Biodiversity
This goal describes how successfully we are preserving the richness and variety of marine life.
Overview
People value the existence of a diverse array of species for their intrinsic qualities and their contribution to the structure and function of resilient ecosystems. The risk of species extinction generates great emotional and moral concern for many people. This concern is demonstrated by the large sums of money that people donate to help conserve species and habitats.
Scores
The Biodiversity score for the Red Sea and Gulf of Aden region was 79.
This region has reasonably good Biodiversity scores. Egypt has the lowest score of 73, and the other countries score 80 or higher. The scores for the Habitat subgoal tend to be lower than the Species subgoal.
The interactive map below shows the scores for the different countries.
For the Global OHI, this goal assesses the conservation status of species based on two subgoals: Species and habitat condition. Species are assessed because they are what one typically thinks of in relation to biodiversity. We also assess Habitats because only a small proportion of marine species worldwide have been mapped and assessed, so we consider habitats a proxy for the condition of the broad suite of species that depend on them.
We calculate each of these subgoals separately and average them to estimate the overall goal score. A score of 100 means all species are at very low risk of extinction and all habitats are conserved.
The subgoal scores can be viewed below.
Subgoal scores (click to expand)
Species condition
The Species subgoal score for the Red Sea and Gulf of Aden region was 81.
Most regions score around 80 or higher, but Israel has the lowest score (63) and Egypt has a relatively low score (73).
The interactive map below shows the scores for the different countries.
Habitat condition
The Habitat subgoal score for the Red Sea and Gulf of Aden region was 77.
The Habitat subgoal is lower for nearly all countries than the Species subgoal. Saudi Arabia has a particularly low score of 62.
The interactive map below shows the scores for the different countries.
Model description
Species
The species component of the biodiversity goal measures the conservation status of marine species.
This subgoal assesses the health of all marine species present in a country’s EEZ, including endangered species and species in relatively good conditions. The presence of species that are not at risk leads to a higher score.
Species calculation details (click to expand)
Species status was calculated as the area weighted average of the conservation status of the assessed species within each region. Marine species distribution and threat category data mostly came from IUCN Red List of Threatened Species, and we limited data to all species having IUCN habitat system of “marine” http://www.iucnredlist.org [@iucn2022; @iucn_spatial_2022]. Seabird distributions data came from Birdlife International http://datazone.birdlife.org [@birdlifeinternationalandhandbookofthebirdsoftheworld2020].
We scaled the lower end of the biodiversity goal to be 0 when 75% species are extinct, a level comparable to the five documented mass extinctions [@barnosky_has_2011] and would constitute a catastrophic loss of biodiversity.
Threat weights, \(w_{i}\), were assigned based on the IUCN threat categories status of each \(i\) species, following the weighting schemes developed by Butchart et al. [-@butchart2007improvements]. For the purposes of this analysis, we included only data for extant species for which sufficient data were available to conduct an assessment. We did not include the Data Deficient classification as assessed species following previously published guidelines for a mid-point approach [@schipper2008status; @hoffmann_impact_2010].
We first calculated each the region’s area-weighted average species risk status, \(\bar R_{spp}\). For each 0.5 degree grid cell within a region, \(c\), the risk status, \(w\), for each species, \(i\), present is summed and multiplied by cell area \(A_c\), to get an area- and count-weighted species risk for each cell. This value is then divided by the sum of count-weighted area \(A_c \times N_c\) across all cells within the region. The result is the area-weighted mean species risk across the entire region.
\[ \bar R_{spp} = \frac { \displaystyle\sum_{ c=1 }^{ M } \left( \displaystyle\sum _{ i=1 }^{N_c} w_i \right) \times A_c } { \displaystyle\sum_{ c=1 }^{ M } A_c \times N_c }, (Eq. 6.4) \] To convert \(\bar R_{spp}\) into a score, we set a floor at 25% (representing a catastrophic loss of biodiversity, as noted above) and then rescaled to produce a \(x_{spp}\) value between zero and one.
\[ x_{spp} = max \left( \frac { \bar R_{SPP} - .25 }{ .75 }, 0 \right), (Eq. 6.5) \]
Weights for assessment of species status based on IUCN risk categories
| Risk Category | IUCN code | Weight |
|---|---|---|
| Extinct | EX | 0.0 |
| Critically Endangered | CR | 0.2 |
| Endangered | EN | 0.4 |
| Vulnerable | VU | 0.6 |
| Near Threatened | NT | 0.8 |
| Least Concern | LC | 1.0 |
Habitat
The habitat component of the Biodiversity goal measures the status of marine habitats that support large numbers of marine species.
Healthier habitats mean healthier species! Habitat is included as a subgoal of the Biodiversity goal to provide a more complete picture of diversity in the system than only considering the conservation status of species (the other subgoal for Biodiversity). This is because species assessments are often incomplete.
This goal assesses the condition of marine habitats that are particularly important in supporting large numbers of marine species. The status of each habitat is its current condition relative to its reference condition, which is often based on historical area. A score of 1 indicates that the condition equals or exceeds the reference point. The subgoal score is then calculated by combining the habitat scores for each region.
For the global OHI assessment, we included mangroves, coral reefs, kelp forests, seagrass beds, salt marshes, sea ice, or subtidal soft-bottom habitats. All habitats measured contribute equally to the score, regardless of their extent, because the presence of a diverse set of habitats, as well as the level of conservation of each, is considered valuable to achieve this goal.
More about global habitats (click to expand)
| Habitat | Condition | Extent | Trend |
|---|---|---|---|
| Seagrass | Increasing or stable trend assigned condition = 1.0; decreasing trend assigned condition = 0.71 based on global loss | Seagrass extent per oceanic region (vector based) | Calculated across data from 1990 - 2000 |
| Kelp | Increasing or stable trend assigned condition = 1.0; decreasing trend assigned condition based on a 2% global yearly loss | Kelp extent per oceanic region (vector based) | Calculated across data from 1983 - 2012 |
| Coral reefs | Current % cover divided by reference % cover | Coral reef extent per oceanic region (Vector based) | Calculated across data from 1975-2006 |
| Mangroves | Current hectares divided by reference hectares, for coastal mangroves only | Mangrove extent per oceanic region (vector based) | Calculated using 5 most recent years of data |
| Salt marsh | All regions assigned condition = 0.75 based on conservative historical extent losses | Salt marsh extent per oceanic region | All regions assigned trend based on historical .28% global yearly loss |
| Sea ice edge | Current (3-year rolling-average using the current year and previous 2 years) % cover of sea ice having 10-50% cover, divided by reference % cover average from 1979-2000 | Same as condition | Calculated from the fitted slope of %-deviation-from-reference per year, of the most recent 5 years of data (each year of data is based on 3-year average) |
| Soft bottom | Soft-bottom destructive fishing practices relative to area of soft-bottom habitat and rescaled to 0-1 based on relative global values | Halpern et al. [-@halpern2008global] | Calculated using 5 most recent years of condition data |
| Tidal flat | Average tidal flat extent of 2010 and 2013 relative to historic extent (average of 1989 and 1992) | Tidal flat extent per oceanic region (vector based) | Calculated across data from 2001-2013 |
A closer look at the data
The biggest factor driving scores, by far, is the current status component. Here, we take a closer look at the data underlying the status scores for each country with EEZ territory in the Red Sea and Gulf of Aden.
:::{callout-note collapse=TRUE}
Other components of an OHI score: Pressures, resilience, and trend
OHI scores are primarily driven by the current status dimension of the score, but pressures, resilience, and past trends are also important components of the goal score. In most cases, these variables will nudge the score a bit higher or lower than the current status score.
There are over 20 pressure variables (e.g., ocean warming, ocean acidification) and about 15 resilience variables (e.g., good governance and high gdp) used in the global assessment.
Each country gets a score for each pressure and resilience variable. For example, for each country we estimated the intensity of increase in ocean temperature, and rescaled these data to range from 0 to 1 (no pressure vs. highest pressure).
Each goal is affected by a subset of the pressure and resilience variables.
We provide a brief description of all the pressure and resilience variables along with how they affect each goal. A brief description of how these variables are incorporated into the final score is here. :::
Current status
We will first look at the data underlying the species condition subgoal and then the habitat subgoal.
Condition of species
Getting the underlying data for this goal requires processing a large amount of spatial data.
Given this, this section is on hold for now.
Habitat condition
The habitats evaluated include coral, mangrove, saltmarsh, tidal flat, seagrass, and subtidal soft-bottom. Habitat health is evaluated on a scale from 0 to 1, with 1 indicating the current condition is at, or better, than the reference point; trend is the average yearly change in health during the most recent 5 years; and extent is not used in the model, but is the estimated area of the habitat in each region in km2.
Habitat data: Country data (click to expand)
Implications
Based on the current model, this goal would be most improved by:
- reducing reliance on fishing practices that are destructive to marine soft-bottom habitats, such as dredging, particularly in Saudi Arabia
- restoring and protecting mangrove habitat
Future assessments should evaluate whether better data is available, particularly habitat data. Most often, countries have access to better habitat data than what we use at the global scale. This goal is driven by how the habitat has changed relative to some historic period, either in extent or condition. Finding data describing how habitats have changed over time is particularly difficult at the global scale, and regional data or expert opinion can provide a more accurate assessment of habitat condition.
Furthermore, future assessments should consider whether all relevant habitats are included in the model.
For the Species subgoal, we have found that pairing IUCN data with local expert opinion to be helpful in fine-tuning these scores.
Other OHI+ analyses have revised the habitat and species subgoals to better reflect local concerns.