(Table 2) Temporal changes in phenological observations between 1978 and 2007, northern Sweden

A 30-year series (1978-2007) of photographic records were analysed to determine changes in lake ice cover, local (low elevation) and montane (high elevation) snow cover and phenological stages of mountain birch (Betula pubescens ssp. czerepanovii) at the Abisko Scientific Research Station, Sweden. In most cases, the photographic-derived data showed no significant difference in phenophase score from manually observed field records from the same period, demonstrating the accuracy and potential of using weekly repeat photography as a quicker, cheaper and more adaptable tool to remotely study phenology in both biological and physical systems. Overall, increases in ambient temperatures coupled with decreases in winter ice and snow cover, and earlier occurrence of birch foliage, signal a reduction in the length of winter, a shift towards earlier springs and an increase in the length of available growing season in the Swedish sub-arctic.

Multi-temporal mapping of seagrass cover, species and biomass of the Eastern Banks, Moreton Bay, Australia, with links to shapefiles

The spatial and temporal dynamics of seagrasses have been studied from the leaf to patch (100 m**2) scales. However, landscape scale (> 100 km**2) seagrass population dynamics are unresolved in seagrass ecology. Previous remote sensing approaches have lacked the temporal or spatial resolution, or ecologically appropriate mapping, to fully address this issue. This paper presents a robust, semi-automated object-based image analysis approach for mapping dominant seagrass species, percentage cover and above ground biomass using a time series of field data and coincident high spatial resolution satellite imagery. The study area was a 142 km**2 shallow, clear water seagrass habitat (the Eastern Banks, Moreton Bay, Australia). Nine data sets acquired between 2004 and 2013 were used to create seagrass species and percentage cover maps through the integration of seagrass photo transect field data, and atmospherically and geometrically corrected high spatial resolution satellite image data (WorldView-2, IKONOS and Quickbird-2) using an object based image analysis approach. Biomass maps were derived using empirical models trained with in-situ above ground biomass data per seagrass species. Maps and summary plots identified inter- and intra-annual variation of seagrass species composition, percentage cover level and above ground biomass. The methods provide a rigorous approach for field and image data collection and pre-processing, a semi-automated approach to extract seagrass species and cover maps and assess accuracy, and the subsequent empirical modelling of seagrass biomass. The resultant maps provide a fundamental data set for understanding landscape scale seagrass dynamics in a shallow water environment. Our findings provide proof of concept for the use of time-series analysis of remotely sensed seagrass products for use in seagrass ecology and management.