Assessing the role of EO in biodiversity monitoring: options for integrating in-situ observations with EO within the context of the EBONE concept

The European Biodiversity Observation Network (EBONE) is a European contribution on terrestrial monitoring to GEO BON, the Group on Earth Observations Biodiversity Observation Network. EBONE’s aims are to develop a system of biodiversity observation at regional, national and European levels by assessing existing approaches in terms of their validity and applicability starting in Europe, then expanding to regions in Africa. The objective of EBONE is to deliver: 1. A sound scientific basis for the production of statistical estimates of stock and change of key indicators; 2. The development of a system for estimating past changes and forecasting and testing policy options and management strategies for threatened ecosystems and species; 3. A proposal for a cost-effective biodiversity monitoring system. There is a consensus that Earth Observation (EO) has a role to play in monitoring biodiversity. With its capacity to observe detailed spatial patterns and variability across large areas at regular intervals, our instinct suggests that EO could deliver the type of spatial and temporal coverage that is beyond reach with in-situ efforts. Furthermore, when considering the emerging networks of in-situ observations, the prospect of enhancing the quality of the information whilst reducing cost through integration is compelling. This report gives a realistic assessment of the role of EO in biodiversity monitoring and the options for integrating in-situ observations with EO within the context of the EBONE concept (cfr. EBONE-ID1.4). The assessment is mainly based on a set of targeted pilot studies. Building on this assessment, the report then presents a series of recommendations on the best options for using EO in an effective, consistent and sustainable biodiversity monitoring scheme. The issues that we faced were many: 1. Integration can be interpreted in different ways. One possible interpretation is: the combined use of independent data sets to deliver a different but improved data set; another is: the use of one data set to complement another dataset. 2. The targeted improvement will vary with stakeholder group: some will seek for more efficiency, others for more reliable estimates (accuracy and/or precision); others for more detail in space and/or time or more of everything. 3. Integration requires a link between the datasets (EO and in-situ). The strength of the link between reflected electromagnetic radiation and the habitats and their biodiversity observed in-situ is function of many variables, for example: the spatial scale of the observations; timing of the observations; the adopted nomenclature for classification; the complexity of the landscape in terms of composition, spatial structure and the physical environment; the habitat and land cover types under consideration. 4. The type of the EO data available varies (function of e.g. budget, size and location of region, cloudiness, national and/or international investment in airborne campaigns or space technology) which determines its capability to deliver the required output. EO and in-situ could be combined in different ways, depending on the type of integration we wanted to achieve and the targeted improvement. We aimed for an improvement in accuracy (i.e. the reduction in error of our indicator estimate calculated for an environmental zone). Furthermore, EO would also provide the spatial patterns for correlated in-situ data. EBONE in its initial development, focused on three main indicators covering: (i) the extent and change of habitats of European interest in the context of a general habitat assessment; (ii) abundance and distribution of selected species (birds, butterflies and plants); and (iii) fragmentation of natural and semi-natural areas. For habitat extent, we decided that it did not matter how in-situ was integrated with EO as long as we could demonstrate that acceptable accuracies could be achieved and the precision could consistently be improved. The nomenclature used to map habitats in-situ was the General Habitat Classification. We considered the following options where the EO and in-situ play different roles: using in-situ samples to re-calibrate a habitat map independently derived from EO; improving the accuracy of in-situ sampled habitat statistics, by post-stratification with correlated EO data; and using in-situ samples to train the classification of EO data into habitat types where the EO data delivers full coverage or a larger number of samples. For some of the above cases we also considered the impact that the sampling strategy employed to deliver the samples would have on the accuracy and precision achieved. Restricted access to European wide species data prevented work on the indicator ‘abundance and distribution of species’. With respect to the indicator ‘fragmentation’, we investigated ways of delivering EO derived measures of habitat patterns that are meaningful to sampled in-situ observations

ENHANCING CONSERVATION WITH HIGH RESOLUTION PRODUCTIVITY DATASETS FOR THE CONTERMINOUS UNITED STATES

Human driven alteration of the earth’s terrestrial surface is accelerating through land use changes, intensification of human activity, climate change, and other anthropogenic pressures. These changes occur at broad spatio-temporal scales, challenging our ability to effectively monitor and assess the impacts and subsequent conservation strategies. While satellite remote sensing (SRS) products enable monitoring of the earth’s terrestrial surface continuously across space and time, the practical applications for conservation and management of these products are limited. Often the processes driving ecological change occur at fine spatial resolutions and are undetectable given the resolution of available datasets. Additionally, the links between SRS data and ecologically meaningful metrics are weak. Recent advances in cloud computing technology along with the growing record of high resolution SRS data enable the development of SRS products that quantify ecologically meaningful variables at relevant scales applicable for conservation and management. The focus of my dissertation is to improve the applicability of terrestrial gross and net primary productivity (GPP/NPP) datasets for the conterminous United States (CONUS). In chapter one, I develop a framework for creating high resolution datasets of vegetation dynamics. I use the entire archive of Landsat 5, 7, and 8 surface reflectance data and a novel gap filling approach to create spatially continuous 30 m, 16-day composites of the normalized difference vegetation index (NDVI) from 1986 to 2016. In chapter two, I integrate this with other high resolution datasets and the MOD17 algorithm to create the first high resolution GPP and NPP datasets for CONUS. I demonstrate the applicability of these products for conservation and management, showing the improvements beyond currently available products. In chapter three, I utilize this dataset to evaluate the relationships between land ownership and terrestrial production across the CONUS domain. The main results of this work are three publically available datasets: 1) 30 m Landsat NDVI; 2) 250 m MODIS based GPP and NPP; and 3) 30 m Landsat based GPP and NPP. My goal is that these products prove useful for the wider scientific, conservation, and land management communities as we continue to strive for better conservation and management practices

Modeling the distribution of riverine vegetation in regulated rivers - from dynamic to static equilibrium

Doutoramento FLUVIO - River Restoration and Management / Instituto Superior de Agronomia / Faculdade de Arquitetura / Instituto Superior Técnico. Universidade de LisboaWhile methodological advances in ecosystem modeling reflect the growing recognition in the importance of accounting for dynamic change in river ecosystems, it is also recognized that various forms of regulation measures have completely disrupted its natural dynamics. In this context the underlying research question of this PhD is how river regulation affects the spatial distribution of riverine vegetation (aquatic and riparian) and whether rather simple static models that assume equilibrium between vegetation and environmental factors are adequate tools for its prediction. In a first step, we presented a systematic, quantitative literature review on models to predict the distribution of riverine vegetation on reach scale and identified research gaps to guide the further development of the thesis. Then, we developed and tested a habitat suitability model for aquatic vegetation based on hydrological variables. We concluded that during artificially stabilized (static) low flows the vegetation is in equilibrium with the physical instream condition and showed how the model can be used to define a flow threshold that reduces the risk of species invasion and proliferation. Further, we reconstructed the historic succession dynamics of a large river floodplain using a dynamic vegetation model and showed that typical regulation measures led to a steady progression of the vegetation communities toward mature phases without regression to younger stages. Finally, we applied different static and dynamic modeling approaches for the distribution of floodplain vegetation to the same study area and concluded from the comparison of their results that due to regulation measures the relevance of succession dynamics and disturbance stochasticity for the prediction of vegetation patterns is much reduced. Consequently, from a river manager ́s perspective, static models seem to be an adequate option for the modeling of the distribution of riverine vegetation in artificially stabilized environments since they show high accuracy, need relatively few resources (data, time, expert knowledge) when compared to dynamic models and are reproducibleN/

ESTIMAP: Ecosystem services mapping at European scale

Mapping, visualization and the access to suitable data as a means to facilitate the dialogue among scientists, policy makers and the general public are among the most challenging issues within current ecosystem service science and application. Recently the attention on spatially explicit ways to map ecosystem services, at local, regional and global scale is increasing. This report presents ESTIMAP: a suite of models for a spatially explicit assessment of three ecosystem services (recreation, pollination and coastal protection) at continental scale. The main objective of the models is to support EU policies with information on ecosystem services.JRC.H.8-Sustainability Assessmen

EU-wide methodology to map and assess ecosystem condition

The EU Biodiversity Strategy for 2030 calls for developing an EU-wide methodology to map, assess and achieve good condition of ecosystems, so they can deliver benefits to society through the provision of ecosystem services. The EU-wide methodology presented in this report addresses this methodological gap. The EU-wide methodology has adopted the System of Environmental Economic Accounting - Ecosystem Accounting (SEEA EA) as reference framework. The SEEA EA is an integrated framework for organizing biophysical information about ecosystems, adopted as a global statistical standard by the United Nations. The SEEA EA is also the reference framework under the proposal for the amendment of Regulation (EU) No 691/2011 on European environmental economic accounts. Building on previous work done within the MAES initiative, the EU-wide methodology presents useful insights to operationalise the SEEA EA at EU level by integrating different EU data streams in a consistent way with this global statistical standard to consistently map and assess ecosystem condition in the EU across all ecosystem types. The adoption of the SEEA EA framework offers the flexibility to integrate different data flows, leveraging the use of available EU data, such as data reported by MS under EU legislation and EU geospatial data. The EU-wide methodology. The implementation of the EU-wide methodology, making use of available data, will provide the scientific knowledge base to support a range of policies and legal instruments

Remote sensing methods for the biophysical characterization of protected areas globally: challenges and opportunities

Protected areas (PAs) are a key strategy to reverse global biodiversity declines, but they are under increasing pressure from anthropogenic activities and concomitant effects. Thus, the heterogeneous landscapes within PAs, containing a number of different habitats and ecosystem types, are in various degrees of disturbance. Characterizing habitats and ecosystems within the global protected area network requires large-scale monitoring over long time scales. This study reviews methods for the biophysical characterization of terrestrial PAs at a global scale by means of remote sensing (RS) and provides further recommendations. To this end, we first discuss the importance of taking into account the structural and functional attributes, as well as integrating a broad spectrum of variables, to account for the different ecosystem and habitat types within PAs, considering examples at local and regional scales. We then discuss potential variables, challenges and limitations of existing global environmental stratifications, as well as the biophysical characterization of PAs, and finally offer some recommendations. Computational and interoperability issues are also discussed, as well as the potential of cloud-based platforms linked to earth observations to support large-scale characterization of PAs. Using RS to characterize PAs globally is a crucial approach to help ensure sustainable development, but it requires further work before such studies are able to inform large-scale conservation actions. This study proposes 14 recommendations in order to improve existing initiatives to biophysically characterize PAs at a global scale

Assessment of high spatial resolution satellite imagery for monitoring riparian vegetation: riverine management in the smallholding

Riverine habitats are essential ecotones that bridge aquatic and terrestrial ecosystems, providing multiple ecosystem services. This study analyses the potential use of high-resolution satellite imagery, provided by the WorldView-2 satellite, in order to assess its viability for monitoring riparian ecosystems. It is performed by calculating the riparian strip quality index (RSQI) and calibrating it with the riparian quality index (QBR). The methodology was implemented in the Umia River, which is characterised by elevated anthropogenic pressures (located in the northwest of Spain). The results obtained by the method have a 92% of veracity and a kappa coefficient of 0.88. The average quality value obtained for the RSQI index was 71.57, while the average value for the QBR was 55.88. This difference could be attributed to the fact that the former does not differ between autochthonous and non-autochthonous vegetation. The areas with more accurate mapping corresponded to stretches of vegetation with optimal cover (80–50%), with good connectivity with the adjacent forest ecosystem and few or no presence of invasive plants. The worst-scoring sites had the next characteristics: low connectivity (< 10%), low forest cover (< 10%) and a higher presence of invasive plants. The degradation of vegetation could be explained by the presence of agriculture and deficient land use rationing caused by the type of ownership of the study area. The application of this index through satellite images will facilitate the environmental governance of multiple ecosystems and in special riparian ecosystems, obtaining a quick and objective methodology, easily replicable in other basins.Universidade de Vigo/CISUGXunta de Galicia | Ref. ED431B 2022/1

A Methodology for Natural Resources Analysis Appropriate for County Level Planning

In this thesis a methodology for developing an integrated cumulative analysis of sensitive natural resources was developed. Themes of natural resources-waterways, wetlands, forested lands, prime agricultural soils, and steep slopes-were brought together in a GIS system, in a grid format, in a manner so that each cell of the grid accumulated value according to the increasing presence of resource themes. For example, an area (30 meter x 30 meter grid cell) containing only one of the above themes is given a value of l, whereas an area containing slopes, streams, and forests might, after weighting factors, have a value of 5. The result is a map that demonstrates the cumulative value of sensitivity of a given area and its relative relation to the landscape under analysis. The methodology uses off-the-shelf GIS software and available GIS data sources, and is designed to require a minimum of technical and financial resources. This methodology is particularly useful for counties in Tennessee in meeting the requirements of Public Chapter 1101, the Growth Policy Act. The case study for this thesis reveals that much development does, in fact, occur in sensitive natural areas and that, therefore, this tool could be well utilized by planners to inform the public and to assist in the development of policy aimed toward the protection of sensitive areas from activities that would reduce their capacity to serve their natural functions

Enhanced wetland monitoring, assessment and indicators to support European and global environmental policy

SWOS Technical publicationBetween 2015 and 2018, the Horizon 2020 SWOS project has supported policies by developing and applying science-based methods that aim at standardising wetland definition, identification, delimitation, and delineation. The primary outputs of the project are satellite-based monitoring tools (SWOS toolbox1, GEO-Wetlands Community Portal2) to enable improved wetland assessment and monitoring capabilities, as well as their application in management and reporting at different scales, and by different users. In addition, the SWOS project includes a capacity-building component to facilitate the uptake of the tools by users. This report presents the project’s technical results (Chapter 3), as well as applied examples of the improved capabilities for wetland conservation and restoration needs (Chapter 4). These two chapters are preceded by an introduction (Chapter 1) and a review of the global and EU policies related to wetlands, including a perspective on the post-2020 agenda (Chapter 2)

Développement d’une méthode de cartographie des services écologiques en appui à l’aménagement durable des forêts : application au bassin versant de la rivière Harry, Terre-Neuve, Canada

La cartographie d'un service écologique (SE) est un moyen efficace pour communiquer l'importance des SEs auprès des gestionnaires forestiers et pour démontrer que la forêt est gérée de façon durable. La cartographie des SEs facilite leur intégration dans le processus décisionnel. Ainsi, ce mémoire propose un cadre méthodologique pour cartographier l’apport potentiel d’un SE développé tout d'abord pour un SE de régulation lié à l'eau - le service de contrôle des sédiments (SCS) - pour un bassin versant dominé par la forêt dans l'ouest de Terre-Neuve au Canada (640 km²). Ensuite le cadre est appliqué à un SE culturel - le service de la chasse - afin de tester la reproductibilité de la démarche méthodologique. Notre démarche méthodologique repose sur une approche « de relations causales de variables de substitution (proxies) », moins complexe à mettre en œuvre que les modèles physiques et moins subjective que les méthodes basées sur l'opinion d'experts. Les variables de substitution sont calculées à partir des données spatiales disponibles et agrégées en un indicateur composé qui est utilisé pour classer sur une échelle relative les sous bassins versants. Deux indicateurs composés ont été développés pour le SCS. Le premier utilise des pondérations égales pour chaque indicateur de substitution et pour le second des poids basés sur l'opinion d'experts ont été attribués. L'utilisation d'un indicateur composé (appelé indice) pour la cartographie permet de prendre en compte la nature multidimensionnelle et complexe des SEs. Les variables de substitution représentent les indicateurs de fonction des écosystèmes (IF) nécessaires pour décrire la relation de causalité entre les fonctions écologiques et le SE associé. Une évaluation du cadre de cartographie est réalisée pour le SCS en comparant les échelles relatives du SCS à une classification du rendement en sédiments simulé à l'aide du modèle hydrologique SWAT (Soil Water Assessment Tool). La précision globale varie de 35 à 81% en fonction des périodes de simulation et du système de pondération et présente de meilleurs résultats pour les périodes comportant davantage d'opérations de gestion forestière et pour le système de pondération basé sur les experts. Les résultats de la mise en œuvre du cadre montrent l’apport potentiel du SCS et du service culturel de la chasse à l’échelle des sous-bassins versants et mettent en évidence les sous-bassins versants les plus susceptibles d’être affectés par les opérations de gestion forestière