Effects of Human Population Density and Proximity to Markets on Coral Reef Fishes Vulnerable to Extinction by Fishing

Abstract

Coral reef fisheries are crucial to the livelihoods of tens of millions of people; yet, widespread habitat degradation and unsustainable fishing are causing severe depletion of stocks of reef fish. Understanding how social and economic factors, such as human population density, access to external markets, and modernization interact with fishing and habitat degradation to affect fish stocks is vital to sustainable management of coral reef fisheries. We used fish survey data, national social and economic data, and path analyses to assess whether these factors explain variation in biomass of coral reef fishes among 25 sites in Solomon Islands. We categorized fishes into 3 groups on the basis of life-history characteristics associated with vulnerability to extinction by fishing (high, medium, and low vulnerability). The biomass of fish with low vulnerability was positively related to habitat condition. The biomass of fishes with high vulnerability was negatively related to fishing conducted with efficient gear. Use of efficient gear, in turn, was strongly and positively related to both population density and market proximity. This result suggests local population pressure and external markets have additive negative effects on vulnerable reef fish. Biomass of the fish of medium vulnerability was not explained by fishing intensity or habitat condition, which suggests these species may be relatively resilient to both habitat degradation and fishing.

Identifying multiple coral reef regimes and their drivers across the Hawaiian archipelago

“…Population density has been used as a coarse proxy for overall human influence on coral reefs [45]. However, in recent studies, the relationships between population density and reef states appear ambiguous [46,47]. This study suggests that population density is a relatively poor predictor of reef regimes across the Hawaiian archipelago, which is overwhelmed by the influence of more refined proxies, particularly those for land-based pollution and land-use change (such as effluent discharge or stream fragmentation).…”

Managing coral reef fish community biomass is a priority for biodiversity conservation in Madagascar

“…The human influence metric does not take account of resource abundance metrics, such as reef area, nor of human infrastructure and travel time, or livelihood alternatives such as agriculture and animal husbandry among other socioeconomic attributes that should influence fishing pressure . Given the better predictions of human influence and environmental factors in other regions (Friedlander et al 2003, Brewer et al 2013, Houk & Musburger 2013, Williams et al 2015, Maire et al 2016, Mellin et al 2016a, the weaker responses found here suggests the need for an evaluation of fishing pressure and the factors that promote it at smaller spatial scales. Good models must account for various local factors influencing the balance between fish production and human impacts.…”

“…Across these broad social-ecological conditions there were likely to be a number of biophysical, infrastructural, cultural, and fisheries management differences that influence the capture of fish (Cinner et al 2009. Nevertheless, our findings indicate some of the weaknesses in the development of spatial predictions and models based on distance to market and population sizes that have been used to predict fish biomass (Brewer et al 2013). For example, a western Indian Ocean fish biomass model based mostly on distance to market and management systems predicted biomass in the Comoros well but underestimated the fishable biomass in Madagascar and Mayotte ).…”

“…The final variables included median photosynthetically active ra diation (PAR), total suspended solids (TSS), median chlorophyll a and, from the temperature time series, SST median, SST standard deviation, SST kurtosis, and SST skewness. A human influence metric was developed based on human population density and distance to nearest markets (Brewer et al 2013). Population data were derived from the Euclidean distance of sites to the nearest town and the populations of the town were added for each record.…”

“…Biomasses in the high human influence areas were composed of taxa of low fisheries or economic value, including small damselfish and odd-shaped piscivores such as lizardfish, cornetfish, scorpionfish, and trumpetfish. Human influence and related variables have been shown to be good predicators of fish biomass and vulnerable taxa in some regions (Brewer et al 2013, Maire et al 2016) but such variables may be a crude metric of human impacts because of variations in the responses of target and non-target taxa and whether or not fishers are migratory (McClanahan & Muthiga 2017). The human influence metric does not take account of resource abundance metrics, such as reef area, nor of human infrastructure and travel time, or livelihood alternatives such as agriculture and animal husbandry among other socioeconomic attributes that should influence fishing pressure .…”