Citizen Science Observations Research Articles

Citizen science observations reveal rapid, multi-decadal ecosystem changes in eastern Long Island Sound

Long-term environmental records are among the most valuable assets for understanding the trajectory and consequences of climate change. Here we report on a newly recovered time-series from Project Oceanology, a non-profit ocean science organization serving New England schools (USA) since 1972. As part of its educational mission, Project Oceanology has routinely and consistently recorded water temperature, pH, and oxygen as well as invertebrate and fish abundance in nearshore waters of the Thames River estuary in eastern Long Island Sound (LIS). We digitized these long-term records to test for decadal trends in abiotic and biotic variables including shifts in species abundance, richness, and diversity. Consistent with previous studies, the data revealed an above-average warming rate of eastern LIS waters over the past four decades (+0.45 °C decade−1), a non-linear acidification trend twice the global average (−0.04 pH units decade−1), and a notable decline in whole water-column dissolved oxygen concentrations (−0.29 mg L−1 decade−1). Trawl catches between 1997 and 2016 suggested a significant decrease in overall species diversity and richness, declines in cold-water adapted species such as American lobster (Homarus americanus), rock crab (Cancer irroratus), and winter flounder (Pseudopleuronectes americanus), but concurrent increases in the warm-water decapod Libinia emarginata (spider crab). Our study confirmed that Long Island Sound is a rapidly changing urban estuary, while demonstrating the value of long-term observations made by citizen-scientists, educators, and other stakeholders.

Citizen Science Observations Reveal Long-Term Population Trends of Common and Pacific Loon in Urbanized Alaska

AbstractFor more than 30 y, the Alaska Loon Watch (1985–1999) and the Alaska Loon and Grebe Watch (2000–2015) engaged citizen scientist participants to record more than 10,000 observations of common loons Gavia immer and Pacific loons Gavia pacifia at 346 lakes in five subregions of southcentral Alaska. We used generalized linear mixed models to estimate long-term trends in adult loon counts and chick survival and examined environmental variables associated with loon abundance. Adult common loon counts increased in all five subregions by 0.6–3.6% annually, whereas Pacific loons decreased 3% in the Anchorage subregion, but otherwise had trends not distinguishable from zero. Lake area was positively associated with common loon abundance and negatively associated with Pacific loon abundance. We also noted an inverse relationship between common loon and Pacific loon presence, consistent with the premise of interspecific competition. We did not find strong relationships between loon presence and predictor variables indicative of human disturbance or lakeshore development. Estimates of chick survival over time also revealed no clear pattern, although common loon chicks showed a decline in survival over the study period in one subregion. Citizen science programs provide agencies with a cost-effective tool to collect data over large spatial and temporal extents, which may not be feasible otherwise. However, there are ramifications of common data deficiencies associated with casual or unstructured observations, which can violate the assumptions required for rigorous statistical analysis. The implementation of a carefully predefined sampling protocol can avoid sampling bias, eliminate stringent assumptions, and ensure higher information content of citizen science data.

Holding steady: Little change in intensity or timing of bird migration over the Gulf of Mexico.

Quantifying the timing and intensity of migratory movements is imperative for understanding impacts of changing landscapes and climates on migratory bird populations. Billions of birds migrate in the Western Hemisphere, but accurately estimating the population size of one migratory species, let alone hundreds, presents numerous obstacles. Here, we quantify the timing, intensity, and distribution of bird migration through one of the largest migration corridors in the Western Hemisphere, the Gulf of Mexico (the Gulf). We further assess whether there have been changes in migration timing or intensity through the Gulf. To achieve this, we integrate citizen science (eBird) observations with 21years of weather surveillance radar data (1995-2015). We predicted no change in migration timing and a decline in migration intensity across the time series. We estimate that an average of 2.1billion birds pass through this region each spring en route to Nearctic breeding grounds. Annually, half of these individuals pass through the region in just 18days, between April 19 and May 7. The western region of the Gulf showed a mean rate of passage 5.4 times higher than the central and eastern regions. We did not detect an overall change in the annual numbers of migrants (2007-2015) or the annual timing of peak migration (1995-2015). However, we found that the earliest seasonal movements through the region occurred significantly earlier over time (1.6days decade-1 ). Additionally, body mass and migration distance explained the magnitude of phenological changes, with the most rapid advances occurring with an assemblage of larger-bodied shorter-distance migrants. Our results provide baseline information that can be used to advance our understanding of the developing implications of climate change, urbanization, and energy development for migratory bird populations in North America.

The spread of the parthenogenetic mourning gecko, Lepidodactylus lugubris (Duméril and Bibron, 1836) to Paradise Island, The Bahamas, with comments on citizen science observations of non-native herpetofauna

The spread of the parthenogenetic mourning gecko, Lepidodactylus lugubris (Duméril and Bibron, 1836) to Paradise Island, The Bahamas, with comments on citizen science observations of non-native herpetofauna

Comparison of simulated radioactive atmospheric releases to citizen science observations for the Fukushima nuclear accident

Citizen science data from the Safecast project were shown to provide a reliable estimation of the spatial distribution of concentrations of elevated radiation levels around Fukushima when compared to government data. A comparison is presented between the HYSPLIT Lagrangian atmospheric transport and dispersion (T&D) model and a reflected Gaussian model to both government and Safecast contributed measurements. The advantage of contributed data with respect to the government data is that they are collected over a long period of time and have a larger spatial coverage.First, the Safecast contributed measurements are compared to aerial surveys completed by the Department of Energy (DOE) and the National Nuclear Security Administration (NNSA). Then the HYSPLIT T&D model is run to simulate the nuclear release using high resolution terrain and meteorological data. A Gaussian dispersion model is also run for comparison using meteorological data observed at the time of the accident. The results of both models and observed data are decay corrected to December 2016 in order to use a larger quantity of contributed measurements in the comparison.The comparison of areas of elevated radiation shows that the citizen science observations align with the prediction of models representing dynamic behavior of radionuclides dispersed in the environment. This paper shows that citizen science data can be used to validate and potentially better calibrate atmospheric T&D models.

Usability of citizen science observations together with airborne laser scanning data in determining the habitat preferences of forest birds

Citizens’ field observations are increasingly stored in accessible databases, which makes it possible to use them in research. Citizen science (CS) complements the field work that must necessarily be carried out to gain an understanding of any of bird species’ ecology. However, CS data holds multiple biases (e.g. presence only data, location error of bird observations, spatial data coverage) that should be paid attention before using the data in scientific research.The use of Airborne Laser Scanning (ALS) enables investigating forest bird species’ habitat preferences in detail and over large areas. In this study the breeding time habitat preferences of 25 forest bird species were investigated by coupling CS observations together with nine forest structure parameters that were computed using ALS data and field plot measurements. Habitat preferences were derived by comparing surroundings of presence-only observations against the full landscape. Also, in order to account for bird observation location errors, we analysed several buffering alternatives.The results correspond well with the known ecology of the selected forest bird species. The size of a bird species’ territory as well as some behavioural traits affecting detectability (song volume, mobility etc.) seemed to determine which bird species’ CS data could be analysed with this approach. Especially the habitats of specialised species with small or medium sized territories differed from the whole forest landscape in the light of several forest structure parameters. Further research is needed to tackle issues related to the behaviour of the observers (e.g. birdwatchers’ preference for roads) and characteristics of the observed species (e.g. preference for edge habitats), which may be the reasons for few unexpected results.Our study shows that coupling CS data with ALS yield meaningful results that can be presented with distribution figures easy to understand and, more importantly, that can cover areas larger than what is normally possible by means of purpose-designed research projects. However, the use of CS data requires an understanding of the process of data collection by volunteers. Some of the biases in the data call for further thinking in terms of how the data is collected and analysed.

Comparing citizen science reports and systematic surveys of marine mammal distributions and densities

Citizen science observations represent a significant and growing source of species and ecosystem knowledge. These data have potential to support traditional surveys. Databases of citizen observations of wildlife are growing, but how to use this information for scientific purposes is less clear owing to uncertainty in sampling distribution and data quality. In this study, we demonstrate how mapping cetacean patterns using citizen observations and systematic surveys generate consistent and different understandings of cetacean distributions and densities, and evaluate potential risk by assessing cumulative human effects in British Columbia, Canada. We used GIS-based map comparison methods that quantified differences and similarities between geographic datasets to locate where cetacean distributions and densities had spatially unique or spatially analogous representation. Where spatial clusters in both data sources are congruent, we interpret with a higher level of confidence that species occur, and mapped patterns accurately reflect distribution and density. In areas where datasets exhibit dissimilar species densities and distributions, we acknowledge lower confidence and advise further sampling. Regions of agreement were primarily in the central-western portion of the study area (off the southeastern coast of Haida Gwaii); areas of disagreement were heterogeneously distributed across the study area. Spatial clusters from citizen data exhibited significantly higher cumulative human effect scores than from systematic surveys, despite previous data adjustments for human effort. We demonstrate the use of citizen observations as a confirmatory dataset to broaden ecological exploration by augmenting scientific survey datasets and identifying strategic areas for future data collection efforts.

Description of four new species of Eadya (Hymenoptera, Braconidae), parasitoids of the Eucalyptus Tortoise Beetle (Paropsis charybdis) and other Eucalyptus defoliating leaf beetles

EucalyptusL’Héritier, 1789 (Myrtales: Myrtaceae) plantations are a global economic resource with a wide array of uses. As this forestry crop grows in popularity around the world, the exotic introduction of pests such as the leaf beetles belonging to the generaParopsisOliver, 1807 andParopsisternaMotschulsky, 1860 increases in frequency. These pest introductions have spurred a need to understand the natural enemies of these pests for use in classical biological control programs. One such enemy,EadyaparopsidisHuddleston & Short, 1978 (Hymenoptera: Braconidae), has shown potential as a biological control agent againstParopsischarybdis, an exotic pest of New ZealandEucalyptusplantations. However, observations made by biocontrol researchers have raised concerns thatE.paropsidisis a complex of cryptic species. A comprehensive large-scale phylogenetic study utilizing both host and molecular data (Peixoto et al. 2018), as well as a morphological multivariate ratio analysis, was utilized to ensure accurate delimitation of the species ofEadya. Here we formally describe the three new species (EadyaannleckieaeRidenbaugh, 2018,sp. n.,EadyadaenerysRidenbaugh, 2018,sp. n.,EadyaspitzerRidenbaugh, 2018,sp. n.), and one additional new species discovered in the Australian National Insect Collection (EadyaduncanRidenbaugh, 2018,sp. n.). All distributions and host associations forEadyaare listed as well as a redescription of the originally describedE.paropsidisandE.falcata. An illustrated key to all known species is included to assist biological control researchers. The value of citizen science observations is discussed, along with the need for a further understanding of mainlandEadyapopulations given the recent spread of paropsine pests. Finally, we discuss the subfamilial placement ofEadya, and suggest it belongs within Euphorinae based on morphological characters.

Automated Identification of Citizen Science Observations for Ecological Studies

Pl@ntNet is an international initiative which was the first one attempting to combine the force of citizens networks with automated identification tools based on machine learning technologies (Joly et al. 2014). Launched in 2009 by a consortium involving research institutes in computer sciences, ecology and agriculture, it was the starting point of several scientific and technological productions (Goëau et al. 2012) which finally led to the first release of the Pl@ntNet app (iOS in February 2013 (Goëau et al. 2013) and Android (Goëau et al. 2014) the following year). Initially based on 800 plant species, the app was progressively enlarged to thousands of species of the European, North American and tropical regions. Nowadays, the app covers more than 15 000 species and is adapted to 22 regional and thematic contexts, such as the Andean plant species, the wild salads of southern Europe, the indigenous trees species of South Africa, the flora of the Indian Ocean Islands, the New Caledonian Flora, etc. The app is translated in 11 languages and is being used by more than 3 millions of end-users all over the world, mostly in Europe and the US. The analysis of the data collected by Pl@ntnet users, which represent more than 24 millions of observations up to now, has a high potential for different ecological and management questions. A recent work (Botella et al. 2018), in particular, did show that the stream of Pl@ntNet observations could allow a fine-grained and regular monitoring of some species of interest such as invasive ones. However, this requires cautious considerations about the contexts in which the application is used. In this talk, we will synthesize the results of this study and present another one related to phenology. Indeed, as the phenological stage of the observed plants is also recorded, these data offer a rich and unique material for phenological studies at large geographical or taxonomical scale. We will share preliminary results obtained on some important pantropical species (such as the Melia azedarach L., and the Lantana camara L.), for which we have detected significant intercontinental phenological patterns, among the project data.

How A Citizen Scientist Can Reuse & Link Biodiversity Heritage Library Data

The Biodiversity Heritage Library (BHL) provides open access to over 54 million pages of biodiversity literature. Much of this literature is either in the public domain or is licensed for reuse under the Creative Commons framework. Anyone can therefore freely reuse much of the information and data provided by BHL. This presentation will outline how the work of a citizen scientist using BHL content might benefit research scientists. It will discuss how a citizen scientist can reuse and link BHL literature and data in Wikipedia and Wikidata. It will explain the research efficiencies that can be obtained through this reuse and linking, for example through the consolidation of database identifiers. The presentation will outline the subsequent reuse of the BHL data added to Wikipedia and Wikidata by the internet search engine Google. It will discuss an example of the linking of this information in the citizen science observation platform iNaturalist. The presentation will explain how BHL, as a result of its open reuse licensing of information and data, helps in the creation of more accurate citizen science generated biodiversity data and assists with the wider and more effective dissemination of biodiversity information.

Green digitization: Online botanical collections data answering real‐world questions

Green digitization: Online botanical collections data answering real‐world questions

Spatial distribution of citizen science casuistic observations for different taxonomic groups

Opportunistic citizen science databases are becoming an important way of gathering information on species distributions. These data are temporally and spatially dispersed and could have limitations regarding biases in the distribution of the observations in space and/or time. In this work, we test the influence of landscape variables in the distribution of citizen science observations for eight taxonomic groups. We use data collected through a Portuguese citizen science database (biodiversity4all.org). We use a zero-inflated negative binomial regression to model the distribution of observations as a function of a set of variables representing the landscape features plausibly influencing the spatial distribution of the records. Results suggest that the density of paths is the most important variable, having a statistically significant positive relationship with number of observations for seven of the eight taxa considered. Wetland coverage was also identified as having a significant, positive relationship, for birds, amphibians and reptiles, and mammals. Our results highlight that the distribution of species observations, in citizen science projects, is spatially biased. Higher frequency of observations is driven largely by accessibility and by the presence of water bodies. We conclude that efforts are required to increase the spatial evenness of sampling effort from volunteers.

Detecting long-term occupancy changes in Californian odonates from natural history and citizen science records

In a world of rapid environmental change, effective biodiversity conservation and management relies on our ability to detect changes in species occurrence. While long-term, standardized monitoring is ideal for detecting change, such monitoring is costly and rare. An alternative approach is to use historical records from natural history collections as a baseline to compare with recent observations. Here, we combine natural history collection data with citizen science observations within a hierarchical Bayesian occupancy modeling framework to identify changes in the occupancy of Californian dragonflies and damselflies (Odonata) over the past century. We model changes in the probability of occupancy of 34 odonate species across years and as a function of climate, after correcting for likely variation in detection probability using proxies for recorder effort and seasonal variation. We then examine whether biological traits can help explain variation in temporal trends. Models built using only opportunistic records identify significant changes in occupancy across years for 14 species, with eight of those showing significant declines and six showing significant increases in occupancy in the period 1900–2013. These changes are consistent with estimates obtained using more standardized resurvey data, regardless of whether resurvey data are used individually or in conjunction with the opportunistic dataset. We find that species increasing in occupancy over time are also those whose occupancy tends to increase with higher minimum temperatures, which suggests that these species may be benefiting from increasing temperatures across California. Furthermore, these species are also mostly habitat generalists, whilst a number of habitat specialists display some of the largest declines in occupancy across years. Our approach enables more robust estimates of temporal trends from opportunistic specimen and observation data, thus facilitating the use of these data in biodiversity conservation and management.

Changes in Distribution of Canada Geese Nesting in Arkansas

The reintroduced Canada goose (Branta canadensis) population in Arkansas has grown in range and abundance in recent decades. We determined the geographic range of Arkansas resident Canada geese from 2004 to 2012 using volume contour maps from citizen science observations using eBird, a citizen science website, and hunter recovery locations from the U.S. Geological Survey Bird Banding Laboratory. Resulting maps indicate an increase in Canada goose encounters toward northwestern and southwestern Arkansas from the original relocations in the Arkansas River valley. We examined movement of Canada geese banded and recovered in Arkansas by determining the distance and angle of movement between initial and final encounter locations; 25% moved east, and 17% went west. The average distance moved from banding to recovery was 50 km (SE = 1 km). Recoveries of Canada geese banded in Arkansas were greatest in the Mississippi Flyway (58% of all geese) followed by the Central Flyway (37%) with some representation in both the Atlantic (4%) and Pacific flyways (0.9%). Movement from Arkansas to other states and Canada was influenced by goose age and sex. Older individuals traveled longer distances than younger ones, and females traveled longer distances than males. Our findings suggest that recently established Canada geese in Arkansas have slowly expanded within the state to the northwest and southwest with the expansion to the east being important now. Movement of Arkansas resident Canada geese on molt-migration can contribute to management issues in other states and provinces.

Completeness of citizen science biodiversity data from a volunteered geographic information perspective

Observations of living organisms by citizen scientists that are reported to online portals are a valuable source of information. They are also a special kind of volunteered geographic information (VGI). VGI data have issues of completeness, which arise from biases caused by the opportunistic nature of the data collection process. We examined the completeness of bird species represented in citizen science observation data from eBird and iNaturalist in US National Parks (NPs). We used approaches for completeness estimation which were developed for data from OpenStreetMap, a crowdsourced map of the world. First, we used an extrinsic approach, comparing species lists from citizen science data with National Park Service lists. Second, we examined two intrinsic approaches using total observation numbers in NPs and the development of the number of new species being added to the data-set over time. Results from the extrinsic approach provided appropriate completeness estimations to evaluate the intrinsic approaches. We found that total observation numbers are a good estimator of species completeness of citizen science data from US NPs. There is also a close relationship between species completeness and the ratio of new species added to observation data vs. observation numbers in a given year.

Evaluating citizen science data for forecasting species responses to national forest management.

The extensive spatial and temporal coverage of many citizen science datasets (CSD) makes them appealing for use in species distribution modeling and forecasting. However, a frequent limitation is the inability to validate results. Here, we aim to assess the reliability of CSD for forecasting species occurrence in response to national forest management projections (representing 160,366 km2) by comparison against forecasts from a model based on systematically collected colonization–extinction data. We fitted species distribution models using citizen science observations of an old‐forest indicator fungus Phellinus ferrugineofuscus. We applied five modeling approaches (generalized linear model, Poisson process model, Bayesian occupancy model, and two MaxEnt models). Models were used to forecast changes in occurrence in response to national forest management for 2020‐2110. Forecasts of species occurrence from models based on CSD were congruent with forecasts made using the colonization–extinction model based on systematically collected data, although different modeling methods indicated different levels of change. All models projected increased occurrence in set‐aside forest from 2020 to 2110: the projected increase varied between 125% and 195% among models based on CSD, in comparison with an increase of 129% according to the colonization–extinction model. All but one model based on CSD projected a decline in production forest, which varied between 11% and 49%, compared to a decline of 41% using the colonization–extinction model. All models thus highlighted the importance of protected old forest for P. ferrugineofuscus persistence. We conclude that models based on CSD can reproduce forecasts from models based on systematically collected colonization–extinction data and so lead to the same forest management conclusions. Our results show that the use of a suite of models allows CSD to be reliably applied to land management and conservation decision making, demonstrating that widely available CSD can be a valuable forecasting resource.

Combining citizen science species distribution models and stable isotopes reveals migratory connectivity in the secretive Virginia rail

Summary Stable hydrogen isotope (δD) methods for tracking animal movement are widely used yet often produce low resolution assignments. Incorporating prior knowledge of abundance, distribution or movement patterns can ameliorate this limitation, but data are lacking for most species. We demonstrate how observations reported by citizen scientists can be used to develop robust estimates of species distributions and to constrain δD assignments. We developed a Bayesian framework to refine isotopic estimates of migrant animal origins conditional on species distribution models constructed from citizen scientist observations. To illustrate this approach, we analysed the migratory connectivity of the Virginia rail Rallus limicola, a secretive and declining migratory game bird in North America. Citizen science observations enabled both estimation of sampling bias and construction of bias‐corrected species distribution models. Conditioning δD assignments on these species distribution models yielded comparably high‐resolution assignments. Most Virginia rails wintering across five Gulf Coast sites spent the previous summer near the Great Lakes, although a considerable minority originated from the Chesapeake Bay watershed or Prairie Pothole region of North Dakota. Conversely, the majority of migrating Virginia rails from a site in the Great Lakes most likely spent the previous winter on the Gulf Coast between Texas and Louisiana. Synthesis and applications. In this analysis, Virginia rail migratory connectivity does not fully correspond to the administrative flyways used to manage migratory birds. This example demonstrates that with the increasing availability of citizen science data to create species distribution models, our framework can produce high‐resolution estimates of migratory connectivity for many animals, including cryptic species. Empirical evidence of links between seasonal habitats will help enable effective habitat management, hunting quotas and population monitoring and also highlight critical knowledge gaps.

Mapping Presence and Predicting Phenological Status of Invasive Buffelgrass in Southern Arizona Using MODIS, Climate and Citizen Science Observation Data

The increasing spread and abundance of an invasive perennial grass, buffelgrass (Pennisetum ciliare), represents a critical threat to the native vegetation communities of the Sonoran desert in southern Arizona, USA, where buffelgrass eradication is a high priority for resource managers. Herbicidal treatment of buffelgrass is most effective when the vegetation is actively growing, but the remoteness of infestations and the erratic timing and length of the species’ growth periods confound effective treatment. The goal of our research is to promote buffelgrass management by using remote sensing data to detect where the invasive plants are located and when they are photosynthetically active. We integrated citizen scientist observations of buffelgrass phenology in the Tucson, Arizona area with PRISM precipitation data, eight-day composites of 250-m Moderate-resolution Imaging Spectroradiometer (MODIS) satellite imagery, and aerially-mapped polygons of buffelgrass presence to understand dynamics and relationships between precipitation and the timing and amount of buffelgrass greenness from 2011 to 2013. Our results show that buffelgrass responds quickly to antecedent rainfall: in pixels containing buffelgrass, higher correlations (R2 > 0.5) typically occur after two cumulative eight-day periods of rain, whereas in pixels dominated by native vegetation, four prior 8-day periods are required to reach that threshold. Using the new suite of phenometrics introduced here—Climate Landscape Response metrics—we accurately predicted the location of 49% to 55% of buffelgrass patches in Saguaro National Park. These metrics and the suggested guidelines for their use can be employed by resource managers to treat buffelgrass during optimal time periods.

Using citizen science reports to define the equatorial extent of auroral visibility

AbstractAn aurora may often be viewed hundreds of kilometers equatorward of the auroral oval owing to its altitude. As such, the NOAA Space Weather Prediction Center (SWPC) Aurora Forecast product provides a “view line” to demonstrate the equatorial extent of auroral visibility, assuming that it is sufficiently bright and high in altitude. The view line in the SWPC product is based upon the latitude of the brightest aurora, for each hemisphere, as specified by the real‐time oval variation, assessment, tracking, intensity, and online nowcasting (OVATION) Prime (2010) aurora precipitation model. In this study, we utilize nearly 500 citizen science auroral reports to compare with the view line provided by an updated SWPC aurora forecast product using auroral precipitation data from OVATION Prime (2013). The citizen science observations were recorded during March and April 2015 using the Aurorasaurus platform and cover one large geomagnetic storm and several smaller events. We find that this updated SWPC view line is conservative in its estimate and that the aurora is often viewable further equatorward than is indicated by the forecast. By using the citizen reports to modify the scaling parameters used to link the OVATION Prime (2013) model to the view line, we produce a new view line estimate that more accurately represents the equatorial extent of visible aurora. An OVATION Prime (2013) energy flux‐based equatorial boundary view line is also developed and is found to provide the best overall agreement with the citizen science reports, with an accuracy of 91%.

Effects of Climate Change on Habitat Availability and Configuration for an Endemic Coastal Alpine Bird.

North America’s coastal mountains are particularly vulnerable to climate change, yet harbour a number of endemic species. With little room “at the top” to track shifting climate envelopes, alpine species may be especially negatively affected by climate-induced habitat fragmentation. We ask how climate change will affect the total amount, mean patch size, and number of patches of suitable habitat for Vancouver Island White-tailed Ptarmigan (Lagopus leucura saxatilis; VIWTP), a threatened, endemic alpine bird. Using a Random Forest model and a unique dataset consisting of citizen science observations combined with field surveys, we predict the distribution and configuration of potential suitable summer habitat for VIWTP under baseline and future (2020s, 2050s, and 2080s) climates using three general circulation models and two greenhouse gas scenarios. VIWTP summer habitat is predicted to decline by an average of 25%, 44%, and 56% by the 2020s, 2050s, and 2080s, respectively, under the low greenhouse gas scenario and 27%, 59%, and 74% under the high scenario. Habitat patches are predicted to become fragmented, with a 52–79% reduction in mean patch size. The average elevation of suitable habitat patches is expected to increase, reflecting a loss of patches at lower elevations. Thus ptarmigan are in danger of being “squeezed off the mountain”, as their remaining suitable habitat will be increasingly confined to mountaintops in the center of the island. The extent to which ptarmigan will be able to persist in increasingly fragmented habitat is unclear. Much will depend on their ability to move throughout a more heterogeneous landscape, utilize smaller breeding areas, and survive increasingly variable climate extremes. Our results emphasize the importance of continued monitoring and protection for high elevation specialist species, and suggest that White-tailed Ptarmigan should be considered an indicator species for alpine ecosystems in the face of climate change.