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Biodiversity can benefit from fires tailored to suit particular ecosystems and species

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AimSpecies distribution models built with geographically restricted data often fail to capture the full range of conditions experienced by species across their entire distribution area. Using such models to predict distribution shifts under future environmental change may, therefore, produce biased projections. However, restricted-scale models have the potential to include a larger sample of taxa for which distribution data are available and to provide finer-resolution projections that are better applied to conservation planning than the forecasts of broad-scale models. We examine the circumstances under which the projected shifts in species richness patterns derived from restricted-scale and broad-scale models are most likely to be similar.LocationEurope.MethodsThe distribution of butterflies in Finland, Belgium/Netherlands and Spain was modelled based on restricted-scale (local) and broad-scale (continental) distribution and climate data. Both types of models were projected under future climate change scenarios to assess potential changes in species richness.ResultsIn Finland, species richness was projected to increase strongly based on restricted-scale models and to decrease slightly with broad-scale models. In Belgium/Netherlands, restricted-scale models projected a larger decrease in richness than broad-scale models. In Spain, both models projected a slight decrease in richness. We obtained similar projections based on restricted-scale and broad-scale models only in Spain because the climatic conditions available here covered the warm part of the distributions of butterflies better than in Finland and Belgium/Netherlands.Main conclusionsRestricted-scale models that fail to capture the warm part of species distributions produce biased estimates of future changes in species richness when projected under climatic conditions with no modern analogue in the study area. We recommend the use of distribution data beyond the boundaries of the study area to capture the pa

Key global indicators of biodiversity decline, such as the IUCN Red List Index and the Living Planet Index, have relatively long assessment intervals. This means they, due to their inherent structure, function as late-warning indicators that are retrospective, rather than prospective. These indicators are unquestionably important in providing information for biodiversity conservation, but the detection of early-warning signs of critical biodiversity change is also needed so that proactive management responses can be enacted promptly where required. Generally, biodiversity conservation has dealt poorly with the scattered distribution of necessary detailed information, and needs to find a solution to assemble, harmonize and standardize the data. The prospect of monitoring essential biodiversity variables (EBVs) has been suggested in response to this challenge. The concept has generated much attention, but the EBVs themselves are still in development due to the complexity of the task, the limited resources available, and a lack of long-term commitment to maintain EBV data sets. As a first step, the scientific community and the policy sphere should agree on a set of priority candidate EBVs to be developed within the coming years to advance both large-scale ecological research as well as global and regional biodiversity conservation. Critical ecological transitions are of high importance from both a scientific as well as from a conservation policy point of view, as they can lead to long-lasting biodiversity change with a high potential for deleterious effects on whole ecosystems and therefore also on human well-being. We evaluated candidate EBVs using six criteria: relevance, sensitivity to change, generalizability, scalability, feasibility, and data availability and provide a literature-based review for eight EBVs with high sensitivity to change. The proposed suite of EBVs comprises abundance, allelic diversity, body mass index, ecosystem heterogeneity, phenology, range

Temporal baselines are needed for biodiversity, in order for the change in biodiversity to be measured over time, the targets for biodiversity conservation to be defined and conservation progress to be evaluated. Limited biodiversity information is widely recognized as a major barrier for identifying temporal baselines, although a comprehensive quantitative assessment of this is lacking. Here, we report on the temporal baselines that could be drawn from biodiversity monitoring schemes in Europe and compare those with the rise of important anthropogenic pressures. Most biodiversity monitoring schemes were initiated late in the 20th century, well after anthropogenic pressures had already reached half of their current magnitude. Setting temporal baselines from biodiversity monitoring data would therefore underestimate the full range of impacts of major anthropogenic pressures. In addition, biases among taxa and organization levels provide a truncated picture of biodiversity over time. These limitations need to be explicitly acknowledged when designing management strategies and policies as they seriously constrain our ability to identify relevant conservation targets aimed at restoring or reversing biodiversity losses. We discuss the need for additional research efforts beyond standard biodiversity monitoring to reconstruct the impacts of major anthropogenic pressures and to identify meaningful temporal baselines for biodiversity.

Revista oficial de la Asociación Española de Teledetección, [EN] Mapping fire severity is determinant to understand landscape evolution after a wildfire and provides useful information for decision making during post fire management. Quantitative fire severity mapping from relative changes in Normalized Burn Ratio index (RdNBR) is not actually being incorporated into decision making processes, being more useful the categorization in severity levels (high, moderate and low). However, the most common mapping severity methodologies based on the definition of RdNBR thresholds from field information are not always possible due to lack of field data or because the published thresholds are unsatisfactory in new regions. The boom in the use of UAVs (Unmanned Aerial Vehicle) has raised these platforms as potential tools for validation of remote sensing data. This paper presents the potential of UAVs as ground truth information in forest fires. From the photointerpretation of high resolution RGB images, the Aerial Severity Proportion Index (ASPI) has been created. Non-linear regression models between RdNBR and ASPI allows to delimitate of thresholds for the classification of Landsat images and to obtain qualitative severity maps. Validation with random points presents a kappa index of 0,5 and a relative accuracy of 70,8%. Therefore, UAV images become a very useful tool for wildfire severity mapping and for fill the gap between remote sensing information and expensive field ground campaigns., [ES] La cuantificación de la severidad de los incendios forestales es determinante para conocer la evolución del paisaje después de un incendio forestal y provee información de gran utilidad frente a la toma de decisiones en la gestión post incendio. La cartografía cuantitativa de severidad de incendios a partir de cambios relativos del índice Normalized Burn Ratio (RdNBR) no está siendo realmente incorporada en los procesos de toma de decisiones, siendo más utilizada la categorización en niveles de severidad (alta, mediana y baja). Sin embargo, las clasificaciones de severidad más comunes, basadas en la definición de umbrales de corte de RdNBR a partir de información de campo, no son siempre posibles por falta de datos de campo o bien porque los umbrales publicados resultan poco satisfactorios en localizaciones distintas a las de su calibración. El auge del uso de UAVs (Unmaned Aerial Vehicle) ha planteado estas plataformas como posible herramienta para la validación de información de satélite. En el presente trabajo se presenta la potencialidad de los UAV como información de verdad terreno en incendios forestales. A partir de la fotointerpretación de imágenes RGB de alta resolución se ha creado el índice ASPI (Aerial Severity Proportion Index), el cual, a partir de modelos de regresión no lineales con el índice RdNBR, permite delimitar umbrales para la clasificación de las imágenes Landsat y obtener un mapa cualitativo de severidad. La validación de los modelos de regresión entre RdNDR y ASPI a partir de puntos al azar muestra un índice kappa de 0,5 con un acierto relativo del 70,8%. Por lo tanto, las imágenes UAV son una herramienta muy útil para la clasificación de la severidad de incendios forestales y para rellenar la brecha existente entre la información proveniente de imágenes de satélite y las costosas campañas de campo.

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Efficient management of biodiversity requires a forward-looking approach based on scenarios that explore biodiversity changes under future environmental conditions. A number of ecological models have been proposed over the last decades to develop these biodiversity scenarios. Novel modelling approaches with strong theoretical foundation now offer the possibility to integrate key ecological and evolutionary processes that shape species distribution and community structure. Although biodiversity is affected by multiple threats, most studies addressing the effects of future environmental changes on biodiversity focus on a single threat only. We examined the studies published during the last 25 years that developed scenarios to predict future biodiversity changes based on climate, land-use and land-cover change projections. We found that biodiversity scenarios mostly focus on the future impacts of climate change and largely neglect changes in land use and land cover. The emphasis on climate change impacts has increased over time and has now reached a maximum. Yet, the direct destruction and degradation of habitats through land-use and land-cover changes are among the most significant and immediate threats to biodiversity. We argue that the current state of integration between ecological and land system sciences is leading to biased estimation of actual risks and therefore constrains the implementation of forward-looking policy responses to biodiversity decline. We suggest research directions at the crossroads between ecological and environmental sciences to face the challenge of developing interoperable and plausible projections of future environmental changes and to anticipate the full range of their potential impacts on biodiversity. An intergovernmental platform is needed to stimulate such collaborative research efforts and to emphasize the societal and political relevance of taking up this challenge.

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Aim: Mediterranean terrestrial ecosystems serve as reference laboratories for the investigation of global change because of their transitional climate, the high spatiotemporal variability of their environmental conditions, a rich and unique biodiversity and a wide range of socio-economic conditions. As scientific development and environmental pressures increase, it is increasingly necessary to evaluate recent progress and to challenge research priorities in the face of global change. Location: Mediterranean terrestrial ecosystems. Methods: This article revisits the research priorities proposed in a 1998 assessment. Results: A new set of research priorities is proposed: (1) to establish the role of the landscape mosaic on fire-spread; (2) to further research the combined effect of different drivers on pest expansion; (3) to address the interaction between drivers of global change and recent forest management practices; (4) to obtain more realistic information on the impacts of global change and ecosystem services; (5) to assess forest mortality events associated with climatic extremes; (6) to focus global change research on identifying and managing vulnerable areas; (7) to use the functional traits concept to study resilience after disturbance; (8) to study the relationship between genotypic and phenotypic diversity as a source of forest resilience; (9) to understand the balance between C storage and water resources; (10) to analyse the interplay between landscape-scale processes and biodiversity conservation; (11) to refine models by including interactions between drivers and socio-economic contexts; (12) to understand forest-atmosphere feedbacks; (13) to represent key mechanisms linking plant hydraulics with landscape hydrology. Main conclusions: (1) The interactive nature of different global change drivers remains poorly understood. (2) There is a critical need for the rapid development of regional- and global-scale models that are more tightly connected with larg

The world's forests and forestry sector are facing unprecedented biological, political, social, and climatic challenges. The development of appropriate, novel forest management and restoration approaches that adequately consider uncertainty and adaptability are hampered by a continuing focus on production of a few goods or objectives, strong control of forest structure and composition, and most importantly the absence of a global scientific framework and long-term vision. Ecosystem-based approaches represent a step in the right direction, but are limited in their ability to deal with the rapid pace of social, climatic, and environmental changes. We argue here that viewing forest ecosystems as complex adaptive system provides a better alternative for both production- and conservation-oriented forests and forestry. We propose a set of broad principles and changes to increase the adaptive capacity of forests in the face of future uncertainties. These span from expanding the sustained-yield, single-good paradigm to developing policy incentives and interventions that promote self-organization and integrated social-ecological adaptation.

Political commitment and policy instruments to halt biodiversity loss require robust data and a diverse indicator set to monitor and report on biodiversity trends. Gaps in data availability and narrow-based indicator sets are significant information barriers to fulfilling these needs.In this paper, the reporting requirements of seven global or European biodiversity policy instruments were reviewed using the list of Essential Biodiversity Variables (EBVs) as an analytical framework. The reporting requirements for the most comprehensive policy instrument, the United Nation's Strategic Plan for Biodiversity 2011–2020, were compared with the indicator set actually used for its reporting, to identify current information gaps. To explore the extent to which identified gaps could be bridged, the potential contribution of data mobilization, modelling and further processing of existing data was assessed.The information gaps identified demonstrate that decision-makers are currently constrained by the lack of data and indicators on changes in the EBV classes Genetic Composition and, to a lesser extent, Species Populations for which data is most often available. Furthermore, the results show that even when there is a requirement for specific information for reporting, the indicators used may not be able to provide all the information, for example current Convention of Biological Diversity indicators provide relatively little information on changes in the Ecosystem Function and Ecosystem Structure classes. This gap could be partly closed by using existing indicators as proxies, whereas additional indicators may be computed based on available data (e.g. for EBVs in the Ecosystem Structure class). However, for the EBV class Genetic Composition, no immediate improvement based on proxies or existing data seems possible.Synthesis and applications. Using Essential Biodiversity Variables (EBVs) as a tool, theory-driven comparisons could be made between the biodiversity information gaps

Species distribution models (SDMs) are increasingly proposed to support conservation decision making. However, evidence of SDMs supporting solutions for on-ground conservation problems is still scarce in the scientific literature. Here, we show that successful examples exist but are still largely hidden in the grey literature, and thus less accessible for analysis and learning. Furthermore, the decision framework within which SDMs are used is rarely made explicit. Using case studies from biological invasions, identification of critical habitats, reserve selection and translocation of endangered species, we propose that SDMs may be tailored to suit a range of decision-making contexts when used within a structured and transparent decision-making process. To construct appropriate SDMs to more effectively guide conservation actions, modellers need to better understand the decision process, and decision makers need to provide feedback to modellers regarding the actual use of SDMs to support conservation decisions. This could be facilitated by individuals or institutions playing the role of 'translators' between modellers and decision makers. We encourage species distribution modellers to get involved in real decision-making processes that will benefit from their technical input; this strategy has the potential to better bridge theory and practice, and contribute to improve both scientific knowledge and conservation outcomes.

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This Editorial presents the focus, scope and policies of the inaugural issue of Nature Conservation, a new open access, peer-reviewed journal bridging natural sciences, social sciences and hands-on applications in conservation management. The journal covers all aspects of nature conservation and aims particularly at facilitating better interaction between scientists and practitioners. The journal will impose no restrictions on manuscript size or the use of colour. We will use an XML-based editorial workflow and several cutting-edge innovations in publishing and information dissemination. These include semantic mark-up of, and enhancements to published text, data, and extensive cross-linking within the journal and to external sources. We believe the journal will make an important contribution to better linking science and practice, offers rapid, peer-reviewed and flexible publication for authors and unrestricted access to content.