Nat ional Red List of Ecosyst ems/ Biot opes (RLE) work in Finland Lasse Kur vi nen Par ks & Wi l dl i f e Fi nl and Petra Pohjola
Background Finland is current ly working on t he nat ional Red • List of Biot opes, or ecosyst ems in IUCN language The last red list is f rom 2008 and covered only • 12 Balt ic underwat er biot opes and also f lads and gloes Now about 50 marine biot opes will be under • evaluat ion Aside f rom t he Balt ic underwat er biot opes, t he • biot opes are divided in t o coast al, f reshwat er, mire, f orest , bedrock, cult ural and f ell biot opes. All t oget her t here are over 400 biot opes t hat are being evaluat ed. Work is coordinat ed by t he Finnish Environment • Inst it ut e (SYKE)
Balt ic t eam • The Balt ic Sea group consist ing of expert s f rom e. g. Parks & Wildlif e Finland, Finnish Environment Inst it ut e, The Geological Survey of Finland, Universit ies and consult ant s • Also invit ed expert s f or specif ic biot opes and consult at ion when needed • Meet ings more or less once mont h • A lot of work also bet ween meet ings • Access dat abase int erf ace developed by SYKE t o st ore and manage evaluat ions
Planned t ime t able 2016 2017 2018 • Biotope • • Results and All evaluations descriptions summaries by finished • Preparation of • biotope groups Justifications data • for evaluations Finishing of • Most of the • manuscrpit, Documenting evaluations editing, online of results finsihed version.. • End seminar and publication by Baltic team quite well on schedule! the end of the year
IUCN met hodology • The met hods used f or t he evaluat ion f ollows IUCNs Red List of Ecosyst ems (RLE) approach (Bland et al 2016). The assessment is based on f ive crit eria • The t ime f rames used f or crit eria A, C & D are past 50 and 100y (1750), t he coming 50y and a moving window of 50y around t he present • The t hreat cat egory will be t he one t hat is t he most severe
Biot opes under evaluat ion • HUB-classif icat ion has been used as basis, but some nat ional modif icat ions have been made • Biot opes have been assessed mainly wit hout using separat e subst rat es • Also some biot ope complexes will be assessed and “ habit at s” t hat have been modif ied f rom HUB or weren’ t in t he classif icat ion as such • Examples HUB: Habit at s dominat ed by: Fucus, Aquat ic mosses, Pot amoget on/ St uckenia, Zannichella/ Ruppia, Myriophyllum, Charales on sand/ gravel, Charales on mud, Naj as marina, Zost era marina, Ranunculus, Eleocharis, unat t ached Fucus, unat t ached Aegagropila linnaei, unat t chad Cerat ophyllum demersum, Myt ilidae, Hydroids, Macoma balt hica, Mya arenaria, Seasonal ice… • Biot ope complex: Coast al Lagoons (Flads and gloes), Est uaries, Reef s and sandbanks • Examples habit at s: Red algae communit ies, Nymphaeid communit ies, habit at s dominat ed by Hippuris species…
Dat a used • Concerning biot ope complexes t here has • Main dat aset used is t he HUB-classif ied been done and is being done VELMU video and dive dat a f rom 2005- improvement s on many N2000 habit at s, 2015 around 100 000 point s such as est uaries, reef s, sandbanks and • There is also dist ribut ion modelling coast al lagoons going on concerning many of t hese • Bent hic monit oring dat a biot opes • WFD dat a • Work is also being done t o classif y t he • dept h dist ribut ion dat a of Fucus et c. inf auna samples collect ed during t he • years. This will be done during t he Classif ied wat erbodies summer, t o be able t o include t he dat a • Hist orical sources when possible f or t he current work • VELMU species dat a has also been used, when HUB class has been missing
Example A crit eria • Hist orical dist ribut ion dat a of t en lacking • The declining dist ribut ion of biot opes has been approximat ed by making dist ribut ion models using current environment al paramet ers and comparing t he result s wit h models using e. g. Secchi-dept h values f rom 100 years ago • Fucus example decline of 60% in 100y -> VU • Somet imes need t o rely solely on expert opinion • Also speculat ions f or possible f ut ure changes wit h changes in salinit y et c. No calcuat ions of t en made
Example B crit eria • EOO Minimum convex polygon • AOO Number of 10x10km cells
Example C (abiot ic) • For crit eria C&D one needs t o st at e a collapse value f or t he variable used, in ESSI KESKINEN order t o calculat e t he relat ive severit y of t he decline • For wat ermosses we used changes in phot ic dept h • • Relat ive severit y (% ) = (Observed or We used t he current dat a f or t he predict ed decline / Maximum decline) × occurence and looked at t he min phot ic 100 dept h • where Observed or predict ed decline = We got a collapse value of 3. 5, which we Init ial value – Present or f ut ure value assumed would be needed t o keep t he mosses saf e f rom ice scraping and Maximum decline = Init ial value – • Collapse value We t hen calculat ed hist orical phot ic dept h f rom secchi values • We werer t hen able t o calculat e t he relat ive severit y f or t he biot ope
Example D (biot ic) • The number of species in t he Chara dominat ed habit at s has been declining • Base on expert knowledge, we assumed t he mean amount of dif f erent Chara species in t he biot ope now, in t he 1960s and in a collapsed st at e • It was est imat ed t hat in t he 1960s t here had been around 4 species on average per locat ion, now 2 and when collapsed 0-1 HELMI MENTULA • Wit h t hese values we were able t o calculat e t he relat ive severit y
Challenges • As we only assess biot opes dominat ed by species which are not int roduced, we can not assess e. g. polychet e bot t oms as t he dominat iing species are alien species • Even t hought t he knowledge of current dist ribut ions has increaed in t he past years, evaluat ions can st ill be dif f icult t o make -> need of expert knowledge
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