High-quality Vegetation Research Articles

Identification of High-Quality Vegetation Areas in Hubei Province Based on an Optimized Vegetation Health Index

This research proposes an optimized method for identifying high-quality vegetation areas, with a focus on forest ecosystems, using an improved Vegetation Health Index (VHI). The study introduces the Land Cover Vegetation Health Index (LCVHI), which integrates the Vegetation Condition Index (VCI) and the Temperature Condition Index (TCI) with land cover data. Utilizing MODIS (Moderate Resolution Imaging Spectroradiometer) satellite imagery and Google Earth Engine (GEE), the study assesses the impact of land cover changes on vegetation health, with particular attention to forested areas. The application of the LCVHI demonstrates that forests exhibit a VHI approximately 25% higher than that of croplands, and wetlands show an 18% higher index compared to grasslands. Analysis of data from 2012 to 2022 in Hubei Province, China, reveals an overall upward trend in vegetation health, highlighting the effectiveness of environmental protection and forest management measures. Different land cover types, including forests, wetlands, and grasslands, significantly impact vegetation health, with forests and wetlands contributing most positively. These findings provide important scientific evidence for regional and global ecological management strategies, supporting the development of forest conservation policies and sustainable land use practices. The research results offer valuable insights into the effective management of regional ecological dynamics.

Transcriptome-wide m6A methylation profile reveals tissue specific regulatory networks in switchgrass (Panicum virgatum L.) under cadmium stress

The heavy metal cadmium (Cd), known for its high toxicity, poses a grave threat to human health through the food chain. N6-methyladenosine (m6A), the most abundant internal modification, regulates plant adaptation to various adversities, yet the panorama of m6A modifications in switchgrass under cadmium stress remains elusive. This study examines the physiological responses of switchgrass roots and shoots exposed to 50 μM CdCl2, alongside an overview of transcriptome-wide m6A methylation patterns. After cadmium treatment, methylation modifications are primarily enriched near stop codons and the 3′UTR region, with a negative correlation between m6A modification and gene expression levels. In shoots, approximately 58 % of DEGs with m6A modifications show upregulation in expression and decrease in m6A peaks, including zinc transporter 4-like (ZIP4). In roots, about 43 % of DEGs with m6A modifications exhibit downregulation in expression and increase in m6A peaks, such as the ABC transporter family member (ABCG25). We further validate the m6A enrichment, gene expression and mRNA stability of ZIP4 in response to Cd treatment. The results suggest that the negative correlation of m6A enrichment and gene expression is due to altered mRNA stability. Our study establishes an m6A regulatory network governing cadmium transport in switchgrass roots and shoots, offering new avenues for candidate gene manipulation in phytoremediation applications of heavy metal pollution.

Radiometric Improvement of Spectral Indices Using Multispectral Lightweight Sensors Onboard UAVs

Close-range remote sensing techniques employing multispectral sensors on unoccupied aerial vehicles (UAVs) offer both advantages and drawbacks in comparison to traditional remote sensing using satellite-mounted sensors. Close-range remote sensing techniques have been increasingly used in the field of precision agriculture. Planning the flight, including optimal flight altitudes, can enhance both geometric and temporal resolution, facilitating on-demand flights and the selection of the most suitable time of day for various applications. However, the main drawbacks stem from the lower quality of the sensors being used compared to satellites. Close-range sensors can capture spectral responses of plants from multiple viewpoints, mitigating satellite remote sensing challenges, such as atmospheric interference, while intensifying issues such as bidirectional reflectance distribution function (BRDF) effects due to diverse observation angles and morphological variances associated with flight altitude. This paper introduces a methodology for achieving high-quality vegetation indices under varied observation conditions, enhancing reflectance by selectively utilizing well-geometry vegetation pixels, while considering factors such as hotspot, occultation, and BRDF effects. A non-parametric ANOVA analysis demonstrates significant statistical differences between the proposed methodology and the commercial photogrammetric software AgiSoft Metashape, in a case study of a vineyard in Fuente-Alamo (Albacete, Spain). The BRDF model is expected to substantially improve vegetation index calculations in comparison to the methodologies used in satellite remote sensing and those used in close-range remote sensing.

Incorporating Environmental Variables Into Spatiotemporal Fusion Model to Reconstruct High-Quality Vegetation Index Data

Incorporating Environmental Variables Into Spatiotemporal Fusion Model to Reconstruct High-Quality Vegetation Index Data

66 Emerging Precision Ranching Technology Is Enabling the Development of a “smart” Biome

Abstract Precision ranching technology is revolutionizing remote data collection from livestock and the land base they depend on, greatly improving our ability to assess the entire biome. Remotely Piloted Aircraft System (RPAS or drone) based remote sensing to date has been used primarily to assess intensive cropping; but RPAS systems equipped with interchangeable cameras: high-resolution visual, thermal, LiDAR, and multi/hyperspectral imagers are now being deployed on rangelands, to monitor subtle changes in the visible, near infrared and infrared spectrums (radiation) that both plants and animals reflect. A single RPAS system can now be used simultaneously for high-quality vegetation mapping and behavioral analysis of animals, providing a suite of comprehensive data-collection tools for studying livestock in a variety of landscapes and rugged terrain. For example, we have used RPAS systems to measure behavioral and physiological indicators of cattle heat stress in feedlots and on pasture (Mufford et al., 2021). These same drones can be utilized for RPAS collection of high-resolution imagery (using multi/hyperspectral imagers and LiDAR) for vegetative and topographical mapping, greatly improving our ability to visualize and characterize habitat attributes such as forage availability, quality (stage of growth) and accessibility. Equipping cattle with new tracking technology, including "smart" GPS ear tags, rumen boluses, and wireless fencing collars (based on low-earth orbit satellites and cellular networks) enable animals to be readily identified and tracked on the landscape, while providing invaluable physiological data, such as internal body temperature to monitor estrous, heat stress, or the onset of disease (Figure 1). Additionally, rapid advances in wireless fencing systems have the potential to improve livestock management through autonomous mustering or the implementation of advanced rotational grazing for use in regenerative agriculture efforts. Wireless fencing may decrease production (infrastructure) costs, while also providing a strategy to better align forage demands with use, and thereby enhance pasture condition at the habitat and landscape level. Finally, non-invasive pasture weighing systems, enabled with or without RPAS technologies, are capable of monitoring key livestock production metrics year-round. Together, these technological advances enabled by this new "smart biome" will improve animal health and welfare while ultimately enhancing the sustainability of extensive livestock production systems.

Environmental variation across multiple spatial scales and temporal lags influences Hendra virus spillover

Abstract Pathogens can spill over and infect new host species by overcoming a series of ecological and biological barriers. Hendra virus (HeV) circulates in Australian flying foxes and provides a data‐rich study system for identifying environmental drivers underlying spillover events. The frequency of spillover events to horses has varied interannually since the virus was first discovered in 1994. These observations suggest that HeV spillover events are driven, in part, by environmental factors, including loss of flying fox habitat and climate variability. We explicitly examine the impact of environmental variation on the risk of HeV spillover at three spatial scales relevant to this system. We use a dataset of 60 spillover events and boosted regression tree methods to identify environmental features (including concurrent and lagged temperature, rainfall, vegetation indices, land cover, and climate indices) at three spatial scales (1‐km, 20‐km, 100‐km radii) associated with horse contacts and reservoir species ecology. We find that temperature, local (1‐km radius) human population density, and landscape (100‐km radius) forest cover and pasture are the most influential environmental features associated with HeV spillover risk. By including multiple spatial scales and temporal lags in environmental features, we can more accurately quantify risk across space and time than with models that use a single scale. For example, high quality vegetation at the local scale and within a foraging radius (20‐km) in the concurrent month and previous years, combined with poorer quality vegetation at the landscape scale in the concurrent month increase risk of HeV spillover. These and other environmental associations likely influence the dynamic foraging behaviour of reservoir flying foxes and drive contacts that facilitate spillover into horse populations. Synthesis and application: Current management of HeV spillover focuses on local‐scale interventions – primarily through vaccination and detection of infected horses. Our study finds that HeV spillover risk is also driven by environmental changes over much larger scales and demonstrates management practices would benefit from incorporating landscape interventions alongside local interventions.

Seasonal range fidelity of a megaherbivore in response to environmental change

For large herbivores living in highly dynamic environments, maintaining range fidelity has the potential to facilitate the exploitation of predictable resources while minimising energy expenditure. We evaluate this expectation by examining how the seasonal range fidelity of African elephants (Loxodonta africana) in the Kruger National Park, South Africa is affected by spatiotemporal variation in environmental conditions (vegetation quality, temperature, rainfall, and fire). Eight-years of GPS collar data were used to analyse the similarity in seasonal utilisation distributions for thirteen family groups. Elephants exhibited remarkable consistency in their seasonal range fidelity across the study with rainfall emerging as a key driver of space-use. Within years, high range fidelity from summer to autumn and from autumn to winter was driven by increased rainfall and the retention of high-quality vegetation. Across years, sequential autumn seasons demonstrated the lowest levels of range fidelity due to inter-annual variability in the wet to dry season transition, resulting in unpredictable resource availability. Understanding seasonal space use is important for determining the effects of future variability in environmental conditions on elephant populations, particularly when it comes to management interventions. Indeed, over the coming decades climate change is predicted to drive greater variability in rainfall and elevated temperatures in African savanna ecosystems. The impacts of climate change also present particular challenges for elephants living in fragmented or human-transformed habitats where the opportunity for seasonal range shifts are greatly constrained.

Characterization of Dry-Season Phenology in Tropical Forests by Reconstructing Cloud-Free Landsat Time Series

Fine-resolution satellite imagery is needed for characterizing dry-season phenology in tropical forests since many tropical forests are very spatially heterogeneous due to their diverse species and environmental background. However, fine-resolution satellite imagery, such as Landsat, has a 16-day revisit cycle that makes it hard to obtain a high-quality vegetation index time series due to persistent clouds in tropical regions. To solve this challenge, this study explored the feasibility of employing a series of advanced technologies for reconstructing a high-quality Landsat time series from 2005 to 2009 for detecting dry-season phenology in tropical forests; Puerto Rico was selected as a testbed. We combined bidirectional reflectance distribution function (BRDF) correction, cloud and shadow screening, and contaminated pixel interpolation to process the raw Landsat time series and developed a thresholding method to extract 15 phenology metrics. The cloud-masked and gap-filled reconstructed images were tested with simulated clouds. In addition, the derived phenology metrics for grassland and forest in the tropical dry forest zone of Puerto Rico were evaluated with ground observations from PhenoCam data and field plots. Results show that clouds and cloud shadows are more accurately detected than the Landsat cloud quality assessment (QA) band, and that data gaps resulting from those clouds and shadows can be accurately reconstructed (R2 = 0.89). In the tropical dry forest zone, the detected phenology dates (such as greenup, browndown, and dry-season length) generally agree with the PhenoCam observations (R2 = 0.69), and Landsat-based phenology is better than MODIS-based phenology for modeling aboveground biomass and leaf area index collected in field plots (plot size is roughly equivalent to a 3 × 3 Landsat pixels). This study suggests that the Landsat time series can be used to characterize the dry-season phenology of tropical forests after careful processing, which will help to improve our understanding of vegetation–climate interactions at fine scales in tropical forests.

Urban Vegetation Mapping from Aerial Imagery Using Explainable AI (XAI).

Urban vegetation mapping is critical in many applications, i.e., preserving biodiversity, maintaining ecological balance, and minimizing the urban heat island effect. It is still challenging to extract accurate vegetation covers from aerial imagery using traditional classification approaches, because urban vegetation categories have complex spatial structures and similar spectral properties. Deep neural networks (DNNs) have shown a significant improvement in remote sensing image classification outcomes during the last few years. These methods are promising in this domain, yet unreliable for various reasons, such as the use of irrelevant descriptor features in the building of the models and lack of quality in the labeled image. Explainable AI (XAI) can help us gain insight into these limits and, as a result, adjust the training dataset and model as needed. Thus, in this work, we explain how an explanation model called Shapley additive explanations (SHAP) can be utilized for interpreting the output of the DNN model that is designed for classifying vegetation covers. We want to not only produce high-quality vegetation maps, but also rank the input parameters and select appropriate features for classification. Therefore, we test our method on vegetation mapping from aerial imagery based on spectral and textural features. Texture features can help overcome the limitations of poor spectral resolution in aerial imagery for vegetation mapping. The model was capable of obtaining an overall accuracy (OA) of 94.44% for vegetation cover mapping. The conclusions derived from SHAP plots demonstrate the high contribution of features, such as Hue, Brightness, GLCM_Dissimilarity, GLCM_Homogeneity, and GLCM_Mean to the output of the proposed model for vegetation mapping. Therefore, the study indicates that existing vegetation mapping strategies based only on spectral characteristics are insufficient to appropriately classify vegetation covers.

17 Comparing Natural Vegetation and Food Plot Preference against Supplemental Protein Pellets in Captive White-tailed Deer (Odocoileus virginianus) and Exotic Species

Abstract Supplemental feed is the most expensive input in the captive wildlife industries. This is due to operations utilizing high-energy pellets as supplemental feed. Low fence operations often utilize food plots with high quality vegetation to minimize cost and increase forage availability for wildlife. The objective of this study was to determine forage preference of animals in captivity, and determine the most cost effective method of supplemental feeding. Seven food plots covering 25 acres contained one of three treatments. The treatments were: a commercial blend of soybeans; a commercial blend of soybeans, sunflowers, and milo; native/unplanted. Three utilization cages were set up to inhibit wildlife access to samples within each food plot to act as a control. Height of vegetative samples, inside and outside of the utilization cages, was collected on days 30, 60, and 90 after planting. The 30-d sample showed a preference of native/unplanted vegetation over the commercial treatments, P < 0.05. However, samples taken on days 60 and 90 showed the preference shifted toward the commercial blends, P < 0.05. This browsing preference indicates stage of maturity had an impact on plant selection. Regardless of sample date, the commercial blends showed a difference of P < 0.01, selecting the soybean blend more frequently. With an increased selection of the forages in the food plots, there was a decrease in cost of purchasing feed pellets with a total savings of approximately $5,500.00 from April 5-July 5, 2019. These results suggest that white-tailed deer and exotic species in captivity prefer forages compared to pelleted feed. Supplemental feeding programs that include food plots could allow for natural feeding tendencies, while being more cost effective for operations in the captive wildlife industries.

16 Comparing Natural Vegetation and Food Plot Preference against Supplemental Protein Pellets in Captive White-tailed Deer (Odocoileus virginianus) and Exotic Species

Abstract Supplemental feed is the most expensive input in the captive wildlife industries. This is due to operations utilizing high-energy pellets as supplemental feed. Low fence operations often utilize food plots with high quality vegetation to minimize cost and increase forage availability for wildlife. The objective of this study was to determine forage preference of animals in captivity, and determine the most cost effective method of supplemental feeding. Seven food plots covering 25 acres contained one of three treatments. The treatments were: a commercial blend of soybeans; a commercial blend of soybeans, sunflowers, and milo; native/unplanted. Three utilization cages were set up to inhibit wildlife access to samples within each food plot to act as a control. Height of vegetative samples, inside and outside of the utilization cages, was collected on days 30, 60, and 90 after planting. The 30-day sample showed a preference of native/unplanted vegetation over the commercial treatments, P < 0.05. However, samples taken on days 60 and 90 showed the preference shifted toward the commercial blends, P < 0.05. This browsing preference indicates stage of maturity had an impact on plant selection. Regardless of sample date, the commercial blends showed a difference of P < 0.01, selecting the soybean blend more frequently. With an increased selection of the forages in the food plots, there was a decrease in cost of purchasing feed pellets with a total savings of approximately $5,500.00 from April 5-July 5, 2019. These results suggest that white-tailed deer and exotic species in captivity prefer forages compared to pelleted feed. Supplemental feeding programs that include food plots could allow for natural feeding tendencies, while being more cost effective for operations in the captive wildlife industries.

Low-maintenance green tram tracks as a socially acceptable solution to greening a city

The creation of green tramways has become a common solution in many European cities in efforts to meet the increasing demands for green areas. However, maintaining high-quality vegetation requires costly maintenance. In this study, we assessed the possibility of managing green tram tracks in a manner that combines people’s attitudes with economic and ecological performance. We examined low-maintenance vegetation along existing tram tracks that has undergone natural succession to answer several specific questions. The aims of the present study include 1) assessment of how residents perceive the existing low-maintenance green tramways of various ages (1-11 years), 2) identification of measurable vegetation quality parameters affecting residents’ aesthetic preferences, and 3) assessment of whether viewing distance (from close up or from a distance) is a factor affecting residents’ perception of green tramways. Based on our results, green tramways were valued five times higher by residents than conventional tram tracks. Respondents indicated that the most important features of green tracks were vegetation coverage, with only a minority specifying factors such as uneven colour (33.9%) or the presence of weeds (7.1%). Perception also depended on turf age and biodiversity. Additionally, the greatest effect on the perception of tramways was the viewing perspective: as deficiencies in quality became less visible and were considered negligible, tramways were perceived 19% more favourably when viewed at a distance than when viewed close-up. The results of our research indicate that low-maintenance green tram tracks are an economically feasible solution for introducing more green areas into cities. Despite deficiencies in turf quality, this approach can become an accepted element of a city’s green infrastructure, and such a solution should be encouraged. Considering residents’ expectations, high-quality turf should be intensively maintained in only areas observed from a short distance.

STUDIES OF VOLUMETRIC RELATION BETWEEN VEGETATION AND BUILDINGS USING LIDAR DATA AND NDVI TO PROPOSE URBAN PARAMETERS

The availability of high-resolution cartographic data is a trigger for the discussion about the quality of urban ambiance, as a result of comparison between indexes of vegetation cover and built area, aiming at the inclusion of new urban parameters in cities' management and planning. This paper aims not only to provide visualization about location and characterization of the vegetation cover but also to the evaluation of its role according to citizens' perception of their value. Pampulha's region, in Belo Horizonte, was adopted as a case study for its high-quality vegetation cover, which has been threatened by the expressive growth of the built-up area. The area is known been projected by Oscar Niemeyer, using as a value the equilibrium between natural and built landscape, what was recently recognized as cultural heritage by UNESCO. Belo Horizonte municipality has the privilege of having LiDAR data of 2007 and 2015, the last one also with high resolution infrared orthophotos. The methodology consisted in mapping the vegetation patches' projections from orthophotos and in calculating their volumes using LiDAR's points, as well as in calculating the buildings' volume using their footprints and heights also from LiDAR data, and comparing their volumetric indexes per block. As indexes classifcation must have references on local culture, in order to defne the scale of "suitability", a research was done interviewing people from the place, using homogeneous areas as spatial units. As the research deals with quantitative approach (volumetric indexes) and qualitative approach (perception of people from the place), it was also important to use an evaluation according to a technical approach, based on comparison of applied indexes from other zones of Belo Horizonte, to present a wider perspective about standards of the relation between building landscape and vegetation. The result is a contribution to support discussions about urban ambiance, based on volumetric values of vegetation and buildings, to be considered in urban parameters in Master Plans.

No evidence for an elephant-termite feedback loop in Sand Forest, South Africa

Termites and mammalian herbivores might derive mutual benefit from each other through positive feedback loops, but empirical evidence is lacking. One suggested positive feedback loop is between termites and elephant, both ecosystem engineers. Termites, as decomposer organisms, contribute to nutrient cycling and soil enrichment, creating hotspots with increased forage quality. Elephant are known to select these high quality vegetation patches, depositing woody debris when foraging, but it is unknown whether elephant presence might affect termites, and if a feedback loop between these two taxa exists. We tested this hypothesis by measuring termite diversity and activity over three months in the summer wet season, inside and outside a long-term (eight years) elephant exclosure experiment in Sand Forest at Phinda Private Game Reserve, South Africa. Termites were sampled using cellulose baits and woody debris was quantified using line transects. Termite activity was not affected by eight years of elephant absence, despite a greater volume of woody debris where elephant were present. Termite assemblages were similarly unaffected by elephant absence. Apart from Schedorhinotermes, all other termite genera were sampled in both treatments. Therefore, the postulated positive feedback loop between termites and elephant is not supported in Sand Forest. However, this does not contradict findings that areas with high termite activity positively influence herbivore foraging, only that elephant foraging does not affect termite activity. This suggests that elephant disturbance (and elephant management policies) has little to no effect on termites and the fundamental roles they play in ecosystems over at least the short-term.

Using dynamic sustainability indicators to assess environmental policy measures in Biosphere Reserves

The assessment of different policy options represents a major tool for decision-makers in Biosphere Reserves, to develop more-resilient strategies for sustainable development and to visualise unintended consequences of these policies.In this work we analyse eight measures proposed by different agents in order to meet the main objectives of environmental sustainability, included in the Action Plan of the Fuerteventura Biosphere Reserve (Spain). We quantified the effects of these measures in terms of the sustainability thresholds of 10 environmental indicators, also proposed by the Action Plan, which was integrated in the Fuerteventura Biosphere Reserve dynamic model. Their behaviours under these measures allow determination of whether the objectives will be met in the period 2012–2025. Although some indicators would improve under these measures, fitting certain objectives, some negative effects on other indicators confirm the existence of trade-offs among these objectives. For instance, grazing limitation would improve the proportion of high-quality vegetation but would negatively affect the Egyptian vulture population, which would even fall below its sustainability threshold. The definition of thresholds for each indicator allows decision-makers to establish a way to prioritise among the eight measures analysed. The results show that these measures are insufficient to meet the sustainability thresholds of four indicators (the landscape indicator, the proportion of renewable energy, the per capita primary energy consumption and carbon dioxide emissions). Focusing on the remaining six indicators and following the rule “Threshold out, measure out”, seven out of the eight measures would exceed some thresholds and should be avoided. Only one option, aimed at growing fodder to feed cattle on restored traditional agricultural lands, would not exceed any of these thresholds. However, this measure also presents certain negative effects regarding indicators related to flagship species (the houbara habitat and the Egyptian vulture population), which would require compensation measures.

Taxonomic and Functional Resilience of Grasshoppers (Orthoptera, Caelifera) to Fire in South Brazilian Grasslands.

Fire is a frequent disturbance in grassland ecosystems enabling variability in habitat characteristics and creating important environmental filters for community assembly. Changes in vegetation have a large influence on herbivore insect assemblages. Here, we explored the responses of grasshoppers to disturbance by fire in grasslands of southern Brazil through a small-scale experiment based in paired control and burned plots. The resilience of grasshoppers was assessed by monitoring changes to their abundance, taxonomic, and functional parameters along time. Burned patches have been already recolonized by grasshoppers 1month after fire and did not differ in terms of abundance and richness from control areas in any evaluated time within 1year. Simpson diversity decreased 1month after fire due to the increased dominance of Dichroplus misionensis (Carbonell) and Orphulella punctata (De Geer). In this period, grasshoppers presented in average a smaller body and a larger relative head size; these are typically nymph characteristics, which are possibly indicating a preference of juveniles for the young high-quality vegetation, or a diminished vulnerability to predation in open areas. Further, at 6months after fire grasshoppers with smaller relative hind femur and thus lower dispersal ability seemed to be benefitted in burned patches. Finally, 1year after fire grasshoppers became more similar to each other in relation to their set of traits. This study demonstrates how taxonomic and functional aspects of grasshopper assemblages can be complementary tools to understand their responses to environmental change.

Agroecological characteristics of Lucerne cultivation in the conditions of Steppe zone

This article is devoted to the impact of wide-seeding methods of sowing with minimum norm of alfalfa varieties «Nadiya» seeding on the formation of high-quality vegetation. Level of pollination and seed performance are determined in the conditions of the steppe zone of Ukraine. Experimental studies show that in order to create qualitative and sparse grass during the formation of seed sowing alfalfa crop is necessary to lay sowing with wide rows 140 cm with a minimum rate of 0.25 million units/ha of certified seeds. It is also set that the wide-row sowing 140 cm and 210 cm influences positively on the level of pollination, formation of flowers per inflorescence and a lot of alfalfa seed. It has been determined that one of the main pollinators of alfalfa were the most active bees Rhophitoides canus, Melitta leporina, Melliturga clavicornis, which in conventional technology worked not actively. The best conditions for wild bees are in wide-row sowing with row spacing of 140 cm. This method of sowing is a new and effective element of the technology of growing alfalfa for seeds in the southern Steppe of Ukraine.

Dynamic integration of sustainability indicators in insular socio-ecological systems

The sustainability assessment on socio-ecological systems requires a systemic perspective in order to address the close relationships between the environmental and socio-economic processes. This need is especially urgent in the case of arid insular systems where limiting factors, as land and water resources, are more evident. The hyperarid island of Fuerteventura (The Canary Islands, Spain) represents a challenging case due to the need for compatibilizing the rising tourist development with the sustainable management of its natural resources, highly vulnerable due to processes such as the degradation of natural habitats – which hosts endemic and endangered species – or the high dependence of allocthonous energy sources for basic processes, including water supply.In this work we present an integral dynamic model, the Fuerteventura sustainability model (FSM), tested and calibrated for 1996–2011 period. The FSM allows to understand the main components of this socio-ecological system and their changes along time, as well as the interaction between the included sustainability indicators and other factors within the system. Results have shown the existence of potential trade-offs not only between socioeconomic development and conservation options, but also between sustainability goals under different management options. The conservation of the Houbara habitat might require the elimination of traditional agro-systems restoration plans, although these agro-systems offer important environmental functions. Besides, a reduction of cattle herd in order to control the degradation of high quality vegetation might negatively affect the endangered population of scavengers on the island. The water–energy binomial offers another trade-off regarding sustainable development, due to the strong dependency of the water availability on energy consumption. In this sense, the FSM has shown to be a useful tool to improve the comprehensive diagnosis of the system and to identify trade-offs between sustainability indicators to orientate management policies for this insular socio-ecological system.

Determinants of pika population density vs. occupancy in the Southern Rocky Mountains.

Species distributions are responding rapidly to global change. While correlative studies of local extinction have been vital to understanding the ecological impacts of global change, more mechanistic lines of inquiry are needed for enhanced forecasting. The current study assesses whether the predictors of local extinction also explain population density for a species apparently impacted by climate change. We tested a suite of climatic and habitat metrics as predictors of American pika (Ochotona princeps) relative population density in the Southern Rocky Mountains, USA. Population density was indexed as the density of pika latrine sites. Negative binomial regression and AICc showed that the best predictors of pika latrine density were patch area followed by two measures of vegetation quality: the diversity and relative cover of forbs. In contrast with previous studies of habitat occupancy in the Southern Rockies, climatic factors were not among the top predictors of latrine density. Populations may be buffered from decline and ultimately from extirpation at sites with high-quality vegetation. Conversely, populations at highest risk for declining density and extirpation are likely to be those in sites with poor-quality vegetation.

Habitat use by the Persian onager, Equus hemionus onager (Perissodactyla: Equidae) in Qatrouyeh National Park, Fars, Iran

Iran’s Persian onager populations are critically endangered. This study of their natural history in Qatrouyeh National Park provides insights for enhancing their conservation. The population as a whole is greatly affected by weather. Wind, rain and cold drive populations from the plains to the valleys of hill-valley habitats. Vegetation features and water also influence habitat use, but differently for different sex and reproductive classes. Females with juveniles use plains with high-quality vegetation, whereas females without young and solitary territorial males choose those of intermediate quality. Females with young foals are also found closest to watering points. Future translocation of Persian onagers will only succeed if prospective habitats have sufficient hill-valley refuges and enough plains with winds to moderately hot conditions. Sufficient plains supporting high-quality vegetation near water for lactating females must co-exist with plains of moderate-quality vegetation that attract females without young, so reducing crowding and competition.