Table 1 Network criteria, conservation targets, and metrics.

CBD network criteria (bold) including definitions quoted from CBD (29), metrics (italics), conservation targets, and metric equations used in this study, with relevant comments.

Network criteria
Metrics
Definitions and metric equations
(normalized to 0 to 5 range)
Conservation targets and comments
Important areas“[Important Areas are] geographically or oceanographically discrete areas that provide important services to one or more
species/populations of an ecosystem or to the ecosystem as a whole, compared to other surrounding areas…”
Major transform faultsAPEI percent coverage/100% × 5.The objective is to protect 100% of important areas. Scores are based on
percent area conserved (for transition zones), percent by number of
features conserved (for hybrid zones), and percent of length conserved
(for transform faults).
Biogeographic transition zones
Genetic hybrid zones
Representativity“Representativity is captured in a network when it consists of areas representing the different biogeographical subdivisions of
the global oceans and regional seas that reasonably reflect the full range of ecosystems, including the biotic and habitat
diversity of those marine ecosystems.”
Discrete habitat variables:
Spreading ridge
Active vents
Inactive vents
Fracture zones
Seamounts
APEI percent coverage/50% × 5,
where any score greater
than 5 was set to 5.
The objective is to protect a representative amount (30 to 50%) of key
habitat within the study region. Scores are based on percent area
conserved (for spreading ridges), percent by number of features
conserved (for active and inactive vents, and seamounts), and by
percent of length conserved (for transform faults).
Note: Active hydrothermal vents and other vulnerable marine ecosystems
are at risk of serious harm from SMS mining activities. We expect 100%
of active hydrothermal vent ecosystems and other habitats at risk of
serious harm to be protected through conservation measures,
including, but not limited, to APEIs.
Continuous variables that
describe the regional
seascape:
Slopes
Depth
Seafloor POC flux
5 − (RMSE × 5)The objective is to mimic the distribution of variables determined to be
key drivers of biodiversity in proportion to their occurrence in the
management subunit. Root mean square error (RMSE) was calculated
as the difference between cumulative frequency distributions within
the APEI scenario and the study region. All variables were classified
into 10 to 15 bins to remove the effect of the number of bins on RMSE.
Connectivity“Connectivity in the design of a network allows for linkages whereby protected sites benefit from larval and/or species
exchanges, and functional linkages from other network sites. In a connected network individual sites benefit one another.”
Regional connectivity6 − (max distance between cores/75th percentile
median dispersal distance), where any score
greater than 5 was set to 5.
The objective is to ensure that there is no major disruption to dispersal
across the network of APEIs. The maximum distance between APEIs
compared to median faunal dispersal distances is an indicator of the
potential for disrupting dispersal within the entire management
subunit.
Network population
persistence
6 − mean gap ratio (that is, the mean distance
between cores/mean core length),
where any score greater than 5 was set to 5.
The objective is to promote the viability of populations by self-seeding
within APEIs and/or dispersal between APEIs. By minimizing the
difference in length of APEI core areas versus distance between core
areas, species that on average disperse beyond the APEI have a good
chance of being able to disperse to adjacent APEIs. Minimizing this
“gap ratio” should enhance persistence of species across the network,
as well as within individual APEIs, and increase resilience across the
network to localized disturbances.
Replication“Replication of ecological features means that more than one site shall contain examples of a given feature in the given
biogeographic area. The term “features” means “species, habitats and ecological processes” that naturally occur in the given
biogeographic area.”
ReplicationNumber of APEIs where any score greater
than 5 was set to 5.
The objective is to have three to five replicate APEIs within a
management unit, to decrease the likelihood of local catastrophes
causing systemic biodiversity loss.
Viability and adequacy“Adequate and viable sites indicate that all sites within a network should have size and protection sufficient to ensure the
ecological viability and integrity of the feature(s) for which they were selected.”
Total area(APEI percent coverage/50%) × 5, where
any score greater than 5 was set to 5.
The objective is to conserve an adequate portion (30 to 50%) of the
management unit to ensure the viability of populations within it. Total
area conserved is a proxy for overall adequacy of a network. The total
area metric was calculated similarly to the habitat representativity
metrics above.
Within APEI persistence5 × (APEI core length/200 km),
where any score greater than
5 was set to 5.
The objective is to ensure that APEIs are large enough to maintain
minimum viable populations, and metapopulations, within a single
APEI. The larger the APEI, the greater the probability self-recruitment
within the APEI, and the lower the percentage of larval export from
the APEI, which should enhance the persistence of populations,
metapopulations, and communities within an APEI. 200 km was used
as the minimum scale required to encompass two times the median
dispersal distance of 75% of deep-sea fauna with known dispersal
scales (53).
Climate Change:
Absolute similarity
5 − (RMSE × 5)The objective is to conserve areas where climate impacts would be
minimized. The more close distributions of key climate variables (pH,
temperature, dissolved O2 concentrations, and seafloor POC flux) in the
future (that is, 2100) APEI cores mimic the current (that is, 2013)
distribution in the management unit, the less impact is expected. RMSE
was calculated as the difference between cumulative frequency
distributions within the APEI scenario and the study region. All
variables were classified into 10 to 15 bins to remove the effect of the
number of bins on RMSE.
Climate change:
Relative local change
(APEI percent coverage/50%) × 5,
where any score greater than
5 was set to 5.
The objective is to conserve 30 to 50% of the areas projected to be least
affected by climate change. Least affected cells were defined as the
10% of cells with the lowest percent change between current (2013)
and predicted (2100) values of the four key climate variables (pH,
temperature, dissolved O2 concentrations, and POC flux to the
seafloor). The percent of those cells falling in APEI cores for each
scenario was calculated following the approach used for
representativity metrics (continuously distributed variables).