksen koordinoimista valtakunnallisten majavalaskentojen pesätiedoista sekä erilaisista paikkatietoaineistoista. Elinympäristönkäytön mallin muuttujat on tuotettu CORINE Land Cover 2012 (CLC2012), vuoden 2011 Valtakunnallisen Metsien Inventoinnin (VMI) ja Maanmittauslaitoksen maastotietokannan digitaalisiin paikkatietoaineistojen avulla. Alueelle luotiin 60 satunnaispistettä, jotka kuvaavat tarjolla olevaa elinympäristöä. Lajien elinympäristöjen käyttöä analysoitiin kahden logistisen regressioanalyysimallin avulla, joista ensimmäisessä tarkastellaan ydinaluetta (50m) ja toisessa elinpiiriä (1km). Analyyseissä verrattiin lajeja keskenään sekä satunnaispisteisiin. Ennen regressioanalyysejä tarkasteltiin muuttujien kolineaarisuutta Variance Inflation Factor:in (VIF) avulla, jonka jälkeen tarkasteltiin aineiston yhteensopivuuttaa mallin kanssa Akaiken informaatiokriteerin (AIC) avulla. Pienin AIC ilmaisee parhaan mallin korkeimman selitysasteen ja mallin yksinkertaisuuden (parsimonisuuden) kompromissina. Ydinalueella ei havaittu merkitseviä eroja elinympäristön vaatimuksissa lajien välillä. Majavien elinympäristönkäyttö ei kuitenkaan ollut satunnaista. Kuusen tilavuudella oli positiivinen vaikutus euroopanmajavan esiintymiseen ja lehtipuiden tilavuudella oli positiivinen vaikutus amerikanmajavan esiintymiseen verrattuna tarjolla olevaan ympäristöön. Elinpiirianalyyseissä lajien välillä havaittiin merkitseviä eroja, joissa euroopanmajava esiintyi alueilla, missä kuusen tilavuus ja sekametsän osuus oli suurempi verrattuna amerikanmajavan elinpiiriin. Kasvavalla kuusen tilavuudella, sekametsän osuudella sekä vesistöjen määrällä oli positiivinen vaikutus euroopanmajavan esiintymiseen ja rakennetuilla alueilla negatiivinen vaikutus euroopanmajavan esiintymiseen verrattaessa tarjolla olevaan ympäristöön. Amerikanmajavan elinympäristön käyttö ei poikennut satunnaisesta. Tulokset saattavat heijastaa rantavyöhykkeen metsäsukkession eri vaiheita, mutta on huomattava, että lajien välillä oli merkittäviä eroja. Elinympäristön muuttujat selittivät huomattavasti enemmän euroopanmajavan esiintymistä alueella verrattuna amerikanmajavaan. Toisin sanoen euroopanmajavan elinympäristön vaatimukset ovat spesifimmät/tarkemmat/ominaisemmat. Tulosten avulla on mahdollista ennustaa niin amerikanmajavan leviämistä alueella kuin hyödyntää tietoja euroopanmajavalle tärkeiden elinympäristöjen suojelussa.
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(2023)Deforestation is the main threat to biodiversity, ecological integrity and socio-ecological resilience of the of the Amazon biome, one of the most biodiverse places on Earth and home to at least 2 million people. A complex network of diverse protection strategies exists across the Amazon as key component of the global strategy to halt biodiversity loss. Biosphere reserves are a part of this network that aims to create spaces to learn how human communities can develop sustainably, while the protecting the environment, by implementing a zonation system with different degrees of protection We consider that it is necessary to produce relevant efficiency assessments on area-based conservation strategies in this region, and to understand how different protection strategies affect conservation outcomes. We used state-of-the-art matching methods to create a counterfactual deforestation avoidance measure of seven Biosphere reserves the western Amazon: Yasuní, Podocarpus-El Cóndor, Sumaco, Manu, BIOAY, Pilón Lajas and Beni. We obtained diverse efficiency results, some of the studied reserves avoiding large quantities of deforestation to reserves that were attracting deforestation. We found that more strictly protected zones were subjected to significatively lower relative pressure levels and did not have higher deforestation avoidance values. Representativity of the matched treatment area was also lower for these zones, meaning that the matching analysis was more difficult to perform in these areas. These research findings add to growing evidence about the important role of biosphere reserves in buffering against deforestation in one of the world’s most important biodiversity hotspots.
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(2021)This study aimed to identify conservation landscapes with potential to be mutually beneficial for people and African savanna elephants (Loxodonta africana) in South Africa through spatial conservation planning analyses that integrate ecological and socioeconomic data. The research questions were: (i) what are the most ecologically suitable areas for the reintroduction of elephants, and (ii) which of these areas provide the best opportunities for also sustaining socioeconomic development of local people. The first question was answered with an ecological model that predicts habitat suitability for elephants, developed by a combination of literature review, expert opinion, and GIS-based methods. The second question was answered by combining the ecological model with socioeconomic criteria in Zonation spatial conservation planning software. The results show that the central part of South Africa holds most potential for elephant conservation as it has the largest uniform area of high-quality habitat, while the area also meets the socioeconomic criteria. The priority areas for the conservation of elephants were classified into top priority classes of 1%, 2%, 5%, 10% and 20%. The identified areas hold an unrealized opportunity in the wildlife and ecotourism sectors, and the reintroduction of elephants to those areas could provide the foundation for long-term economic activity of local communities e.g. in the form of elephant-based ecotourism, while contributing to the conservation of elephants. Conserving just the top 5% priority areas would grow South African protected area estate by approximately three million hectares and increase the current elephant range by approximately 75%. Ideally, the results of this study could be used to inform the on-going decision-making process on where to allocate resources for elephant conservation in South Africa.
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(2022)Climate change and biodiversity loss are among the two most serious environmental issues humanity is currently facing. One way of mitigating climate change is to build more wind energy. In Finland, upcoming wind farms are going to increase the national wind energy capacity by almost tenfold. As more wind farms are built, helping in climate change mitigation, the negative biodiversity impacts caused by wind turbines are also increasing. Negative biodiversity effects caused by wind energy include habitat loss, avian mortalities, habitat fragmentation and avoidance behaviour in wildlife. This conflict where two desirable environmental goals have negative counter-effect on each other can be called green-green dilemma. This thesis looks at the biodiversity impacts on habitats caused by wind farms in Finland, and what would be the scale of a habitat tax paid for displacing natural habitat, that would help solve the green-green dilemma. This thesis utilizes geographical information system data of upcoming and in production wind farms and habitats to figure out which habitats are displaced by wind farms in Finland. Also, a wind farm level cost-benefit analysis was done for wind farms in production determine a scale of taxes, which would make 10 % or 25 % of wind farms with lowest net present value compared to habitat impact non-profitable. Two kinds of taxes were considered. Tax based on the quantity of habitat displaced, and a tax based on the quality of habitat displaced. For the determination of the quality of habitat, European red list of habitats was utilized in creation of a prioritization system for different habitats based on their endangerment category. With the prioritization system, each wind farm was given habitat points based on the habitats it was displacing. According to the results of the thesis, wind farms in Finland are mostly displacing woodland habitats. The second most common habitat displaced was marine habitats and the third most common were mires, bogs and fens. According to the prioritization system created for this thesis, most habitats displaced by wind farms are not considered threatened. Still, there should be some consideration about the habitats displaced by wind farms, as minority of habitats were considered threatened according to the prioritization system. Also, we cannot draw too many conclusions about the status of the habitats displaced as the prioritization system has flaws. The two different taxes looked in this thesis both ended up making mostly the same wind farms non-profitable, meaning there were outlier wind farms with low benefits with relatively high habitat impacts. Quantity of habitats-based tax which made 10 % of the wind farms non-profitable was 1.6 million euros per hectare of displaced habitat, and the higher tax rate making 25 % of the wind farms non-profitable was 2.5 million euros per hectare. The habitat quality-based tax was 510,000 € per habitat point for lower rate, and 750,000 € per habitat point for the higher rate. On average, quality tax in Finnish wind farms would be 1.75 million euros with the lower rate per hectare of habitat displaced, and 2.3 million euros per hectare with the higher rate according to the calculations in this thesis. Habitat tax can be one solution for solving the green-green dilemma. Taxes presented in this thesis are considerable higher than habitat restoration costs estimated for Finland, which are approximately between 8000 € and 15000 € per hectare, depending on the habitat restored. Still, a habitat tax needs to be high enough to have an impact on the economic decision making of wind farm developers. If a tax habitat tax would be implemented, it would be best to think about the desired effect of the tax, which will affect the scale of the tax. Also, all kinds of activities displacing natural habitat should be included in the tax, not just displacement caused by wind farms for the tax to be more comprehensive.
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