The authors have declared that no competing interests exist.
Conceived and designed the experiments: CTE CL BSH CS TP GD. Performed the experiments: CTE CL TP. Analyzed the data: CTE DH BDB BSH CS. Contributed reagents/materials/analysis tools: CTE BSH DH BDB GD TP. Wrote the paper: CTE CL BSH GD.
Brazil has one of the largest and fastest growing economies and one of the largest coastlines in the world, making human use and enjoyment of coastal and marine resources of fundamental importance to the country. Integrated assessments of ocean health are needed to understand the condition of a range of benefits that humans derive from marine systems and to evaluate where attention should be focused to improve the health of these systems. Here we describe the first such assessment for Brazil at both national and state levels. We applied the Ocean Health Index framework, which evaluates ten public goals for healthy oceans. Despite refinements of input data and model formulations, the national score of 60 (out of 100) was highly congruent with the previous global assessment for Brazil of 62. Variability in scores among coastal states was most striking for goals related to mariculture, protected areas, tourism, and clean waters. Extractive goals, including Food Provision, received low scores relative to habitat-related goals, such as Biodiversity. This study demonstrates the applicability of the Ocean Health Index at a regional scale, and its usefulness in highlighting existing data and knowledge gaps and identifying key policy and management recommendations. To improve Brazil's ocean health, this study suggests that future actions should focus on: enhancing fisheries management, expanding marine protected areas, and monitoring coastal habitats.
Brazil's coastline spans more than 7,000 km with a vast diversity of ecosystems, including extensive mangrove areas in the Amazon basin, coral reefs in the Northeast, and lagoons, estuaries and saltmarshes in the south. These systems play a fundamental role in the economy and identity of the country. As Brazil's economy continues to grow – for 2012 it was listed as the seventh largest economy in the world
Given this context, there is a great need in Brazil for tools to assess and monitor the overall health of coastal ecosystems, as well as the status of components of the system. A framework was recently developed to do just that, and was applied to every coastal country in the world
Goal | Subgoal | Benefit measured |
Food Provision (FP) | Fisheries (FIS) | Seafood sustainably harvested for human consumption from wild, or cultured stocks |
Mariculture (MAR) | ||
Artisanal fishing opportunity (AO) | Opportunity to engage in artisanal fishing as a social, cultural and livelihood activity | |
Natural products (NP) | Amount of sustainably harvested natural products (other than for food provision) | |
Carbon storage (CS) | Conservation of coastal habitats affording carbon storage and sequestration | |
Coastal protection (CP) | Conservation of coastal habitats affording protection from inundation and erosion | |
Tourism and recreation (TR) | Opportunity to enjoy coastal areas for recreation for locals and tourists | |
Coastal livelihoods and economies (LE) | Livelihoods (LIV) | Employment (livelihoods) and revenues (economies) from marine-related sectors |
Economies (ECO) | ||
Sense of place (SP) | Iconic species (ICO) | Sense of place and cultural connectedness to the ocean afforded by lasting special places and iconic species |
Lasting special places (LSP) | ||
Clean waters (CW) | Clean waters that are free from pollution, debris and safe to swim in | |
Biodiversity (BD) | Habitats (HAB) | Conservation of biodiversity of species and habitats for their existence value |
Species (SPP) |
The Index is based on the understanding that humans are part of ecosystems and that the health of natural and human systems are tightly coupled
The novelty of the Index is that it provides an integrated framework in which to quantitatively assess and compare the condition of these benefits, thus providing a portfolio perspective useful for informing management decisions. The Index can also be used to track progress in achieving specific management goals, because it establishes a target or reference point to which current status and likely future condition are compared (
Here we present a case study, applying the Ocean Health Index framework to Brazil at the national and sub-national levels. The global analysis
Applying the Ocean Health Index to Brazil provides an important opportunity to test the scalability and flexibility of the Index to be adapted to country-specific concerns by including higher resolution information, place-specific targets and regional proxies for calculating goals. The case study also highlights a number of challenges related to data quality and quantity for assessing the range of benefits evaluated under the Index framework. Here, we show how the Index can be adapted to the Brazilian context, and discuss the main patterns and policy implications emerging from our analysis. Our intent is that the lessons learned from this case study can be used to guide future assessments and management strategies in Brazil, and help to inform other current and future regional applications of the Ocean Health Index.
Details on calculation of the Index are provided in Halpern
The Index is comprised of ten widely-held public goals: Food Provision, Artisanal Opportunities, Natural Products, Carbon Storage, Coastal Protection, Coastal Livelihoods and Economies, Tourism and Recreation, Sense of Place, Clean Waters and Biodiversity (
For each goal, a score is calculated from four dimensions – current status, recent trend, existing pressures and expected resilience in the near-term based on current management actions. The Index value (
The weights determine the relative importance of each goal in the overall Index score and ideally reflect people's values within the region. Here we used equal weighting, as an in-depth interview process with stakeholders from all Brazilian coastal states was outside the scope of this case study (for an example, see
Each goal score,
The present status of goal
The reference point, Xi, R, is determined a number of ways depending on the purpose (management objective) and data constraints of each goal. The main ways of establishing a reference point are: through a known functional relationship (e.g. a target value of extracting the maximum sustainable yield of a given fish stock), a time series approach (e.g. historical habitat extent), a spatial comparison (e.g. the country with highest wages in marine-related sectors), or through a known or established target value (e.g. no species at risk of extinction, or 30% of marine waters designated in protected areas). A more detailed discussion of the considerations and process for selecting reference points is found in Samhouri
The likely near-term future status of a goal,
where
Trend is calculated as the change in Status (slope) over the previous five years. The annual rate of change was multiplied by five to give an estimation of the Status in the near-term future
The Pressure for each goal (
where γ is the relative weight for ecological vs. social pressures and is set equal to 0.5. Total Pressure scores range between 0 and 100 with 100 being the highest threat.
To calculate Resilience (Table S8 in
where the three measures are scaled 0–100, and gamma is assumed to be 0.5 (such that ecological and social Resilience components are equivalent). Ecological integrity (
The Index was calculated for each Brazilian coastal state (
The following islands were considered within the jurisdiction of states specified in parenthesis: 1. São Pedro & São Paulo Archipelago (PE), 2. Rocas Atoll (RN), 3. Fernando de Noronha (PE), 4. Abrolhos Archipelago (BA), 5. Trindade & Martim Vaz (ES).
Spatial resolution | Goal or sub-goal | Geographic Domain | ||
Terrestrial coastline | Coastal waters (0–12 nmi)* | Federal waters (0–200 nmi) | ||
Coastal State | Clean Waters | x | x | |
Tourism and Recreation | x | |||
Mariculture (FP) | x | x | ||
Lasting Special Places (SP) | x | x | ||
Mixed State and National | Carbon Storage | x | x | |
Coastal Protection | x | x | ||
Habitats (BD) | x | x | ||
National | Fisheries (FP) | x | ||
Artisanal Opportunities | x | |||
Natural Products | x | |||
Livelihoods (LE) | x | x | ||
Economies (LE) | x | x | ||
Iconic Species (SP) | x | |||
Species (BD) | x |
Where sub-goals are shown, the respective goal is indicated in brackets (for acronyms see
Region | FP | AO | NP | CS | CP | LE | TR | SP | CW | BD | |||||||||
Index | FIS | MAR | LIV | ECO | ICO | LSP | HAB | SPP | |||||||||||
Brazil | 60 | 42 | 36 | 6 | 62 | 29 | 89 | 92 | 56 | 52 | 48 | 31 | 47 | 48 | 48 | 77 | 95 | 85 | 74 |
Alagoas (AL) | 55 | 40 | 33 | 1 | 59 | 28 | 90 | 89 | 55 | 51 | 46 | 22 | 46 | 33 | 20 | 60 | 94 | 82 | 70 |
Amapá (AP) | 62 | 42 | 42 | 62 | 28 | 93 | 94 | 54 | 50 | 46 | 3 | 47 | 73 | 98 | 90 | 96 | 85 | 74 | |
Bahia (BA) | 66 | 41 | 34 | 1 | 61 | 29 | 93 | 93 | 56 | 52 | 48 | 88 | 47 | 58 | 69 | 71 | 97 | 85 | 73 |
Ceará (CA) | 56 | 41 | 36 | 12 | 60 | 29 | 75 | 76 | 55 | 51 | 47 | 34 | 47 | 35 | 24 | 85 | 90 | 81 | 73 |
Espírito Santo (ES) | 57 | 42 | 35 | 3 | 61 | 29 | 95 | 94 | 56 | 52 | 48 | 15 | 47 | 38 | 28 | 62 | 97 | 85 | 74 |
Maranhão (MA) | 57 | 40 | 34 | 0 | 60 | 28 | 87 | 88 | 55 | 50 | 46 | 9 | 46 | 53 | 60 | 79 | 93 | 82 | 72 |
Pará (PA) | 55 | 41 | 34 | 0 | 60 | 28 | 92 | 93 | 55 | 50 | 46 | 1 | 46 | 37 | 29 | 74 | 96 | 84 | 72 |
Paraíba (PB) | 55 | 40 | 33 | 1 | 59 | 28 | 87 | 89 | 55 | 51 | 46 | 11 | 46 | 44 | 43 | 62 | 93 | 82 | 71 |
Pernambuco (PE) | 60 | 41 | 34 | 2 | 60 | 29 | 85 | 88 | 56 | 52 | 48 | 58 | 47 | 41 | 35 | 70 | 94 | 83 | 73 |
Piauí (PI) | 47 | 40 | 33 | 1 | 59 | 27 | 81 | 82 | 54 | 50 | 45 | 2 | 45 | 27 | 10 | 31 | 91 | 80 | 69 |
Paraná (PR) | 60 | 42 | 40 | 27 | 63 | 29 | 95 | 96 | 56 | 53 | 49 | 3 | 48 | 53 | 59 | 85 | 99 | 87 | 76 |
Rio De Janeiro (RJ) | 71 | 44 | 36 | 0 | 65 | 30 | 99 | 99 | 57 | 54 | 50 | 100 | 50 | 57 | 65 | 77 | 99 | 88 | 78 |
Rio Grande Do Norte (RN) | 50 | 40 | 34 | 5 | 59 | 28 | 33 | 74 | 55 | 50 | 46 | 33 | 46 | 32 | 17 | 79 | 77 | 74 | 71 |
Rio Grande Do Sul (RS) | 60 | 43 | 36 | 0 | 63 | 30 | 100 | 100 | 57 | 53 | 49 | 5 | 49 | 42 | 35 | 84 | 100 | 88 | 77 |
Santa Catarina (SC) | 62 | 42 | 46 | 66 | 62 | 29 | 93 | 94 | 56 | 52 | 49 | 37 | 48 | 39 | 31 | 77 | 99 | 87 | 75 |
Sergipe (SE) | 54 | 40 | 34 | 2 | 60 | 28 | 89 | 90 | 55 | 51 | 47 | 11 | 46 | 45 | 45 | 47 | 95 | 83 | 71 |
São Paulo (SP) | 66 | 45 | 37 | 1 | 66 | 30 | 97 | 97 | 58 | 54 | 51 | 29 | 51 | 63 | 75 | 95 | 99 | 89 | 80 |
Empty cells are goals not relevant to that region. Goals (two-letter codes) and sub-goals (three-letter codes) are reported separately; LE, SP and BD goals are the average of sub-goal scores; FP scores are the weighted average of sub-goal scores. Acronyms are the same as in
To see how the Ocean Health Index compares with another across-sector index, we compared current versus likely future status scores for each state with an independent metric used in Brazil to track development status (FIRJAN Development Index score, IFDM). IFDM is an index of human development, measured in three areas: jobs and income, education, and health, providing a useful comparison to our evaluation of ocean health.
The overall Index score for Brazil was 60 out of 100, with state-level scores ranging from 47 to 71 (
Mariculture (6) scored lowest in the Index at the national level. Other extractive goals or sub-goals, such as Natural Products (29) and Fisheries (42) were also low. Iconic species (47), scored lower than the Species sub-goal, indicating that a high proportion of culturally and aesthetically valued species are threatened (
Goals and sub-goals for which state-level data were used showed high variability among regions (
Scores for the Artisanal Opportunity goal (62) and Livelihoods (56) and Economies (48) sub-goals were low, but were evaluated at the country-level, likely masking important regional differences. Similarly, Carbon Storage (89), Coastal Protection (92) and the Habitats sub-goal of Biodiversity (95) showed high scores, with little variation among regions (
Comparisons of current and likely future status scores for each state's combined Index score revealed that the level of development of a state (assessed using the independent measure of development status, IFDM) was influential in determining the state's likely future score (
Points below the dashed line are trending negatively into the future, and above are trending positively. IFDM scores range from 0 to 1 (low development = 0–0.4, average development = 0.4–0.6, moderate development = 0.6–0.8, and high development = 0.8–1).
This study is the first integrated assessment of the health of Brazil's ocean, based on the Ocean Health Index framework
Differences in Food Provision scores between coastal states were driven by the Mariculture sub-goal (
Habitat-based goals, including Carbon Storage, Coastal Protection and the Habitat sub-goal of Biodiversity, scored high across most states, with the exception of Rio Grande do Norte (
The Lasting Special Places sub-goal was assessed using a national database of protected areas (including fully-protected and sustainable use designations at federal, state and municipal levels) and Indigenous lands. The remote state of Amapá achieved a score of 98, almost reaching the target value of 30% protection of the coastal zone (
The Tourism and Recreation goal had large variation in scores (
Scores for the Clean Waters goal (
Perhaps unsurprisingly, a state's level of development influences its current and likely future status score. States with stronger economies, and better infrastructure and management, such as São Paulo and Rio de Janeiro, are more likely to pursue sustainable development paths and improve their Index scores, while less developed states show the opposite trend (
Here we compare results from this case-study with scores for Brazil from the global analysis (year 2012; reported in Halpern
For some goals, the national scores remained similar to those from the global assessment
Key differences are found in Artisanal Fishing Opportunities, Tourism and Recreation, Lasting Special Places and Iconic Species. Overall Index scores (center) for the regional study are remarkably similar to global results for Brazil.
The Index framework was designed to be flexible to different societal values and data contexts. Important model changes were made to some goals to reflect local conditions or to incorporate higher quality data. Below we discuss some changes to goal models and data layers and how they impact resulting scores.
The Food Production goal was analyzed using the same conceptual framework as in Halpern
The Artisanal Opportunity goal scored lower than the global analysis (62 versus 88). The global model considered several aspects potentially related to the need and opportunity for people to fish artisanally, including regulations targeted to artisanal, subsistence and recreational fishing
For Tourism and Recreation we used fine-scale data on hotel employment at the coastal municipality level, providing a better picture of ocean-related tourism than that derived from international arrivals data (used in Halpern
For Biodiversity, regional assessments of threatened species showed significant differences from IUCN global assessments. For species assessed both globally and nationally, 58% held the same threat category, 33% had a higher risk of extinction, and 9% had a lower risk of extinction in national assessments. This difference was particularly notable for sharks and rays where 39% are considered threatened in Brazilian waters based on regional assessments
Clean Waters scores were nearly identical for both regional and global studies (77 and 76). The regional analysis used the same models for chemical and nutrient pollution
Finally, we adapted measures of pressures and resilience to address those that are important to the local context. We incorporated state-level data on ecological resilience (protected areas) and social resilience (UIE management index of Brazilian states). Pressure layers with new regional data sources included: Human Pathogens, Trash, Intertidal Habitat Destruction, and Shrimp farming in mangroves (See
Our assessment shows that the Index can utilize data of varied quantity and quality. Our aim was to adapt to the regional context, while recognizing gaps and understanding potential limitations of the available information. We sought to gather the best currently available data that met minimum requirements for Index score calculation. For this, data needed to be collected with similar protocols across regions, available for all 17 coastal states (or sampled across all states, or ocean areas, but aggregated to the national level), and have enough spatial and/or temporal resolution for a reference point to be determined. When such requirements were not met, we used global data with country-level resolution. Better quality data sets were available for localized regions, which have been the focus of more intense research efforts in Brazil (e.g. Lagoa dos Patos region in Rio Grande do Sul state). Although such data are valuable for analyzing issues of a specific region, they are less suited for the integrated, comparative look used in the Index.
Our analysis reveals some important trends across states and at the country level. Here we focus on two key policy implications related to fisheries management and habitat protection.
First, Brazil has substantial room for improvement in sustainable food production. Landings from wild capture fisheries far exceeded sustainable target levels in the main portion of the Brazilian coast and Trindade and Martim Vaz islands (Figure S2 in
Fisheries management in Brazil has been characterized by decades of open access to most fisheries and consequently to high fishing exploitation levels impacting both sustainability and profitability of its fisheries
The second set of policy implications relate to habitat-based goals. In our analysis, only 12% of the coastal zone (defined as 1 km inland and 3 nmi offshore) was in protected areas. These areas only cover 0.35% of the Brazilian EEZ (as noted above, APAs were excluded). This falls well below the target of 10% marine area to be protected by 2020 under the Convention of Biological Diversity
With an immense coastline and diverse coastal habitats, Brazil still lacks systematic mapping and monitoring data for its marine habitats. Although initiatives for broad-scale mapping and monitoring of marine and coastal habitats are emerging in Brazil (e.g. SISBiota:
While data are available for some economic sectors (e.g. tourism, mariculture, waste disposal, and protected areas), the country lacks monitoring plans for many of the types of information required to understand human uses of the marine environment, thus posing a practical challenge for long-term management of the health of marine ecosystems. Notwithstanding, we found that the Index can be a useful metric, using currently available information for illuminating ecological and social patterns related to ocean health. We also showed how it is a scalable, flexible approach that can be applied at different management units, and this flexibility will allow incorporating newer and more relevant data as these become available.
The results presented here represent a first attempt to assess ocean health in a comprehensive manner for Brazil. As such, this study offers an important baseline against which future change can be measured. It also highlights where better information is needed, and can help to guide policy and management actions at national and sub-national scales.
Supporting Information.
(DOCX)
We are grateful to the Brazilian Ministry of the Environment, and the Chico Mendes Institute for Biodiversity Conservation for help with obtaining regional data. We would like to thank Monica Brick Peres, Estevão Carino Fernandes de Souza, Ugo Eichler Vercillo and Steve Katona for their valuable input. A number of additional scientists contributed advice on regional datasets. We would also like to thank two anonymous referees for their useful feedback.