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Although biodiversity is crucial for Sustainable Development Goals (SDGs), following the current trajectory, we risk failing SDG 15. Using a new indicator quantifying the loss of functional habitat (habitat that is simultaneously suitable and well-connected), we show that the real impact of renewable energy is far larger than previously assumed. Specifically, we estimate that the construction of hydropower reservoirs in south Norway caused a loss of ca. 222 km2 of functional habitat for wild reindeer (Rangifer tarandus)—which is far larger than assumed based on land inundation indices (110 km2). Fully mitigating these impacts is challenging: scenario analyses reveal that the measures proposed by societal actors would yield only a fraction of the habitat lost (2–12 km2) and could cause trade-off risks with other SDGs. Using indices of functional connectivity is crucial for environmental impact assessments, as entire ecological networks for several species can be affected far beyond the reservoirs.

Aim: Macroecological studies that require habitat suitability data for many species often derive this information from expert opinion. However, expert- based informa-tion is inherently subjective and thus prone to errors. The increasing availability of GPS tracking data offers opportunities to evaluate and supplement expert- based in-formation with detailed empirical evidence. Here, we compared expert- based habitat suitability information from the International Union for Conservation of Nature (IUCN) with habitat suitability information derived from GPS-tracking data of 1,498 individu-als from 49 mammal species.Location: Worldwide.Time period: 1998–2021.Major taxa studied: Forty- nine terrestrial mammal species.Methods: Using GPS data, we estimated two measures of habitat suitability for each individual animal: proportional habitat use (proportion of GPS locations within a habi-tat type), and selection ratio (habitat use relative to its availability). For each individual we then evaluated whether the GPS- based habitat suitability measures were in agree-ment with the IUCN data. To that end, we calculated the probability that the ranking of empirical habitat suitability measures was in agreement with IUCN's classification into suitable, marginal and unsuitable habitat types.Results: IUCN habitat suitability data were in accordance with the GPS data (> 95% probability of agreement) for 33 out of 49 species based on proportional habitat use estimates and for 25 out of 49 species based on selection ratios. In addition, 37 and 34 species had a > 50% probability of agreement based on proportional habitat use and selection ratios, respectively.Main conclusions: We show how GPS-tracking data can be used to evaluate IUCN habitat suitability data. Our findings indicate that for the majority of species in-cluded in this study, it is appropriate to use IUCN habitat suitability data in macro-ecological studies. Furthermore, we show that GPS-tracking data can be used to identify and prioritize species and habitat types for re-evaluation of IUCN habitat suitability data. expert opinion, GPS, habitat suitability, habitat type, habitat use, IUCN, mammals, movement, selection ratio, telemetry

Many publications make use of opportunistic data, such as citizen science observation data, to infer large‐scale properties of species’ distributions. However, the few publications that use opportunistic citizen science data to study animal ecology at a habitat level do so without accounting for spatial biases in opportunistic records or using methods that are difficult to generalize. In this study, we explore the biases that exist in opportunistic observations and suggest an approach to correct for them. We first examined the extent of the biases in opportunistic citizen science observations of three wild ungulate species in Norway by comparing them to data from GPS telemetry. We then quantified the extent of the biases by specifying a model of the biases. From the bias model, we sampled available locations within the species’ home range. Along with opportunistic observations, we used the corrected availability locations to estimate a resource selection function (RSF). We tested this method with simulations and empirical datasets for the three species. We compared the results of our correction method to RSFs obtained using opportunistic observations without correction and to RSFs using GPS‐telemetry data. Finally, we compared habitat suitability maps obtained using each of these models. Opportunistic observations are more affected by human access and visibility than locations derived from GPS telemetry. This has consequences for drawing inferences about species’ ecology. Models naïvely using opportunistic observations in habitat‐use studies can result in spurious inferences. However, sampling availability locations based on the spatial biases in opportunistic data improves the estimation of the species’ RSFs and predicted habitat suitability maps in some cases. This study highlights the challenges and opportunities of using opportunistic observations in habitat‐use studies. While our method is not foolproof it is a first step toward unlocking the potential of opportunistic citizen science data for habitat‐use studies., We provide a novel method to use citizen science data for fine‐scale studies.

Ecosystem functioning depends on multiple successful interactions, many supported by individual movements. The degree to which the landscape allows these interactions to take place has been referred to as ‘effective connectivity’ (EC). Many of the cumulative impacts of anthropogenic activities on ecosystem functioning arise from changes in EC. Therefore, a coherent framework to quantify EC is urgently needed. Recent theoretical developments propose that studying EC requires the simultaneous consideration of spatial, environmental and species intrinsic characteristics (SEI framework). In this paper we further expand the SEI framework by integrating advances in geographic information science, ecological niche modelling, movement ecology, island biogeography and network sciences to develop a comprehensive three-step methodological approach for quantifying EC. First, using niche modelling and movement ecology, we quantify the species movement probabilities with respect to local environmental conditions. Second, we quantify ecological distances between non-adjacent locations by integrating species movement responses to the local environment with the spatial configuration of the landscape using the expected cost obtained from the randomized shortest paths (RSP) framework. This expected cost generalizes the two most frequently used ecological distance metrics, i.e. least-cost distance and resistance distance. Moreover the ‘absorbing random walk’ properties of RSP allow the integration of new developments in connectivity research, i.e. spatial absorbing Markov chains, to account for movement-related mortality. Third, drawing from island biogeography and metapopulation ecology, we scale ecological distances by relevant speciesand area-specific parameters to estimate EC for the ecological process of interest, e.g. migration, dispersal or gene flow. The integrative and highly interdisciplinary approach we propose can lead to increasingly more realistic measures of EC at different organizational levels. Moreover efficient computation allows its application to large-scale high-resolution landscapes for theoretical studies, conservation planning and sustainable management of real landscapes. Circuitscape, movement cost, landscape resistance, least-cost distance, randomized shortest paths, resistance distance, SAMC, step selection function, survival

Increasingly precise spatial data (e.g. high-resolution imagery from remote sensing) allow for improved representations of the landscape network for assessing the combined effects of habitat loss and connectivity declines on biodiversity. However, evaluating large landscape networks presents a major computational challenge both in terms of working memory and computation time. We present the ConScape (i.e. “connected landscapes”) software library implemented in the high-performance open-source Julia language to compute metrics for connected habitat and movement flow on high-resolution landscapes. The combination of Julia's ‘just-in-time’ compiler, efficient algorithms and ‘landmarks’ to reduce the computational load allows ConScape to compute landscape ecological metrics—originally developed in metapopulation ecology (such as ‘metapopulation capacity’ and ‘probability of connectivity’)—for large landscapes. An additional major innovation in ConScape is the adoption of the randomized shortest paths framework to represent connectivity along the continuum from optimal to random movements, instead of only those extremes. We demonstrate ConScape's potential for using large datasets in sustainable land planning by modelling landscape connectivity based on remote-sensing data paired with GPS tracking of wild reindeer in Norway. To guide users, we discuss other applications, and provide a series of worked examples to showcase all ConScape's functionalities in Supplementary Material. Built by a team of ecologists, network scientists and software developers, ConScape is able to efficiently compute landscape metrics for high-resolution landscape representations to leverage the availability of large data for sustainable land use and biodiversity conservation. As a Julia implementation, ConScape combines computational efficiency with a transparent code base, which facilitates continued innovation through contributions from the rapidly growing community of landscape and connectivity modellers using Julia. circuitscape, conefor, ecological networks, least-cost path, metapopulation, random walk, randomized shortest paths

The challenge to harmonize nature-based tourism with species conservation is important both from an economic, cultural and ecological perspective. One approach for understanding this interaction is to compare the spatiotemporal overlap between tourism activities and the focal species’ space use, with the purpose to identify areas, periods, and conditions in which tourism exerts the highest negative impact. Here, we combine GPS data from 66 wild reindeer with on-site surveys of tourist (n = 13434 respondents at 66 locations) and trail use counters (n = 99 sites) in three Norwegian national parks. Our findings highlight a large-scale segregation during the summer season, as wild reindeer move to areas less prone to disturbance by humans. Based on these findings, we discuss a management model to segregate tourists from wild reindeer in space and/or time during summer with the goal of long-term sustainable coexistence.

Partial migration, whereby a proportion of a population migrates between distinct seasonal ranges, is common throughout the animal kingdom. However, studies linking existing theoretical models of migration probability, with empirical data are lacking. The competitive release hypothesis for partial migration predicts that due to density-dependent habitat selection, the proportion of migrants increases as the relative quality and size of the seasonal range increases, but decreases with increasing migration cost and population density. To test this prediction, we developed a quantitative framework to predict the proportion of migrants, using empirical data from 545 individually GPS-marked moose Alces alces from across Fennoscandia, spanning latitudes of 56°to 68°N. Moose contracted their ranges to common and spatially limited winter areas (typically at lower elevation), but expanded them during summer due to an increase in suitable habitat (at highland ranges). As predicted from our model, a better and larger highland range relative to the lowland range corresponded to a higher propor-tion of migrants in an area. Quantitative predictions coupling the balance of habitat availability of seasonal ranges with the probability of migrating in a large herbivore is a necessary step towards an enhanced understanding of the mechanisms underlying migration at the population level. ideal-free distribution, resource selection functions, seasonal habitat selection, ungulates

Sustainable wildlife harvest is challenging due to the complexity of uncertain social-ecological systems, and diverse stakeholder perspectives of sustainability. In these systems, semi-complex stochastic simulation models can provide heuristics that bridge the gap between highly simplified theoretical models and highly context-specific case-studies. Such heuristics allow for more nuanced recommendations in low-knowledge contexts, and an improved understanding of model sensitivity and transferability to novel contexts. We develop semi-complex Management Strategy Evaluation (MSE) models capturing dynamics and variability in ecological processes, monitoring, decision-making, and harvest implementation, under a diverse range of contexts. Results reveal the fundamental challenges of achieving sustainability in wildlife harvest. Environmental contexts were important in determining optimal harvest parameters, but overall, evaluation contexts more strongly influenced perceived outcomes, optimal harvest parameters and optimal harvest strategies. Importantly, simple composite metrics popular in the theoretical literature (e.g. focusing on maximizing yield and population persistence only) often diverged from more holistic composite metrics that include a wider range of population and harvest objectives, and better reflect the trade-offs in real world applied contexts. While adaptive harvest strategies were most frequently preferred, particularly for more complex environmental contexts (e.g. high uncertainty or variability), our simulations map out cases where these heuristics may not hold. Despite not always being the optimal solution, overall adaptive harvest strategies resulted in the least value forgone, and are likely to give the best outcomes under future climatic variability and uncertainty. This demonstrates the potential value of heuristics for guiding applied management.

Rising ambient temperatures associated with global climate change threaten the persistence of numerous species of wildlife. Moose (Alces alces), for instance, are purported to experience heat stress occurring when ambient temperatures rise above specific seasonal temperature thresholds. These temperature thresholds, however, were established in a study that linked physiological changes in thermoregulation to ambient temperatures among a small study group of captive-reared moose. Here, we quantified movement rate of 127 moose GPS-tracked during summer from 2006 to 2010 in central Norway as a function of ambient temperature. We found little evidence of a threshold response in moose movement in relation to rising ambient temperatures during summer. We did, however, detect differences in moose movement in relation to temperature variation between daylight and twilight–night periods. Moose increased their movement in the twilight–night period when ambient temperatures were high, suggesting a compensatory response to climate variation. Our analysis identifies that dynamics of moose movement in relation to ambient temperature are complex and may not be well correlated with temperature thresholds that were previously described.

Summary A critical question in the conservation of large mammals in the Anthropocene is to know the extent to which they can tolerate human disturbance. Surprisingly, little quantitative data is available about large-scale effects of human activity and land use on their broad scale distribution in Europe. In this study, we quantify the relative importance of human land use and protected areas as opposed to biophysical constraints on large mammal distribution. We analyze data on large mammal distribution to quantify the relative effect of anthropogenic variables on species' distribution as opposed to biophysical constraints. We finally assess the effect of anthropogenic variables on the size of the species' niche by simulating a scenario where we assumed no anthropogenic pressure on the landscape. Results show that large mammal distribution is primarily constrained by biophysical constraints rather than anthropogenic variables. This finding offers grounds for cautious optimism concerning wildlife conservation in the Anthropocene., Graphical abstract, Highlights • Biophysical factors had a far greater impact on species distribution than human factors • This indicates that most species have a broad tolerance of human land use at coarse scales • We provide grounds for cautious optimism for wildlife conservation in the Anthropocene, Earth sciences; Environmental science; Nature conservation

1. Hunting and culling are frequently used to combat infectious wildlife diseases. The aim is to markedly lower population density in order to limit disease transmission or to eradicate the host. Massive host culling can yield a trade-off when combating wildlife disease; it follows that intrusive actions may have unintended behavioural side effects, leading to the geographic spread of disease. The manner in which such excessive hunting and culling of hosts can affect the movement and dispersion of cervids has not been studied. 2. In this study, we quantified the behaviour (daily movements and habitat use) and dispersion of GPS-marked reindeer (n = 24) before and during the eradication of an entire population (>2,000 reindeer) infected with chronic wasting disease (CWD) in Norway. We compared behaviour and dispersion during 10 ordinary hunting seasons (2007–2016), an extended hunting season (2017) and marksmen culling (2017/2018). 3. Seasonality had a major impact on movements. Reindeer movements during the early hunting season (20 August–20 September) did not increase the overall movements compared to that in the pre-hunt season (20 July–19 August), while extended hunting into October (as in 2017) and marksmen culling from November to February markedly increased daytime movements relative to that normally observed in this time of the year. Towards the end of the eradication, the remaining reindeer sought refuge at restricted high-elevation areas with limited forage production. Reindeer used novel areas towards the perimeter of the range, but active herding during culling stopped one herd from leaving the CWD zone. 4. Synthesis and applications. With emerging wildlife diseases, host culling is becoming a more frequently used tool for managers in Europe. Our study highlights the potential trade-off between combating disease transmission within a population and the risk of geographic spread. Such insight is important to design mitigation measures, such as perimeter fencing or herding, to avoid the risk of the geographic spread of disease in cases of severe and economically important wildlife diseases. cervids, chronic wasting disease, disease ecology, disease management, host culling, movement ecology, spatial organization, unintended side effects

Many animal populations providing ecosystem services, including harvest, live in seasonal environments and migrate between seasonally distinct ranges. Unfortunately, two major sources of human-induced global change threaten these populations: climate change and anthropogenic barriers. Anthropogenic infrastructure developments present a global threat to animal migrations through increased migration mortality or behavioral avoidance. Climate change alters the seasonal and spatial dynamics of resources and therefore the effects of migration on population performance. We formulated a population model with ideal-free migration to investigate changes in population size and harvest yield due to barriers and seasonal dynamics. The model predicted an increasing proportion of migrants when the difference between areas in seasonality or carrying capacity increased. Both migration cost and behavioral avoidance of barriers substantially reduced population size and harvest yields. Not surprisingly, the negative effects of barriers were largest when the population benefited most from migration. Despite the overall decline in harvest yield from a migratory population due to barriers, barriers could result in locally increased yield from the resident population following reduced competition from migrants. Our approach and results enhance the understanding of how global warming and infrastructure development worldwide may change population dynamics and harvest offtake affecting livelihoods and rural economies. Seasonal migration · Ideal-free distribution · Anthropogenic infrastructure · Mobile agent–based ecosystem services © The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creativecommonshorg/licenses/by/4.0/.

The cumulative impact of human activities has driven many species into severe declines across the globe. However, the recent focus on conservation optimism has begun to highlight case studies that go against this trend. Reforestation, agricultural abandonment, reintroduction and legislative change have led to a situation where large mammals have recovered and are now widespread across the European continent. This study summarizes the knowledge about wild ungulate distribution in Europe and review the diversity of ways in which they interact with humans. Drawn from a wide range of sources, we built distribution maps of European wild ungulates. Results show that 90% of Europe is home to at least 1 species of wild native ungulate, with roe deer and wild boar occupying 74% and 64% of Europe respectively. In contrast, wild native mountain ungulates only occupy 5% of Europe, and are often associated with protected areas. The wide distribution of most European ungulates combined with the extensive human activity within Europe result in a wide range of interactions between ungulates and humans. These interactions can be classified as services or disservices depending on the value orientation and economic position of the various stakeholders perceiving this relationship. Overall, our survey highlights the success of wildlife management policies in Europe and the potential for continental scale conservation of large mammals in human-dominated landscapes. However, maintaining the success of wild ungulate conservation requires actions from national and European institutions to improve coordinated management across jurisdictional borders and sectorial coordination for the whole landscape. This is an open access article distributed under the terms of the Creative Commons CC-BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

In Norway, recovering populations of large carnivores commonly prey on roe deer (Capreolus capreolus). Understanding predator habitat use and ecology requires fine-scaled information on prey distribution and abundance. However, the massive spatial scales at which large carnivores use the landscape presents many practical and statistical challenges for developing functional prey distribution models. Pellet-count data from > 1000 km of transects gathered across southeastern Norway between 2005 and 2011 were used to derive a map of the relative prey abundance for roe deer. These data were modeled using zero-inflated hurdle models using both environmental and anthropogenic variables. Snow depth and agricultural fields were the most significant variables in explaining both presence and abundance. Internal k-cross validation of the model showed medium accuracy (Spearman's r = 0.35), whereas external evaluation carried out on the basis of independently collected snow-tracking data (Spearman's r = 0.37) and hunti...

Made available in DSpace on 2018-11-26T17:44:52Z (GMT). No. of bitstreams: 0 Previous issue date: 2018-01-26 Robert Bosch Foundation Animal movement is fundamental for ecosystem functioning and species survival, yet the effects of the anthropogenic footprint on animal movements have not been estimated across species. Using a unique GPS-tracking database of 803 individuals across 57 species, we found that movements of mammals in areas with a comparatively high human footprint were on average one-half to one-third the extent of their movements in areas with a low human footprint. We attribute this reduction to behavioral changes of individual animals and to the exclusion of species with long-range movements from areas with higher human impact. Global loss of vagility alters a key ecological trait of animals that affects not only population persistence but also ecosystem processes such as predator-prey interactions, nutrient cycling, and disease transmission. Senckenberg Gesell Naturforsch, Senckenberg Biodivers & Climate Res Ctr, D-60325 Frankfurt, Main, Germany Goethe Univ, Dept Biol Sci, D-60438 Frankfurt, Main, Germany Univ Maryland, Dept Biol, College Pk, MD 20742 USA Univ Maryland, SESYNC, Annapolis, MD 21401 USA Univ Guelph, Dept Integrat Biol, Guelph, ON N1G 2W1, Canada Norwegian Inst Nat Res, POB 5685 Torgard, NO-7485 Trondheim, Norway Duke Univ, Dept Biol, Durham, NC 27708 USA Duke Univ, Dept Evolut Anthropol, Durham, NC 27708 USA Hirola Conservat Programme, Garissa, Kenya Swedish Univ Agr Sci, Dept Wildlife Fish & Environm Studies, S-90183 Umea, Sweden Radboud Univ Nijmegen, Dept Anim Ecol & Physiol, Inst Water & Wetland Res, NL-6500 GL Nijmegen, Netherlands Univ Fed Mato Grosso do Sul, Ecol & Conservat Grad Program, Campo Grande, MS, Brazil Univ Alberta, Dept Biol Sci, Edmonton, AB, Canada Univ London, Royal Vet Coll, Struct & Motion Lab, London NW1 0TU, England Wildlife Conservat Soc, Mongolia Program, Ulaanbaatar, Mongol Peo Rep Mississippi State Univ, Forest & Wildlife Res Ctr, Carnivore Ecol Lab, Box 9690, Mississippi State, MS USA Sao Paulo State Univ, Anim Biol Postgra Program, BR-15054000 Sao Jose Do Rio Preto, SP, Brazil Michigan Dept Nat Resources, 1990 US 41 South, Marquette, MI 49855 USA Univ Calif Davis, Dept Anthropol, Davis, CA 95616 USA Aarhus Univ, Dept Biosci, DK-4000 Roskilde, Denmark Max Planck Inst Ornithol, Vogelwarte Radolfzell, D-78315 Radolfzell am Bodensee, Germany Wildlife Conservat Soc, Bronx, NY 10460 USA Univ Potsdam, Plant Ecol & Nat Conservat, D-14476 Potsdam, Germany Middle Tennessee State Univ, Dept Biol, Murfreesboro, TN 37132 USA Univ Pretoria, Dept Zool & Entomol, Mammal Res Inst, ZA-0028 Gauteng, South Africa Fdn Edmund Mach, Res & Innovat Ctr, Dept Biodivers & Mol Ecol, I-38010 San Michele All Adige, TN, Italy Harvard Univ, Dept Organism & Evolutionary Biol, Cambridge, MA 02138 USA Natl Zool Pk, Smithsonian Conservat Biol Inst, Front Royal, VA USA Univ Evora, Depat Fitotecn, P-7002554 Evora, Portugal Univ Evora, ICAAM, Inst Mediterranean Agr & Environm Sci, Evora, Portugal Univ Montpellier, Univ Paul Valery Montpellier, CNRS,EPHE, Ctr Ecol Fonctionnelle & Evolut,UMR 5175, F-34293 Montpellier 5, France Phillip Isl Nat Parks, Cowes, Vic, Australia Monash Univ, Sch Biol Sci, Melbourne, Vic, Australia Ohio State Univ, Dept Civil Environm & Geodet Engn, Columbus, OH 43210 USA Fiji Natl Univ, Dept Biol, POB 5529, Natabua, Lautoka, Fiji Univ Massachusetts, US Geol Survey, Massachusetts Cooperat Fish & Wildlife Res Unit, Amherst, MA 01003 USA Penn State Univ, US Geol Survey, Penn Cooperat Fish & Wildlife Res Unit, University Pk, PA 16802 USA Univ Oxford, Dept Zool, Oxford OX1 3PS, England Giraffe Conservat Fdn, POB 86099, Eros, Namibia German Primate Ctr, Behav Ecol & Sociobiol Unit, D-37077 Gottingen, Germany Tech Univ Munich, Dept Ecol & Ecosyst Management, Restorat Ecol, D-85354 Freising Weihenstephan, Germany Cary Inst Ecosyst Studies, Millbrook, NY 12545 USA Univ British Columbia, Irving K Barber Sch Arts & Sci, Unit 2, Biol, Okanagan Campus, Kelowna, BC V1V 1V7, Canada Univ Zurich, Dept Evolutionary Biol & Environm Studies, CH-8057 Zurich, Switzerland Univ Wyoming, Dept Zool & Physiol, Laramie, WY 82071 USA Univ Washington, Sch Environm & Forest Sci, Seattle, WA 98195 USA Univ Montana, Coll Forestry & Conservat, Dept Ecosyst & Conservat Sci, Wildlife Biol Program, Missoula, MT 59812 USA Bavarian Forest Natl Pk, Dept Conservat & Res, D-94481 Grafenau, Germany Albert Ludwigs Univ Freiburg, Wildlife Ecol & Management, D-79106 Freiburg, Germany Univ Toulouse, INRA, CEFS, Castanet Tolosan, France Univ Calif Davis, Anim Behav Grad Grp, Davis, CA 95616 USA Bionet Natr Onderzoek, NL-6171 EL Stein, Netherlands Univ Vet Med Vienna, Res Inst Wildlife Ecol, A-1160 Vienna, Austria Univ Coll Cork, Sch Biol Earth & Environm Sci, Cork, Ireland Univ Wyoming, US Geol Survey, Dept Zool & Physiol, Wyoming Cooperat Fish & Wildlife Res Unit, Laramie, WY USA North Carolina Museum Nat Sci, Raleigh, NC 27601 USA North Carolina State Univ, Dept Forestry & Environm Resources, Raleigh, NC 27695 USA Karatina Univ, Dept Nat Resource Management, POB 195710101, Karatina, Kenya Univ Lethbridge, Dept Psychol, Lethbridge, AB T1K 3M4, Canada Columbia Univ, Lamont Doherty Earth Observ, Palisades, NY 10964 USA Univ Valencia, Terr Vertebrates Grp, Cavanilles Inst Biodivers & Evolutionary Biol, E-46980 Valencia, Spain SUNY Stony Brook, Dept Anthropol, Stony Brook, NY 11794 USA TSG, SSC, IUCN, Rua Licuala 622,Damha 1,Campo Grande, BR-79046150 Mato Grosso Sul, Brazil IPE Inst Pesquisas Ecol Inst Ecol Res, Caixa Postal 47, BR-12960000 Sao Paulo, Brazil Univ Alicante, Dept Ciencias Ambient & Recursos Natur, Vertebrates Zool Res Grp, Alicante, Spain Embrapa Pantanal, BR-79320900 Corumba, MS, Brazil Chico Mendes Inst Conservat Biodivers, Natl Res Ctr Carnivores Conservat, BR-12952011 Atiba, SP, Brazil Univ Glasgow, Inst Biodivers Anim Hlth & Comparat Med, Glasgow, Lanark, Scotland NYU, Dept Biol, Ctr Genom & Syst Biol, New York, NY 10003 USA Univ Calif Davis, Dept Microbiol & Mol Genet, Davis, CA 95616 USA Univ Oslo, Dept Biosci, Ctr Ecol & Evolutionary Synth, NO-0316 Oslo, Norway Hebrew Univ Jerusalem, Alexander Silberman Inst Life Sci, Dept Ecol Evolut & Behav, Movement Ecol Lab, IL-91904 Jerusalem, Israel Norwegian Inst Nat Res, NO-0349 Oslo, Norway Norwegian Univ Sci & Technol NTNU, Dept Math Sci & Ctr Biodivers Dynam, N-7491 Trondheim, Norway Univ Fed Mato Grosso do Sul, Dept Ecol, BR-79070900 Campo Grande, MS, Brazil Field Museum Nat Hist, Integrat Res Ctr, Chicago, IL 60605 USA Consorzio Parco Nazl Stelvio, Bormio, Sondrio, Italy Univ Grenoble Alpes, Irstea, UR LESSEM, BP 76, F-38402 St Martin Dheres, France Univ Bayreuth, BayCEER, D-95447 Bayreuth, Germany Natl Park Schwarzwald, D-77889 Seebach, Germany Univ New South Wales, Evolut & Ecol Res Ctr, Sydney, NSW 2052, Australia Univ New South Wales, Sch Biol Earth & Environm Sci, 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Management strategy evaluation (MSE) is a powerful tool for simulating all key aspects of natural resource management under conditions of uncertainty.We present the R package GMSE, which applies genetic algorithms to provide a generalised tool for simulating adaptive decision-making management scenarios between stakeholders with competing objectives under complex social-ecological interactions and uncertainty.GMSE models can be agent-based and spatially explicit, incorporating a high degree of realism through mechanistic modelling of links and feedbacks among stakeholders and with the ecosystem; additionally, user-defined sub-models can also be incorporated as functions into the broader GMSE framework.We show how GMSE simulates a social-ecological system using the example of an adaptively managed waterfowl population on an agricultural landscape; simulated waterfowl exploit agricultural land, causing conflict between conservation interests and the interest of food producers maximising their crop yield.The R package GMSE is open source under GNU Public License; source code and documents are freely available on GitHub.

Roads affect wildlife in many direct and indirect ways. For ungulates, roads may inhibit seasonal migration and may cause an effective loss of habitat due to avoidance. On the other hand, roadsides and associated agricultural lands offer high quality forage that may attract ungulates and increase the frequency of car accidents. Mitigating actions require detailed knowledge on space use in relation to roads. Using data from 67 global positioning system (GPS)-marked red deer in Norway, we quantified 1) scale of avoidance of roads, 2) crossing frequency, and 3) selection of crossing sites. Red deer avoided roads only on a very local scale and only during daytime, with minor influence of variation in road size (traffic burden). Marked red deer crossed roads, on average, 2 times per day. Females crossed more frequently than males and crossings were most frequent during autumn and winter and during night. Deer selected forested crossing sites close to agricultural pastures, reflecting that roads are crossed most often on nightly feeding excursions. Our findings imply that red deer in our study area have adjusted to exploit feeding habitat close to roads at times of low traffic burden. The high frequency of crossings suggests a limited influence on seasonal migration patterns. The frequency at which red deer cross highways suggests that mitigation measures to reduce road mortality may be effective if targeted in the right areas. © 2012 The Wildlife Society.

Recent studies of animal habitat selection are inferring more detail regarding the behavioural mechanisms involved, like functional responses and familiarity effects. Changes in animals’ use or selection of a habitat type with changing availability are commonly interpreted as a functional response in habitat preference. Studies of familiarity inferred preference for familiar locations from selection for previously visited locations after accounting for habitat-related preference. We simulated movement paths on discrete landscapes using random walk models with known habitat selection behaviour to assess emergent properties related to habitat selection in the context of functional and familiarity responses. The behavioural interpretation of functional responses relies on the relationship between habitat use and preference. Unfortunately, this relationship is not unique and depends upon the habitat choice mechanism: habitat use can be proportional to preference or proportional to availability (called respectively, hierarchical and simultaneous choice). We found that when the analytical method did not match the choice mechanism, strong functional responses were observed in habitat selection, even though habitat preference was kept constant. Therefore, functional responses need to be discussed in the context of an animal’s habitat choice mechanism. In the absence of familiarity-related preference, we found no familiarity effect while accounting for all habitat variables. However, when habitat models were incomplete (e.g. lack of information about resources and habitats in the landscape) – as in all field studies – spurious preference for familiar locations arose. Our study aids the interpretation of behavioural mechanisms in habitat selection studies, but also calls for a more thorough study of the approaches used to infer behavioural mechanisms in habitat selection studies.

Identifying factors shaping variation in resource selection is central for our understanding of the behaviour and distribution of animals. We examined summer habitat selection and space use by 108 Global Positioning System (GPS)-collared moose in Norway in relation to sex, reproductive status, habitat quality, and availability. Moose selected habitat types based on a combination of forage quality and availability of suitable habitat types. Selection of protective cover was strongest for reproducing females, likely reflecting the need to protect young. Males showed strong selection for habitat types with high quality forage, possibly due to higher energy requirements. Selection for preferred habitat types providing food and cover was a positive function of their availability within home ranges (i.e. not proportional use) indicating functional response in habitat selection. This relationship was not found for unproductive habitat types. Moreover, home ranges with high cover of unproductive habitat types were larger, and smaller home ranges contained higher proportions of the most preferred habitat type. The distribution of moose within the study area was partly related to the distribution of different habitat types. Our study shows how distribution and availability of habitat types providing cover and high-quality food shape ungulate habitat selection and space use. Electronic supplementary material The online version of this article (doi:10.1007/s00442-011-2072-3) contains supplementary material, which is available to authorised users.

Summary 1. Animal migration has long intrigued scientists and wildlife managers alike, yet migratory species face increasing challenges because of habitat fragmentation, climate change and over-exploitation. Central to the understanding migratory species is the objective discrimination between migratory and nonmigratory individuals in a given population, quantifying the timing, duration and distance of migration and the ability to predict migratory movements. 2. Here, we propose a uniform statistical framework to (i) separate migration from other movement behaviours, (ii) quantify migration parameters without the need for arbitrary cut-off criteria and (iii) test predictability across individuals, time and space. 3. We first validated our novel approach by simulating data based on established theoretical movement patterns. We then formulated the expected shapes of squared displacement patterns as nonlinear models for a suite of movement behaviours to test the ability of our method to distinguish between migratory movement and other movement types. 4. We then tested our approached empirically using 108 wild Global Positioning System (GPS)collared moose Alces alces in Scandinavia as a study system because they exhibit a wide range of movement behaviours, including resident, migrating and dispersing individuals, within the same population. Applying our approach showed that 87% and 67% of our Swedish and Norwegian subpopulations, respectively, can be classified as migratory. 5. Using nonlinear mixed effects models for all migratory individuals we showed that the distance, timing and duration of migration differed between the sexes and between years, with additional individual differences accounting for a large part of the variation in the distance of migration but not in the timing or duration. Overall, the model explained most of the variation (92%) and also had high predictive power for the same individuals over time (69%) as well as between study populations (74%). 6. The high predictive ability of the approach suggests that it can help increase our understanding of the drivers of migration and could provide key quantitative information for understanding and managing a broad range of migratory species.

Animal locations estimated by Global Positioning System (GPS) inherently contain errors. Screening procedures used to remove large positional errors often trade data accuracy for data loss. We developed a simple screening method that identifies locations arising from unrealistic movement patterns. When applied to a large data set of moose (Alces alces) locations, our method identified virtually all known errors with minimal loss of data. Thus, our method for screening GPS data improves the quality of data sets and increases the value of such data for research and management.

Partially migratory populations comprise both resident and migratory individuals. Th ese tactics may coexist if their demographic contribution to future generations (i.e. fitness) are equal or vary temporally with environmental conditions, or if individuals switch between being migrant and resident. Alternatively, the choice of movement tactic can be based on individual attributes such as age, competitive ability or personality. In the latter cases, the two tactics are not expected to have similar average fitness. In this study, we examined the eff ect of movement tactic on reproductive performance and survival of 82 GPS-marked female moose and their off spring in a partial migratory population in central Norway. The results indicated higher growth in the migrating part of the population because migrating females produced more twins than resident females. We found no diff erences in pregnancy rates or survival of adults or their off spring, indicating a net fitness benefit of being migrant. We found the average shoulder height of residents to be slightly lower than of migrants, but doubt that this aff ected their migration ability. A more likely explanation is that migratory females are both more fecund and grow bigger because of better conditions in their summer ranges. This may be a temporal phenomenon if the fitness differences between migratory and resident moose vary according to environmental fluctuations. © 2016 The Authors. This article is Online Open . This work is licensed under a Creative Commons Attribution 4.0 International License (CC-BY)

Summary 1. Animal space use has been studied by focusing either on geographic (e.g. home ranges, species’ distribution) or on environmental (e.g. habitat use and selection) space. However, all patterns of space use emerge from individual movements, which are the primary means by which animals change their environment. 2. Individuals increase their use of a given area by adjusting two key movement components: the duration of their visit and/or the frequency of revisits. Thus, in spatially heterogeneous environments, animals exploit known, high-quality resource areas by increasing their residence time (RT) in and/or decreasing their time to return (TtoR) to these areas. We expected that spatial variation in these two movement properties should lead to observed patterns of space use in both geographic and environmental spaces. We derived a set of nine predictions linking spatial distribution of movement properties to emerging space-use patterns. We predicted that, at a given scale, high variation in RT and TtoR among habitats leads to strong habitat selection and that long RT and short TtoR result in a small home range size. 3. We tested these predictions using moose (Alces alces) GPS tracking data. We first modelled the relationship between landscape characteristics and movement properties. Then, we investigated how the spatial distribution of predicted movement properties (i.e. spatial autocorrelation, mean, and variance of RT and TtoR) influences home range size and hierarchical habitat selection. 4. In landscapes with high spatial autocorrelation of RT and TtoR, a high variation in both RT and TtoR occurred in home ranges. As expected, home range location was highly selective in such landscapes (i.e. second-order habitat selection); RT was higher and TtoR lower within the selected home range than outside, and moose home ranges were small. Within home ranges, a higher variation in both RT and TtoR was associated with higher selectivity among habitat types (i.e. third-order habitat selection). 5. Our findings show how patterns of geographic and environmental space use correspond to the two sides of a coin, linked by movement responses of individuals to environmental heterogeneity. By demonstrating the potential to assess the consequences of altering RT or TtoR (e.g. through human disturbance or climatic changes) on home range size and habitat selection, our work sets the basis for new theoretical and methodological advances in movement ecology.

The loss, fragmentation and degradation of habitat everywhere on Earth prompts increasing attention to identifying landscape features that support animal movement (corridors) or impedes it (barriers). Most algorithms used to predict corridors assume that animals move through preferred habitat either optimally (e.g. least cost path) or as random walkers (e.g. current models), but neither extreme is realistic. We propose that corridors and barriers are two sides of the same coin and that animals experience landscapes as spatiotemporally dynamic corridor-barrier continua connecting (separating) functional areas where individuals fulfil specific ecological processes. Based on this conceptual framework, we propose a novel methodological approach that uses high-resolution individual-based movement data to predict corridor-barrier continua with increased realism. Our approach consists of two innovations. First, we use step selection functions (SSF) to predict friction maps quantifying corridor-barrier continua for tactical steps between consecutive locations. Secondly, we introduce to movement ecology the randomized shortest path algorithm (RSP) which operates on friction maps to predict the corridor-barrier continuum for strategic movements between functional areas. By modulating the parameter Ѳ, which controls the trade-off between exploration and optimal exploitation of the environment, RSP bridges the gap between algorithms assuming optimal movements (when Ѳ approaches infinity, RSP is equivalent to LCP) or random walk (when Ѳ → 0, RSP → current models). Using this approach, we identify migration corridors for GPS-monitored wild reindeer (Rangifer t. tarandus) in Norway. We demonstrate that reindeer movement is best predicted by an intermediate value of Ѳ, indicative of a movement trade-off between optimization and exploration. Model calibration allows identification of a corridor-barrier continuum that closely fits empirical data and demonstrates that RSP outperforms models that assume either optimality or random walk. The proposed approach models the multiscale cognitive maps by which animals likely navigate real landscapes and generalizes the most common algorithms for identifying corridors. Because suboptimal, but non-random, movement strategies are likely widespread, our approach has the potential to predict more realistic corridor-barrier continua for a wide range of species.

Habitats have substantial influence on the distribution and abundance of animals. Animals' selective movement yields their habitat use. Animals generally are more abundant in habitats that are selected most strongly. Models of habitat selection can be used to distribute animals on the landscape or their distribution can be modelled based on data of habitat use, occupancy, intensity of use or counts of animals. When the population is at carrying capacity or in an ideal-free distribution, habitat selection and related metrics of habitat use can be used to estimate abundance. If the population is not at equilibrium, models have the flexibility to incorporate density into models of habitat selection; but abundance might be influenced by factors influencing fitness that are not directly related to habitat thereby compromising the use of habitat-based models for predicting population size. Scale and domain of the sampling frame, both in time and space, are crucial considerations limiting application of these models. Ultimately, identifying reliable models for predicting abundance from habitat data requires an understanding of the mechanisms underlying population regulation and limitation.

Summary 1. Decreasing rate of migration in several species as a consequence of climate change and anthropic pressure, together with increasing evidence of space-use strategies intermediate between residency and complete migration, are very strong motivations to evaluate migration occurrence and features in animal populations. 2. The main goal of this paper was to perform a relative comparison between methods for identifying and charact erizing migration at the individual and population level on the basis of animal location data. 3. We classified 104 yearly individual trajectories from five populations of three deer species as migratory or non-migratory, by means of three methods: seasonal home range overlap, spatio-temporal separation of seasonal clusters and the Net Squared Displacement (NSD) method. For migr atory cases, we also measured timing and distance of migration and resi- dence time on the summer range. Finally, we comp ared the classification in migration cases across methods and populations. 4. All methods consistently identified migration at the population level, that is, they coherently dis- tinguished between complete or almost complete migr atory populations and partially migratory populations. Ho wever, in the latter case, methods co heren tly classified only about 50% of the sin- gle cases, that is they classified differently at the individual-animal level. We therefore infer that the compariso n of methods may help point to ‘less-stereo typed ’ cases in the residency -to-migration continuum. For ca ses consistently classified by all methods, no signifi cant differences were found in migration distance, or residence time on summer ranges. Timing of migration estimated by NSD was ea rlier than by the other two methods, both for spring and autumn migrations. 5. We suggest three steps to identify improper inferences from migration data and to enhance understanding of intermedia te space-use strategies. We recommend (i) classifying migration behaviours using more than one method, (ii) performing sensitivity analysis on method parame- ters to identify the extent of the differences and (iii) investigating inconsistently classified cases as these may often be ecologically interest ing (i.e. less-stereotyped migratory behaviours). adehabitat, hom e range overlap, movement patterns, Net Squared Displacement, red deer, reindeer, residence behaviour, roe deer, spatial clusters

Summary 1. Impediments to animal movement are ubiquitous and vary widely in both scale and permeability. It is essential to understand how impediments alter ecological dynamics via their influence on animal behavioural strategies governing space use and, for anthropogenic features such as roads and fences, how to mitigate these effects to effectively manage species and landscapes. 2. Here, we focused primarily on barriers to movement, which we define as features that cannot be circumnavigated but may be crossed. Responses to barriers will be influenced by the movement capabilities of the animal, its proximity to the barriers, and habitat preference. We developed a mechanistic modelling framework for simultaneously quantifying the permeability and proximity effects of barriers on habitat preference and movement. 3. We used simulations based on our model to demonstrate how parameters on movement, habitat preference and barrier permeability can be estimated statistically. We then applied the model to a case study of road effects on wild mountain reindeer summer movements. 4. This framework provided unbiased and precise parameter estimates across a range of strengths of preferences and barrier permeabilities. The quality of permeability estimates, however, was correlated with the number of times the barrier is crossed and the number of locations in proximity to barriers. In the case study we found that reindeer avoided areas near roads and that roads are semi-permeable barriers to movement. There was strong avoidance of roads extending up to c. 1 km for four of five animals, and having to cross roads reduced the probability of movement by 68� 6% (range 3� 5–99� 5%). 5. Human infrastructure has embedded within it the idea of networks: nodes connected by linear features such as roads, rail tracks, pipelines, fences and cables, many of which divide the landscape and limit animal movement. The unintended but potentially profound consequences of infrastructure on animals remain poorly understood. The rigorous framework for simultaneously quantifying movement, habitat preference and barrier permeability developed here begins to address this knowledge gap.

Strictly speaking, fundamental niches are inestimable. Nevertheless, ecologists attempt approximating them to understand species ’ distribution and plasticity to environmental changes, with invaluable repercussions on both theoretical and applied ecology. So far, individual-based habitat selection models only characterized realized niches of populations delimited by physical (e.g. fences), historical (colonization) and biotic (competition) barriers constraining access to a subset of resources available to the species. As populations with diff erent realized niches share the same fundamental niche, we developed a novel framework to scale-up response curves from population-scale habitat selection models to approximate the species ’ optimal habitat choices, unbiased by barriers constraining accessibility. We used GPS-locations from 147 wild mountain reindeer Rangifer t. tarandus , belonging to 7 of the remaining populations scattered throughout the subspecies ’ range. We linked individual choices to accessible habitat features using conditional-logistic regression with log-link function in a use-available design. Focal variables were modeled using 2nd degree polynomials on log-scale, which correspond to a Gaussian curve used to approximate the fundamental niche optimum (curve mean) and breadth (variance). Using both real and simulated data we demonstrate that robust approximations of a fundamental niche optimum and breadth can be estimated using a relatively small number of representative populations with relatively few individuals. While each classical realized niche model had strong predictive power for the focal population but poorly predicted across populations, the approximation of the fundamental niche allowed for robust inter-population comparisons in habitat quality. Th e proposed approach brings individual-based habitat selection models forward along the continuum from investigating the realized niche of a population towards investigating a species ’ fundamental niche, and allows us to quantify empirically the relationship between realized and fundamental niches. Th is allows improving the understanding of diff erences in fi tness among populations, the prediction of species ’ distributions and plasticity to environmental changes, and suggestions for mitigation priorities.

The previous chapters explored the wide set of tools that PostgreSQL and PostGIS offer to manage tracking data. In this chapter, you will expand database functionalities with those provided by dedicated software for statistical computing and graphics: the R programming language and software environment. Specifically, you will use the advanced graphics available through R and its libraries (especially ‘adehabitat’) to perform exploratory analysis of animal tracking data. This data exploration is followed with two short ecological analyses. These ecological analyses are discussed in the context of two central concepts in animal space use: geographic versus environmental space, and the spatiotemporal scale of the research question. In the first analysis, you investigate the animal’s home range, which is its use of geographic space. In the second, to explore an animal’s use of environmental space we introduce briefly the study of both use and selection of environmental features by animals. For both demonstrations we consider explicitly the temporal scale of the study through the seasonal changes introduced by seasonal migration.

Habitat selection studies generally assume that animals select habitat and food resources at multiple scales to maximise their fitness. However, animals sometimes prefer habitats of apparently low quality, especially when considering the costs associated with spatially heterogeneous human disturbance. We used spatial variation in human disturbance, and its consequences on lynx survival, a direct fitness component, to test the Hierarchical Habitat Selection hypothesis from a population of Eurasian lynx Lynx lynx in southern Norway. Data from 46 lynx monitored with telemetry indicated that a high proportion of forest strongly reduced the risk of mortality from legal hunting at the home range scale, while increasing road density strongly increased such risk at the finer scale within the home range. We found hierarchical effects of the impact of human disturbance, with a higher road density at a large scale reinforcing its negative impact at a fine scale. Conversely, we demonstrated that lynx shifted their habitat selection to avoid areas with the highest road densities within their home ranges, thus supporting a compensatory mechanism at fine scale enabling lynx to mitigate the impact of large-scale disturbance. Human impact, positively associated with high road accessibility, was thus a stronger driver of lynx space use at a finer scale, with home range characteristics nevertheless constraining habitat selection. Our study demonstrates the truly hierarchical nature of habitat selection, which aims at maximising fitness by selecting against limiting factors at multiple spatial scales, and indicates that scale-specific heterogeneity of the environment is driving individual spatial behaviour, by means of trade-offs across spatial scales. © 2013 Basille et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Norwegian wild reindeer Rangifer tarandus tarandus are divided into 23 virtually isolated populations, primarily due to the abandonment of traditional migration and movement corridors caused by the development of infrastructures. By conducting a nation-wide, interdisciplinary pre-post study on a temporal scale spanning centuries, we modelled current reindeer movements with respect to archaeological findings to quantify long-term changes in area use related to anthropogenic disturbance. The location of 3,113 pitfall traps and hunting blinds, built 600–2000 years ago and used until 350–400 years ago, testified the location of traditional movement corridors. Current movement routes were delineated using Brownian Bridge Movement Models based on 147 reindeer GPS-monitored during 10 years. Using Path Analysis we quantified direct, indirect and total effects of different infrastructures within multiple scales (1, 5, and 10 km-radius buffers) on the current probability of use of ancient movement corridors. Tourist cabins and roads had the strongest long-term direct effects at most scales: 1 tourist cabin and 1 km road within a 1 km-radius buffer would lead, respectively, to complete area abandonment, and to a 46 % decrease in the probability of use. Power lines and private cabins had significant indirect effects on area use through their effect on roads, while hiking trails and, in particular, hydroelectric dams had highly variable effects, not significant at a nation-wide scale. Finally, we provide a flexible tool to estimate the potential long-term direct and cumulative effects of different types of infrastructures at the desired spatial scale to be used for the development of future sustainable land management plans.

1. Movement is fundamental to individual and population dynamics, as it allows individuals to meet their basic requirements. Although movement patterns reflect interactions between internal and external factors, only few studies have examined the effects of these factors on movement simultaneously, and they generally focused on particular biological contexts (e.g. dispersal, foraging). 2. However, the relative importance of these factors in driving individual routine movements might reflect a species’ potential flexibility to cope with landscape changes and therefore buf- fer their potential impact on fitness. 3. We used data from GPS collars on Scandinavian brown bears to investigate the relative role of these factors, as well as an additional factor (period of the year) on routine move- ments at two spatial scales (hourly and daily relocations). 4. As expected, internal factors played a major role in driving movement, compared to exter- nal factors at both scales, but its relative importance was greater at a finer scale. In particu- lar, the interaction between reproductive status and period of the year was one of the most influential variables, females being constrained by the movement capacity of their cubs in the first periods of the year. The effect of human disturbance on movement was also greater for females with cubs than for lone females. 5. This study showed how reciprocal modulation of internal and external factors is shaping space use of brown bears. We stress that these factors should be studied simultaneously to avoid the risk of obtaining context-dependent inferences. Moreover, the study of their relative contribution is also highly relevant in the context of multiple-use landscapes, as human activi- ties generally affect the landscape more than they affect the internal states of an individual. Species or individuals with important internal constraints should be less responsive to changes in their environment as they have less freedom from internal constraints and should thus be more sensitive to human alteration of the landscape, as shown for females with cubs in this study.

The forage-maturation hypothesis (FMH) states that herbivores migrate along a phenological gradient of plant development in order to maximize energy intake. Despite strong support for the FMH, the actual relationship between plant phenology and ungulate movement has remained enigmatic. We linked plant phenology (MODIS–normalized difference vegetation index [NDVI] data) and space use of 167 migratory and 78 resident red deer (Cervus elaphus), using a space-time-time matrix of “springness,” defined as the instantaneous rate of green-up. Consistent with the FMH, migrants experienced substantially greater access to early plant phenology than did residents. Deer were also more likely to migrate in areas where migration led to greater gains in springness. Rather than “surfing the green wave” during migration, migratory red deer moved rapidly from the winter to the summer range, thereby “jumping the green wave.” However, migrants and, to a lesser degree, residents did track phenological green-up through parts of the growing season by making smaller-scale adjustments in habitat use. Despite pronounced differences in their life histories, we found only marginal differences between male and female red deer in this study. Those differences that we did detect pointed toward additional constraints on female space-use tactics, such as those posed by calving and caring for dependent offspring. We conclude that whereas in some systems migration itself is a way to surf the green wave, in others it may simply be a means to reconnect with phenological spring at the summer range. In the light of ubiquitous anthropogenic environmental change, understanding the relationship between the green wave and ungulate space use has important consequences for the management and conservation of migratory ungulates and the phenomenon of migration itself. © 2012 by The University of Chicago.