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This book provides a foundation for modern applied ecology. Much of current ecology research and conservation addresses problems across landscapes and regions, focusing on spatial patterns and processes. This book is aimed at teaching fundamental concepts and focuses on learning-by-doing through the use of examples with the software R. It is intended to provide an entry-level, easily accessible foundation for students and practitioners interested in spatial ecology and conservation

"Ecology is about understanding how organisms interact with other organisms and the environment they inhabit (i.e. fundamental and realised niches). It is easy to imagine an individual organism of any kind as a dot with all sorts of arrows impinging upon it, an arrow can represent abiotic factors (temperature, light, etc.), as well as many arrows for all the other organisms (biotic factors, intra- and inter-specific interactions) that affect it. Ecology aims therefore to determine the magnitude and rate associated with some of the arrows, and which are the most important and why. Each organism also has its own effects on the same list of factors, even if the effects may be small, so we can also imagine arrows going out from the same dot, one to each of the same list of factors (they can be dots too). Again, a challenge is to determine the associated weights and importance for the arrows, some of which are directed toward other organisms. As soon as we consider more than a single organism, even just a few, we immediately have a complex structure of dots and arrows: an ecological network! It is an obvious step to consider ecological systems as ecological networks, and as such to assess how network theory (concepts and methods) might be applied to them. Network theory and the mathematics of graph theory that underlie network analysis provide simple concepts that can applied to systems that are complex both in structure and dynamics. It is those concepts that allow us to provide a sorted set of methods for the quantitative analysis of 10 ecological networks, along with thoughts and advice on how best to proceed. Through the years, the need to take a network analysis framework to study complex system has arisen in many fields (physics, computer science, communication science (transportation, electricity, social), and bio- and ecoinformatics), and there is a challenging diversity of approaches, methods, and measures that should be understood, or at least sorted, before applying them to our own data. The overarching goal of this book is to help ecologists in selecting the appropriate network methods to represent, analyse, and model their ecological system using network theory"--

Nowadays, ecologists worldwide recognize the use of spatial analysis as essential. However, because of the fast-growing range of methods available, even an expert might occasionally find it challenging to choose the most appropriate one. Providing the ecological and statistical foundations needed to make the right decision, this second edition builds and expands upon the previous one by: • Encompassing the basic methods for spatial analysis, for both complete census and sample data • Investigating updated treatments of spatial autocorrelation and spatio-temporal analysis • Introducing detailed explanations of currently developing approaches, including spatial and spatio-temporal graph theory, scan statistics, fibre process analysis, and Hierarchical Bayesian analysis • Offering practical advice for specific circumstances, such as how to analyze forest Permanent Sample Plot data and how to proceed with transect data when portions of the data series are missing. Written for graduates, researchers and professionals, this book will be a valuable source of reference for years to come

La question du paysage se trouve aujourd'hui à un tournant. Après vingt ans marqués par l'annonce de la crise du paysage et la menace de sa disparition, puis par la mise en place d'outils légaux et réglementaires d'intervention, suivie de leur difficile et inégale mobilisation par les acteurs locaux, nous nous trouvons face à un contexte qui conjugue forte demande sociale et mise à l'épreuve des politiques publiques. C'est le constat qui est à l'origine de ce dossier, issu principalement d'une session du colloque de l'ASRDLF de 2008, intitulée « Du territoire au paysage : quelles contributions originales pour comprendre et agir sur les dynamiques de développement ? ». Plusieurs des auteurs de ce dossier, français et québécois ont confronté à cette occasion leurs expériences et réflexions autour de ces trois mots clés : paysage, territoire et développement

Water clarity has been extensively assessed in Landsat-based remote sensing studies of inland waters, regularly relying on locally calibrated empirical algorithms, and close temporal matching between field data and satellite overpass. As more satellite data and faster data processing systems become readily accessible, new opportunities are emerging to revisit traditional assumptions concerning empirical calibration methodologies. Using Landsat 8 images with large water clarity datasets from southern Canada, we assess: (1) whether clear regional differences in water clarity algorithm coefficients exist and (2) whether model fit can be improved by expanding temporal matching windows. We found that a single global algorithm effectively represents the empirical relationship between in situ Secchi disk depth (SDD) and the Landsat 8 Blue/Red band ratio across diverse lake types in Canada. We also found that the model fit improved significantly when applying a median filter on data from ever-wider time windows between the date of in situ SDD sample and the date of satellite overpass. The median filter effectively removed the outliers that were likely caused by atmospheric artifacts in the available imagery. Our findings open new discussions on the ability of large datasets and temporal averaging methods to better elucidate the true relationships between in situ water clarity and satellite reflectance data.

Available data show that future changes in global change drivers may lead to an increasing impact of fires on terrestrial ecosystems worldwide. Yet, fire regime changes in highly humanised fire-prone regions are difficult to predict because fire effects may be heavily mediated by human activities We investigated the role of fire suppression strategies in synergy with climate change on the resulting fire regimes in Catalonia (north-eastern Spain). We used a spatially-explicit fire-succession model at the landscape level to test whether the use of different firefighting opportunities related to observed reductions in fire spread rates and effective fire sizes, and hence changes in the fire regime. We calibrated this model with data from a period with weak firefighting and later assess the potential for suppression strategies to modify fire regimes expected under different levels of climate change. When comparing simulations with observed fire statistics from an eleven-year period with firefighting strategies in place, our results showed that, at least in two of the three sub-regions analysed, the observed fire regime could not be reproduced unless taking into account the effects of fire suppression. Fire regime descriptors were highly dependent on climate change scenarios, with a general trend, under baseline scenarios without fire suppression, to large-scale increases in area burnt. Fire suppression strategies had a strong capacity to compensate for climate change effects. However, strong active fire suppression was necessary to accomplish such compensation, while more opportunistic fire suppression strategies derived from recent fire history only had a variable, but generally weak, potential for compensation of enhanced fire impacts under climate change. The concept of fire regime in the Mediterranean is probably better interpreted as a highly dynamic process in which the main determinants of fire are rapidly modified by changes in landscape, climate and socioeconomic factors such as fire suppression strategies. ; This study has received financial support from the projects CGL2008-05506-C02-01/BOS, CGL2011-29539/BOS and Consolider Montes CSD2008-00040 granted by the Spanish Ministry of Education and Science (MEC). Additional funding to LB and MC was received from the Catalan government through projects 2010 BE 272 and the 'Beatriu de Pinós' Programme (2009 BP-B 00342).

Fire has been a source of global biodiversity for millions of years. However, interactions with anthropogenic drivers such as climate change, land use, and invasive species are changing the nature of fire activity and its impacts. We review how such changes are threatening species with extinction and transforming terrestrial ecosystems. Conservation of Earth's biological diversity will be achieved only by recognizing and responding to the critical role of fire. In the Anthropocene, this requires that conservation planning explicitly includes the combined effects of human activities and fire regimes. Improved forecasts for biodiversity must also integrate the connections among people, fire, and ecosystems. Such integration provides an opportunity for new actions that could revolutionize how society sustains biodiversity in a time of changing fire activity. ; The workshop leading to this paper was funded by the Centre Tecnològic Forestal de Catalunya and the ARC Centre of Excellence for Environmental Decisions. L.T.K. was supported by a Victorian Postdoctoral Research Fellowship (Victorian Government), a Centenary Fellowship (University of Melbourne), and an Australian Research Council Linkage Project Grant (LP150100765). A.R. was supported by the Xunta de Galicia (Postdoctoral Fellowship ED481B2016/084-0) and the Foundation for Science and Technology under the FirESmart project (PCIF/MOG/0083/2017). A.L.S. was supported by a Marie Skłodowska-Curie Individual Fellowship (746191) under the European Union Horizon 2020 Programme for Research and Innovation. L.R. was supported by the Australian Government's National Environmental Science Program through the Threatened Species Recovery Hub. L.B. was partially supported by the Spanish Government through the INMODES (CGL2014-59742-C2-2-R) and the ERANET-SUMFORESTS project FutureBioEcon (PCIN-2017-052). This research was supported in part by the U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station.