Identify Landscape Features Research Articles

Effective dispersal patterns in prairie plant species across human-modified landscapes.

Effective dispersal among plant populations is dependent on vector behaviour, landscape features and availability of adequate habitats. To capture landscape feature effects on dispersal, studies must be conducted at scales reflecting single-generation dispersal events (mesoscale). Many studies are conducted at large scales where genetic differentiation is due to dispersal occurring over multiple generations, making it difficult to interpret the effects of specific landscape features on vector behaviour. Genetic structure at the mesoscale may be determined by ecological and evolutionary processes, such as the consequences of vector behaviour on patterns of gene flow. We used chloroplast haplotypes and nuclear genome SNP surveys to identify landscape features influencing seed and pollen dispersal at a mesoscale within the Rogue River Valley in southern Oregon. We evaluated biotic and abiotic vector behaviour by contrasting two annual species with differing dispersal mechanisms; Achyrachaena mollis (Asteraceae) is a self-pollinating and anemochoric species, and Plectritis congesta (Caprifoliaceae) is biotically pollinated with barochoric seeds. Using landscape genetics methods, we identified features of the study region that conduct or restrict dispersal. We found chloroplast haplotypes were indicative of historic patterns of gene flow prior to human modification of landscapes. Seed dispersal of A. mollis was best supported by models of isolation by distance, while seed-driven gene flow of P. congesta was determined by the distribution of preserved natural spaces and quality habitat. Nuclear genetic structure was driven by both pollen and seed dispersal, and both species responded to contemporary landscape changes, such as urban and agricultural conversion, and habitat availability.

New Approach to Landscape-Based Spatial Planning Using Meaningful Geolocated Digital Traces

The integration of landscape-based approaches into regional and town planning policies is one of the main objectives of the European Landscape Convention. In the twenty-first century, the traditional discipline of city spatial-planning has gradually been incorporating two types of tactics linked to a landscape-based approach: nature-based strategies, which focus on sustainable goals; and people-based strategies, which integrate a social dimension into decision-making processes. A backbone of landscape-based spatial planning challenge consists of reshaping consolidated urban areas to improve quality of life, encouraging people’s physical activity, and supporting healthier urban lifestyles. This study assumes that physical activity is further encouraged by itineraries that incorporate both landscape features—i.e., natural assets and sense of place—and functional diversity associated with urban activities—i.e., public facilities. A methodology was elaborated to define a preliminary landscape-based spatial planning approach, centering on the analysis of walking-related activity in urban and peri-urban areas. For this purpose, geolocated digital traces are intertwined: official city routes, urban facility locations, users’ Wikiloc trails, and Google Places API data. Once applied to selected medium-sized European cities in the Mediterranean area, these data sources lead to the identification of intangible values and dynamics in places where landscape-based spatial planning solutions could be enhanced. As a result, the present work shows the suitability of interrelating these geolocated data sources, permitting to identify landscape features as key components of spatial planning, which permit balancing individual goals, the aims of local communities, and administrative functions.

The salmonid and the subsurface: Hillslope storage capacity determines the quality and distribution of fish habitat

AbstractWater in rivers is delivered via the critical zone (CZ)—the living skin of the Earth, extending from the top of the vegetation canopy through the soil and down to fresh bedrock and the bottom of significantly active groundwater. Consequently, the success of stream‐rearing salmonids depends on the structure and resulting water storage and release processes of this zone. Physical processes below the land surface (the subsurface component of the CZ) ultimately determine how landscapes “filter” climate to manifest ecologically significant streamflow and temperature regimes. Subsurface water storage capacity of the CZ has emerged as a key hydrologic variable that integrates many of these subsurface processes, helping to explain flow regimes and terrestrial plant community composition. Here, we investigate how subsurface storage controls flow, temperature, and energetic regimes that matter for salmonids. We illustrate the explanatory power of broadly applicable, storage‐based frameworks across a lithological gradient that spans the Eel River watershed of California. Study sites are climatically similar but differ in their geologies and consequent subsurface CZ structure that dictates water storage dynamics, leading to dramatically different hydrographs, temperature, and riparian regimes—with consequences for every aspect of salmonid life history. Lithological controls on the development of key subsurface CZ properties like storage capacity suggest a heretofore unexplored link between salmonids and geology, adding to a rich literature that highlights various fluvial and geomorphic influences on salmonid diversity and distribution. Rapidly advancing methods for estimating and observing subsurface water storage dynamics at large scales present new opportunities for more clearly identifying landscape features that constrain the distributions and abundances of organisms, including salmonids, at watershed scales.

Correlating fluency theory-based visual aesthetic liking of landscape with landscape types and features

ABSTRACT People inherently assess landscapes by creating spontaneous aesthetic liking judgments based on the surrounding stimuli. To understand these judgements objectively, use may be made of the fluency theory of aesthetic pleasure (the psychological processes through which people experience beauty). This study aims to predict people’s visual aesthetic preferences based on fluency theory and to correlate these preferences with landscape types and features. An ordinary least squares (OLS) regression model was developed to predict visual aesthetic liking, using image statistics as explanatory variables. We determined types of landscape using Landscape Character Assessment (LCA) and applied viewshed analyses distinguishing between near, medium, and far zones. We identified landscape features by content analysis making use of machine learning-based image recognition supplied by Google Cloud Vision API. The results show that vegetation and geological forms were the most significant features for people’s visual aesthetic liking, followed by waterscapes and built structures/human settlements. The viewshed analyses indicated that ‘medium-altitude, low-gradient artificial areas’ were visible in photographs with high aesthetic visual liking in all zones (i.e., at all distances). When the photographs showing this type of landscape are examined, the artificial areas in the photographs turn out to consist mostly of historical buildings or remains. This finding suggests that historical sites are not just important for their cultural value, but for their visual aesthetic value as well.

The delivery of Cultural Ecosystem Services in urban forests of different landscape features and land use contexts

Abstract Urban greenspace provides citizens with important cultural ecosystem services (CES). Identifying landscape features and land use contexts that facilitate CES delivery is critical for guiding urban greenspace management. However, how landscape features and urban context interact with each other in influencing the CES of greenspaces remains unclear. Studies on the CES of patchy urban forests are needed as they are essential urban CES providers, but vulnerable under urban land use pressure. To address these concerns, we compared the CES of 20 urban forest patches in Helsinki, Finland, with five different combinations of landscape features (i.e. size and connectivity) and land use contexts (i.e. surrounding construction density). CES were assessed through an on‐site survey on visitors' use, perceptions of CES experience and overall satisfaction, to capture the possible disparities among CES measurements. In larger (>20 ha) forests, visitors were highly satisfied with CES, particularly appreciating the experience of physical health improvement and inspiration through longer and more intense physical uses. Visitors of urban forests in a low construction density context appreciated experiences of cultural heritage, psychological restoration and physical health improvement. Urban forests deliver unique CES characterised by physical use and the benefit of restoration, aesthetics and contact with nature. We suggest that maintaining large urban forests is more effective in promoting CES in high‐density areas. In low‐density areas, maintaining small forests with open greenspace in the surroundings can also promote CES experiences. We identify management gaps caused by a mismatch between use intensity and CES experiences of urban forests, while both are important in determining people's overall satisfaction. Read the free Plain Language Summary for this article on the Journal blog.

Nightlight Intensity Change Surrounding Nature Reserves: A Case Study in Orbroicher Bruch Nature Reserve, Germany

Persistent global urbanization has a direct relationship to measurable artificial light at night (ALAN), and the Defense Meteorological Satellite Program has served an important role in monitoring this relationship over time. Recent studies have observed significant declines in insect abundance and populations, and ALAN has been recognized as a contributing factor. We investigated changes in nightlight intensity at various spatial scales surrounding insect traps located in Orbroicher Bruch Nature Reserve, Germany. Using a time series of global nighttime light imagery (1992–2010), we evaluated pixel-level trends through linear regressions and the Mann–Kendall test. Paired with urban land cover delineation, we compared nightlight trends across rural and urban areas. We utilized high-resolution satellite imagery to identify landscape features potentially related to pixel-level trends within areas containing notable change. Approximately 96% of the pixel-level trends had a positive slope, and 22% of pixels experienced statistically significant increases in nightlight intensity. We observed that 80% of the region experienced nightlight intensity increases >1%, concurrent with the observed decline in insect biomass. While it is unclear if these trends extend to other geographic regions, our results highlight the need for future studies to concurrently investigate long-term trends in ALAN and insect population decline across multiple scales, and consider the spatial and temporal overlaps between these patterns.

Deep learning and satellite imagery predict genetic diversity and differentiation

Abstract During the last decade, convolutional neural networks (CNNs) have revolutionised the application of deep learning (DL) methods to classification tasks and object recognition. These procedures can capture key features of image data that are not easily visible to the human eye and use them to classify and predict outcomes with exceptional precision. Here, we show for the first time that CNNs provide highly accurate predictions for small‐scale genetic differentiation and diversity in Ctenomys australis, a subterranean rodent from central Argentina. Using microsatellite genotypes and high‐resolution satellite imagery, we trained a simple CNN to predict local FST and mean allele richness. To identify landscape features with high impact on predicted values, we applied species distribution models to obtain the distribution of suitable habitat. Subsequent use of a machine learning algorithm (random forest) allowed us to identify the attributes that contribute the most to predictions of population genetic metrics. Predictions obtained from the CNN accounted for more than 98% of the variation observed both in FST and mean allele richness values. Random forest regression on landscape metrics indicated that features involving connectivity and consistent prevalence of suitable habitat promoted genetic diversity and reduced genetic differentiation in C. australis. Validation with synthetic data via simulations of genetic differentiation based on the landscape structure of the study area and of a nearby area showed that DL models are able to capture complex relationships between actual data and synthetic data in the same landscape and between synthetic data generated under different landscapes. Our approach represents an objective and powerful approach to landscape genetics because it can extract information from patterns that are not easily identified by humans. Spatial predictions from the CNN may assist in the identification of areas of interest for biodiversity conservation and management of populations.

Distribution and protection of avian specialization in Europe

AbstractAimWe assessed the spatial distribution of four different types of avian specialization throughout Europe, identifying landscape features associated with specialization and quantifying where the Natura 2000 network intersects with areas of high avian specialization.LocationEurope.Time periodPresent day.Taxa studiedEuropean breeding birds.MethodsWe used the European Atlas of breeding birds and four avian specialization measures (diet, foraging behaviour, foraging substrate and habitat). We calculated specialization richness and identified geographical hotspots for each of these ecological traits. We tested whether elevational gradient, landscape heterogeneity or dominant land use predicted each type of specialization richness. We determined which types of European protected areas are most associated with higher specialization richness.ResultsDiet and foraging substrate specialists increased with elevation, whereas richness of foraging behavioural specialists decreased. There was a greater richness of dietary and habitat specialists in forests than in other environments. The Natura 2000 areas declared under Bird and both directives (Birds and Habitats) intersected with a high dietary, foraging substrate and habitat specialist richness. The richness of foraging behaviour specialists was high in Birds directive areas. Single and multiple hotspots of specialization were greater in protected than non‐protected areas. However, almost 30% of specialization hotspots did not intersect with protected areas.Main conclusionsOur findings suggest that higher levels of avian specialization in Europe are positively associated with elevation and forested land cover. Importantly, we found that the Natura 2000 network supports all types of avian ecological specialization, albeit mainly in areas declared under both directives.

Functional connectivity in a continuously distributed, migratory species as revealed by landscape genomics

Maintaining functional connectivity is critical for the long‐term conservation of wildlife populations. Landscape genomics provides an opportunity to assess long‐term functional connectivity by relating environmental variables to spatial patterns of genomic variation resulting from generations of movement, dispersal and mating behaviors. Identifying landscape features associated with gene flow at large geographic scales for highly mobile species is becoming increasingly possible due to more accessible genomic approaches, improved analytical methods and enhanced computational power. We characterized the genetic structure and diversity of migratory mule deer Odocoileus hemionus using 4051 single nucleotide polymorphisms in 406 individuals sampled across multiple habitats throughout Wyoming, USA. We then identified environmental variables associated with genomic variation within genetic groups and statewide using a stepwise approach to first evaluate nonlinear relationships of landscape resistance with genetic distances and then use mixed‐effects modeling to choose top landscape genomic models. We identified three admixed genetic groups of mule deer and found that environmental variables associated with gene flow varied among genetic groups, revealing scale‐dependent and regional variation in functional connectivity. At the statewide scale, more gene flow occurred in areas with low elevation and mixed habitat. In the southern genetic group, more gene flow occurred in areas with low elevation. In the northern genetic group, more gene flow occurred in grassland and forest habitats, while highways and energy infrastructure reduced gene flow. In the western genetic group, the null model of isolation by distance best represented genetic patterns. Overall, our findings highlight the role of different seasonal ranges on mule deer genetic connectivity, and show that anthropogenic features hinder connectivity. This study demonstrates the value of combining a large, genome‐wide marker set with recent advances in landscape genomics to evaluate functional connectivity in a wide‐ranging migratory species.

Using i-tree canopy vegetation cover subtype classification to predict peri-domestic tick presence

While extant literature has generally indicated significant associations between vegetation cover and tick activity, no study has demonstrated the relative association between peri-domestic area vegetation cover subtypes and tick presence. In this study, we seek to determine whether neighborhood wood index and residential tick control practices confound or modify the effect of peri-domestic vegetation cover subtypes on tick presence. We conducted an ecological inventory of vegetation cover distribution using i-Tree Canopy on 210 private residential/peri-domestic properties in Indiana, USA. Results were paired with field obtained tick presence/absence data for each property together with online survey data provided by primary occupant of the property. Amblyomma americanum was the predominant tick species in peri-domestic areas. Higher proportion of vegetation cover in the peri-domestic area was significantly associated with tick presence. Of the four vegetation cover subtypes, (grass, shrubs, understory, and canopy), canopy was the most prevalent vegetation in peri-domestic areas of Indiana, USA. It was also the most significant predictor of tick presence. Among residential tick control processes, frequent leaf litter removal was significantly associated with reduced likelihood of peri-domestic tick presence. Neighborhood Wood Index (NWI) confounded the relationship between canopy and peri-domestic tick presence, while leaf-litter removal confounded the effect of understory vegetation subtype on peri-domestic tick presence. Compared to peri-domestic areas in neighborhoods with sparse NWI, those in neighborhoods with heavy/dense NWI had a 3.5x odd of peri-domestic tick presence (AOR = 3.46; 95 % CI: 1.23–9.65). Compared to peri-domestic areas in the central region, those in the southern region of Indiana were 8.7x more likely to have peri-domestic tick presence. Canopy as a vegetation cover subtype and frequent leaf litter removal represent particularly key peri-domestic variables that have significant implications for peri-domestic tick presence. Beyond parcel-scale landscape features, neighborhood wood index also plays an important role in peri-domestic tick presence. Additionally, i-Tree Canopy represents a promising methodological tool for identifying landscape features that predict tick presence.

Genetic Population Structure of Wild Pigs in Southern Texas.

Simple SummaryWild pigs are the most abundant wild exotic ungulate in the United States. In Texas, particularly, they are abundant and represent a threat to ecosystems, agriculture and humans. Our objective was to apply a landscape-scale analysis of population genetic structure of wild pigs to aid in their management in southern Texas. We used microsatellites to assist large-scale applied management. We found that some populations were isolated from one another. However, many individuals and local populations were admixed, which indicates that multiple introductions and artificial movement of individuals has occurred. Wild pig management efficiency and effectiveness may be able to improve if illegal translocations stop (e.g., enforcing laws) and if management cooperatives are created to manage spatially extensive areas of southern Texas.Wild pigs (Sus scrofa) alter ecosystems, affect the economy, and carry diseases that can be transmitted to livestock, humans, and wildlife. Understanding wild pig movements and population structure data, including natural population boundaries and dispersal, may potentially increase the efficiency and effectiveness of management actions. We trapped, conducted aerial shootings, and hunted wild pigs from 2005 to 2009 in southern Texas. We used microsatellites to assist large-scale applied management. We quantify broad-scale population structure among 24 sites across southern Texas by computing an overall FST value, and a Bayesian clustering algorithm both with and without considering the spatial location of samples. At a broad geographic scale, pig populations displayed a moderate degree of genetic structure (FST = 0.11). The best partition for number of populations, based on 2nd order rate of change of the likelihood distribution, was K = 10 genetic clusters. The spatially explicit Bayesian clustering algorithm produced similar results, with minor differences in designation of admixed sites. We found evidence of past (and possibly ongoing) translocations; many populations were admixed. Our original goal was to identify landscape features, such as barriers or dispersal corridors, that could be used to aid management. Unfortunately, the extensive admixture among clusters made this impossible. This research shows that large-scale management of wild pigs may be necessary to achieve control and ameliorate damages. Reduction or cessation of translocations is necessary to prevent human-mediated dispersion of wild pigs.

Genetic Structure of Invasive Baby's Breath (Gypsophila paniculata L.) Populations in a Michigan Dune System.

Coastal sand dunes are dynamic ecosystems with elevated levels of disturbance and are highly susceptible to plant invasions. One invasive plant that is of concern to the Great Lakes system is Gypsophila paniculata L. (perennial baby’s breath). The presence of G. paniculata negatively impacts native species and has the potential to alter ecosystem dynamics. Our research goals were to (1) estimate the genetic structure of invasive G. paniculata along the Michigan dune system and (2) identify landscape features that influence gene flow in this area. We analyzed 12 populations at 14 nuclear and two chloroplast microsatellite loci. We found strong genetic structure among populations (global FST = 0.228), and pairwise comparisons among all populations yielded significant FST values. Results from clustering analysis via STRUCTURE and discriminant analysis of principal components (DAPC) suggest two main genetic clusters that are separated by the Leelanau Peninsula, and this is supported by the distribution of chloroplast haplotypes. Land cover and topography better explained pairwise genetic distances than geographic distance alone, suggesting that these factors influence the genetic distribution of populations within the dunes system. Together, these data aid in our understanding of how invasive populations move through the dune landscape, providing valuable information for managing the spread of this species.

Female brown bears use areas with infanticide risk in a spatially confined population

Areas used by female brown bears (Ursus arctos) with cubs-of-the-year (hereafter, FCOY) during the first months after den exit are crucial for offspring survival, primarily because of the risk of infanticide by male bears. Therefore, FCOY may avoid areas frequented by adult males during the mating season. The main aim of this study was to identify landscape features (i.e., structure, composition, and human footprint) that may differentiate the habitat use of FCOY in the small bear population of the Cantabrian Mountains (northwestern Spain; 2001–2016) from (a) areas frequented by females with yearlings, because older cubs are at less risk of infanticide than cubs-of-the-year, and (b) bear mating areas (i.e., the riskiest areas for FCOY because of the presence of adult males). During the first months after den emergence (Apr–Jun), FCOY settled in the roughest areas of the Cantabrian Mountains at most spatial scales. This settlement pattern might represent a behavioral adaptation of FCOY to reduce the risk of encounters with males during the mating season. However, FCOY also settled in similar landscapes to those used by adult bears during the mating season, which may increase the likelihood of risky encounters. Indeed, we observed a spatial overlap between observed locations of FCOY and mating areas, which may help explain the high frequency of infanticide observed in the Cantabrian Mountains. We hypothesize that the need for both shelter and food in early spring may ‘trap’ FCOY in otherwise favorable areas that overlap with mating areas. This may occur predominately in small and confined bear populations, such as the one in the Cantabrian Mountains, where a restricted range and limited habitat availability might prevent FCOY from avoiding risky areas successfully.

Forest structure and snow depth alter the movement patterns and subsequent expenditures of a forest carnivore, the Pacific marten

Energetic balance is central to the survival and persistence of free‐ranging animals. Quantifying expenditures and identifying factors that drive energetics informs our understanding of species' ecology and their responses to shifting environmental conditions. Approaches used to estimate energetic expenditures of free‐ranging species, such as doubly‐labelled water (DLW), are precise but difficult to implement. Global positioning system (GPS) collars and accelerometers have emerged as alternatives for estimating expenditures, but these techniques have few applications in terrestrial species and no applications in small‐bodied (<5 kg) terrestrial animals. Here, we estimated movement characteristics and field metabolic rates (FMR) of Pacific martens Martes caurina, a small‐bodied carnivore with relatively high energetic costs, in a heterogeneous landscape to explore the role of movement and landscape characteristics in energetics. We concurrently used DLW and GPS collars to investigate the relationship between movement characteristics and FMR. Movement velocity explained the greatest amount of variation in mass‐specific FMR and we used this relationship to predict expenditures of previously collared martens. We found that predicted mass‐specific FMR was highest among males and increased in open patches primarily as a result of increased velocity and more erratic movements. Additionally, martens moving through deep snow also exhibited increased FMR. Our work shows movement metrics can effectively explain variation in FMR and identify landscape features, like forest structure and snow depth, that influence movements with cascading effects on energetics for free‐ranging mammals in rapidly changing systems.

State-space modeling reveals habitat perception of a small terrestrial mammal in a fragmented landscape.

Habitat loss is a major cause of species loss and is expected to increase. Loss of habitat is often associated with fragmentation of remaining habitat. Whether species can persist in fragmented landscapes may depend on their movement behavior, which determines their capability to respond flexibility to changes in habitat structure and spatial distribution of patches.Movement is frequently generalized to describe a total area used, or segmented to highlight resource use, often overlooking finer‐scale individual behaviors. We applied hidden Markov models (HMM) to movement data from 26 eastern bettongs (Bettongia gaimardi) in fragmented landscapes. HMMs are able to identify distinct behavior states associated with different movement patterns and discover how these behaviors are associated with habitat features.Three distinct behavior states were identified and interpreted as denning, foraging, and fast‐traveling. The probability of occurrence of each state, and of transitions between them, was predicted by variation in tree‐canopy cover and understorey vegetation density. Denning was associated with woodland with low canopy cover but high vegetation density, foraging with high canopy cover but low vegetation density, and fast‐traveling with low canopy cover and low vegetation density.Bettongs did move outside woodland patches, often fast‐traveling through pasture and using smaller stands of trees as stepping stones between neighboring patches. Males were more likely to fast‐travel and venture outside woodlands patches, while females concentrated their movement within woodland patches. Synthesis and applications: Our work demonstrates the value of using animal movement to understand how animals respond to variation in habitat structure, including fragmentation. Analysis using HMMs was able to characterize distinct habitat types needed for foraging and denning, and identify landscape features that facilitate movement between patches. Future work should extend the use of individual movement analyses to guide management of fragmented habitat in ways that support persistence of species potentially threatened by habitat loss.

Landscape and population genetics reveal long distance sharp-tailed grouse (Tympanuchus phasianellus) movements and a recent bottleneck in Minnesota

Sharp-tailed grouse (Tympanuchus phasianellus) are an area-sensitive species that relies on open landscapes of grass and brush. These areas have become highly fragmented in the Great Lakes Region by succession to forest, agriculture, and other human land uses. We used microsatellites in a landscape-genetic approach to identify landscape features that influence movement and connectivity for sharp-tailed grouse in Minnesota, where they have a regional stronghold. Feathers from leks and hunter wing submissions resulted in 367 individuals from the northwest (NW) and 84 from the east-central (EC) management regions. Both the NW and EC regions were genetically diverse and distinct, with high connectivity between them, although it is unclear whether this connection is contemporary or historical. Our analysis indicated that sharp-tailed grouse were structured across regions by land cover or by the amount of agriculture, grasslands, shrublands, and wet meadows on the larger landscape. Numerous long distance dispersal events were detected. Population clustering analysis indicated greatest support for two genetic clusters in the NW and three clusters in the EC region; however, mapping sample locations of individuals by assigned cluster revealed panmixia of clusters in the EC region. High genetic diversity, a low inbreeding coefficient, and significant excess in heterozygosity are consistent with a recent demographic compression or bottleneck in the EC region, and also consistent with surveys indicating a recent decline there. Sustained low population size or further declines would be expected to reduce genetic diversity. We recommend increasing grassland and shrubland quantity and quality to increase population size in the EC region soon.

Functional attributes of ungulate migration: landscape features facilitate movement and access to forage.

Long-distance migration by terrestrial mammals is a phenomenon critical to the persistence of populations, but such migrations are declining globally because of over-harvest, habitat loss, and movement barriers. Increasingly, there is a need to improve existing routes, mitigate route segments affected by anthropogenic disturbance, and in some instances, determine whether alternative routes are available. Using a hypothesis-driven approach, we identified landscape features associated with the primary functional attributes, stopovers and movement corridors, of spring migratory routes for mule deer in two study areas using resource selection functions. Patterns of selection for landscape attributes of movement corridors and stopovers mostly were similar; however, landscape features associated with movement corridors aligned better with areas that facilitated movement, whereas selection of stopovers was consistent with sites offering early access to spring forage. For movement corridors, deer selected for dry sites, low elevation, and low anthropogenic disturbance. For stopovers, deer selected for dry sites, with consistently early green-up across years, south-southwesterly aspects, low elevation, and low anthropogenic disturbance. Stopovers and movement corridors of a migratory route presumably promote different functions, but for a terrestrial migrant, patterns of habitat selection indicate that the same general habitat attributes may facilitate both movement and foraging in spring. Our findings emphasize the roles of topographical wetness, vegetation phenology, and anthropogenic disturbance in shaping use of the landscape during migration for this large herbivore. Avoiding human disturbance and tracking ephemeral forage resources appear to be a consistent pattern during migration, which reinforces the notion that movement during migration has a nutritional underpinning and disturbance potentially alters the net benefits of migration.

Climatic, topographic, and anthropogenic factors determine connectivity between current and future climate analogs in North America.

As climatic conditions shift in coming decades, persistence of many populations will depend on their ability to colonize habitat newly suitable for their climatic requirements. Opportunities for such range shifts may be limited unless areas that facilitate dispersal under climate change are identified and protected from land uses that impede movement. While many climate adaptation strategies focus on identifying refugia, this study is the first to characterize areas which merit protection for their role in promoting climate connectivity at a continental extent. We identified climate connectivity areas across North America by delineating paths between current climate types and their future analogs that avoided nonanalogous climates, and used centrality metrics to rank the contribution of each location to facilitating dispersal across the landscape. The distribution of connectivity areas was influenced by climatic and topographic factors at multiple spatial scales. Results were robust to uncertainty in the magnitude of future climate change arising from differing emissions scenarios and general circulation models, but sensitive to analysis extent and assumptions concerning dispersal behavior and maximum dispersal distance. Paths were funneled along north-south trending passes and valley systems and away from areas of novel and disappearing climates. Climate connectivity areas, where many potential dispersal paths overlapped, were distinct from refugia and thus poorly captured by many existing conservation strategies. Existing protected areas with high connectivity values were found in southern Mexico, the southwestern US, and western and arctic Canada and Alaska. Ecoregions within the Isthmus of Tehuantepec, Great Plains, eastern temperate forests, high Arctic, and western Canadian Cordillera hold important climate connectivity areas which merit increased conservation focus due to anthropogenic pressures or current low levels of protection. Our coarse-filter climate-type-based results complement and contextualize species-specific analyses and add a missing dimension to climate adaptation planning by identifying landscape features which promote connectivity among refugia.

Environmental factors affecting population level genetic divergence of the striped field mouse (Apodemus agrarius) in South Korea

The cognizing of connectivity among small mammal populations across heterogeneous landscapes is complicated due to complex influences of landscape and anthropogenic factors on gene flow. A landscape genetics approach offers inferences on how landscape features drive population structure. Through a landscape genetics approach, we investigated influences of geographical, environmental, and anthropogenic features on populations of Apodemus agrarius, the striped field mouse, the prime vector of hemorrhagic fever by a landscape genetic approach. We identified landscape features that might affect the population structure of striped field mice by analyzing microsatellite markers of 197 striped field mice from 21 populations throughout South Korea. We developed Maximum-likelihood population effects models based on landscape distances and resistance matrices and pairwise FST values for meta-populations of striped field mouse. We also conducted Mantel and partial Mantel tests to investigate geographic patterns of genetic similarities. In Mantel and partial Mantel tests, the FST was significantly correlated with all three models of movement; movement cost, Euclidian distance and least-cost distance, although the magnitudes of correlations varied. The 4 top-ranked models included three variables; temperature, precipitation and one human disturbance factor (population). We did not attain a significant effect for anthropogenic factors on genetic similarities among populations in the Korean striped field mouse, but we confirmed a significant association for genetic similarity with climatic features (temperature and precipitation).

Landscape features determining the occurrence of Rhagoletis mendax (Diptera: Tephritidae) flies in blueberries

Non-crop areas surrounding farms can support pest populations if they provide overwintering habitats or alternative hosts for them to feed and/or mate. Here we tested the hypothesis that a native North American pest of highbush blueberry, the blueberry maggot fly (Rhagoletis mendax Curran) is more abundant near forest habitats. For this, we monitored R. mendax adult occurrence using a trapping network across multiple farms and years (2009–2012) in New Jersey (USA), and then performed geospatial analysis on these data to determine whether traps in blueberry fields near forest habitats experience higher R. mendax adult captures than others. In addition, we conducted mark-release-recapture studies to determine the distance R. mendax flies can move into blueberry fields. Our results reveal that proximity to forest habitats positively affects R. mendax adult occurrence on traps. However, the type of forest was critical such that presence of flies on traps declined with increasing distance from upland forest while distance from wetland forest had no effect. We also showed that R. mendax flies can disperse up to 76 m into a blueberry field from adjacent wooded habitat within 48 h. In sum, our study identified landscape features important for R. mendax occurrence in blueberry fields, which can improve sampling methods and the development of precision-based pest management programs. Based on our findings, monitoring efforts and insecticide applications for R. mendax should be targeted mainly to fields close to upland forest and directed to the field borders within distances of less than 80 m from field edges.