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Cumming, S.

Publications and source records attributed to Cumming, S..

2 recordsLinked to original sources

Comparing global and regional maps of intactness in the boreal region of North America: Implications for conservation planning in one of the world's remaining wilderness areas

Though North Americas boreal forest contains some of the largest remaining intact and wild ecosystems in the world, human activities are systematically reducing its extent. Consequently, forest intactness and human influence maps are increasingly used for monitoring and conservation planning in the boreal region. We compare eight forest intactness and human impact maps to provide a multi-model assessment of intactness in the boreal region. All maps are global in extent except for Global Forest Watch Canadas Human Access (2000) and Intact Forest Landscapes (2000, 2013) maps, although some global maps are restricted to areas that were at least 20% treed. As a function of each maps spatial coverage in North America, the area identified as intact ranged from 55% to 79% in Canada and from 32% to 96% in Alaska. Likewise, the similarity between pairs of datasets in the Canadian boreal ranged from 0.58 to 0.86 on a scale of 0-1. In total, 45% of the region was identified as intact by the seven most recent datasets. There was also variation in the ability of the datasets to account for anthropogenic disturbances that are increasingly common in the boreal region, such as those associated with resource extraction. In comparison to a recently developed high resolution regional disturbance dataset, the four human influence datasets (Human Footprint, Global Human Modification, Large Intact Areas, and Anthropogenic Biomes), in particular, omitted 59-85% of all linear disturbances and 54-89% of all polygonal disturbances. In contrast, the global IFL, Canadian IFL, and Human Access maps omitted 2-7% of linear disturbances and 0.1-5% of polygonal disturbances. Several differences in map characteristics, including input datasets and methods used to develop the maps may help explain these differences. Ultimately, the decision on which dataset to use will depend on the objectives of each specific conservation planning project, but we recommend using datasets that 1) incorporate regional anthropogenic activities, 2) are updated regularly, 3) provide detailed information of the methods and input data used, and 4) can be replicated and adapted for local use. This is especially important in landscapes that are undergoing rapid change due to development, such as the boreal forest of North America.

ecology

Towards development of a statistical framework to evaluate myotonic dystrophy type 1 mRNA biomarkers in the context of a clinical trial

Myotonic dystrophy type 1 (DM1) is a rare genetic disorder, characterised by muscular dystrophy, myotonia, and other symptoms. DM1 is caused by the expansion of a CTG repeat in the 3-untranslated region of DMPK. Longer CTG expansions are associated with greater symptom severity and earlier age at onset. The primary mechanism of pathogenesis is thought to be mediated by a gain of function of the CUG-containing RNA, that leads to trans-dysregulation of RNA metabolism of many other genes. Specifically, the alternative splicing (AS) and alternative polyadenylation (APA) of many genes is known to be disrupted. In the context of clinical trials of emerging DM1 treatments, it is important to be able to objectively quantify treatment efficacy at the level of molecular biomarkers. We show how previously described candidate mRNA biomarkers can be used to model an effective reduction in CTG length, using modern high-dimensional statistics (machine learning), and a blood and muscle mRNA microarray dataset. We show how this model could be used to detect treatment effects in the context of a clinical trial.

bioinformatics