Taimede mitmekesisus Euroopas: vaadeldud ja tume elurikkus

Väitekirja elektrooniline versioon ei sisalda publikatsioone.Elurikkuse hoidmine on looduskaitse olulisemaid eesmärke. Traditsiooniliselt on kasutatud elurikkuse mõõdikuna mingil maa alal esinevate liikide arvu ehk liigirikkust. Kahjuks vaadeldes vaid liikide arvu, ei arvestata liigifondide varieerumist. Liigifondiks nimetatakse liikide kogumit, mis kas juba kuuluvad kooslusesse (vaadeldud liigirikkus), või võiksid sinna potentsiaalselt levida ja sealsetes ökoloogilistes tingimustes elada (tume elurikkus). Tume elurikkus täiendab vaadeldud liigirikkust. Kasutades tumeda elurikkuse käsitlust on võimalik leida ala täielikkuse indeks. Ala täielikkus näitab, kui suur osa liigifondist on tegelikult uurimisalal realiseerunud. Seetõttu tuleks täieliku elurikkuse pildi saamiseks lisaks vaadeldud liigirikkusele arvestada ka puuduolevate, kuid ökoloogiliselt sobivate liikidega ehk tumeda elurikkusega. Antud töö eesmärk oli kasutada tumeda elurikkuse kontseptsiooni, et hinnata taimede elurikkuse jaotust Euroopas. Tumeda elurikkuse leidmiseks rakendasime erinevaid matemaatilisi meetodeid ja pakkusime välja tumeda elurikkuse rakendusi looduskaitses ja invasiooniökoloogias. Antud töös leidsime, et tumeda elurikkuse levikumuster oli üldjoontes sarnane vaadeldud liigirikkusele, siis suured ning väikesed täielikkuse väärtused oli hajali üle kogu Euroopa. Me leidsime, et inimesega seotud tegurid mõjutasid nii vaadeldud liigirikkust kui ka täielikust enam kui keskkonnafaktorid. Kui võtame elurikkuse uuringutes arvesse ka vaatlusalale sobivaid, kuid hetkel puuduolevaid liike, saame paremini põhjustest, miks osad liigid on uurimisalal kohal, aga teised jäävad tumedasse elurikkusesse. Looduskaitsele võib olla eriti informatiivne täielikkuse indeks, kuna see hõlmab üheaegselt nii ala vaadeldud liigirikkuse kui ka tumeda elurikkuse.Preserving biodiversity is one of most important goals of nature conservation. Traditionally a number of species (observed species richness) has been used as measure of biodiversity. Unfortunately species richness as diversity metric could be insufficient due to co-variation of species pools. A species pool is defined as species which are already at the site (observed species richness) and species which could potentially disperse and tolerate local environmental conditions (dark diversity). Dark diversity complements commonly used observed species richness. Using the dark diversity concept, we can calculate the completeness of site diversity. Completeness of site diversity shows how much of the species pool is actually realized at the site. Therefore in order to get more complete picture we should also account also with dark diversity than using observed species richness alone. The purpose of this work was to use the dark diversity concept to quantify plant diversity at the European scale. We use different mathematical methods to estimate dark diversity and how dark diversity can be used in nature conservation and invasion ecology. In this work we found that dark diversity showed similar distribution patterns as observed species richness, although completeness of site diversity showed scattered pattern across Europe. We also found that anthropogenic factors associated more with both observed species richness and completeness of site diversity than natural factors. Accounting for absent but suitable species in biodiversity studies can improve our understanding of processes why we observe species as they are distributed nowadays and why some species remain in dark diversity. Especially completeness of site diversity can be a valuable metric in nature conservation as it accounts for both observed and dark diversity

Saaremaa jäätmekäitluse tulevik

https://www.ester.ee/record=b5486192*es

Spatially-Explicit Estimation of Geographical Representation in Large-Scale Species Distribution Datasets

<div><p>Much ecological research relies on existing multispecies distribution datasets. Such datasets, however, can vary considerably in quality, extent, resolution or taxonomic coverage. We provide a framework for a spatially-explicit evaluation of geographical representation within large-scale species distribution datasets, using the comparison of an occurrence atlas with a range atlas dataset as a working example. Specifically, we compared occurrence maps for 3773 taxa from the widely-used Atlas Florae Europaeae (AFE) with digitised range maps for 2049 taxa of the lesser-known Atlas of North European Vascular Plants. We calculated the level of agreement at a 50-km spatial resolution using average latitudinal and longitudinal species range, and area of occupancy. Agreement in species distribution was calculated and mapped using Jaccard similarity index and a reduced major axis (RMA) regression analysis of species richness between the entire atlases (5221 taxa in total) and between co-occurring species (601 taxa). We found no difference in distribution ranges or in the area of occupancy frequency distribution, indicating that atlases were sufficiently overlapping for a valid comparison. The similarity index map showed high levels of agreement for central, western, and northern Europe. The RMA regression confirmed that geographical representation of AFE was low in areas with a sparse data recording history (e.g., Russia, Belarus and the Ukraine). For co-occurring species in south-eastern Europe, however, the Atlas of North European Vascular Plants showed remarkably higher richness estimations. Geographical representation of atlas data can be much more heterogeneous than often assumed. Level of agreement between datasets can be used to evaluate geographical representation within datasets. Merging atlases into a single dataset is worthwhile in spite of methodological differences, and helps to fill gaps in our knowledge of species distribution ranges. Species distribution dataset mergers, such as the one exemplified here, can serve as a baseline towards comprehensive species distribution datasets.</p></div

Spatial autocorrelation, expressed as Moran’s <i>I</i>, with incrementing distance class for the full datasets of the Hultén & Fries atlas (dotted line) and AFE (solid line), and for the residuals of the reduced major axis model of the two (dashed line).

<p>Spatial autocorrelation, expressed as Moran’s <i>I</i>, with incrementing distance class for the full datasets of the Hultén & Fries atlas (dotted line) and AFE (solid line), and for the residuals of the reduced major axis model of the two (dashed line).</p

Species richness distribution and the maximum species richness per cell (N_max) for (a) records of the complete AFE (N_max = 643), (b) records of the complete Hultén & Fries atlas (N_max = 1149), (c) the merger of the two atlases (N_max = 1417) and (d) the intersection of species occurring in both atlases (N_max = 353).

<p>In each of the panels the relative species richness is illustrated using a seven-category scale legend, where a light grey tone indicates low species richness, and a dark grey tone indicates high species richness. Cells without species records were left empty. Projection: Albers equal-area conic.</p

Results of the <i>t</i>-tests of latitudinal and longitudinal ranges and area of occupancy of species.

<p>All tests were paired by species between the AFE and the Hultén & Fries atlas. A negative <i>t</i> value indicates that the AFE value was lower than that of the Hultén & Fries value.</p

Frequency distributions of the area of occupancy (number of grid cells occupied) and total species number (<i>n</i>) for (a) the complete AFE atlas (n = 3773), (b) the complete Hultén & Fries atlas (<i>n</i> = 2049), the intersection of species co-occurring in (c) AFE (<i>n</i> = 601) or (d) the Hultén & Fries atlas (<i>n</i> = 601), species exclusive to (e) AFE (<i>n</i> = 3172) or (f) the Hultén & Fries atlas (<i>n</i> = 1448).

<p>Frequency distributions of the area of occupancy (number of grid cells occupied) and total species number (<i>n</i>) for (a) the complete AFE atlas (n = 3773), (b) the complete Hultén & Fries atlas (<i>n</i> = 2049), the intersection of species co-occurring in (c) AFE (<i>n</i> = 601) or (d) the Hultén & Fries atlas (<i>n</i> = 601), species exclusive to (e) AFE (<i>n</i> = 3172) or (f) the Hultén & Fries atlas (<i>n</i> = 1448).</p

Results of the reduced major axis (RMA) regression analysis between AFE and the Hultén & Fries atlas for each of the four analytical categories.

<p>CI = Confidence interval of the value in the preceding column.</p