Catálogo de publicaciones - libros

It became apparent a few decades ago that biodiversity is declining worldwide at nearly unprecedented rates. This poses ethical and self-interested challenges to people, and has triggered renewed efforts to understand the status and trends of what remains. Since biodiversity does not recognise human boundaries, this requires the sharing of information between countries, agencies within countries, non-governmental bodies, citizen groups and researchers. The effective monitoring of biodiversity and sharing of the data requires convergence on methods and definitions, best achieved within a relatively loose organisational structure, called a network. The Group on Earth Observations Biodiversity Observation Network (GEO BON) is one such structure. This chapter acts as an introduction to the GEO BON biodiversity observation handbook, which documents some of the co-learning achieved in its first years of operation. It also addresses the basic questions of how to set up a biodiversity observation network, usually consisting of a number of pre-existing elements.

This chapter covers the questions of ecosystem definition and the organisation of a monitoring system. It treats where and how ecosystems should be measured and the integration between in situ and RS observations. Ecosystems are characterised by composition, function and structure. The ecosystem level is an essential link in biodiversity surveillance and monitoring between species and populations on the one hand and land use and landscapes on the other. Ecosystem monitoring requires a clear conceptual model that incorporates key factors influencing ecosystem dynamics to base the variables on that have to be monitored as well as data collection methods and statistics. Choices have to be made on the scale at which monitoring should be carried out and eco-regionalisation or ecological stratification are approaches for identification of the units to be sampled. This can be done on expert judgement but nowadays also on stratifications derived from multivariate statistical clustering. Data should also be included from individual research sites over the entire world and from organically grown networks covering many countries. An important added value in the available monitoring technologies is the integration of in situ and RS observations, as various RS technologies are coming into reach of ecosystem research. For global applications this development is essential. We can employ an array of instruments to monitor ecosystem characteristics, from fixed sensors and in situ measurements to drones, planes and satellite sensors. They allow to measure biogeochemical components that determine much of the chemistry of the environment and the geochemical regulation of ecosystems. Important global databases on sensor data are being developed and frequent high resolution RS scenes are becoming available. RS observations can complement field observations as they deliver a synoptic view and the opportunity to provide consistent information in time and space especially for widely distributed habitats. RS has a high potential for developing distribution maps, change detection and habitat quality and composition change at various scales. Hyperspectral sensors have greatly enhanced the possibilities of distinguishing related habitat types at very fine scales. The end-users can use such maps for estimating range and area of habitats, but they could also serve to define and update the sampling frame (the statistical ‘population’) of habitats for which field sample surveys are in place. Present technologies and data availability allow us to measure fragmentation through several metrics that can be calculated from RS data. In situ data have been collected in several countries over a longer term and these are fit for statistical analysis, producing statistics on species composition change, habitat richness and habitat structure. It is now possible to relate protocols for RS and in situ observations based on plant life forms, translate them and provide direct links between in situ and RS data.

Ecosystem services are increasingly incorporated into explicit policy targets and can be an effective tool for informing decisions about the use and management of the planet’s resources, especially when trade-offs and synergies need to be taken into account. The challenge is to find meaningful and robust indicators to quantify ecosystem services, measure changes in demand and supply and predict future direction. This chapter addresses the basic requirements for collecting such observations and data on ecosystem services. Biodiversity regulates the ability of the ecosystem to supply ecosystem services, can be directly harvested to meet people’s material needs, and are valued by societies for its non-tangible contributions to well-being. Societies are deeply embedded within ecosystems, depending on and influencing the ecosystem services they produce. The different types of ecosystem services (provisioning, regulating, and cultural), and their different components (supply, delivery, contribution to well-being, and value) can be monitored at global to local scales. Different data sources are best suited to account for different components of ecosystem services and spatial scales and include: census data at national scales, remote sensing, field-based estimations, community monitoring, and models. Data availability, advantages and limitations of each are discussed. Progress towards monitoring different types of services and gaps are explored. Ways of exploring synergies and trade-offs among services and stakeholders, using scenarios to predict future ecosystem services, and including stakeholders in monitoring ecosystem services are discussed. The need of a network for monitoring ecosystem services to synergise efforts is stressed. Monitoring ecosystem services is vital for informing policy (or decision making) to protect human well-being and the natural systems upon which it relies at different scales. Using this information in decision making across all scales will be central to our endeavours to transform to more sustainable and equitable futures.

The Group on Earth Observations Biodiversity Observation Network (GEO BON) is developing a monitoring framework around a set of Essential Biodiversity Variables (EBVs) which aims at facilitating data integration, spatial scaling and contributing to the filling of gaps. Here we build on this framework to explore the monitoring of EBV classes at the species level: species populations, species traits and community composition. We start by discussing cross-cutting issues on species monitoring such as the identification of the question to be addressed, the choice of variables, taxa and spatial sampling scheme. Next, we discuss how to monitor EBVs for specific taxa, including mammals, amphibians, butterflies and plants. We show how the monitoring of species EBVs allows monitoring changes in the supply of ecosystem services. We conclude with a discussion of challenges in upscaling local observations to global EBVs and how indicator and model development can help address this challenge.

DNA is the most elemental level of biodiversity, drives the process of speciation, and underpins other levels of biodiversity, including functional traits, species and ecosystems. Until recently biodiversity indicators have largely overlooked data from the molecular tools that are available for measuring variation at the DNA level. More direct analysis of trends in genetic diversity are now feasible and are ready to be incorporated into biodiversity monitoring. This chapter explores the current state-of-the-art in genetic monitoring, with an emphasis on new molecular tools and the richness of data they provide to supplement existing approaches. We also briefly consider proxy approaches that may be useful for many-species, global scale monitoring cases.

Recognition of the threats to biodiversity and its importance to society has led to calls for globally coordinated sampling of trends in marine ecosystems. As a step to defining such efforts, we review current methods of collecting and managing marine biodiversity data. A fundamental component of marine biodiversity is knowing what, where, and when species are present. However, monitoring methods are invariably biased in what taxa, ecological guilds, and body sizes they collect. In addition, the data need to be placed, and/or mapped, into an environmental context. Thus a suite of methods will be needed to encompass representative components of biodiversity in an ecosystem. Some sampling methods can damage habitat and kill species, including unnecessary bycatch. Less destructive alternatives are preferable, especially in conservation areas, such as photography, hydrophones, tagging, acoustics, artificial substrata, light-traps, hook and line, and live-traps. Here we highlight examples of operational international sampling programmes and data management infrastructures, notably the Continuous Plankton Recorder, Reef Life Survey, and detection of Harmful Algal Blooms and MarineGEO. Data management infrastructures include the World Register of Marine Species for species nomenclature and attributes, the Ocean Biogeographic Information System for distribution data, Marine Regions for maps, and Global Marine Environmental Datasets for global environmental data. Existing national sampling programmes, such as fishery trawl surveys and intertidal surveys, may provide a global perspective if their data can be integrated to provide useful information. Less utilised and emerging sampling methods, such as artificial substrata, light-traps, microfossils and eDNA also hold promise for sampling the less studied components of biodiversity. All of these initiatives need to develop international standards and protocols, and long-term plans for their governance and support.

This chapter aims to assist biodiversity observation networks across the world in coordinating comprehensive freshwater biodiversity observations at national, regional or continental scales. We highlight special considerations for freshwater biodiversity and methods and tools available for monitoring. We also discuss options for storing, accessing, evaluating and reporting freshwater biodiversity data and for ensuring their use in making decisions about the conservation and sustainable management of freshwater biodiversity and provision of ecosystem services.

Remote sensing (RS)—taking images or other measurements of Earth from above—provides a unique perspective on what is happening on the Earth and thus plays a special role in biodiversity and conservation applications. The periodic repeat coverage of satellite-based RS is particularly useful for monitoring change and so is essential for understanding trends, and also provides key input into assessments, international agreements, and conservation management. Historically, RS data have often been expensive and hard to use, but changes over the last decade have resulted in massive amounts of global data being available at no cost, as well as significant (if not yet complete) simplification of access and use. This chapter provides a baseline set of information about using RS for conservation applications in three realms: terrestrial, marine, and freshwater. After a brief overview of the mechanics of RS and how it can be applied, terrestrial systems are discussed, focusing first on ecosystems and then moving on to species and genes. Marine systems are discussed next in the context of habitat extent and condition and including key marine-specific challenges. This is followed by discussion of the special considerations of freshwater habitats such as rivers, focusing on freshwater ecosystems, species, and ecosystem services.

The involvement of non-professionals in scientific research and environmental monitoring, termed Citizen Science (CS), has now become a mainstream approach for collecting data on earth processes, ecosystems and biodiversity. This chapter examines how CS might contribute to ongoing efforts in biodiversity monitoring, enhancing observation and recording of key species and systems in a standardised manner, thereby supporting data relevant to the Essential Biodiversity Variables (EBVs), as well as reaching key constituencies who would benefit Biodiversity Observation Networks (BONs). The design of successful monitoring or observation networks that rely on citizen observers requires a careful balancing of the two primary user groups, namely data users and data contributors (i.e., citizen scientists). To this end, this chapter identifies examples of successful CS programs as well as considering practical issues such as the reliability of the data, participant recruitment and motivation, and the use of emerging technologies.

Modelling provides an effective means of integrating the complementary strengths of biodiversity data derived from in situ observation versus remote sensing. The use of modelling in biodiversity change observation, or monitoring, is just one of a number of roles that modelling can play in biodiversity assessment. These roles place different levels of emphasis on explanatory versus predictive modelling, and on modelling across space alone, versus across both space and time, either past-to-present or present-to-future. One of the most challenging, yet vitally important, applications of modelling to biodiversity monitoring involves mapping change in the distribution and retention of terrestrial biodiversity. Unlike many structural and functional attributes of ecosystems, most biological entities at the species and genetic levels of biodiversity cannot be readily detected through remote sensing. Estimating change in these levels of biodiversity across large spatial extents is therefore benefiting from advances in both species-level and community-level approaches to model-based integration of in situ biological observations and remotely sensed environmental data.