Using social media, machine learning and natural language processing to map multiple recreational beneficiaries

Information and numbers on the use and appreciation of nature are valuable information for protected area (PA) managers. A promising direction is the utilisation of social media, such as the photo-sharing website Flickr. Here we demonstrate a novel approach, borrowing techniques from machine learning (image analysis), natural language processing (Latent Semantic Analysis (LSA)) and self-organising maps (SOM), to collect and interpret >20,000 photos from the Camargue region in Southern France. From the perspective of Cultural Ecosystem Services (CES), we assessed the relationship between the use of the Camargue delta and the presence of natural elements by consulting local managers. Clustering algorithms applied to results of the LSA data revealed six distinct user groups, which included those interested in nature, ornithology, religious pilgrimage, general tourists and aviation enthusiasts. For each group, we produced high-resolution spatial and seasonal maps, which matched known recreational attractions and annual festivals in the Camargue. The accuracy of the group identification, and the spatial and temporal patterns of photo activity, in the Camargue delta were evaluated by local managers of the Camargue regional park. This study demonstrates how PA managers can harness social-media to monitor recreation and improve their management decision making

Taking stock of nature: Essential biodiversity variables explained

In 2013, the Group on Earth Observations Biodiversity Observation Network (GEO BON) developed the framework of Essential Biodiversity Variables (EBVs), inspired by the Essential Climate Variables (ECVs). The EBV framework was developed to distill the complexity of biodiversity into a manageable list of priorities and to bring a more coordinated approach to observing biodiversity on a global scale. However, efforts to address the scientific challenges associated with this task have been hindered by diverse interpretations of the definition of an EBV. Here, the authors define an EBV as a critical biological variable that characterizes an aspect of biodiversity, functioning as the interface between raw data and indicators. This relationship is clarified through a multi-faceted stock market analogy, drawing from relevant examples of biodiversity indicators that use EBVs, such as the Living Planet Index and the UK Spring Index. Through this analogy, the authors seek to make the EBV concept accessible to a wider audience, especially to non-specialists and those in the policy sector, and to more clearly define the roles of EBVs and their relationship with biodiversity indicators. From this we expect to support advancement towards globally coordinated measurements of biodiversity

The use of scenarios and models to evaluate the future of nature values and ecosystem services in Mediterranean forests

Science and society are increasingly interested in predicting the effects of global change and socio-economic development on natural systems, to ensure maintenance of both ecosystems and human well-being. The Intergovernmental Platform on Biodiversity and Ecosystem Services has identified the combination of ecological modelling and scenario forecasting as key to improving our understanding of those effects, by evaluating the relationships and feedbacks between direct and indirect drivers of change, biodiversity, and ecosystem services. Using as case study the forests of the Mediterranean basin (complex socio-ecological systems of high social and conservation value), we reviewed the literature to assess (1) what are the modelling approaches most commonly used to predict the condition and trends of biodiversity and ecosystem services under future scenarios of global change, (2) what are the drivers of change considered in future scenarios and at what scales, and (3) what are the nature and ecosystem service indicators most commonly evaluated. Our review shows that forecasting studies make relatively little use of modelling approaches accounting for actual ecological processes and feedbacks between different socio-ecological sectors; predictions are generally made on the basis of a single (mainly climate) or a few drivers of change. In general, there is a bias in the set of nature and ecosystem service indicators assessed. In particular, cultural services and human well-being are greatly underrepresented in the literature. We argue that these shortfalls hamper our capacity to make the best use of predictive tools to inform decision-making in the context of global change.This work was supported by the Spanish Government through the INMODES project (grant number CGL2017-89999-C2-2-R), the ERA-NET FORESTERRA project INFORMED (grant number 29183), and the project Boscos Sans per a una Societat Saludable funded by Obra Social la Caixa (https://obrasociallacaixa.org/). AMO and AA were supported by Spanish Government through the “Juan de la Cierva” fellowship program (IJCI-2016-30349 and IJCI-2016-30049, respectively). JVRD was supported by the Government of Asturias and the FP7-Marie Curie-COFUND program of the European Commission (Grant “Clarín” ACA17-02)

Land and farming system dynamics and their drivers in the Mediterranean Basin

Given the heterogeneity and richness of Mediterranean farming systems, it is difficult to assess the nature and causes of observed dynamics based on single case studies. This research identifies case studies conducted on the north and south of the Mediterranean basin to provide a comprehensive overview of the current land and farming system dynamics and their main drivers. We analyze 80 papers published in international journals from 1985 to 2015. The studies vary in spatial scale, from 4 km2 in the case of peri-urban regions and small agricultural areas to more than 500,000 km2 in the case of national-based analyses. Most of the papers focus on mountainous rural areas, whereas only a few case studies are located in mixed regions or peri-urban inland regions. We analyze the farm trajectories behind the general dynamics to understand the ongoing processes at the agricultural level and their related drivers. Social and demographic drivers are indicated as particularly relevant for abandonment, which is frequently associated with intensification processes. Intensification dynamics are driven mainly by economic factors, which particularly affect annual crop production. Few papers analyze the dynamics of extensification and more research in this field is needed to understand this process and its eventual transition to the abandonment of agricultural areas. This analysis provides an opportunity for the exchange of ideas and information from a diverse range of disciplines and interest groups, which should be combined to formulate effective land use policies

State-of-the-art practices in farmland biodiversity monitoring for North America and Europe

Policy makers and farmers need to know the status of farmland biodiversity in order to meet conservation goals and evaluate management options. Based on a review of 11 monitoring programs in Europe and North America and on related literature, we identify the design choices or attributes of a program that balance monitoring costs and usefulness for stakeholders. A useful program monitors habitats, vascular plants, and possibly faunal groups (ecosystem service providers, charismatic species) using a stratified random sample of the agricultural landscape, including marginal and intensive regions. The size of landscape samples varies with the grain of the agricultural landscape; for example, samples are smaller in Europe and larger in North America. Raw data are collected in a rolling survey, which distributes sampling over several years. Sufficient practical experience is now available to implement broad monitoring schemes on both continents. Technological developments in remote sensing, metagenomics, and social media may offer new opportunities for affordable farmland biodiversity monitoring and help to lower the overall costs of monitoring programs

Ecosystem services and integrity trend

Turton, SM ORCiD: 0000-0001-6279-7682Ecosystems are dynamic complexes of plant, animal, and microorganism communities, interacting with the nonliving environment (soils, water, minerals, air) in the form of functional units. These functional units occupy a diverse range of scales in the environment. Ecosystem services may be defined as goods and services from ecosystem structures and functions such as food, fiber, and fuel and climate regulation. These services have also been described as nature’s contributions to people, implying that humans are passive and active recipients of these services but rarely pay for them in any monetary sense. Ecosystem integrity may be defined as the system’s capacity to maintain structure and ecosystem functions using processes and components characteristic for its particular eco-region, i.e., an area where there are similar geographical characteristics, such as geology, vegetation, and climate. Ecosystem services integrity trend refers to changes in ecosystem goods and services, their ecosystem structures and functions, and hence their ability to provide food, fiber, and fuel and regulate climate. Human activities are the main drivers of changes in trends in ecosystem services and hence their integrity trend at different spatial and temporal scales. Social-ecological systems are complex adaptive systems composed of many diverse human and non-human entities that interact; these inherently linked systems adapt to changes in their environment, and their environment changes as a result