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Using effective mesh size (meff)
in conservation planning
Dr. Jochen Jaeger
Concordia University, Montréal
Department of Geography, Planning and Environment
2018 CCEA National Workshop
Toronto, 1-5 October 2018
1969
Brugger (1992)
Landscape
fragmentation
1988
1969
Brugger (1992)
Landscape
fragmentation
1988
1969
Brugger (1992)
Landscape
fragmentation
a threat to the sustainability of
human land use, to biodiversity,
and to many ecosystem
functions and services.
4
Length of major roads:
7,133 km
Southern Ontario
Fenech et al. (2004)
Ottawa
Toronto
5
Length of major roads:
7,133 km
Fenech et al. (2004)
6
Length of major roads:
7,133 km
35,637 km
fivefold increase!
Fenech et al. (2004)
7
Need for indicators for environmental reporting
on the state of ecosystems
Add Env. Signals here + regulation.:
Why monitor landscape fragmentation?
to document the changes pace of landscape change, changes in trends
e.g., as an indicator of environmental quality or sustainability
to assist in the planing of new roads and railways
Why monitor landscape fragmentation?
to document the changes pace of landscape change, changes in trends
e.g., as an indicator of environmental quality or sustainability
to assist in the planing of new roads and railways
to reveal relationships with the presence andabundance of species and discover thresholds
Why monitor landscape fragmentation?
to document the changes pace of landscape change, changes in trends
e.g., as an indicator of environmental quality or sustainability
to assist in the planing of new roads and railways
to reveal relationships with the presence andabundance of species and discover thresholds
to compare and balance new construction projectsand mitigation measures and compare scenarios
Why monitor landscape fragmentation?
to document the changes pace of landscape change, changes in trends
e.g., as an indicator of environmental quality or sustainability
to assist in the planing of new roads and railways
to reveal relationships with the presence andabundance of species and discover thresholds
to compare and balance new construction projectsand mitigation measures and compare scenarios
to introduce quantitative environmental quality standards objectives and limits
12
Outline How can we monitor
landscape fragmentation?
Effective mesh size
Applications: Some examples
Switzerland
Europe
Ontario
Canadian prairies
California
City Biodiversity Index
Conclusions
13
Switzerland
Landscape fragmentation
in Switzerland (Jaeger et al. 2007, etc.)
Landscape fragmentation
in Europe (EEA & FOEN 2011)
14
Switzerland
15
1885Patch size
Bertiller et al. (2007)
16
1935
Bertiller et al. (2007)
Patch size
17
1960
Bertiller et al. (2007)
Patch size
18
1980
Bertiller et al. (2007)
Patch size
19
2002
Bertiller et al. (2007)
Patch size
20
Definition of
Landscape Fragmentation
Dictionary: “breaking apart into pieces”
Wide functional definition: disruption of
ecological interrelations between spatially
connected parts of the landscape.
Structural definition: obstacles (lines and areas)
against the movement of animals (separating
patches of habitat); often including emissions,
collisions, and aesthetic impacts.
21
How to measure the degree of
landscape fragmentation?
Serious problems with earlier methods
New method: effective mesh size, meff
Probability that two randomly chosen points in the landscape will be in the same patch:
meff is included in the programm FRAGSTATS
(available online)
Jaeger (2000),
Landscape Ecology
22
Effective Mesh Size (meff)
Interpretation: possibility that two individuals
can encounter each other (e.g., gene flow)
Multiplication with Atotal to convert this
probability into an area (= effective mesh size)
pAm ×= totaleff
23
An example
A1
A3A2
Atotal = 4 km2
Landscape with two
roads (three patches)
A1 = 2 km2,
A2 and A3 are 1 km2.
24
An example
A1
A3A2
Atotal = 4 km2
2
total
1
2
totaleff
321
32
2
total
11
km5.1
375.08
3
16
1
4
1
4
1
2
1
2
1
==*=
==++=
==×=
÷÷ø
öççè
æ=×=
å=
A
A
pAm
pppp
pp
A
Ap
n
i
i
25
An example
A1
A3A2
Atotal = 4 km2
2
total
1
2
totaleff
321
32
2
total
11
km5.1
375.08
3
16
1
4
1
4
1
2
1
2
1
==*=
==++=
==×=
÷÷ø
öççè
æ=×=
å=
A
A
pAm
pppp
pp
A
Ap
n
i
i
26
An example
A1
A3A2
Atotal = 4 km2
2
total
1
2
totaleff
321
32
2
total
11
km5.1
375.08
3
16
1
4
1
4
1
2
1
2
1
==*=
==++=
==×=
÷÷ø
öççè
æ=×=
å=
A
A
pAm
pppp
pp
A
Ap
n
i
i
27
An example
A1
A3A2
Atotal = 4 km2
2
total
1
2
totaleff
321
32
2
total
11
km5.1
375.08
3
16
1
4
1
4
1
2
1
2
1
==*=
==++=
==×=
÷÷ø
öççè
æ=×=
å=
A
A
pAm
pppp
pp
A
Ap
n
i
i
28
The formula of the
effective mesh size:
( )222
2
2
1
total
eff......
1niFFFF
Fm +++++= ( )222
2
2
1
total
eff......
1niFFFF
Fm +++++=
( )
å=
=
+++++=
n
i
i
ni
AA
AAAAA
m
1
2
total
222
2
2
1
total
eff
1
......1
29
Implications
If the landscape becomes more fragmented encountering probability p is lower & effective mesh size is lower
Fragmenting large patches has a big effect on
the effective mesh size
Fragmenting small patches also has an effect on the
effective mesh size, but the effect is less strong
30
meff corresponds to
the definition of landscape connectivity as „the
degree to which a landscape facilitates of impedes
animal movement“ (Taylor et al. 1993)
31
meff corresponds to
the definition of landscape connectivity as „the
degree to which a landscape facilitates of impedes
animal movement“ (Taylor et al. 1993)
and to the suggestion by Taylor et al. (1993) to
measure landscape connectivity “for a given
organism using the probability of movement between
all points or resource patches in a landscape”.
32
33
Effective mesh density: seff = 1/meff
0
10
20
30
40
50
60
70
80
90
100
1940 1960 1980 2000 2020
Jahr
Eff. mesh size (km2)
0
5
10
15
20
25
30
35
40
45
50
1940 1960 1980 2000 2020
Jahr
Eff. mesh density (no of
meshes per 1000 km2)
Hypothetical example where the trend is constant.
Linear increase in the eff. mesh density corresponds to a 1/x-curve in
eff. mesh size.
Year Year
34
Effective mesh density: seff = 1/meff
0
10
20
30
40
50
60
70
80
90
100
1940 1960 1980 2000 2020
Jahr
Eff. mesh size (km2)
0
5
10
15
20
25
30
35
40
45
50
1940 1960 1980 2000 2020
Jahr
Eff. mesh density (no of
meshes per 1000 km2)
Landscape connectivity = „the
degree to which a landscape
facilitates of impedes animal
movement“ (Taylor et al. 1993)
Year Year
Landscape fragmentation
35
Outline How can we monitor
landscape fragmentation?
Effective mesh size
Applications: Some examples
Switzerland
Europe
Ontario
Canadian prairies
California
City Biodiversity Index
Conclusions
36
Schweiz
1. Zerschneidungskarte
Jura: 19.02 km2
Lowlands: 10.8 km2
Northern Alps:
367.5 km2
Southern Alps:
381.7 km2
Central Alps: 249.8 km2
meff
Jaeger et al. (2008)
37
1885Patch size
Bertiller et al. (2007)
38
1935
Bertiller et al. (2007)
Patch size
39
1960
Bertiller et al. (2007)
Patch size
40
1980
Bertiller et al. (2007)
Patch size
41
2002
Bertiller et al. (2007)
Patch size
42
Switzerland 1885 to 2002 and trends
Switzerland, FG 4
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
1880 1900 1920 1940 1960 1980 2000 2020 2040 2060
Year
s (
1/1
000
km
2)
+ 229% + 370%
+ 320%
- 76%
- 79%
- 70%
Effective mesh size Effective mesh density
FG 4: Land areas below 2100 m
Jaeger et al. (2007)
43
Jaeger et al. (2007)
also in French and German
Online:
www.gpe.concordia.ca/jaeger
44
Jaeger et al. (2007)
also in French and German
Online:
www.gpe.concordia.ca/jaeger
Jaeger et al. (2008)
Results 1935-2002 are used in „Swiss Environmental
Statistics – Brief Guide 2006“
100
0
1935 1960 1980 2002
- 60%
- 43%
- 37%
100
0
1935 1960 1980 2002
- 47%
- 47%
- 52%
- 47%
- 60%
- 43%
- 37%
49
Swiss Federal Statistical
Office (2007)
50
Swiss Federal Statistical Office (2007, p. 17)
51
Swiss Federal Statistical Office (2007, p. 18)
52
53
Also used in
LABES:
Monitoring of
landscape quality
in Switzerland
54
Kienast et al.
(2015)
55
2. Landscape Fragmentation
in Europe
What is the extent of
landscape fragmentation in
Europe?
To what degree can the
differences between the
regions in Europe be
explained by socio-economic
factors?
population density, GDP, volume
of freight transportation, etc.
Jaeger et al. (2011)
56Jaeger et al. (2011)
57
3 immediate priorities:
Immediate protection of large unfragmented
areas and wildlife corridors
Monitoring of landscape fragmentation
Application of fragmentation analysis as a
tool in transportation planning and regional
planning
Online: www.eea.europa.eu/publications/landscape-fragmentation-in-europe
3. Ontario
58
59
3
Pressures on Biodiversity
Status:
In 2011, the effective mesh size in southern Ontario ranged from a low of 0.03 km2 in the Toronto
Ecodistrict to a high of 144 km2 in the Charleston Lake Ecodistrict.
Median effective mesh size for ecodistricts in the Mixedwood Plains Ecozone was 1.3 km2. The
effective mesh size for all seven ecodistricts in the southwestern portion of the ecozone was less
than the median value.
Analysis of effective mesh size in Ontario is ongoing (Ontario Shield and Hudson Bay Lowlands
ecozones as well as an examination of trends in the Mixedwood Plains Ecozone).
Links:
Related Targets: N/A
Related Themes: N/A
References:
Andrén, H. 1994. Effects of habitat fragmentation on birds and mammals in landscapes with different proportions of suitable habitat. Oikos 71:355-366.
Fahrig, L. 2003. The effects of habitat fragmentation on biodiversity. Annual Review of Ecology, Evolution and Systematics 34:487-515.
Jaeger, J.A.G. 2000. Landscape division, splitting index, and effective mesh size: new measures of landscape fragmentation. Landscape Ecology 15:115-130.
McIntosh, T.E., and A. J. Dextrase. 2015. Terrestrial landscape fragmentation in Ontario. State of Ontario’s Biodiversity Technical Report Series, Report #SOBTR-04, Ontario Biodiversity Council, Peterborough, ON.
Moser, B., and J.A.G. Jaeger. 2007. Modification of the effective mesh size for measuring landscape fragmentation to solve the boundary problem. Landscape Ecology 22:447-459.
Ontario Biodiversity Council (OBC). 2010. State of Ontario’s biodiversity 2010. A report of the Ontario Biodiversity Council, Peterborough, ON.
Ontario Ministry of Finance. 2014.Onatrio population projections: fall 2014 based on the 2011 Census. Queen’s Printer for Ontario, Toronto, ON.
Ontario Ministry of Natural Resources and Forestry (OMNRF). 2015. Southern Ontario land resource information system (SOLRIS) – data specifications version 2.0. Ontario Ministry of Natural Resources, Peterborough, ON.
Varrin, R., J. Bowman, and P.A. Gray. 2007. The known and potential effects of climate change on biodiversity in Ontario’s terrestrial ecosystems: case studies and recommendations for adaptation. Ontario Ministry of Natural Resources Applied Research and Development Section, Sault Ste. Marie, ON. Climate Change Research Report CCRR-09.
Citation Ontario Biodiversity Council. 2015. State of Ontario's Biodiversity [web application]. Ontario Biodiversity Council, Peterborough, Ontario. [Available at: http://ontariobiodiversitycouncil.ca/sobr (Date Accessed: May 19, 2015)].
60
3
Pressures on Biodiversity
Status:
In 2011, the effective mesh size in southern Ontario ranged from a low of 0.03 km2 in the Toronto
Ecodistrict to a high of 144 km2 in the Charleston Lake Ecodistrict.
Median effective mesh size for ecodistricts in the Mixedwood Plains Ecozone was 1.3 km2. The
effective mesh size for all seven ecodistricts in the southwestern portion of the ecozone was less
than the median value.
Analysis of effective mesh size in Ontario is ongoing (Ontario Shield and Hudson Bay Lowlands
ecozones as well as an examination of trends in the Mixedwood Plains Ecozone).
Links:
Related Targets: N/A
Related Themes: N/A
References:
Andrén, H. 1994. Effects of habitat fragmentation on birds and mammals in landscapes with different proportions of suitable habitat. Oikos 71:355-366.
Fahrig, L. 2003. The effects of habitat fragmentation on biodiversity. Annual Review of Ecology, Evolution and Systematics 34:487-515.
Jaeger, J.A.G. 2000. Landscape division, splitting index, and effective mesh size: new measures of landscape fragmentation. Landscape Ecology 15:115-130.
McIntosh, T.E., and A. J. Dextrase. 2015. Terrestrial landscape fragmentation in Ontario. State of Ontario’s Biodiversity Technical Report Series, Report #SOBTR-04, Ontario Biodiversity Council, Peterborough, ON.
Moser, B., and J.A.G. Jaeger. 2007. Modification of the effective mesh size for measuring landscape fragmentation to solve the boundary problem. Landscape Ecology 22:447-459.
Ontario Biodiversity Council (OBC). 2010. State of Ontario’s biodiversity 2010. A report of the Ontario Biodiversity Council, Peterborough, ON.
Ontario Ministry of Finance. 2014.Onatrio population projections: fall 2014 based on the 2011 Census. Queen’s Printer for Ontario, Toronto, ON.
Ontario Ministry of Natural Resources and Forestry (OMNRF). 2015. Southern Ontario land resource information system (SOLRIS) – data specifications version 2.0. Ontario Ministry of Natural Resources, Peterborough, ON.
Varrin, R., J. Bowman, and P.A. Gray. 2007. The known and potential effects of climate change on biodiversity in Ontario’s terrestrial ecosystems: case studies and recommendations for adaptation. Ontario Ministry of Natural Resources Applied Research and Development Section, Sault Ste. Marie, ON. Climate Change Research Report CCRR-09.
Citation Ontario Biodiversity Council. 2015. State of Ontario's Biodiversity [web application]. Ontario Biodiversity Council, Peterborough, Ontario. [Available at: http://ontariobiodiversitycouncil.ca/sobr (Date Accessed: May 19, 2015)].
Still missing:
- Changes in time
- Comparison of
potential future
scenarios
61
Roch and Jaeger (2014)
4. Fragmentation of Grasslands
in the Canadian Prairies
62
Results
Roch and Jaeger (2014)
63
Roch and Jaeger (2014)
64
Monitor ing an ecosystem at r isk: What is the degreeof grassland fragmentation in the Canadian Prair ies?
Laura Roch & Jochen A. G. Jaeger
Received: 18 June 2013 /Accepted: 19 November 2013 /Published online: 4 January 2014# Springer Science+Business Media Dordrecht 2014
Abstract Increasing fragmentation of grassland habi-
tatsby human activities isamajor threat to biodiversity
and landscape quality. Monitoring their degree of frag-
mentation has been identified as an urgent need. This
study quantifies for the first time the current degree of
grassland fragmentation in the Canadian Prairies using
four fragmentation geometries(FGs) of increasing spec-
ificity (i.e. more restrictivegrassland classification) and
five types of reporting units (7 ecoregions, 50 census
divisions, 1,166 municipalities, 17 sub-basins, and 108
watersheds). We evaluated the suitability of 11 datasets
based on 8 suitability criteria and applied the effective
mesh size (meff) method to quantify fragmentation. We
recommend the combination of the Crop Inventory
Mapping of the Prairies and the CanVec datasets as the
most suitable for monitoring grassland fragmentation.
The grassl and area remai ni ng amounts to
87,570.45 km2 in FG4 (strict grassland definition) and
183,242.042 km2 in FG1 (broad grassland definition),
out of 461,503.97 km2 (entire Prairie Ecozone area).
The very low values of meff of 14.23 km2 in FG4 and
25.44 km2 in FG1 indicate an extremely high level of
grassland fragmentation. The meff method is supported
in this study as highly suitable and recommended for
long-term monitoring of grasslands in the Canadian
Prairies; it can help set measurable targets and/or limits
for regionsto guidemanagement effortsandasatool for
performance review of protection efforts, for increasing
awareness, and for guidingeffortstominimizegrassland
fragmentation. This approach can also be applied in
other parts of the world and to other ecosystems.
Keywords Effectivemeshsize. Ecological indicators.
Grasslandconservation . Landscapefragmentation .
Fragmentationper se. Protectedareas. Prairieecozone.
Roads. Urbansprawl
Abbreviations used
CBI City Biodiversity Index
FG Fragmentation geometry
CESI Canadian Environmental Sustainability
Indicators
FSDS Federal Sustainable Development
Strategy
meff Effective mesh size
seff Effective mesh density
AAFC Agriculture and Agri-Food Canada
SpATS Spatial and Temporal Variation in
Nesting Success of Prairie Ducks Study
CUT
procedure
Cutting-out procedure
CBC
procedure
Cross-boundary connections procedure
CD Censusdivision
WS Watershed
Environ Monit Assess (2014) 186:2505–2534
DOI 10.1007/s10661-013-3557-9
Electronic supplementary material The online version of this
article (doi:10.1007/s10661-013-3557-9) containssupplementary
material, which is available to authorized users.
L. Roch: J. A. G. Jaeger (* )
Department of Geography, Planning and Environment,
Concordia University Montreal,
1455 De Maisonneuve Blvd. West, Suite H1255, Montreal,
QC H3G 1M8, Canada
e-mail: jochen.jaeger@concordia.ca
L. Roch
e-mail: lauraroch5@gmail.com
Author's personal copy
Roch and
Jaeger (2014)
5. California
+ lakes, major rivers, high elevations4
+ agricultural fields3
+ minor roads2
Highways, major roads, railroads,
urbanized areas1
Elements IncludedFragmentation
Geometry
Girvetz/Thorne/Berry/Jaeger (2008)
Girvetz/Jaeger/Thorne/Berry (2008)
FG 4
FG 3FG 1
FG 2
68
Girvetz et al. (2008)
6. Use of meff in the City biodiversity Index (CBI)
69
THE SINGAPORE
BIODIVERSITY
Introduction
Figure 1: In a study conducted by Corporate Knights on good sustainable development practices in Canadian cities,
Montreal (left) and Edmonton (right) both attributed their perfect score for biodiversity monitoring to their application of the
Singapore Index.
Global Partnership on Local and
Sub-national Action for Biodiversity
Cities occupy only 2% of the surface, yet
consume about 75% of its natural resources and
has an ecological impact on an exponentially vast
area. The projected global human population by
2050 is 9.2 billion, with 6.4 billion residing in urban
areas. As such, cities will play an increasingly
crucial role in biodiversity conservation.
Cities are increasingly forming alliances to share
best practices, notably the Global Partnership on
Local and Sub-national Action for Biodiversity.
However, there was no single index which
meaningfully measured biodiversity conservation
efforts at the city level.
At the High-Level Segment of the 9th Meeting of
the Conference of Parties to the Convention on
Biological Diversity (COP-9) in 2008, Mr Mah Bow
Tan, then Minister for National
Development, proposed the development of an
index for cities to benchmark conservation efforts
and evaluate progress in reducing the rate of
biodiversity loss, led by the Secretariat of the
Convention on Biological Diversity (SCBD).
At COP-10 in 2010, Parties endorsed the Plan of
Action on Sub-national Governments, Cities and
Other Local Authorities for Biodiversity (Decision
X/22) which encourages Parties to actively
engage cities and local authorities in
implementing the CBD. The Plan of Action
highlights the City Biodiversity Index (CBI), also
known as the Singapore Index on
Biodiversity (Singapore Index), as a monitoring
tool to assist local authorities to evaluate their
progress in urban biodiversity conservation.
© C
laud
e D
uch
aîn
e,
Air
Im
ex
11. Regulation of Quantity of Water: 4 points
12. Climate Regulation: Carbon Storage and Cooling Effect of Vegetation: 4 points
13. Recreation and Education: Area of Parks with Natural Areas: 4 points
14. Recreation and Education: Number of Formal Education Visits per Child Below 16 Years to Parks with Natural Areas per Year: 4 points
Ecosys
tem
S
erv
ices (
16 p
oin
ts)
Table 1: Indicators of the Singapore Index on Cities’ Biodiversity
Nativ
e B
iodiv
ers
ity
in th
e C
ity (
40 p
oin
ts)
Gove
rnance a
nd M
anagem
ent
of
Bio
div
ers
ity (
36 p
oin
ts)
1. Proportion of Natural Areas in the City: 4 points
2. Connectivity Measures: 4 points
3. Native Biodiversity in Built-up Areas (Bird Species): 4 points
4. Change in Number of Vascular Plant Species: 4 points
5. Change in Number of Bird Species: 4 points
6. Change in Number of Butterfly Species: 4 points
7. Change in Number of Species (any other taxonomic group selected by the city):
4 points
8. Change in Number of Species ( any other taxonomic group selected by the city):
9. Proportion of Protected Natural Areas: 4 points
10. Proportion of Invasive Alien Species: 4 points
15. Budget Allocated to Biodiversity: 4 points
16. Number of Biodiversity Projects Implemented by the City Annually: 4 points
17. Existence of Local Biodiversity Strategy and Action Plan: 4 points
18. Institutional Capacity: Number of Biodiversity-related Functions: 4 points
19. Institutional Capacity: Number of City or Local Government Agencies Involved in Inter-agency Cooperation Pertaining to Biodiversity Matters: 4 points
20. Participation and Partnership: Existence of Formal or Informal Public Consultation Process: 4 points
21. Participation and Partnership: Number of Agencies/ Private Companies/ NGOs/ Academic Institutions/ International Organisations with which the City is Partnering in Biodiversity Activities, Projects and Programmes: 4 points
22. Education and Awareness: Is Biodiversity or Nature Awareness Included in the School Curriculum: 4 points
23. Education and Awareness: Number of Outreach or Public Awareness Events Held in the City per Year: 4 points
Maxim
um
Tota
l: 9
2 p
oin
ts
Octo
be
r 2
012
For more information, please contact:
Muslim Anshari and Wendy Yap
National Parks Board, Singapore
muslim_anshari_rahman@nparks.gov.sg
wendy_yap@nparks.gov.sg
Global Partnership on Local and
Sub-national Action for Biodiversity
4 points
The 23 indicators of the CBI (Singapore Index)
1: Proportion of natural area in the city
2: Connectivity of natural areas
3: Native biodiversity in built-up areas
4-8: Change in number of native species
9: Proportion of protected natural areas
10: Proportion of invasive species
11: Regulation of quantity of water
12: Carbon storage and cooling effect of vegetation
13-14: Recreational and educational services
15: Budget allocated to biodiversity
16: Number of biodiversity projects implemented by the city annually
17: Existence of local biodiversity strategy and action plan
18-19: Biodiversity-related institutions
20-21: Participation and partnership in biodiversity projects
22-23: Education and awareness projects
City Biodiversity Index (CBI):
Heritage Laurentien (2009)
Areas to be preserved/restored
Existing areas
Areas for potential enhancement
Heritage Laurentien (2009)
Areas to be preserved/restored
Existing areas
Areas for potential enhancement
Research Questions
1. What is the current level connectivity in the
network?
2. What is the potential future level of connectivity in
the network?
3. What is Meadowbrook’s contribution to connectivity?
Megan Deslauriers
Future Scenario
Baseline Situation
semi-natural areas
semi-natural areas
11.2 8.99
2.2
97.3
34.9
62.4
10.6 8.97
1.6
55.9
33.0
22.8
0
20
40
60
80
100
120
Meadowbrookpreserved
Meadowbrookdeveloped
Total Total Within-patch Between-patch
Baseline Potential for the futureC
onnectivity v
alu
es f
or
natu
ral are
as (
ha)
- 63%
Deslauriers et al. (2018)
11.2 8.99
2.2
97.3
34.9
62.4
10.6 8.97
1.6
55.9
33.0
22.8
0
20
40
60
80
100
120
Meadowbrookpreserved
Meadowbrookdeveloped
Total Within-patch Between-patch Total Within-patch Between-patch
Baseline Potential for the futureC
onnectivity v
alu
es f
or
natu
ral are
as (
ha)
- 28%
- 63%
Deslauriers et al. (2018)
11.2 8.99
2.2
97.3
34.9
62.4
10.6 8.97
1.6
55.9
33.0
22.8
0
20
40
60
80
100
120
Meadowbrookpreserved
Meadowbrookdeveloped
Total Within-patch Between-patch Total
Baseline Potential for the futureC
onnectivity v
alu
es f
or
natu
ral are
as (
ha)
- 28%
Deslauriers et al. (2018)
11.2 8.99
2.2
97.3
34.9
62.4
10.6 8.97
1.6
55.9
33.0
22.8
0
20
40
60
80
100
120
Meadowbrookpreserved
Meadowbrookdeveloped
Total Within-patch Between-patch Total Within-patch Between-patch
Baseline Potential for the futureC
onnectivity v
alu
es f
or
natu
ral are
as (
ha)
- 28%
- 63%
Deslauriers et al. (2018)
Conclusions
With Meadowbrook developed, we would loose
Meadowbrook’s significant contribution to connectivity for
wildlife (and people)
and in particular it’s large potential for increased
connectivity in the area in the future
80
Deslauriers
et al. (2018)
81
Conclusions
Examples
Switzerland
Europe
Ontario
Canadian prairies
California
City Biodiversity Index
meff is easy to use & can be applied in various ways
Monitoring
environmental, biodiversity, landscape quality, ...
compare between-patch connectivity and within-patch connectivity
Comparison of scenarios
Setting of targets and limits
Thank you!
Christian Schwick, René Bertiller
Felix Kienast
Megan Deslauriers, Adrienne
Asgary, Naghmeh Nazarnia
For funding:
German Research Foundation (DFG)
Swiss Federal Office for the
Environment (FOEN)
Environment Canada
et al.
Any Questions?
83
Potential slides for the discussion
Why monitor landscape fragmentation?
to describe the changes pace of landscape change, changes in trends
e.g., as an indicator of environmental quality or sustainability
to assist in the planing of new roads and railways
to reveal relationships with the presence andabundance of species and discover thresholds
to compare and balance new construction projectsand mitigation measures compare scenarios
to introduce quantitative environmental quality standards objectives and limits
85
Wildlife populations
are increasingly
enmeshed by roads
and urban
development.
86
1
Pressures on Biodiversity
INDICATOR: TERRESTRIAL LANDSCAPE FRAGMENTATION
STRATEGIC DIRECTION: Reduce Threats
TARGET: N/A
THEME: Pressures on Ontario’s Biodiversity – Habitat Loss
Background Information:
Landscape fragmentation is the process by which habitat loss results in the division of large, continuous habitats into smaller, more isolated remnants. Recent scientific evidence shows that landscape fragmentation has negative effects on biodiversity (Fahrig 2003), largely resulting from the loss of the original habitat, reduction in habitat patch size and increasing isolation of habitat patches (Andrén 1994). More specifically, landscape fragmentation causes a reduction in habitat area, with associated declines in population density and species richness, and significant alterations to community composition, species interactions and ecosystem functioning (Fahrig 2003). Species occupying fragmented landscapes are also less able to shift their distributions to compensate for altered habitat quality resulting from changing climatic conditions. Thus, there is an important synergy between climate change and landscape fragmentation that may lead to increased loss of biodiversity (Varrin et al. 2008).
Landscape fragmentation not only deprives plants and animals of habitat, but also has indirect impacts, generating noise, light and air pollution or changing microclimates. Some species avoid human structures, which reduces their potential habitats even more. As a result, areas in which animals feel undisturbed become ever more scarce due to landscape fragmentation (Jaeger 2000). Further, landscape fragmentation results in an abundance of edge habitat, where edge-sensitive species or those that require large, undisturbed habitat are excluded (Fahrig 2003).
Landscape fragmentation is most evident in intensively used regions, where the habitat is divided by urbanization, agriculture, roads or other human developments (Fahrig 2003). Fragmentation has been rapidly increasing in Ontario, particularly in the south where human development is greatest (OBC 2010). This trend is likely to continue as Ontario’s population is projected to grow by 31% over the next 28 years, from an estimated 13.5 million in 2013 to almost 17.8 million by 2041, resulting in greater fragmentation of the remaining ecological network (Ontario Ministry of Finance 2014).
This indicator assesses terrestrial landscape fragmentation in Ontario using effective mesh size, an unbiased measure of the sizes of habitat patches within regions.
Data Analysis:
Terrestrial landscape fragmentation in southern Ontario was assessed based on natural and anthropogenic land cover types in 2011 aggregated from the Southern Ontario Land Resource and Information System (SOLRIS v 2.0; OMNRF 2015). Landscape fragmentation was measured using effective mesh size (Jaeger 2000). Effective mesh size (meff) is a method to quantify fragmentation based on the probability that two points chosen at random in a region will be connected (i.e., found in the same habitat patch; Jaeger 2000). It is measured in units of area (i.e., ha or km2)
The 26 cantons in
2002
(FG 4)
Jaeger et al. (2008)
88
Canton Aargau 1885 and 2002 (FG 4)
1885 2002
89
Canton Aargau
90
Tunnels
8 km
meff = 26 km2 meff = 50 km2
4 km
Applications:
91
Bundling of transportation infrastructure
8 km
meff = 16 km2 meff = 37,7 km2
2 km 2 km
each 0,1 km
5,8 km
Applications:
92
Detour roads:
keep them as close to the town as possible
8 km
meff = 14,6 km2 meff = 12,4 km2
4 km
Applications:
Raskop, 2005, unpubl.
94
Review of 38 EIAs in Europe(Gontier et al. 2006)
95
Review of 38 EIAs in Europe(Gontier et al. 2006)
● biodiversity assessment was confined to local scales
did not allow assessment of effects of habitat loss
and fragmentation
● lack of quantifications and methods for impact
predictions
● development and implementation of new methods
appear necessary
96
Declaration of the
German Federal Government in 1985
Goal to „reverse the trend in land consumption and landscape fragmentation“(Bundesminister des Innern 1985)
Intention to preserve large, un-fragmented spaces with little traffic as a central principle of regional planning and landscape planning
97
Proposal of the German Environmental Agency
to establish
limits to landscape fragmentation
UBA (2003), Penn-Bressel (2005)
Situation in 2002
Value of meff
Target until 2015:
Reduction in meff should be less
than
98
Lesson 9:
(9) There is a need to care about the
quality of the entire landscape, not
just about protected areas or wildlife
corridors.
99
Lesson 10:
(10) Protecting enough habitat is
important; wildlife corridors alone will
not be enough.
100
Permeability of transportation infrastructure
Jaeger (2007)
101
Permeability of transportation infrastructure
Jaeger (2007)
102
Permeability of transportation infrastructure
Jaeger (2007)
103
( )212211
)1(21
AABAAAAA
m ××-×+×+×=total
Permeability of transportation infrastructure
Jaeger (2007)
104
( )212211
)1(21
AABAAAAA
m ××-×+×+×=total
Barrier strength
Permeability of transportation infrastructure
Barrier strength: B
Jaeger (2007)
105
Crossing structures
( )212211
21
AANDAAAAA
m ××××+×+×=total
Jaeger (2007)
106
( )212211
21
AANDAAAAA
m ××××+×+×=total
Permeability
Crossing structures
Jaeger (2007)
107
( )212211
21
AANDAAAAA
m ××××+×+×=total
Probability of use
Permeability
Crossing structures
Jaeger (2007)
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