Suchergebnisse

The Mediterranean seagrass Posidonia oceanica maintains a biodiverse ecosystem and it is a world-wide important carbon sink. It grows for millennia, accumulating organic-rich soils (mats) beneath the meadows. This marine habitat is protected by the European Union; however, it is declining rapidly due to coastal development. Understanding its response to disturbances could inform habitat restoration, but many environmental impacts predate monitoring programs (years). This research explores the palaeoecological potential of Posidonia mats to reconstruct six thousand years of environmental change that could have affected Posidonia meadows and, in turn, left an imprint on the mats. Palynological, microcharcoal, magnetic susceptibility and glomalin-related soil protein (GRSP) analyses on Posidonia mats enabled us to detect climate- and human-induced environmental processes impacting on the seagrass during the Late Holocene. The pollen and microcharcoal records reconstructed anthropogenic disturbances attributed to agriculture. The record of GRSP shows that agrarian activities affected continental soil quality. Changes in magnetic susceptibility reveal that enhanced soil erosion was caused by both climate (major flooding events in the NW Mediterranean) and humans (cultivation) which impacted on the Posidonia mat. Finally, increased human impact is linked to eutrophication of coastal waters since Roman-Medieval times. Synthesis. This study shows that climate and land-use changes in the western Mediterranean resulted in enhanced loadings of terrigenous material to the coastal zone since the Late Holocene, likely disturbing the Posidonia meadows and their mat carbon accumulation dynamics. Under the current global change scenario in which CO2 emissions are projected to increase, restoring carbon sinks is a priority. Seagrass habitat restoration should consider not only the coastal perturbations, but also the continental ones at a catchment scale to preserve the socio-economic ecosystem services provided by seagrasses.

Strengthening links between school and community is critical for improving people's participation in environmental issues. However, Mexican education programmes are generally unrelated to rural students' life experience and are planned without considering either teachers' or students' opinions. This paper describes the participatory construction of a preparatory school environmental education programme in Ixtlan de Juarez, a Mexican indigenous community internationally recognized for sustainable forest management. The qualitative research methods used are based on the action research methodology. Results from interviews conducted with the preparatory school's headmaster, the coordinator, and nine teachers provided the needed documentation of the school site for contextualising learning activities. Feedback during focus group with six students, three teachers, five local communal authorities, and two researchers highlighted that all participants perceived the need for creating an educational programme focused on local forest management. The contents and activities of the programme were designed by the focus group's participants. The programme has been continuously taught by teachers and forest workers since 2005 and was officially integrated with the preparatory school science curriculum in 2006. This participative educational experience has thus transformed the mandatory school curriculum in Ixtlan.

With the growing recognition that effective action on climate change will require a combination of emissions reductions and carbon sequestration, protecting, enhancing and restoring natural carbon sinks have become political priorities. Mangrove forests are considered some of the most carbon-dense ecosystems in the world with most of the carbon stored in the soil. In order for mangrove forests to be included in climate mitigation efforts, knowledge of the spatial distribution of mangrove soil carbon stocks are critical. Current global estimates do not capture enough of the finer scale variability that would be required to inform local decisions on siting protection and restoration projects. To close this knowledge gap, we have compiled a large georeferenced database of mangrove soil carbon measurements and developed a novel machine-learning based statistical model of the distribution of carbon density using spatially comprehensive data at a 30m resolution. This model, which included a prior estimate of soil carbon from the global SoilGrids 250m model, was able to capture 63% of the vertical and horizontal variability in soil organic carbon density (RMSE of 10.9 kgm*3). Of the local variables, total suspended sediment load and Landsat imagery were the most important variable explaining soil carbon density. Projecting this model across the global mangrove forest distribution for the year 2000 yielded an estimate of 6.4 Pg C for the top meter of soil with an 86–729 Mg C ha*1 range across all pixels. By utilizing remotely-sensed mangrove forest cover change data, loss of soil carbon due to mangrove habitat loss between 2000 and 2015 was 30–122 Tg C with >75% of this loss attributable to Indonesia, Malaysia and Myanmar. The resulting map products from this work are intended to serve nations seeking to include mangrove habitats in payment-for- ecosystem services projects and in designing effective mangrove conservation strategies.

With the growing recognition that effective action on climate change will require a combination of emissions reductions and carbon sequestration, protecting, enhancing and restoring natural carbon sinks have become political priorities. Mangrove forests are considered some of the most carbon-dense ecosystems in the world with most of the carbon stored in the soil. In order for mangrove forests to be included in climate mitigation efforts, knowledge of the spatial distribution of mangrove soil carbon stocks are critical. Current global estimates do not capture enough of the finer scale variability that would be required to inform local decisions on siting protection and restoration projects. To close this knowledge gap, we have compiled a large georeferenced database of mangrove soil carbon measurements and developed a novel machine-learning based statistical model of the distribution of carbon density using spatially comprehensive data at a 30m resolution. This model, which included a prior estimate of soil carbon from the global SoilGrids 250m model, was able to capture 63% of the vertical and horizontal variability in soil organic carbon density (RMSE of 10.9 kgm*3). Of the local variables, total suspended sediment load and Landsat imagery were the most important variable explaining soil carbon density. Projecting this model across the global mangrove forest distribution for the year 2000 yielded an estimate of 6.4 Pg C for the top meter of soil with an 86–729 Mg C ha*1 range across all pixels. By utilizing remotely-sensed mangrove forest cover change data, loss of soil carbon due to mangrove habitat loss between 2000 and 2015 was 30–122 Tg C with >75% of this loss attributable to Indonesia, Malaysia and Myanmar. The resulting map products from this work are intended to serve nations seeking to include mangrove habitats in payment-for- ecosystem services projects and in designing effective mangrove conservation strategies.