Back

Using a residency index to estimate the economic value of saltmarsh provisioning services for commercially important fish species

Mills, M.; McCormick, H.; Davis, K.; Salguero-Gomez, R.

2019-09-11 ecology
10.1101/755835 bioRxiv
Show abstract

Every year, 100 hectares of saltmarsh in the United Kingdom are lost due to sea level rise. The remaining areas are threatened by land conversion, agricultural activities, and climate change. There are important economic consequences to saltmarsh loss, as saltmarsh provides valuable ecosystem services including flood protection, carbon sequestration, and nursery habitat for commercially fished species. Quantifying the economic value of these ecosystem services can help target policies for saltmarsh restoration, or managed realignment, of new saltmarsh areas. In this study, we quantify the economic value of saltmarsh as a habitat for commercially fished species by developing a residency index. The residency index weights the relative importance of saltmarsh along a species lifecycle by explicitly incorporating the target species life histories and the estimated proportion of time it spends in saltmarsh at juvenile and adult life stages. Using this index, we estimate the value of saltmarsh to UK commercial fisheries landings. We find that UK saltmarsh contributes annually between 16.7% and 18.2% of total UK commercial landings for European seabass (Dicentrarchus labrax), European plaice (Pleuronectes platessa), and Common sole (Solea solea). Our findings highlight the importance of saltmarsh protection and restoration. Furthermore, our approach provides a general framework that integrates population ecology methods and economic analyses to assess the value of saltmarsh and other coastal habitats for fisheries worldwide.

Matching journals

The top 10 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.