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\"The conservation and sustainable use of biodiversity in the environments where this diversity originated or is being used, are issues which are high on the policy agenda. This book is the first to set out a clear overview of community biodiversity management (CBM) as an approach to meet social, economic and environmental change\"-- Provided by publisher.

The conservation and sustainable use of biodiversity are issues that have been high on the policy agenda since the first Earth Summit in Rio in 1992. As part of efforts to implement in situ conservation, a methodology referred to as community biodiversity management (CBM) has been developed by those engaged in this arena. CBM contributes to the empowerment of farming communities to manage their biological resources and make informed decisions on the conservation and use of agrobiodiversity. This book is the first to set out a clear overview of CBM as a methodology for meeting socio-environmental changes. CBM is shown to be a key strategy that promotes community resilience, and contributes to the conservation of plant genetic resources. The authors present the underlying concepts and theories of CBM as well as its methodology and practices, and introduce case studies primarily from Brazil, Ethiopia, France, India, and Nepal. Contributors include farmers, leaders of farmers' organizations, professionals from conservation and development organizations, students and scientists. The book offers inspiration to all those involved in the conservation and use of agrobiodiversity within livelihood development and presents ideas for the implementation of farmers' rights. The wide collection of experiences illustrates the efforts made by communities throughout the world to cope with change while using diversity and engaging in learning processes. It links these grassroots efforts with debates in policy arenas as a means to respond to the unpredictable changes, such as climate change, that communities face in sustaining their livelihoods.

We assess whether and how datasets collected by the general public, so-called citizen science programmes, can improve biogeographical studies and contribute to large-scale conservation target-setting. Worldwide. We first set a general framework highlighting the prerequisites of a relevant dataset for conservation biogeography. We then illustrate how many different citizen science programmes currently running in different countries can be placed within this framework. We highlight that citizen science is particularly useful to address issues spanning large temporal and spatial extents. We then show how datasets based on citizen science can be used to investigate major aspects of global change impacts on biodiversity. We further highlight why these programmes are also particularly valuable in developing the preventative and educational component of conservation biogeography. Conservation biogeography requires considerable amounts of data collected over large spatial and/or temporal extents. Beyond increasing technical advances to collect and analyse these data, citizen science seems to be a highly valuable tool in many aspects. However, while citizen science programmes are now popular and increasingly used in several countries, they are lacking in many others. We argue that the development of citizen science programmes should be encouraged as they can both be highly valuable for conservation biogeography and promote the reconnection between people and nature and more generally between people and science.

Citizen scientists play a pivotal role in providing necessary biodiversity data. To ensure the continued involvement of a strong volunteer base, insight into the concerns and motivations of voluntary recorders is crucial. This paper presents the findings of a large-scale survey ( N  = 2193) among Dutch volunteer biodiversity recorders of diverse taxa, and focuses on three questions: what are the characteristics of these citizen scientists regarding their activities and socio-demographic background, what are their motivations for recording biodiversity, and what are their views on data sharing and ownership? Our findings show that a connection to, interest in and concern for nature are the most important motivations for biodiversity recorders. Volunteer recorders have high expectations regarding the impact of their data, both for their own learning as well as for science and management. Almost half the volunteers consider their data to be public goods, but this does not mean they support unconditional data sharing. Instead, the acceptability of data sharing with third parties seems strongly linked to the goals of the user. We discuss the implications of our findings for practitioners, such as the role of biology curricula and the importance of learning opportunities to redress the lack of younger volunteers. We argue that conceptualising volunteer recorders as data custodians rather than owners helps to understand their perspective on data sharing, and emphasize the importance of clear and transparent data policy that respects volunteers’ views on their data.

Because of a range of constraints, the availability of biodiversity-related information varies considerably over space, time, taxa, and types of data, thereby causing gaps in knowledge. Despite growing awareness of this issue among scientists, it is still poorly known how—and whether—scientific efforts have contributed to overcoming these information gaps. Focusing on spatial gaps in global biodiversity data, we show that the accumulation rates of nonbird species occurrence records stored in the Global Biodiversity Information Facility have not improved—and have even potentially declined—over the past three decades in data-poor, often biodiversity-rich regions. Meanwhile, one citizen-science project, eBird, has been making a considerable contribution to the collection and sharing of bird records, even in the data-poorest countries, and is accelerating the accumulation of bird records globally. We discuss the potentials and limitations of citizen-science projects for tackling gaps in biodiversity information, particularly from the perspective of biodiversity conservation.

This paper critically analyses the transformative capacity of citizen science (CS), and in particular, the issue of learning in the context of CS. A narrative review focussed on CS and social learning literature was conducted collaboratively, followed by a case study review to evaluate learning aspects in fourteen CS projects from across the European Union. A template approach to explore learning arrangements in CS projects was used to explain how the desired changes can be achieved in a learning context offered by CS. Based on this assessment these are concluded that: 1) recent studies aiming to define CS for analytical purposes often fail to improve the clarity of conceptualisation 2) CS programmes may have transformative learning potential, especially contributing to the development of individual level skills, while such transformation is not necessarily occurring at organisational and institutional levels, 3) there is existing fair evidence on simple and visible learning outcomes, whereas the assessment of transformative effects of learning is often based on assumptions rather than empirical observation, 4) learning in CS is unanimously considered as important but in practice is often forgotten and rarely evaluated.

Citizen science has the potential to expand the scope and scale of research in ecology and conservation, but many professional researchers remain skeptical of data produced by nonexperts. We devised an approach for producing accurate, reliable data from untrained, nonexpert volunteers. On the citizen science website www.snapshotserengeti.org, more than 28,000 volunteers classified 1.51 million images taken in a large-scale camera-trap survey in Serengeti National Park, Tanzania. Each image was circulated to, on average, 27 volunteers, and their classifications were aggregated using a simple plurality algorithm. We validated the aggregated answers against a data set of 3829 images verified by experts and calculated 3 certainty metrics—level of agreement among classifications (evenness), fraction of classifications supporting the aggregated answer (fraction support), and fraction of classifiers who reported \"nothing here\" for an image that was ultimately classified as containing an animal (fraction blank)—to measure confidence that an aggregated answer was correct. Overall, aggregated volunteer answers agreed with the expert-verified data on 98% of images, but accuracy differed by species commonness such that rare species had higher rates of false positives and false negatives. Easily calculated analysis of variance and post-hoc Tukey tests indicated that the certainty metrics were significant indicators of whether each image was correctly classified or classifiable. Thus, the certainty metrics can be used to identify images for expert review. Bootstrapping analyses further indicated that 90% of images were correctly classified with just 5 volunteers per image. Species classifications based on the plurality vote of multiple citizen scientists can provide a reliable foundation for large-scale monitoring of African wildlife. La ciencia ciudadana tiene el potencial de expandir el alcance y la escala de la investigación en la ecología y la conservación, pero muchos investigadores profesionales permanecen escépticos sobre los datos producidos por quienes no son expertos. Diseñamos una estrategia para generar datos precisos y fiables a partir de voluntarios no expertos y sin entrenamiento. En el sitio web de ciencia ciudadana www.snapshotserengeti.org más de 28, 000 voluntarios clasificaron 1.51 millón de imágenes que fueron tomadas en un censo a gran escala de cámaras trampa en el Parque Nacional Serengueti, Tanzania. Cada imagen llegó, en promedio, hasta 27 voluntarios, cuyas clasificaciones se conjuntaron mediante el uso de un algoritmo de pluralidad simple. Validamos el conjunto de respuestas frente a un juego de datos de 3, 829 imágenes verificadas por expertos y calculamos tres medidas de certeza: nivel de concordancia entre las clasificaciones (uniformidad), fracción de clasificaciones que apoyan al conjunto de respuestas (fracción de apoyo) y fracción de clasificadores que reportaron \"nada aquí\" en una imagen que al final se clasificó como que sí tenía un animal (fracción en blanco). Estas medidas se usaron para estimar la confianza de que un conjunto de respuestas estuviera en lo correcto. En general, el conjunto de respuestas de los voluntarios estuvo de acuerdo con los datos verificados por los expertos en un 98% de las imágenes, pero la certeza varió según la preponderancia de la especie, de tal forma que las especies raras tuvieron una tasa más alta de falsos positivos y falsos negativos. El análisis de varianza calculado fácilmente y las pruebas post-hoc de Tukey indicaron que las medidas de certeza fueron indicadores significativos de si cada imagen estuvo clasificada correctamente o si era clasificable. Por esto, las medidas de certeza pueden utilizarse para identificar imágenes para una revisión de expertos. Los análisis de bootstrapping indicaron más a fondo que el 90 % de las imágenes estuvieron clasificadas correctamente con sólo cinco voluntarios por imagen. Las clasificaciones de especies basadas en el voto de pluralidad de múltiples científicos ciudadanos puede proporcionar un fundamento fiable para un monitoreo a gran escala de la vida silvestre africana.

1. Invasive species management aims to prevent or mitigate the impacts of introduced species but management interventions can themselves generate social impacts that must be understood and addressed. 2. Established approaches for addressing the social implications of invasive species management can be limited in effectiveness and democratic legitimacy. More deliberative, participatory approaches are emerging that allow integration of a broader range of socio-political considerations. Nevertheless, there is a need to ensure that these are rigorous applications of social science. 3. Social impact assessment offers a structured process of identifying, evaluating and addressing social costs and benefits. We highlight its potential value for enabling meaningful public participation in planning and as a key component of integrated assessments of management options. 4. Policy implications. As invasive species management grows in scope and scale, social impact assessment provides a rigorous process for recognising and responding to social concerns. It could therefore produce more democratic, less conflict-prone and more effective interventions.

Citizen Science (CS) provides valuable data to assist professional scientists in making informed decisions on macroinvertebrate conservation. However, CS is not developed nor implemented uniformly across the globe, and there are biases and challenges in the extent that it can contribute to global macroinvertebrate conservation. Here, a meta-analysis was performed using 107 Citizen Science Projects (CSPs) to identify underlying biases related to taxon representativity, country wealth, and demographic participation. Macroinvertebrate orders with the highest representativity were Lepidoptera and Hymenoptera, accounting for 53% of represented macroinvertebrate groups. The orders Scorpiones, Parasitiformes, and Spirobolida had proportionately the highest IUCN threat statuses, but significantly lower CSP representation, indicating that these orders require more public attention. Hymenoptera, Odonata, Coleoptera, Hemiptera, Diptera and Clitellata had the highest levels of Data Deficient species, suggesting that the primary objective of CSPs targeted at these orders should be collecting distribution and abundance data to improve Red List assessments. Global distribution of CSPs was uneven and the number of CSPs per country was positively correlated with national Gross Domestic Product (GDP) and GDP per capita, suggesting that countries with relatively low GDP face challenges to successfully establish and maintain CSPs. Establishing new CSPs can assist macroinvertebrate conservation in these countries, where biodiversity levels are often high. To accommodate these biases, CSP development should adopt a bottom-up approach, in which CSPs are designed to address data gaps, and to address local socio-economic limitations and cultural ideologies. Guidelines for such development are presented here, with emphasis on addressing societal variations and inter-disciplinary communication gaps to ensure equitable opportunities for CSP participation.