Forest conservation delivers highly variable coral reef conservation outcomes

Coral reefs are threatened by human activities on both the land (e.g., deforestation) and the sea (e.g., overfishing). Most conservation planning for coral reefs focuses on removing threats in the sea, neglecting management actions on the land. A more integrated approach to coral reef conservation, inclusive of land–sea connections, requires an understanding of how and where terrestrial conservation actions influence reefs. We address this by developing a land–sea planning approach to inform fine-scale spatial management decisions and test it in Fiji. Our aim is to determine where the protection of forest can deliver the greatest return on investment for coral reef ecosystems. To assess the benefits of conservation to coral reefs, we estimate their relative condition as influenced by watershed-based pollution and fishing. We calculate the cost-effectiveness of protecting forest and find that investments deliver rapidly diminishing returns for improvements to relative reef condition. For example, protecting 2% of forest in one area is almost 500 times more beneficial than protecting 2% in another area, making prioritization essential. For the scenarios evaluated, relative coral reef condition could be improved by 8–58% if all remnant forest in Fiji were protected rather than deforested. Finally, we determine the priority of each coral reef for implementing a marine protected area when all remnant forest is protected for conservation. The general results will support decisions made by the Fiji Protected Area Committee as they establish a national protected area network that aims to protect 20% of the land and 30% of the inshore waters by 2020. Although challenges remain, we can inform conservation decisions around the globe by tackling the complex issues relevant to integrated land–sea planning

Setting conservation priorities in Fiji: Decision science versus additive scoring systems

There is a well-established scientific field - decision science - that can be used to rigorously set conservation priorities. Despite well-documented shortcomings, additive scoring approaches to conservation prioritization are still prevalent. This paper discusses the shortcomings and advantages of both approaches applied in Fiji to identify priorities for terrestrial protected areas. The two main shortcomings of using a scoring approach (discussed in Keppel (2014) [1]) that are resolved with decision science approaches (presented in Klein et al. (2014) [2]) in Fiji were (1) priorities did not achieve one of the most important stated conservation goals of representing ~40% of Fiji's major vegetation types and (2) the weighting of different selection criteria used was arbitrary. Both approaches considered expert knowledge and land-sea connections important to decision makers in Fiji, but only decision science can logically integrate both, in addition to other important considerations. Thus, decision makers are urged to use decision science and avoid additive scoring systems when prioritizing places for conservation. Fiji has the opportunity to be a global leader in using decision science to support integrated land-sea planning decisions

Incorporating uncertainty associated with habitat data in marine reserve design

One of the most pervasive forms of uncertainty in data used to make conservation decisions is error associated with mapping of conservation features. Whilst conservation planners should consider uncertainty associated with ecological data to make informed decisions, mapping error is rarely, if ever, accommodated in the planning process. Here, we develop a spatial conservation prioritization approach that accounts for the uncertainty inherent in coral reef habitat maps and apply it in the Kubulau District fisheries management area, Fiji. We use accuracy information describing the probability of occurrence of each habitat type, derived from remote sensing data validated by field surveys, to design a marine reserve network that has a high probability of protecting a fixed percentage (10-90%) of every habitat type. We compare the outcomes of our approach to those of standard reserve design approaches, where habitat-mapping errors are not known or ignored. We show that the locations of priority areas change between the standard and probabilistic approaches, with errors of omission and commission likely to occur if reserve design does not accommodate mapping accuracy. Although consideration of habitat mapping accuracy leads to bigger reserve networks, they are unlikely to miss habitat conservation targets. We explore the trade-off between conservation feature representation and reserve network area, with smaller reserve networks possible if we give up on trying to meet targets for habitats mapped with a low accuracy. The approach can be used with any habitat type at any scale to inform more robust and defensible conservation decisions in marine or terrestrial environments. (C) 2013 Elsevier Ltd. All rights reserved

Predicting climate-sensitive water-related disease trends based on health, seasonality and weather data in Fiji

Leptospirosis, typhoid and dengue are three water-related diseases influenced by environmental factors. We examined whether seasonality and rainfall predict reported syndromes associated with leptospirosis, typhoid and dengue in Fiji. Poisson generalised linear models were fitted with s6 early warning, alert and response system (EWARS) syndromic conditions from March 2016 until December 2020, incorporating seasonality, temperature and rainfall. Watery diarrhoea, prolonged fever and suspected dengue displayed seasonal trends with peaks corresponding with the rainy season, while bloody diarrhoea, acute fever with rash and acute jaundice syndrome did not. Seasonality was the most common predictor for watery and bloody diarrhoea, prolonged fever, suspected dengue, and acute fever plus rash in those aged 5 and over, explaining between 0.4 % – 37.8 % of the variation across all conditions. Higher rainfall was the most common predictor for acute fever plus rash and acute jaundice syndrome in children under 5, explaining between 1.0 % – 7.6 % variation across all conditions. Each EWARS syndromic condition case peak was associated with a different rainfall lag, varying between 0 and 11 weeks. The relationships between EWARS, rainfall and seasonality show that it is possible to predict when outbreaks will occur by following seasonality and rainfall. Pre-positioning of diagnostic and treatment resources could then be aligned with seasonality and rainfall peaks to plan and address water-related disease outbreaks

Optimized fishing through periodically harvested closures

1. Periodically harvested closures (PHCs) are a traditional form of fisheries management that improve fishing efficiency during harvests, partly by reducing fish wariness to fishers during closed periods. However, whether PHCs also result in high yields and healthy marine ecosystems is unknown, even as PHCs are being promoted as a culturally appropriate management tool in the Indo-Pacific.2. We integrated field-derived estimates of change in fish wariness into a bioeconomic fisheries model to quantify to what degree PHCs can maximize harvest efficiency, fisheries yield and fish stock biomass.3. Our model indicated that PHCs that had a closure period of one to a few years between a single pulse harvest were able to generate equivalent fisheries yield and stock biomass levels, with greater harvest efficiency than was able to be achieved using permanent closures and other fisheries management tools.4. Fish life-history traits had little impact on the optimality of PHCs in maximizing the triple objective of harvest efficiency, fisheries yield and stock abundance, with overfishing similarly having little effect at anything under extreme levels. Under moderate overfishing, there was a trade-off between PHCs, which maximised harvest efficiency, and no-take permanent closures that maximised yield. However, the former outweighed the latter, and only at extreme levels of overfishing, where stock was reduced to < 18 % of unfished biomass, were permanent closures favoured over PHCs

Dispersal can spread management benefits: Insights from a modeled Fijian coral reef network

The combined effects of coral and macroalgal propagule dispersal, local bistability dynamics and pressures that span the land‐sea interface are not well understood, and consequently, are not well accounted for in coral reef management planning. In particular, fishing and sedimentation from nearby watersheds can tip reefs from coral‐dominated stable states to macroalgal‐dominated stable states. To address these knowledge gaps, we developed a mathematical model of the benthic cover dynamics of a 75‐Reef network in Fiji to compare the effectiveness of three different management intervention types: extending the area of periodic fishery closures to encompass more reefs (modeled by increasing herbivore grazing rates; managing a sea‐based pressure), improving water quality across Fiji (modeled by decreasing coral mortality rates; managing a land‐based pressure) and the two interventions combined (managing land and sea‐based pressures simultaneously). We ran the model with three grazing scenarios (low, medium, high) to account for uncertainty in actual herbivore grazing rates among reefs, as well as to represent regimes of macroalgal‐dominated, bistable and coral‐dominated dynamics in isolated reefs. Our results indicate that the presence of connectivity in the model stabilized the dynamics, with the final benthic cover and management effects exhibiting almost no sensitivity to initial conditions under the medium grazing scenario. The model predicts that the integrated land‐sea management is the most effective management intervention for ensuring high coral cover (>30%). We also find that fishery closure management that improves the grazing rate in less than half of the reef network can lead to increases in coral cover across the entire reef network. This result suggests that, as long as a few reefs in the network have high grazing, reefs across the network may trend to high coral cover as long as environmental conditions do not change. Based on an expected value of perfect information analysis, we find that the effectiveness of the integrated land‐sea management intervention is robust to the three grazing scenarios and suggests that this model can inform management decisions even with uncertainty. These findings advance our understanding of how a network of ecosystem patches with local bistability could behave and informs their management

Coastal seawater turbidity and thermal stress control growth of reef-building Porites spp. corals in Fiji

Nearshore reefs, at the interface of land-sea interactions, provide essential ecosystem services, but are susceptible to multiple global and local stressors. These stressors can detrimentally impact coral growth and the continuity of the reef framework. Here, we analyse coral growth records (1998 – 2016) of massive Porites spp. colonies from nearshore reefs in Fiji. Our aim is to assess the role of thermal stress and turbidity on coral growth across a range of environments. Our findings reveal a negative linear relationship between linear extension and seawater turbidity across locations (GLM, R2 = 0.42, p < 0.001), indicating that average coral growth is significantly influenced by local environmental conditions. On interannual timescales, all locations experienced a 14% to 30% decrease in linear extension in response to acute thermal stress during the 2013 – 2016 period. This finding highlights the existence of compounding effects between water quality and thermal stress. We suggest that inshore, long-lived massive hard corals in areas of high turbidity are more vulnerable to increasing SSTs due to an already reduced mean growth. Integrated management strategies in these regions that considers managing for multiple, interacting local stressors are warranted to enhance resilience

Natural and anthropogenic changes to mangrove distributions in the Pioneer River Estuary (QLD, Australia)

We analyzed a time series of aerial photographs and Landsat satellite imagery of the Pioneer River Estuary (near Mackay, Queensland, Australia) to document both natural and anthropogenic changes in the area of mangroves available to filter river runoff between 1948 and 2002. Over 54 years, there was a net loss of 137 ha (22%) of tidal mangroves during four successive periods that were characterized by different driving mechanisms: (1) little net change (1948– 1962); (2) net gain from rapid mangrove expansion (1962–1972); (3) net loss from clearing and tidal isolation (1972–1991); and (4) net loss from a severe species-specific dieback affecting over 50% of remaining mangrove cover (1991–2002). Manual digitization of aerial photographs was accurate for mapping changes in the boundaries of mangrove distributions, but this technique underestimated the total loss due to dieback. Regions of mangrove dieback were identified and mapped more accurately and efficiently after applying the Normalized Difference Vegetation Index (NDVI) to Landsat Thematic Mapper satellite imagery, and then monitoring changes to the index over time. These remote sensing techniques to map and monitor mangrove changes are important for identifying habitat degradation, both spatially and temporally, in order to prioritize restoration for management of estuarine and adjacent marine ecosystems

Trade-offs between data resolution, accuracy, and cost when choosing information to plan reserves for coral reef ecosystems

Conservation planners must reconcile trade-offs associated with using biodiversity data of differing qualities to make decisions. Coarse habitat classifications are commonly used as surrogates to design marine reserve networks when fine-scale biodiversity data are incomplete or unavailable. Although finely-classified habitat maps provide more detail, they may have more misclassification errors, a common problem when remotely-sensed imagery is used. Despite these issues, planners rarely consider the effects of errors when choosing data for spatially explicit conservation prioritizations. Here we evaluate trade-offs between accuracy and resolution of hierarchical coral reef habitat data (geomorphology and benthic substrate) derived from remote sensing, in spatial planning for Kubulau District, Fiji. For both, we use accuracy information describing the probability that a mapped habitat classification is correct to design marine reserve networks that achieve habitat conservation targets, and demonstrate inadequacies of using habitat maps without accuracy data. We show that using more detailed habitat information ensures better representation of biogenic habitats (i.e. coral and seagrass), but leads to larger and more costly reserves, because these data have more misclassification errors, and are also more expensive to obtain. Reduced impacts on fishers are possible using coarsely-classified data, which are also more cost-effective for planning reserves if we account for data collection costs, but using these data may under-represent reef habitats that are important for fisheries and biodiversity, due to the maps low thematic resolution. Finally, we show that explicitly accounting for accuracy information in decisions maximizes the chance of successful conservation outcomes by reducing the risk of missing conservation representation targets, particularly when using finely classified data