Nat ional Red List of Ecosyst ems/ Biot opes (RLE) work in Finland - - PowerPoint PPT Presentation

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 2018 2017

• Biotope

descriptions

• Preparation of

data

• Most of the

evaluations finsihed

• All evaluations

finished

• Justifications

for evaluations

• Documenting
• f results
• Results and

summaries by biotope groups

• Finishing of

manuscrpit, editing, online version..

• End seminar and

publication by the end of the year

Baltic team quite well on schedule!

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

• Main dat aset used is t he HUB-classif ied

VELMU video and dive dat a f rom 2005- 2015 around 100 000 point s

• There is also dist ribut ion modelling

going on concerning many of t hese biot opes

• Work is also being done t o classif y t he

inf auna samples collect ed during t he

• years. This will be done during t he

summer, t o be able t o include t he dat a f or t he current work

• VELMU species dat a has also been used,

when HUB class has been missing

• Concerning biot ope complexes t here has

been done and is being done improvement s on many N2000 habit at s, such as est uaries, reef s, sandbanks and coast al lagoons

• Bent hic monit oring dat a
• WFD dat a
• dept h dist ribut ion dat a of Fucus et c.
• Classif ied wat erbodies
• Hist orical sources when possible

Example A crit eria

• Hist orical dist ribut ion dat a
• f 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
• n expert opinion
• Also speculat ions f or possible

f ut ure changes wit h changes in salinit y et c. No calcuat ions

• f 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

• rder t o calculat e t he relat ive severit y
• f t he decline
• Relat ive severit y (%

) = (Observed or predict ed decline / Maximum decline) × 100 where Observed or predict ed decline = Init ial value – Present or f ut ure value and Maximum decline = Init ial value – Collapse value

• For wat ermosses we used changes in

phot ic dept h

• We used t he current dat a f or t he
• ccurence and looked at t he min phot ic

dept h

• We got a collapse value of 3. 5, which we

assumed would be needed t o keep t he mosses saf e f rom ice scraping

• 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

ESSI KESKINEN

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

• Wit h t hese values we were able t o

calculat e t he relat ive severit y

HELMI MENTULA

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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