Improving biodiversity monitoring using satellite remote sensing to provide solutions towards the 2020 conservation targets

1 INTRODUCTION

The preservation of biodiversity has become a major challenge for sustainable development at national, European (Natura 2000 and Habitats Directive) and international levels (Convention on Biological Diversity, 2011–2020). To address the current conservation needs, there is a need to operationalise methods to assess the distribution of natural resources while integrating information on habitat condition; inform conservation planning and support the assessment of ecosystem services. Increased access to satellite imagery and new developments in data analyses can support progress towards biodiversity conservation targets by stepping up monitoring processes at various spatial and temporal scales. Satellite imagery is indeed increasingly being made accessible to all, while analytical techniques to capitalise on the information contained in spatially explicit species data, such as Global Biodiversity Information Facility (GBIF), are constantly developing, and offering a plurality of options for application. Free and open data policy is having a dramatic impact on our ability to understand how biodiversity is being affected by anthropogenic pressures, leading to increased opportunities to predict the consequences of changes in drivers at different scales and plan for more efficient mitigation measures.

Satellite remote sensing is however no panacea, and little can be achieved without a robust understanding of the socio-ecological system considered. Similarly, access to relevant field-based information is the key to satellite imagery to be properly calibrated, analysed and validated. This need for close collaboration between ecologists, modellers and remote sensing experts to derive meaningful information can represent a serious challenge (Pettorelli, Safi, & Turner, 2014). With this special feature, we aim to illustrate why tackling this challenge is worth doing, by demonstrating how the coupling of satellite remote sensing data with ground observations and adequate modelling can provide tangible operational solutions towards a better understanding and management of natural systems.

The contributions featured in this special feature result from targeted invitations to prominent satellite remote sensing experts, who have a known interest in applied ecology and are currently working on innovative applications and methodological development to improve environmental management outcomes. These contributions focus on three key conservation challenges, namely (1) the monitoring of biodiversity; (2) the development of an improved understanding of biodiversity patterns; (3) the assessment of biodiversity's vulnerability to climate change.

2 MONITORING BIODIVERSITY

It is now clear that human activities have led to stress and disturbance to biodiversity and ecosystems from local to global scales. Reliably monitoring biodiversity globally is an important component of the grand plan required to prevent further biodiversity loss and restore healthy levels of biodiversity worldwide. Biodiversity is a multidimensional, complex concept that refers to all multiscalar and multitemporal structures and processes occurring at different levels of functional organisation, that is, from the genetic to the ecosystemic level. One of the most used methodologies to track changes in species composition and turnover is based on taxonomic approaches and community ecology theories, yet there are satellite-based alternatives to this common approach. Specifically, various studies have demonstrated how satellite remote sensing can be used to infer species richness but few have addressed the measurement of species compositional turnover from satellite imagery. This challenge is tackled in this special issue, by Rocchini and colleagues, who provide an example of how compositional turnover (β-diversity) can be estimated from satellite imagery. This original work introduces a novel technique to measure β-diversity from airborne or satellite remote sensing, demonstrating how critical information on the distribution of biodiversity over wide areas can be garnered in a standardised way and in a reasonable time.

Knowing about where things are, is sadly not enough. An understanding and consideration of changes in quality or condition is also necessary to assess how biodiversity is faring. While focusing on terrestrial systems, Lausch and colleagues compare different approaches to vegetation health monitoring, specifically in situ species approaches and remote sensing techniques. While doing so, they provide an overview of in situ species approaches, that is, the biological species concept, the phylogenetic species concept, and the morphological species concept, as well as an overview of the remote sensing spectral trait/spectral trait variation concept to monitor status, processes of stress, disturbances, and resource limitations affecting vegetation health.

3 DEVELOPING AN IMPROVED UNDERSTANDING OF BIODIVERSITY PATTERNS

It is clear now that human activities have led to stress and disturbance to biodiversity and ecosystems from local to global scales. But monitoring is only one component of the grand plan required to prevent further biodiversity loss and restore healthy levels of biodiversity worldwide. A key aspect of management is the need for developing an understanding of what is happening that is good enough to support the elaboration of realistic and scientifically informed predictions. Satellite remote sensing has been extensively discussed in the context of biodiversity monitoring; yet one obvious contribution of this technology is in its ability to support the development and implementation of ecological models. For this special issue, Pasetto and colleagues provide a review that illustrate how satellite remote sensing has so far been used in ecosystem models, contrasting situations where satellite data have been used as (1) input to define model drivers; (2) reference to validate model results; and (3) as a tool to sequentially update the state variables, and to quantify and reduce model uncertainty. One key message from this contribution is that the synergetic use of satellite data and ecosystem models is far too uncommon, and likely to increase in scope and intensity as a broader range of satellite data become accessible.

Developing a global understanding of the factors driving changes in biodiversity requires access to comparable information about elements of biodiversity in various places on Earth. To this end, efforts over the past decade have focused on the identification of essential biodiversity variables (EBVs; Pereira et al., 2013), defined as variable or a group of linked variables that allows quantification of the rate and direction of change in one aspect of the state of biodiversity over time and across space (Pettorelli et al., 2018). EBVs are planned to harmonise assessment of biodiversity monitoring at any scales, and to support the aims of the Convention on Biological Diversity and IPBES. From the start, satellite remote sensing has been expected to be an important methodology for the derivation of EBVs, and indeed, satellite remote sensing EBVs (SRS-EBVs) have been conceptualised as the subset of EBVs whose monitoring relies largely or wholly on the use of satellite-based data. So far, there has been little agreement on what these SRS-EBVs should be (Skidmore et al., 2015) and most potential SRS-EBVS discussed rely on a single type of sensor (primarily optical). Alleaume and colleagues here introduce a generic remote sensing approach to derive operational SRS-EBVs for conservation planning. One interesting aspect of this work (Alleaume et al., this issue; Pettorelli et al., 2016) is that hybrid methods and data fusion using very high spatial resolution sensors are being explicitly considered and tested in different complex landscapes encompassing three French biogeographical regions. EBVs are planned to harmonise assessment of biodiversity monitoring at any scales, and to support the aims of the Convention on Biological Diversity and IPBES.

All in all, biodiversity includes multiscalar and multitemporal structures and processes, with different levels of functional organisation, from genetic to ecosystemic levels. Still, one of the mostly used methods to infer biodiversity is based on taxonomic approaches and community ecology theories. However, as stressed in the aforementioned papers published in this special feature, gathering extensive data in the field is difficult due to logistic problems, especially when aiming at modelling biodiversity changes in space and time, which assumes statistically sound sampling schemes. In this context, we would like to stress the use of airborne or satellite remote sensing to gather critical information over wide areas in a reasonable time. Presently, few studies have addressed the measurement of species compositional turnover from space, most of the biodiversity mapping obtained from remote sensing have been based on the inference of species richness. Rocchini and colleagues (this issue) provide an example of compositional turnover (β-diversity) estimation. This original work adds crucial information in relation to relative abundance of different species instead of just richness, proposing a novel technique to measure β-diversity from airborne or satellite remote sensing.

4 ASSESSING BIODIVERSITY'S VULNERABILITY TO CLIMATE CHANGE

Climate change represents a major threat to biodiversity and a challenge to improve efficient monitoring methods. The scientific community has so far devoted a lot of energy into developing methods and frameworks enabling the assessment of current and future species vulnerability to climate change, but much less has been done for ecosystems. Satellite remote sensing technology is expected to represent one of the most cost-effective ways to identify ecosystems put at risk from changes in climatic conditions, but this potential remains to be fully demonstrated. Focusing on a series of mangrove ecosystems around the world, Duncan et al. (2018) illustrate how to capitalise on the current availability and diversity of satellite products to (1) assess both coastal ecosystem resilience and resistance capacity to sea level rise, and (2) identify landscape-level and anthropogenic factors driving these capacities. It must be highlighted that coastal ecosystems, especially mangroves are of key importance for a variety of ecosystem services, however highly threatened by ongoing human activities. In that sense, the work presented in this feature by Duncan et al. (2018) addressed their importance while developed at the same time a rigorous novel remote sensing product for assessing coastal resilience and resistance capacity concerning seas level rise. Alarmingly low resilience and resistance across the study region could be seen and stressed the importance of regular remotely sensed assessment of these systems.

The developed approach provides a remarkable addition to the remote monitoring and assessment toolkit for adaptive coastal ecosystem management, providing a new opportunity to inform conservation and management priority assessments in data deficient regions.

5 CONCLUSIONS

The study cases presented in this special feature clearly demonstrate how satellite remote sensing data can support biodiversity monitoring and conservation at different spatio-temporal resolutions and scales, and how high level of integration between field data and satellite imagery can lead to significant improvements in our understanding of the natural world. In particular, we stress the importance to make use of the imagery that is becoming available as open data to significantly improve monitoring natural habitats in answer to urgent conservation planning needs. All in all, we aimed to highlight recent developments in satellite remote sensing techniques, and demonstrate through study cases how operational solutions can be designed and implemented to increase our understanding of natural systems and to improve our ability to manage them. The set of papers in this special feature provide operational concrete examples of management relevant, satellite-based methodologies that are technically feasible, economically viable and sustainable in time.