Satellite remote sensing, biodiversity research and conservation of the future

Biodiversity monitoring, earth observations and the ecology of scale

Human activity and land-use change are dramatically altering the sizes, geographical distributions and functioning of biological populations worldwide, with tremendous consequences for human well-being. Yet our ability to measure, monitor and forecast biodiversity change - crucial to addressing it - remains limited. Biodiversity monitoring systems are being developed to improve this capacity by deriving metrics of change from an array of in situ data (e.g. field plots or species occurrence records) and Earth observations (EO; e.g. satellite or airborne imagery). However, there are few ecologically based frameworks for integrating these data into meaningful metrics of biodiversity change. Here, I describe how concepts of pattern and scale in ecology could be used to design such a framework. I review three core topics: the role of scale in measuring and modelling biodiversity patterns with EO, scale-dependent challenges linking in situ and EO data and opportunities to apply concepts of pattern and scale to EO to improve biodiversity mapping. From this analysis emerges an actionable approach for measuring, monitoring and forecasting biodiversity change, highlighting key opportunities to establish EO as the backbone of global-scale, science-driven conservation.

Spatiotemporal analysis of the effect of climate change on vegetation health in the Drakensberg Mountain Region of South Africa

The impact of climate change on mountain ecosystems has been in the spotlight for the past three decades. Climate change is generally considered to be a threat to ecosystem health in mountain regions. Vegetation indices can be used to detect shifts in ecosystem phenology and climate change in mountain regions while satellite imagery can play an important role in this process. However, what has remained problematic is determining the extent to which ecosystem phenology is affected by climate change under increasingly warming conditions. In this paper, we use climate and vegetation indices that were derived from satellite data to investigate the link between ecosystem phenology and climate change in the Namahadi Catchment Area of the Drakensberg Mountain Region of South Africa. The time series for climate indices as well as those for gridded precipitation and temperature data were analyzed in order to determine climate shifts, and concomitant changes in vegetation health were assessed in the resultant epochs using vegetation indices. The results indicate that vegetation indices should only be used to assess trends in climate change under relatively pristine conditions, where human influence is limited. This knowledge is important for designing climate change monitoring strategies that are based on ecosystem phenology and vegetation health.

Monitoring protected areas from space: A multi-temporal assessment using raptors as biodiversity surrogates

Monitoring protected areas (PAs) is essential for systematic evaluation of their effectiveness in terms of habitat protection, preservation and representativeness. This study illustrates how the use of species distribution models that combine remote sensing data and information about biodiversity surrogates can contribute to develop a systematic protocol for monitoring PAs. In particular, we assessed the effectiveness of the Natura 2000 (N2000) network, for conserving and preserving the representativeness of seven raptor species in a highly-dynamic landscape in northwest Spain between 2001 and 2014. We also evaluated the cost-effectiveness of the N2000 network by using the total area under protection as a proxy for conservation costs. Overall, the N2000 network was found to poorly represent the habitats of the raptor species. Despite the low representativeness, this network showed a high degree of effectiveness due to increased overall habitat availability for generalist and forest specialist species between 2001 and 2014. Nevertheless, additional protected areas should be established in the near future to increase their representativeness, and thus ensure the protection of open-habitat specialist species and their priority habitats. In addition, proactive conservation measures in natural and semi-natural ecosystems (in particular, montane heathlands) will be essential for long-term protection of Montagu's harrier (species listed in the Annex I of the Bird Directive), and thus complying with the current European Environmental Legislation. This study sheds light on how the development and application of new protected area indices based on the combined use of freely-available satellite data and species distribution models may contribute substantially to the cost-efficiency of the PA monitoring systems, and to the 'Fitness Check' process of EU Nature Directives.

Upland vegetation mapping using Random Forests with optical and radar satellite data

Uplands represent unique landscapes that provide a range of vital benefits to society, but are under increasing pressure from the management needs of a diverse number of stakeholders (e.g. farmers, conservationists, foresters, government agencies and recreational users). Mapping the spatial distribution of upland vegetation could benefit management and conservation programmes and allow for the impacts of environmental change (natural and anthropogenic) in these areas to be reliably estimated. The aim of this study was to evaluate the use of medium spatial resolution optical and radar satellite data, together with ancillary soil and topographic data, for identifying and mapping upland vegetation using the Random Forests (RF) algorithm. Intensive field survey data collected at three study sites in Ireland as part of the National Parks and Wildlife Service (NPWS) funded survey of upland habitats was used in the calibration and validation of different RF models. Eight different datasets were analysed for each site to compare the change in classification accuracy depending on the input variables. The overall accuracy values varied from 59.8% to 94.3% across the three study locations and the inclusion of ancillary datasets containing information on the soil and elevation further improved the classification accuracies (between 5 and 27%, depending on the input classification dataset). The classification results were consistent across the three different study areas, confirming the applicability of the approach under different environmental contexts.

Wind estimation based on thermal soaring of birds

The flight performance of birds is strongly affected by the dynamic state of the atmosphere at the birds' locations. Studies of flight and its impact on the movement ecology of birds must consider the wind to help us understand aerodynamics and bird flight strategies. Here, we introduce a systematic approach to evaluate wind speed and direction from the high-frequency GPS recordings from bird-borne tags during thermalling flight. Our method assumes that a fixed horizontal mean wind speed during a short (18 seconds, 19 GPS fixes) flight segment with a constant turn angle along a closed loop, characteristic of thermalling flight, will generate a fixed drift for each consequent location. We use a maximum-likelihood approach to estimate that drift and to determine the wind and airspeeds at the birds' flight locations. We also provide error estimates for these GPS-derived wind speed estimates. We validate our approach by comparing its wind estimates with the mid-resolution weather reanalysis data from ECMWF, and by examining independent wind estimates from pairs of birds in a large dataset of GPS-tagged migrating storks that were flying in close proximity. Our approach provides accurate and unbiased observations of wind speed and additional detailed information on vertical winds and uplift structure. These precise measurements are otherwise rare and hard to obtain and will broaden our understanding of atmospheric conditions, flight aerodynamics, and bird flight strategies. With an increasing number of GPS-tracked animals, we may soon be able to use birds to inform us about the atmosphere they are flying through and thus improve future ecological and environmental studies.

Digital technology and the conservation of nature

Digital technology is changing nature conservation in increasingly profound ways. We describe this impact and its significance through the concept of 'digital conservation', which we found to comprise five pivotal dimensions: data on nature, data on people, data integration and analysis, communication and experience, and participatory governance. Examining digital innovation in nature conservation and addressing how its development, implementation and diffusion may be steered, we warn against hypes, techno-fix thinking, good news narratives and unverified assumptions. We identify a need for rigorous evaluation, more comprehensive consideration of social exclusion, frameworks for regulation and increased multi-sector as well as multi-discipline awareness and cooperation. Along the way, digital technology may best be reconceptualised by conservationists from something that is either good or bad, to a dual-faced force in need of guidance.

The social implications of using drones for biodiversity conservation

Unmanned aerial vehicles, or 'drones', appear to offer a flexible, accurate and affordable solution to some of the technical challenges of nature conservation monitoring and law enforcement. However, little attention has been given to their possible social impacts. In this paper, I review the possible social impacts of using drones for conservation, including on safety, privacy, psychological wellbeing, data security and the wider understanding of conservation problems. I argue that negative social impacts are probable under some circumstances and should be of concern for conservation for two reasons: (1) because conservation should follow good ethical practice; and (2) because negative social impacts could undermine conservation effectiveness in the long term. The paper concludes with a call for empirical research to establish whether the identified social risks of drones occur in reality and how they could be mitigated, and for self-regulation of drone use by the conservation sector to ensure good ethical practice and minimise the risk of unintended consequences.