气候变化领域集成服务门户

Monitoring the impacts of pressures, such as climate change, on marine benthic ecosystems is of high conservation priority. Novel imaging technologies, such as autonomous underwater vehicles (AUVs), remotely operated vehicles (ROVs), and towed systems, now give researchers the ability to monitor benthic ecosystems over large spatial and temporal scales. The design of monitoring programmes that use such technologies is currently hindered by a lack of information about the typical abundance and spatial distributions of target indicators and the level of sampling required to detect changes. A further complicating factor is that these sampling platforms are often not able to be exactly relocated when conducting repeat surveys. How the spatial properties of benthic organisms influence the estimates of cover, given alternative designs that vary in the geolocation precision of transects and the sampling intensity of images, is explored. A geostatistical modelling approach is used to quantify the spatial distribution of 20 key deep-water invertebrate species at a long-term monitoring site. The parameter estimates from these models are then used to simulate repeat transects with geolocation error and different levels of sampling. Results suggest that species with short effective ranges (i.e. those with strong spatial dependence over relatively short distances) and large spatial variance, which suggests strong spatial dependence effects, will require greater sampling effort to achieve a given standard of precision. Spatial offsets of 2 m, typical of an AUV, are unlikely to have dramatic impacts on the precision of estimates when sufficient images are sampled, but offsets of 10 m that are typical of towed systems may require a prohibitively high sampling effort for some species. These findings have important implications for benthic monitoring programmes, and highlight the importance of considering the interactions between sampling design, the technical limitations of survey equipment, and the spatial properties of indicator species.