Preferred Vegetation Research Articles

Perception of the Vegetation Elements of Urban Green Spaces with a Focus on Flower Beds.

Urban vegetation plays a crucial role in meeting the challenges posed by rapid urbanization and climate change. The presence of plants and green spaces in urban areas provides a variety of environmental, social, and economic benefits. Understanding how users perceive ornamental plants in public green spaces and what their preferences are for certain vegetation elements is extremely important for planning and designing functional and aesthetically interesting urban landscapes. Although landscape experts sometimes use their creativity to create new trends, it is important not to ignore the attitudes and preferences of the public, who sometimes have a different opinion from that of the experts. The aim of the study was to determine the perceptions and preferences of the public and landscape experts for different vegetation elements and the differences in attitudes between these two groups. The study was conducted in Croatia in April 2012 using an online survey (n = 348). The results showed that trees were the most preferred vegetation element and that the public preferred flower beds and lawns to a greater extent than the professionals. All respondents perceived vegetation elements as volumes (trees, shrubs, and hedges) and plains (flower beds and lawns). In addition, respondents perceived two basic types of flower beds according to the features that characterize them: conventional and sustainable. The results show that users perceive the functional and spatial characteristics of the different vegetation elements, which is very important for the design of functional and sustainable urban green spaces.

Dispersal‐related plant traits are associated with range size in the Atlantic Forest

AbstractAimThe efficiency of animal‐mediated seed dispersal is threatened by the decline of animal populations, especially in tropical forests. We hypothesise that large‐seeded plants with animal‐mediated dispersal tend to have limited geographic ranges and face an increased risk of extinction due to the potential decline in seed dispersal by large‐bodied fruit‐eating and seed‐dispersing animals (frugivores).LocationAtlantic Forest, Brazil, South America.TaxonAngiosperms.MethodsFirst, we collected dispersal‐related traits (dispersal syndrome, fruit size, and seed size), growth form (tree, climber, and other) and preferred vegetation type (open and closed) data for 1052 Atlantic Forest plant species. Next, we integrated these with occurrence records, extinction risk assessments, and phylogenetic trees. Finally, we performed phylogenetic generalised least squares regressions to test the direct and interactive effects of dispersal‐related traits and vegetation type on geographical range size.ResultsLarge‐seeded species had smaller range sizes than small‐seeded species, but only for species with animal‐mediated dispersal, not for those dispersed by abiotic mechanisms. However, plants with abiotic dispersal had overall smaller range sizes than plants with animal‐mediated dispersal. Furthermore, we found that species restricted to forests had smaller ranges than those occurring in open or mixed vegetation. Finally, at least 29% of the Atlantic Forest flora is threatened by extinction, but this was not related to plant dispersal syndromes.Main ConclusionsLarge‐seeded plants with animal‐mediated dispersal may be suffering from dispersal limitation, potentially due to past and ongoing defaunation of large‐bodied frugivores, leading to small range sizes. Other factors, such as deforestation and fragmentation, will probably modulate the effects of dispersal on range size, and ultimately extinction. Our study sheds light on the relationship between plant traits, mutualistic interactions, and distribution that are key to the functioning of tropical forests.

Assessing hurricane impact on vegetation and endangered deer habitat using airborne lidar and multispectral images

In the lower Florida Keys, the endangered Florida Key deer and numerous other wildlife species inhabit a vulnerable island environment susceptible to storm surges and rising seawater due to low elevation and flat terrain. Timely and reliable assessment of vegetation damage from natural disasters, such as Hurricane Irma, is crucial for effective habitat management. The study’s overall objective is to examine Hurricane Irma’s impact on vegetation on No Name Key, Florida, using remote sensing. The study relates the area change in vegetation obtained from remote sensing analysis to Florida Key deer population changes following the storm. The methodology involved performing a thematic change detection analysis using the following data sources: (1) aerial multispectral images (for pre- and post-Hurricane), (2) airborne lidar data (for pre- and post-Hurricane), (3) an existing vegetation map, and (4) soil data. A Support Vector Machine (SVM) image classification algorithm was applied to pre- and post-storm input image stacks to create pre- and post-Hurricane Irma vegetation maps. We were then able to obtain the area change information (for various vegetation categories) by performing the change detection analysis of the 2 SVM-classified images. The differences in areas following the storm were calculated for 7 affected vegetation types. Using the area change information following Hurricane Irma, we estimated the number of deer supported by the storm-affected vegetation. These estimated deer numbers, based on the area differences in post-Hurricane Irma vegetation types, were compared to observed deer numbers collected during the post-Hurricane Irma Texas A&M Natural Resources Institute (NRI) deer field survey. The results showed the following: mangroves had the largest negative area changes (area loss), followed by pinelands, hardwoods/hammocks, developed areas, and buttonwoods. Freshwater marshes had the largest positive area changes (area gain). The deer's preferred vegetation areas had decreased post-Hurricane Irma, resulting in a reduced deer population compared to pre-storm numbers. The predicted number of the Key deer post-Hurricane Irma fell within a 95% confidence interval of the observed deer population from the post-storm field survey. The study findings and techniques could be applied to study climate change impact, especially sea level rise. This methodology can be valuable in assessing the impact of storms on other wildlife species in similar environments. The applications and methodology are especially relevant considering the increasing frequency and intensity of storm surges and the accelerating rate of sea level rise.

Cherry Tree Crown Extraction Using Machine Learning Based on Images from UAVs

Remote sensing stands out as one of the most widely used operations in the field. In this research area, UAVs offer full coverage of large cultivation areas in a few minutes and provide orthomosaic images with valuable information based on multispectral cameras. Especially for orchards, it is helpful to isolate each tree and then calculate the preferred vegetation indices separately. Thus, tree detection and crown extraction is another important research area in the domain of Smart Farming. In this paper, we propose an innovative tree detection method based on machine learning, designed to isolate each individual tree in an orchard. First, we evaluate the effectiveness of Detectron2 and YOLOv8 object detection algorithms in identifying individual trees and generating corresponding masks. Both algorithms yield satisfactory results in cherry tree detection, with the best F1-Score up to 94.85%. In the second stage, we apply a method based on OTSU thresholding to improve the provided masks and precisely cover the crowns of the detected trees. The proposed method achieves 85.30% on IoU while Detectron2 gives 79.83% and YOLOv8 has 75.36%. Our work uses cherry trees, but it is easy to apply to any other tree species. We believe that our approach will be a key factor in enabling health monitoring for each individual tree.

Modelling Red-Crowned Parrot (Psittaciformes: Amazona viridigenalis [Cassin, 1853]) distributions in the Rio Grande Valley of Texas using elevation and vegetation indices and their derivatives.

Texas Rio Grande Valley Red-crowned Parrots (Psittaciformes: Amazona viridigenalis [Cassin, 1853]) primarily occupy vegetated urban rather than natural areas. We investigated the utility of raw vegetation indices and their derivatives as well as elevation in modelling the Red-crowned parrot's general use, nest site, and roost site habitat distributions. A feature selection algorithm was employed to create and select an ensemble of fine-scale, top-ranked MaxEnt models from optimally-sized, decorrelated subsets of four to seven of 199 potential variables. Variables were ranked post hoc by frequency of appearance and mean permutation importance in top-ranked models. Our ensemble models accurately predicted the three distributions of interest ([Formula: see text] Area Under the Curve [AUC] = 0.904-0.969). Top-ranked variables for different habitat distribution models included: (a) general use-percent cover of preferred ranges of entropy texture of Normalized Difference Vegetation Index (NDVI) values, entropy and contrast textures of NDVI, and elevation; (b) nest site-entropy textures of NDVI and Green-Blue NDVI, and percent cover of preferred range of entropy texture of NDVI values; (c) roost site-percent cover of preferred ranges of entropy texture of NDVI values, contrast texture of NDVI, and entropy texture of Green-Red Normalized Difference Index. Texas Rio Grande Valley Red-crowned Parrot presence was associated with urban areas with high heterogeneity and randomness in the distribution of vegetation and/or its characteristics (e.g., arrangement, type, structure). Maintaining existing preferred vegetation types and incorporating them into new developments should support the persistence of Red-crowned Parrots in southern Texas.

Differentiation characteristics of karst vegetation resilience and its response to climate and ecological restoration projects

AbstractIn light of the recent pressure from global warming, extreme drought events, and deleterious human activity, the strength and long‐term change trends of vegetation in karst regions—in terms of their resistance to external disturbances—have not been studied systematically. Therefore, herein, we quantified the vegetation resilience and its nonlinear change trends in south China karst under different environmental gradients by measuring the lag‐1 autocorrelation to time‐series Normalized Difference Vegetation Index (1990–2018), clarifying the driving forces of vegetation resilience changes. It was shown that the vegetation resilience change in south China karst was not monotonous. In the first stage (pre‐2002), precipitation and warming promoted the increase of regional vegetation resilience (slope = −0.045, p < 0.0001). In the second stage (during 2002–2010), the increasing trend of vegetation resilience was not obvious and vegetation resilience was difficult to keep up with vegetation productivity, indicating the time‐lagged effect of ecological restoration projects to vegetation resilience. In the third stage (post‐2010), due to the continuous advancement of ecological restoration projects, vegetation resilience increased significantly and had the largest amplitude (slope = −0.128, p < 0.0001). Simultaneously, under different environmental gradients, vegetation resilience showed significant differentiation characteristics. In comparison to non‐karst regions, increases in the vegetation resilience were more obvious in karst regions especially in the post‐2010. With increases in the soil depth, the vegetation resilience exhibited an increasing trend, indicating its dependence on soil. At slopes >25°, the vegetation resilience increased most obviously and the resilience of meadows was the largest, which can be the preferred vegetation type for ecological restoration projects. This research provides another perspective to understand karst vegetation ecosystem and the results will facilitate the protection of karst ecosystems.

Anchoring grassland sustainability with a nature-based small burrowing mammal control strategy.

Over the last 40 years, a burrowing mammal eradication policy has been prevalent on the Qinghai-Tibetan Plateau (QTP). This policy is based on similar burrowing mammal eradication programs in other areas and is justified on the assumptions that burrowing mammals compete with livestock for forage and contribute to grassland degradation. However, there is no clear theoretical or experimental evidence supporting these assumptions. This paper synthesizes the ecological functioning of small burrowing mammals in natural grasslands and discusses the irrationality and consequences of burrowing mammal eradication for sustainable livestock grazing and grassland degradation. Past burrowing mammal eradication efforts have failed because increased food availability for the remaining rodents and reduced predator populations led to rapid population rebounds. Herbivores differ in diet, and there is clear evidence that burrowing mammals, especially plateau zokors Myospalax baileyi, have a different diet than livestock. In QTP meadows, burrowing mammal eradication induces a shift towards plant communities with fewer species preferred by livestock and more species preferred by burrowing mammals. Thus, eradicating burrowing mammals has the opposite effect, a reduction in livestock preferred vegetation. We suggest that the policy of poisoning burrowing mammals needs to be reconsidered and revoked as soon as possible. We argue that incorporating density-dependent factors such as predation and food availability are essential for maintaining a low burrowing mammal density. For degraded grasslands, we suggest that the optimal sustainable approach is to decrease the intensity of livestock grazing. Lower grazing induces changes in vegetation structure and plant species composition that increases predation on burrowing mammals and decreases the abundance of plants preferred by burrowing mammals. Such a nature-based grassland management system maintains the density of burrowing mammals at a low stable density while minimizing human management and interventions.

Research on Grape-Planting Structure Perception Method Based on Unmanned Aerial Vehicle Multispectral Images in the Field

In order to accurately obtain the distribution of large-field grape-planting sites and their planting information in complex environments, the unmanned aerial vehicle (UAV) multispectral image semantic segmentation model based on improved DeepLabV3+ is used to solve the problem that large-field grapes in complex environments are affected by factors such as scattered planting sites and complex background environment of planting sites, which makes the identification of planting areas less accurate and more difficult to manage. In this paper, firstly, the standard deviation (SD) and interband correlation of UAV multispectral images were calculated to obtain the best band combinations for large-field grape images, and five preferred texture features and two preferred vegetation indices were screened using color space transformation and grayscale coevolution matrix. Then, supervised classification methods, such as maximum likelihood (ML), random forest (RF), and support vector machine (SVM), unsupervised classification methods, such as the Iterative Self-organizing Data Analysis Techniques Algorithm (ISO DATA) model and an improved DeepLabV3+ model, are used to evaluate the accuracy of each model in combination with the field visual translation results to obtain the best classification model. Finally, the effectiveness of the classification features on the best model is verified. The results showed that among the four machine learning methods, SVM obtained the best overall classification accuracy of the model; the DeepLabV3+ deep learning scheme based on spectral information + texture + vegetation index + digital surface model (DSM) obtained the best accuracy of overall accuracy (OA) and frequency weight intersection over union (FW-IOU) of 87.48% and 83.23%, respectively, and the grape plantation area relative error of extraction was 1.9%. This collection scheme provides a research basis for accurate interpretation of the planting structure of large-field grapes.

Investigation into spatial distribution of Pangolin (Phataginus tetradactyla) In Mbe Mountain Corridor of Cross River National Park

Background: This study assessed the distribution of Pangolin (Phataginus tetradactyla) in Mbe Mountain Corridor of Cross River National Park with a view to estimate its spatial distribution, population structure and vegetation distribution for a period of four months (September to December 2020). Method: The sites were visited from 7.00 am- 10.00 am in the morning and 4.00pm to 6.00 pm in the evening. Data obtained were analyzed using descriptive statistics. Results: The spatial distribution of Pangolin (Phataginus tetradactyla) revealed that Obue trail had the highest percentage of 56.3%, follows by Mbe trail with 31.2% and the least was sighted in Mbep trail with 12.5%. The highest number of observations was recorded in the month of December with 9 sighting, followed by October with 3 observations while the month of September and November recorded 2 observations each. The sex distribution of pangolin revealed that females were the higher in the observations with 11 sighting than the male with only 5 observations. The populations structure of pangolin (P. tetradactyla) shows that sub-adult was the highest in observation (7) while adult and juvenile recorded 5 and 4 observations respectively. 56.3% of the observations were sighted at Diospyros mistiliformis vegetation, Terminalia superba with 31.2% while 12.5% were observed at Brachystegia eurycoma vegetation. P. tetradactyla were seen running more than feeding with sleeping being the least activity observed. Conclusion: The study revealed the presence of P. tetradactyla (Pangolin) in all the three trails in the study area. This study has confirmed the presence of Pangolin in Mbe Mountain Corridor of Cross River National Park and their preferred vegetation.

Forests have a higher soil C sequestration benefit due to lower C mineralization efficiency: Evidence from the central loess plateau case

Soil carbon (C) mineralization varies with vegetation restoration and plays an essential role in the soil C cycle. However, the response of soil C mineralization to different vegetation restoration types remains unclear. In this study, three vegetation restoration types for the restoration of cropland, namely forestland (Robinia pseudoacacia), shrubland (Caragana korshinskii), and grassland (Artemisia sacrorum and Stipa bungeana), were selected to determine how vegetation restoration types affect soil C mineralization. The vegetation in the assessed areas had been restored 20 years before this study. The results showed that vegetation restoration significantly increased soil CO2 efflux, whereas soil C mineralization efficiency (CME) decreased after cropland conversion. The lowest soil CO2 efflux and CME were observed in forestland, with the highest stable soil organic carbon (SOC) pool. Vegetation restoration significantly increased SOC and its C fraction stocks, and the variation in soil C fractions was regulated by vegetation restoration type. Soil microbial biomass carbon (MBC) and dissolved organic carbon (DOC) effectively reflected the variation in soil C mineralization and stability of the SOC pool, respectively. Soil CO2 efflux was controlled by litter biomass, macroaggregates, particulate organic C, MBC, and DOC, whereas CME was mainly influenced by aboveground biomass, pH, silt and clay content, macroaggregates and DOC. The study suggested that forestland should be selected as the preferred vegetation restoration type in the central Loess Plateau owing to its lower CME with similar C stocks.

Forage offering and seasonal intake comparisons to evaluate European rabbit threat in Nothofagus forests of southern Patagonia

BackgroundThe European rabbit (Oryctolagus cuniculus L. 1758) was introduced into different regions of the world, generating significant trade-offs that critically impacted native vegetation. Here, we evaluate the rabbit's forage intakes in three vegetation types (forests, shrublands, and grasslands) along the four seasons in a temperate forest landscape in Southern Patagonia and discuss the potential threats over native vegetation. We formulated the following questions: (i) what is the forage offer at each vegetation type? (ii) what is the rabbit's forage intake and how it varied across the seasons along the year? and (iii) which vegetation types and plant life forms were more used according to the rabbit's forage intakes?MethodsWe censused understory vegetation to characterize the forage offer at each vegetation type and determined seasonal dietary intakes using microhistological analysis of pellets. The plant species identified in the field were grouped according to life form classes (tree regeneration, shrubs, forbs, graminoids, orchids, ferns, bryophytes, and hemiparasites). Data were analysed through uni- and multi-variate analyses, determining relationships between forage offer and the rabbit's forage intakes.ResultsForage intakes revealed changes in plant life form consumption across vegetation types, where intake pressure was considerably different for tree regeneration (p = 0.001), graminoids (p = 0.001), and hemiparasites (p = 0.001). Besides, significant changes in consumption among seasons were detected for shrubs (p = 0.001), ferns (p = 0.030), and hemiparasites (p = 0.002). Although many species play an important role in the rabbit's forage intake networks (e.g., Chiliotrichum diffusum, Holcus lanatus), the strongest intake linkages were found in exotic grasses (e.g., Poa pratensis and Festuca sp.), native hemiparasites (e.g., Misodendrum sp.), native shrubs (e.g., Empetrum rubrum), and native trees (e.g., Nothofagus sp.). The summer and autumn seasons presented higher intake compared to the winter and spring seasons. Furthermore, hemiparasites intake (e.g., Misodendrum sp.) suggests that rabbits utilize different forage sources depending on the vegetation types.ConclusionsRabbits regularly inhabit the forest, even though it is not their preferred vegetation type to live. Rabbit management entails isolating regions that are more favourable to intake and emphasizing the year's season for rabbit control efforts.

Nesting habitats of free-ranging Indian peafowl, Pavo cristatus, revealed by sniffer dogs in Okinawa, Japan

The Indian peafowl, Pavo cristatus, is the largest of the pheasants and ground-nesting bird. Because this species was introduced in Okinawa, Japan about 40 years ago and is now increasingly recognized as a pest in the Yaeyama region, and the extermination of this species has been promoted for ecosystem conservation. It was thought that there is need to develop a method to reduce the peafowl population and dogs were trained to detect them. We faced two difficulties in developing sniffer dogs to detect peafowl nests as below; (i) it is difficult to obtain a sufficient number of eggs to train the detection dogs, (ii) another difficulty is that the nesting period of peahens and the preferred vegetation used for nesting in Okinawa have not been reported. At first, we screened and trained two dogs of Welsh Corgi Pembroke and one dog of Brittany Spaniel for peafowl nest detection dogs with peahen feathers instead of peahen eggs. These dogs demonstrated a 100% sensitivity rate and there were no false-positives of their precision test. In second step, display survey of peacock to predict the nesting period of peahen was conducted in Kohama (KHM) and Kuroshima (KRS) islands, and the earliest dates of trail displays were observed in late February between 2014 and 2019 in both Islands. We predicted that the eggs would begin hatching in early April. We surveyed peahen nests for a total of 837 h and 1153 km on 962 transects with sniffer dogs and detected 423 peahen’s nests in KHM and KRS islands between 2014 and 2019. Peahens made her nests mainly in Poaceae or Asteraceae plants in research areas. The peak hatching was between mid-April and early May. In this study, we were able to detect peahen nests in the field by dogs trained with peahen feather, and we also identified the exact nesting season and preferred vegetation in Okinawa to control of Indian peafowl as an invasive species.

Roosting patterns of House Sparrow Passer domesticus Linn., 1758 (Aves: Passeridae) in Bhavnagar, Gujarat, India

The House Sparrow Passer domesticus is widely distributed across the world, and local alarming declines in sparrow populations have prompted studies focused on this species. An understanding of fundamental life history aspects such as roosting patterns is necessary for the development of efficient conservation strategies. This study examined House Sparrow roosting patterns in urban, suburban and rural areas of Bhavnagar during 2017–2018. Potential roosting sites were identified, and peak arrival/ departure times and roosting duration of sparrows were recorded. We found that peak arrival and departure times were correlated with solar timings, indicating a strong influence of photoperiod on sparrow behaviour. Little variation was observed in sparrow arrival and departure times across the urban, suburban and rural gradient. However, arrival duration was significantly larger in urban and suburban areas. This may be due to the restricted availability of suitable patches within these habitats, requiring birds to spend more time foraging. House Sparrows mostly preferred thick vegetation for pre-roosting activities and roosting, and the loss of thick vegetation poses a threat to sparrow populations worldwide. In addition to increasing nesting opportunities by providing artificial nest sites, the importance of retaining appropriate habitats should be a major focus of conservation strategies.

Specialization directs habitat selection responses to a top predator in semiaquatic but not aquatic taxa

Habitat selectivity has become an increasingly acknowledged mechanism shaping the structure of freshwater communities; however, most studies have focused on the effect of predators and competitors, neglecting habitat complexity and specialization. In this study, we examined the habitat selection of semiaquatic (amphibians: Bufonidae; odonates: Libellulidae) and aquatic organisms (true bugs: Notonectidae; diving beetles: Dytiscidae). From each family, we selected one habitat generalist species able to coexist with fish (Bufo bufo, Sympetrum sanguineum, Notonecta glauca, Dytiscus marginalis) and one species specialized in fishless habitats (Bufotes viridis, Sympetrum danae, Notonecta obliqua, Acilius sulcatus). In a mesocosm experiment, we quantified habitat selection decisions in response to the non-consumptive presence of fish (Carassius auratus) and vegetation structure mimicking different successional stages of aquatic habitats (no macrophytes; submerged and floating macrophytes; submerged, floating, and littoral-emergent macrophytes). No congruence between habitat specialists and generalists was observed, but a similar response to fish and vegetation structure defined both semiaquatic and aquatic organisms. While semiaquatic generalists did not distinguish between fish and fishless pools, specialists avoided fish-occupied pools and had a preferred vegetation structure. In aquatic taxa, predator presence affected habitat selection only in combination with vegetation structure, and all species preferred fishless pools with floating and submerged macrophytes. Fish presence triggered avoidance only in the generalist bug N. glauca. Our results highlight the significance of habitat selectivity for structuring freshwater ecosystems and illustrate how habitat selection responses to a top predator are dictated by specialization and life history.

On the impact of earthquake-induced landslides on Red Panda Ailurus fulgens (Mammalia: Carnivora: Ailuridae) habitat in Langtang National Park, Nepal

In addition to the threats of human encroachment, infrastructure development, tourism activities, habitat fragmentation, and human-wildlife interactions, natural disasters also pose a threat to the habitat of endangered species such as the Red Panda. This study aims to assess the impact of the 2015 Gorkha earthquake-induced landslides on the Red Panda’s habitat in Langtang National Park (LNP), central Nepal Himalaya. Remote sensing and geographical information system were applied to estimate the potential and core habitats of the Red Panda, and collect information on earthquake-induced landslides. Field sampling and verification of remotely collected data were done within a year of the earthquake. Considering preferred vegetation types, elevation range, aspects, distance from water sources, and Red Panda presence points, an area of 214.34 km2 was estimated as the potential habitat of Red Panda in the Park. Thirty-nine landslides were identified in LNP triggered by the Gorkha earthquake, 14 of which occurred in the core Red Panda habitat. As a result of the earthquake-induced landslides, a significant decrease in tree density was observed in the areas affected by the landslides. Similarly, the bamboo cover was observed to be significantly lower in the areas affected by landslides compared to the unaffected adjacent areas. The average size of the landslide, causing damage to the Red Panda habitat was 0.8 ha. The potential habitat damaged by the earthquake-induced landslide was estimated to be 11.20 ha which is equivalent to the habitat required by one Red Panda. The findings could be useful in initiating restoration of the damaged Red Panda habitat in LNP.

The benefit and strategy of spring movements in Mongolian gazelles

Abstract Animal movement is predicted to be nomadic in areas with low temporal predictability of environmental conditions, but it remains unclear whether the costs of nomadic movement outweigh the benefits received. To examine the spring movement strategy of Mongolian gazelles (Procapra gutturosa) in Mongolia, where predictability of vegetation conditions is relatively low, we identified the type of each movement, evaluated the preferred vegetation conditions for gazelles, and quantified the benefit achieved through each spring movement. The surveyed gazelles continuously preferred areas with intermediate normalized difference vegetation index (NDVI) values from May to July, and spatial and temporal shifts of the distribution of preferred areas explain the long-distance movements of many gazelles in spring. Three movement types, sedentary, linear, and nomadic movement, were identified. The period when benefit varied most greatly among individuals differed between the linear and nomadic movement types. During the spring movement period, the variance of benefit was larger for the nomadic movement type, whereas during the summer it was larger for the linear movement type, suggesting the existence of different movement strategies in the Mongolian gazelle. Linear long-distance movements over a short period in the linear movement type suggest the so-called jumper strategy, whereas other movement patterns might represent the searcher strategy. Benefit loss through movements of individuals in both strategies indicate low interannual predictability of vegetation conditions in the study area, and it would explain the co-existence of multiple movement types or strategies used by Mongolian gazelles in spring.

Habitat choices of African buffalo (Syncerus caffer) and plains zebra (Equus quagga) in a heterogeneous protected area

Abstract ContextAn understanding of large herbivore habitat choices in heterogeneous African protected areas is important for the better management of these key ecosystems. AimsTo determine habitat use of African buffalo (Syncerus caffer) and plains zebra (Equus quagga) in a heterogeneous protected area. MethodsZambezi National Park (ZNP), Zimbabwe, was divided into five vegetation types using an unsupervised classification on a Landsat satellite image that was classified into five land cover classes, using the K-means classification algorithm. African buffalo and plains zebra densities were then determined in each vegetation type using road transect surveys monthly between January 2013 and December 2015. Normalised difference vegetation index (NDVI), grass biomass, grass height and grass quality (nitrogen, calcium, phosphorus and acid detergent fibre content) were determined in each vegetation type during the wet (November to April) and dry (August to October) seasons to establish their quality as habitats for African buffalo and plains zebra. Key resultsBoth African buffalo and plains zebra mostly foraged in mixed and grassland areas, and avoided Zambezi teak vegetation type. Zambezi teak vegetation type had high NDVI due to the dense tree cover. Both African buffalo and plains zebra preferred vegetation types with intermediate grass biomass (approximately 300gm−2) and grass height (approximately 16cm). Grass nutritive value (in terms of nitrogen, phosphorus and acid detergent fibre) declined from wet to dry season in all vegetation types. ConclusionsAfrican buffalo and plains zebra in the ZNP confined their habitat use mostly to two vegetation types (mixed and grassland), which together covered 25% of the protected area. ImplicationsTeak (Baikiaea plurijuga) vegetation, which accounted for about 60% of the ZNP, was avoided by both African buffalo and plains zebra, suggesting that a significant part of the protected area was not used by the two herbivores.

Does vegetation change over 28 years affect habitat use and reproductive success?

Abstract Individuals should prefer and use habitats that confer high fitness, but habitat use is not always adaptive. Vegetation in natural landscapes changes gradually and the ability of species to adaptively adjust their habitat use to long-term changes is largely unstudied. We studied nest patch and territory use over 28 yr in Orange-crowned Warblers (Oreothlypis celata) in a system that has undergone natural long-term changes in vegetation. Abundance of maple (Acer grandidentatum), its preferred nesting habitat, gradually declined from 1987 to 2015. We examined whether habitat use and its fitness consequences changed as the availability of preferred habitat decreased. We used resource selection function models to determine changes over time in the probability of using a nest patch given available patches, and the probability of using a territory given available territories. We estimated nest survival to evaluate changes over time in the fitness consequences of nest patch use. We also compared habitat use (nest patch and territory) and fitness (nest survival) between areas with naturally reduced abundance of maple and experimentally increased abundance of maple (fenced areas). Nest patch use depended on maple abundance and did not change drastically across 28 yr, even though the availability of preferred maple patches decreased over time. In contrast, nest survival tended to decrease over time. We did not see differences in nest patch use and nest survival between unfenced and fenced areas, unlike territory use, which increased with the abundance of maple in fenced areas and decreased in unfenced areas. Our study depicts one example of relatively unchanged habitat use in the face of decreased availability of preferred vegetation across years, with a resulting decrease in reproductive success. Investigating changes in habitat use and fitness consequences for animals exposed to long-term habitat change is necessary to understand adaptive behavioral responses.

Habitat Characteristics and Selection by Ornate Box Turtles in the Sandhills of South Dakota

The ornate box turtle (Terrapene ornata Agassiz) is a species of greatest conservation need in South Dakota. Habitat loss through agricultural development and fragmentation is the main threat to the species throughout its range, which extends from Wisconsin and northern Indiana through the central Great Plains, and from southern South Dakota to Arizona, northern Mexico, and the Gulf Coast of Texas. The objectives of this study were to determine the ornate box turtle's preferred vegetation characteristics (microhabitat) compared to the available habitat (macrohabitat) on the Pine Ridge Reservation, South Dakota Sandhills region, during 2010–2011. In both years, using a modified Robel pole method, we determined that turtles selected microhabitat with greater visual obstruction readings (VORs) than those within the random available macrohabitat (P < 0.01), with means of 22 cm and 15 cm, respectively. Higher VOR values indicate greater vegetation height and/or density. Canopy cover results showed that ornate box turtles exhibited high selection (P < 0.01) for sand sagebrush (Artemisia filifolia Torr.) coverage (38%) but selected lower cover than available within the macrohabitat for total grasses (37%), total forbs (19%), and bare ground (14%). Shrubs, such as sand sagebrush, are an important component of box turtle microhabitat, as they facilitate thermoregulation by providing cool areas during the summer and favorable hibernation sites during the winter. Shrub coverage is highly reco mmended for consideration when developing habitat management plans that aim to increase or sustain ornate box turtle populations in the Sandhills ecological type.

Autumn habitat selection of the harvest mouse (Micromys minutus Pallas, 1771) in a rural and fragmented landscape

The harvest mouse Micromys minutus has, through nest findings, been documented to live in wetlands in tall sedges and grasses in Central Europe. However, there is very little information on the type of habitat this species uses outside of nesting, because this rodent is difficult to capture in ordinary trapping set-ups. In France and Switzerland, the harvest mouse populations have decreased strongly in the past two centuries due to the drastic reduction of its favored habitat. The present study used radiotracking to examine a small population in Eastern France living in a fragmented rural landscape. The aim was to learn more about the habitat and vegetation selection of this population during autumn. The results showed that the most favored habitats were in patches of stinging nettles (Urtica dioica) and American goldenrod (Solidago gigantea) rather than in their supposedly preferred vegetation type, which are tall grass wetlands. The results also presented migrating behavior in three out of the eight monitored individuals, which lead to the discovery of a possible wintering area in an unmown grassy site around a plant dump. These results suggest that disturbed, but unmown areas are important for the harvest mouse as wintering vegetation and should be available in the surrounding of a reproduction site. The results also showed that wetland management must take into account the affinity of this mammal for areas invaded by American goldenrod, in order to prevent the harvest mouse populations from decreasing in those secondary habitats. (Less)