Thu, Aug 18, 2022: 8:15 AM-8:30 AM
513E
Background/Question/MethodsNorthern protected areas are important refuges for species migrating north due to climate change; however, with their fixed spatial boundaries, protected areas are themselves highly vulnerable to environmental change. In this study, we use remote sensing and geostatistical modelling to identify drivers of past and future land cover change for the 9,700 km2 extent of Torngat Mountains National Park (TMNP) in Nunatsiavut and Nunavik, Canada.
Results/ConclusionsTMNP has undergone significant environmental change in recent decades, including rapid temperature warming, a decline in the extent of glaciers, permafrost, and sea ice, and a globally significant amount of vegetation ‘greening’. Model hindcasting showed that a 235% increase in shrub cover and 105% increase in wet vegetation occurred from 1985 to 2019. Shrub cover was highly persistent and frequently displaced wet vegetation in low-elevation areas in the south of the park. Predictive modelling showed biotic (initial land cover class, number of neighbouring shrub pixels) and topographic variables (elevation, latitude, distance to coast) to be strong predictors of shrub expansion and forecast a further 51% increase in shrub cover by 2039/43. Establishing long-term monitoring plots in areas where rapid vegetation change is mostly likely to occur would be beneficial for model validation, and would improve our understanding of the consequences of environmental change for biotic and abiotic components of the tundra ecosystem, including for important cultural keystone species.
Results/ConclusionsTMNP has undergone significant environmental change in recent decades, including rapid temperature warming, a decline in the extent of glaciers, permafrost, and sea ice, and a globally significant amount of vegetation ‘greening’. Model hindcasting showed that a 235% increase in shrub cover and 105% increase in wet vegetation occurred from 1985 to 2019. Shrub cover was highly persistent and frequently displaced wet vegetation in low-elevation areas in the south of the park. Predictive modelling showed biotic (initial land cover class, number of neighbouring shrub pixels) and topographic variables (elevation, latitude, distance to coast) to be strong predictors of shrub expansion and forecast a further 51% increase in shrub cover by 2039/43. Establishing long-term monitoring plots in areas where rapid vegetation change is mostly likely to occur would be beneficial for model validation, and would improve our understanding of the consequences of environmental change for biotic and abiotic components of the tundra ecosystem, including for important cultural keystone species.