Miljø- og Fødevareudvalget 2020-21
MOF Alm.del Bilag 602
Offentligt
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The Environment and Food Committee
Biological reference conditions in Danish coastal waters
Criteria for seagrass restoration
Joao G. Ferreira
NOVA - Universidade Nova de Lisboa, Portugal
Copenhagen, 26
th
May 2021
http://ecowin.org/eelgrass
 MOF, Alm.del - 2020-21 - Bilag 602: Materiale fra Landbrug & Fødevarers foretræde for udvalget 26/5-21 om international forskerkritik af kvælstofmål fra Aarhus Universitet
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Objectives of the study
•
Analyse the approach proposed by Denmark in
its definition of reference conditions for eelgrass
•
Evaluate the relevance of the indicators chosen
for assessment of the status of this BQE
•
Examine the consistency and adequacy of the
measures proposed to enable the coastal
systems and fjords to meet the BQE reference
condition for eelgrass
Spatial
scope
Influencing
factors
Reference
conditions
Pressure-state
indicators
Criteria for N
loading targets
Consistent measures should be based on robust criteria, Adequate measures should succeed in
meeting the desired objectives for WFD ecological status (good or high).
 MOF, Alm.del - 2020-21 - Bilag 602: Materiale fra Landbrug & Fødevarers foretræde for udvalget 26/5-21 om international forskerkritik af kvælstofmål fra Aarhus Universitet
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WFD Biological Quality Elements (BQE) and indicators
•
Denmark selected eelgrass as representative of
the BQE
•
The reference condition is for distribution but not
for abundance, which was not quantified during the
early 1900’s survey work
•
Status assessment has been largely based on
eelgrass depth, i.e. related to water transparency.
Common eelgrass (the wildlife trust)
•
Water transparency was chosen as the primary indicator, but light penetration is not the
only factor limiting eelgrass recovery—eelgrass is subject to multiple stressors
There is a consensus in the Herman et al (2017) report and in my own review that the indicators
should be eelgrass abundance and composition. This is in the spirit of the WFD legislation.
 MOF, Alm.del - 2020-21 - Bilag 602: Materiale fra Landbrug & Fødevarers foretræde for udvalget 26/5-21 om international forskerkritik af kvælstofmål fra Aarhus Universitet
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Cause and Effect
Single-stressor model
Multi-stressor model
Nutrient
loading
Algae (chlorophyll)
Light
Warming
Eelgrass die-off
Light decrease
Space
Disease
Eelgrass die-off
Management measures focused on nitrogen load reduction from Denmark appear to deal only
with a single-stressor model for eelgrass restoration.
 MOF, Alm.del - 2020-21 - Bilag 602: Materiale fra Landbrug & Fødevarers foretræde for udvalget 26/5-21 om international forskerkritik af kvælstofmål fra Aarhus Universitet
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Timeline
Milestones
1
2
3
4
5
6
7
6700 km
2
of
eelgrass in
Danish waters
Onset of eelgrass
wasting disease in
the North Atlantic
Start of
increase in N
load from land
Rapid increase Mussel dredging Return to post-war
of nitrogen
peaked in the
nitrogen loading
load from land 1980s
from land
1900
Environmental drivers
of eelgrass restoration
Pressures
Less light
1930
1960
1980
2000
2021
Nitrogen loading
Mussel dredging
Less space, less light
Regime shift
Disease
Higher mortality
Climate change
Several Danish authors and international colleagues identify eelgrass loss as a complex multi-
stressor issue. Water clarity is very important, but it only establishes the potential for recovery.
 MOF, Alm.del - 2020-21 - Bilag 602: Materiale fra Landbrug & Fødevarers foretræde for udvalget 26/5-21 om international forskerkritik af kvælstofmål fra Aarhus Universitet
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Effectiveness of measures
–
two questions
Question 1: Is the reduction in nitrogen loading effectively increasing water clarity?
N load from land (1000’s tons)
Secchi disk depth (metres)
Slightly better water
clarity since the 1980’s
Krause-Jensen, D., Duarte. C.M., Sand-Jensen, K., Carstensen, J., 2021.
Century-long records reveal shifting challenges to seagrass recovery.
Global change Biology 27(3) . DOI: 10.1111/gcb.15440
No change in water clarity
since the 1980’s
Water clarity shows a slight improvement (but erratic) in open waters and no significant
improvement in fjords, despite (i) a 60% reduction in N load; and (ii) a forty-year period.
 MOF, Alm.del - 2020-21 - Bilag 602: Materiale fra Landbrug & Fødevarers foretræde for udvalget 26/5-21 om international forskerkritik af kvælstofmål fra Aarhus Universitet
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Effectiveness of measures
–
two questions
Question 2: How much of the chlorophyll production is driven by Danish emissions?
DHI model
0-10%
11-20%
21-30%
31-40%
41-50%
51-60%
61-70%
70-100%
Most Danish load
reductions on the
eastern seaboard
would affect at best
30% of production
Baltic Sea low
oxygen area has
doubled in the
last twenty years
Carstensen et al, 2014. Hypoxia in Baltic Sea. Ambio 43 (26-36)
Apart from inland areas such as the Limfjord and Roskilde Fjord, most of the chlorophyll in the
water is not driven by Danish N loading. Neither is the increase in low oxygen area in the Baltic.
 MOF, Alm.del - 2020-21 - Bilag 602: Materiale fra Landbrug & Fødevarers foretræde for udvalget 26/5-21 om international forskerkritik af kvælstofmål fra Aarhus Universitet
Findings
•
The use of historical data for eelgrass distribution as a reference condition is
appropriate, although nothing can be stated concerning abundance;
•
The only indicator chosen is the SQE
‘Transparency’,
rather than the eelgrass
BQE itself. The emphasis must be on the biological indicator;
•
There is little consistency between N loading determined for small catchments at
present, and the restoration of eelgrass to conditions observed in 1900;
•
The adequacy of the proposed measures (reduction in nitrogen loading from land)
is not clear, because these fail to address restoration as a multi-stressor question;
•
This complex multi-stressor problem has been reduced to setting a target for
nutrient emissions, which is unlikely to lead to good ecological status.
 MOF, Alm.del - 2020-21 - Bilag 602: Materiale fra Landbrug & Fødevarers foretræde for udvalget 26/5-21 om international forskerkritik af kvælstofmål fra Aarhus Universitet
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Recommendations
•
The eelgrass distribution and abundance should be the primary chosen indicators
since they represent the overall outcome of management measures;
•
Water transparency is indispensable for eelgrass growth, but other SQE such as
‘Structure
and substrate of the coastal bed’
should also be included, to deal with
other stressors such as mussel dredging;
•
Make full use of mathematical modelling, taking advantage of DHI competence.
Only a model can address source apportionment and transboundary issues, but
ultimately management decisions belong to policy makers;
•
Management measures must connect drivers, pressure, and state in order to be
effective. For water clarity, investigate the relationship between land-based N
loading and the components of light attenuation;
•
If reductions in nutrient emissions do not result in eelgrass restoration, the trade-off
in social costs to farming communities and acceptance of management measures
by Danish society will become divisive issues.
http://ecowin.org/eelgrass