High-elevation Areas Research Articles

Agro-climatic Characterization of Potato Production Areas in Rwanda: Meteorological Data Analysis and Farmer Perceptions

From years ago, climate change effects are happening in different areas of the world, including Rwanda. Potato as one of main commodities grown mainly in the cooler and wetter highlands of Rwanda, its production could be facing the global warming. The purpose of this study is to carry out weather (temperature and rainfall) change dynamics in the potato growing zones of Rwanda over the last thirty years. Weather daily data from 1987 to 2016 were collected from three weather stations, at Kawangire for low elevation, at Gikongoro mid elevation, and at Kora high elevation, respectively. Farmers were interviewed to know their perceptions on weather conditions during past thirty years. Weather data were analyzed by ombrothermic diagram, Nickolson Index and graphing with generated trend equation methods. Interview data were analyzed with Chi-square test at P =.05. Results have shown as dry June, July and August months in low elevation; June, July and August in medium elevation and June and July in high elevation depending on decade. Rainfall was increasing in low and medium elevations, while it was decreasing in high elevation. Temperature was decreasing in low elevation area and it was increasing in medium and high elevation areas. All interviewed farmers confirmed long term-shift in temperature and precipitations. A total of 95%, 54% and 43% of farmers from respectively low, medium and high elevations reported that weather was becoming wetter during last years. As conclusion, potato growing cooler and wetter conditions of high elevation are shifting to low elevation in Rwanda. For climate change mitigation, Rwanda needs to promote potato in its Eastern part, the low elevation region, in order to increase the crop production in the future.

Genetic structure and population history of a peat swamp forest tree species, Shorea albida (Dipterocarpaceae), in Brunei Darussalam.

Southeast Asia supports high biodiversity, in a mosaic of forest types formed by the expansion and contraction of habitats through past climate changes. Among the region's forest types, the geographical distribution of peat swamp forests has fluctuated intensely over the past 120,000 years. Most peat swamp forests in Southeast Asia are found in coastal regions and formed within the last 7,000 years after a decline in sea level. However, some peat swamps were initiated earlier on substrates of slightly higher elevation, and these peat swamps might have been refugia for peat swamp species in the last glacial period and the high sea level period. We assessed genetic diversity, genetic structure and divergence time of current genetic groups for Shorea albida in Brunei, an endemic tree species of Bornean peat swamp forests, using 18 microsatellite markers. Genetic diversity was not lower than has been found in other Shorea species, possibly because of the high density of S. albida in Brunei. Although overall genetic divergence between populations was low, two populations (Ingei and Labi Road 3) were distinct from the other populations. Analysis using DIYABC estimated that three genetic groups (Ingei, Labi Road 3 and others) diverged simultaneously from their ancestral population, whose effective size was very small, about 7,500 years ago, corresponding to a recent sea level peak in the Belait-Baram river basin. In that high sea level period, some higher-elevation lands remained, and peat formation had already started in this region. We propose that the current genetic structure of S. albida in Brunei was formed from small refugial populations that survived the period of higher sea level in these higher-elevation areas. Because of their relatively high genetic diversity, Brunei's S. albida populations should become an important genetic resource for the recovery of genetically healthy populations in other parts of northwest Borneo.

A peculiar specimen of Panochthus (Xenarthra, Glyptodontidae) from the Eastern Cordillera, Bolivia

Panochthus Burmeister is one of the most diversified and widely distributed glyptodonts in the Pleistocene of South America, which includes areas located at high altitudes (>4,000 m a.s.l.). Within the genus, eight species (P. intermedius Lydekker, P. subintermedius Castellanos, P. tuberculatus (Owen), P. frenzelianus Ameghino, P. greslebini Castellanos, P. jaguaribensis Moreira, P. hipsilis Zurita, Zamorano, Scillato-Yané, Fidel, Iriondo and Gillette, and P. florensis Brambilla, López and Parent) are currently recognized. Here, we report a dorsal carapace (UATF-V n/n) from the Pleistocene of the surroundings of Potosí, Bolivia, that shows some morphological particularities when compared to the carapace of P. intermedius, P. frenzelianus, P. subintermedius and P. tuberculatus, including: a) its maximum dorso-ventral diameter is at the anterior half, meanwhile in other species is at mid-point (e.g., Propalaehoplophorus) or at posterior half (e.g., Glyptodon); b) the dorsal profile is different in comparison to other glyptodonts (e.g., Glyptodon, Glyptotherium, Neosclerocalyptus, Propalaehoplophorus); c) the ornamentation pattern of the osteoderms shows a central figure surrounded by small polygonal figures along the most exposed surface of the carapace (except for the mid-dorsal region that shows reticular ornamentation pattern), being different from that of the remaining species: of Panochthus, in which central figures are limited to the caudal/cephalic and most lateral regions of the carapace. In summary, the combination of characters suggests that it could belong to a new species or, alternatively, to P. floriensis or P. jaguaribensis in which the dorsal carapace is not yet known. The phylogenetic analysis confirms its basal position among Panochthus and highlights the importance of these high elevation areas of the Andes in South America in order to understand the complex evolutionary history of glyptodonts.

Landslide susceptibility assessment using the certainty factor and deep neural network

Areas with vulnerable ecological environments often breed many geological disasters, especially landslides, which pose a severe threat to the safety of people’s lives and property in these areas. To aid in landslide prevention and mitigation, an approach combining the coefficient of determination method (CF) and a deep neural network (DNN) were proposed in this study for landslide susceptibility evaluation. The deep neural network can excavate the deep features of samples and improve the accuracy of the susceptibility model. In addition, the logistic regression model (LRM) and support vector machine (SVM) were selected to create landslide susceptibility maps for comparison, which also involved the coefficient of determination method (CF). Based on landslide remote sensing interpretation and field investigations, a spatial database of mudstone landslides in the Xining area was established. Eight different conditional factors, including the elevation, slope, slope aspect, undulation, curvature, watershed, distance from a fault, and distance from a road, in the study area were selected as the evaluation factors to evaluate the susceptibility. The results revealed that four factors (i.e., the ground elevation, curvature, distance from a fault, and distance from a road) had relatively significant influences on the landslide susceptibility in the study area. Finally, the confusion matrix was used to evaluate the accuracy of the results obtained using the three methods, and the optimal result was selected to evaluate the landslide susceptibility in the study area. It was found that the combined CF-DNN method was more suitable for evaluating the landslide susceptibility in this area. Landslide susceptibility zoning was conducted to divide the study area into four sensitivity levels: low (32.65%), medium (35.12%), high (22.44%), and extremely high (9.79%) susceptibility. The high-risk areas were primarily distributed in the high-elevation areas along the eastern edge of the Huangshui Basin.

Tsunami Vulnerability Assessment and Multi-Criteria Decision Making Analysis of Eastern Coast of India Using GIS-Based Tools

The marine environment is a vital resource that sustains many people and a variety of ecosystems rich in biodiversity. However, coastal resources and human dwellings are exposed to natural calamities like tsunamis. This article explains a GIS-based multi-criteria study of tsunami exposure along India's eastern coast. Six geographical parameters were employed to determine the research area's vulnerability: elevation, slope, population density, coastal proximity, land use land cover (LULC), and flow accumulation. Additionally, the Analytic Hierarchy Process (A.H.P.) was used to weight the characteristics' criteria. Comparing the vulnerability map to the other parameter maps reveals that highly vulnerable locations are either densely populated or with lower surface elevation or agricultural. GIS-based analyses can assist in various disaster assessments and expedite regional planning for natural disaster prevention and response, like tsunamis. The tsunami susceptibility mapping is expected to aid in the initial stages of tsunami mitigation and management measures along the eastern coast of India in the case of a future tsunami. Moreover, connectivity and safe locations map with primary roads, secondary roads, railway routes, and possible safe locations (high elevation areas) is also mapped to ease the mitigation during an actual tsunami.

Salt marsh vegetation change during a half-century of experimental nutrient addition and climate-driven controls in Great Sippewissett Marsh

Vegetative cover was mapped annually, 1976–2022, in experimental plots in Great Sippewissett Marsh, Cape Cod, USA, chronically fertilized at different doses, and subject to changes in sea level and other climate-related variables. Dominant species within areas of higher elevation in the plots followed different decadal trajectories: rise in sea level diminished cover of Spartina patens; higher N supplies increased cover of Distichlis spicata. The opportunistic growth response of D. spicata to high N supplies unexpectedly fostered increased platform accretion, a feature that persisted for succeeding decades and led to further changes in vegetation: D. spicata functioned as an effective ecosystem engineer with long-term ecological consequences. Shrubs usually found in upper marsh margins expanded into areas where D. spicata had stimulated accretion, then shaded and excluded D. spicata, but subsequently lost cover as sea level rise continued. Increased N supply converted stands of Spartina alterniflora, the dominant low marsh species, from short to taller ecophenotypes; sea level rise had minor effects on S. alterniflora, but during 2019–2022 appeared to reach a tipping point that fostered taller S. alterniflora and bare space even in un-fertilized control plots, and in Great Sippewissett Marsh in general. Model results anticipate that—in spite of potential accretion enhanced by vegetation and ecosystem engineer effects—there will be loss of high marsh, transient increases of low marsh, followed by loss of low marsh, and eventual conversion to shallow open water by the end of the century. Dire local projections match those of the plurality of recent reports from salt marshes around the world. Proposed management strategies may only delay unfortunate outcomes rather than maintain wetlands. Concerted reductions of warming from greenhouse gases, and lower N loads seem necessary to address the coming crises in wetlands—and many other environmental threats.

Assessment of Topographic Effect on Habitat Quality in Mountainous Area Using InVEST Model

The topographic differentiation patterns of changes in habitat quality are of great significance for the scientific formulation of environmental protection policies in mountainous areas. Here, the distribution, changing trends, and the effects of the topographic gradient on habitat quality were studied using the InVEST model, the topographic distribution index, and the Mann–Kendall test. The results showed that at p < 0.05 (Z = 1.67), the habitat quality from 2000 to 2020 showed three types of trends (significant decline, non-significant change, and significant increase), accounting for 22.2%, 41.8%, and 36% of the changes, respectively. Because of the livelihood structure of the local residents and geological disasters in high-elevation areas, this terrain was the predominant area showing a significant decline in habitat quality. Thanks to the consolidation of projects for the protection of natural forest resources, the return of farmland to forest, and the implementation of projects for protecting the natural forest, the low-lying topography was the predominant area showing a significant increase in habitat quality. The middle topographic position was the predominant area showing no significant changes in habitat quality. Based on the results of the analysis, ecological management and protection measures for high-, medium-, and low-elevation areas were suggested.

Trade-offs across values in cesspool management highlight challenges to policy making

On-site Sewage Disposal Systems (OSDS) are globally common, and in Hawai'i they present a risk of contamination to drinking water sources and nearshore waters. State legislation has commanded that all cesspools are to be banned by 2050, thus requiring tens of thousands of systems to be converted in the coming decades. This project followed a participatory structured decision-making (SDM) approach to collaboratively design cost-effective and equitable solutions for thousands of cesspools in the high elevation areas of north Maui, Hawai'i. Participatory workshops with a diverse group of stakeholders set ten objectives and brainstormed 33 alternatives, for which the technical team then modeled groundwater nutrients, costs, and equity. All alternatives posed trade-offs, though composting toilets performed best across most objectives, albeit with high maintenance burden. Discounting innovative toilets, the multi-objective analysis suggests that the state should invest in cluster sewering of high-density communities, followed by incentivizing septic tank solutions in properties with the highest effluent flow first, then expanding across the area. The total project cost (installation and operation/maintenance) would be $183–258 million, depending upon the sewer-septic combination. An efficiency frontier reveals sub-par combinations, including aerobic treatment units and passive absorption systems, which cost much more and deliver lower mass flux reduction than more cost-effective alternatives. This study contributes a novel case of rural sanitation to the literature in which decision support tools are used to facilitate evidence-based, collaborative decision-making for sanitation planning. The state could use a similar participatory SDM process when approaching other communities to discuss their cesspool upgrade strategies. Broadening the use of decision analytic techniques can have wider ecological, economic, and social benefits for the state and contexts beyond Hawai'i, as SDM provides a transparent and rigorous, evidence-based decision-theoretic framework to explore multiple values and strategies to address difficult resource management problems.

Environmental heterogeneity determines beta diversity and species turnover for woody plants along an elevation gradient in subtropical forests of China.

To understand how diversity change with environmental gradients is a fundamental aim for clarifying biodiversity pattern and underlying mechanisms. Here, we studied the characteristics of beta diversity and its partitioning components for woody plant communities along an elevation gradient in subtropical forests of China, and thus explored the effects of environment and space on beta diversity. By using the Classification Method, we divided the species of Daiyun Mountain into four groups, namely generalists, high-elevation specialists, low-elevation specialists and rare species. We then calculated beta diversity, and partitioned it into species turnover and species nestedness. dbRDA was conducted to analyze the impact of spatial and environmental distance on the beta diversity and its partitioning components. Beta diversity comprised of two components: species turnover and species nestedness. Species turnover was the larger contributor to total beta diversity, and it tended to increase as elevation changed. This pattern can be attributed to environmental heterogeneity, resulting in the differentiation of specialized species and an increase in species turnover and beta diversity. Environmental factors, specifically the air temperature and slope, played a significant role in explaining the variation of turnover and beta diversity. However, spatial variables did not have a significant influence on these patterns. The maintenance of biodiversity in Daiyun Mountain was mainly governed by environmental filtering. Future conservation efforts should focus on strengthening the protection of specialized species in high elevation areas.

Reliable Sound Re-labeling Approach for Bird Sound Classification

Passive acoustic monitoring has become an effective and economically scalable solution for wildlife monitoring in recent years, especially for population monitoring of endangered birds in hardly accessible and high-elevation areas. As sound recorders are deployed on the field for extended periods (months), continuous sound streams are often complex in nature, with noises and intermittent signals. Generally, it is prohibitively expensive to label bird sounds with the exact onset and offset time, thus, during training, the data is often provided with only presence/absence labeling (weak labeling) that states which bird species are present in each long recording without temporal information. During test time, it is, however, desirable to provide fine-grained detection in short audio segments. To bridge the gap between the difference of weak labels used for training and strong labels used for testing, we propose a re-labeling approach with two stages: (1) we train a model with weak labeling; and (2) using the model obtained from stage 1, we generate labels for short audio segments and retrain the model on short audio segments with the newly generated labels. We applied our approach in both classification and sound event detection and achieved consistently good performance across multiple random seeds. In BirdCLEF 2022, our model ranked in the top 1.1%, the 9th best entry out of the total 807 entries in the competition.

SERVIÇOS ECOSSISTÊMICOS DE REGULAÇÃO EM UMA BACIA HIDROGRÁFICA NO SEMIÁRIDO DO BRASIL

Human pressures on ecosystems from the use and suppression of vegetation cover cause negative actions on biodiversity, impacting nature and the ecosystem services provided by the same. The focus of this research is to evaluate the ability to provide Ecosystem Services in the Seridó River Basin (RN / PB). Modeling techniques were applied from USLE, in addition to vegetation and organic carbon indices. The results showed that the highest values ​​of NDVI are in areas of higher elevation and slope, and the lowest values ​​found in flat areas. Six classes of land use were identified, namely: Water bodies, urban area, Pasture and exposed rock, Caatinga Subarbustiva, Subarbórea and Arbórea. As a result, the areas of greatest relevance for providing Organic Carbon stock services are in the highest areas, with the areas with the greatest erosion control located in escarpment areas. Key words: Ecosystem Services; Modeling; Caatinga; Semiarid; Hydrographic basin.

Trends and variability of rainfall characteristics influencing annual streamflow: A case study of southeast Australia

AbstractThe trend and variability in rainfall characteristics that influence annual streamflow of southeast Australia is assessed using two methods, non‐parametric Kendall test and linear slope, and two gridded daily rainfall datasets (SILO and AWAP) and 1,196 station rainfall data for 1971–2021 period. The rainfall anomaly before, during and after the Millennium Drought (1997–2009) is compared to quantify the variability. The results show: (a) a declining rainfall trend is detected as the recent dry decades were preceded by wet decades. The declining trend largely occurs from autumn through to spring with the largest trend in August to October followed by April and May; (b) the trend is more significant for number of rainfall days and for multi‐day rainfall totals (and more so for longer accumulations) than for annual rainfall; (c) the very high extreme rainfall shows a small increasing trend in summer and mixed signal in the other seasons; (d) the streamflow in the post drought period is lower than the long‐term mean, despite the mean annual rainfall being slightly higher. This can be partly explained by the rainfall‐runoff relationship of catchments not having fully recovered from the prolonged drought and partly by changes in rainfall characteristics, like the wet spell length and multi‐day rainfall, influencing annual streamflow; (e) The general conclusions for analyses with different sources of daily rainfall data are the same. However, some differences do exist, with SILO gridded rainfall and station data having larger areas with statistically significant trend than the AWAP gridded rainfall, as well as larger declining trends in the high elevation areas. The general conclusions of this study are drawn from an Australia case study but could have implications for other regions to investigate the attributions of rainfall characteristics other than annual rainfall to the non‐stationary rainfall‐streamflow relationship.

Patch-level processes of vegetation underlying site-level restoration patterns in a megatidal salt marsh

Vegetation patterns during salt marsh restoration reflect underlying processes related to colonization, reproduction, and interactions of halotolerant plants. Examining both pattern and process during recovery is valuable for understanding and managing salt marsh restoration projects. We present a decade of vegetation dynamics during salt marsh restoration (2011–2020) at a study site in the Bay of Fundy with megatidal amplitudes, strong currents, cold winter temperatures, and ice. We mainly investigated reproduction (asexual and sexual) and associated spread rates of Spartina grasses, and their health-related states (stem density, canopy height, and percent flowering) which help inform the probability of processes occurring. We also estimated modes of colonization and began quantifying the effects of interspecific interactions and environmental conditions on plant state. Spartina pectinata was the only pastureland plant to survive dike-breaching and saltwater intrusion in 2010; however, it was stunted compared to reference plants. Spartina pectinata patches remained consistent initially, before decreasing in size, and disappearing by the fifth year (2015). This early dynamic may provide initial protection to a developing salt marsh before Spartina alterniflora becomes established. Spartina alterniflora first colonized the sites in year 2 (2012), likely via deposition of rhizomal material, and then spread asexually before seedlings (sexual reproduction) appeared in year 4 (2014). Vegetation cover subsequently increased greatly until near-complete in year 9 (2019). The early successional dynamics of S. pectinata and S. alterniflora occurred spatially independently of each other, and likely contributed to sediment retention, creating an improved environment for S. patens, the dominant high marsh species in our region. Spartina patens have been slowly spreading into restoration sites from high elevation areas since year 6 (2016). We expect that competition between S. alterniflora and S. patens will result in the typical distinct zonation between high and low marsh zones. A next study will use the quantified processes for spatial-explicit modeling to simulate patterns of vegetation recovery, and to evaluate different salt marsh restoration strategies for the Bay of Fundy and elsewhere. Thus, proper identification and quantification of pattern-building processes in salt marsh vegetation recovery, the focus of our present study, was an essential step.

Complex (multispecies) livestock keeping: Highland agricultural strategy in the northern Horn of Africa during the Pre-Aksumite (1600 BCE–400 BCE) and Aksumite (400 BCE–CE 800) periods

The earliest settlements and states in the Horn of Africa were founded in mid to high-elevation areas by farmers and herders who were pioneers in agriculture and herding. Even today, places between mid- and high-elevation remain densely populated. The ancient Pre-Aksumites and Aksumites (1600 cal BCE–800 cal CE) of the north Ethiopian and Eritrean highlands established one of the most powerful states in the Horn of Africa in these high elevation areas through control of long-distance trade and intensive and extensive agriculture. However, despite the fact that agriculture was a significant source of wealth and subsistence for these ancient polities, there has been little research into the agricultural strategies of Pre-Aksumite and Aksumite societies. Using archaeological and faunal data collected from the site of Mezber dating from 1600 cal BCE to 400 cal CE, as well as prevsiously published data, this article provides zooarchaeological evidence for the earliest farming practices in the Horn of Africa. The research demonstrates a resilient highland agricultural strategy based on multispecies animal and plant resources, similar to most tropical agricultural systems today. A second important strategy of Pre-Aksumite farmers was the incorporation of both indigenous and exogenous plants and animals into their subsistance strategies. The Mezber site also offers one of the most thoroughly collected data to support multispecies farming practice in the north Ethiopian and Eritrean highlands.

Deep learning U-Net classification of Sentinel-1 and 2 fusions effectively demarcates tropical montane forest's deforestation

Tropical montane forests (TMF) play a vital role in providing numerous ecosystem services. This ecosystem is characterized by towering mountains, cold weather, tall trees such as pine, and dwarfed plants. Although the combination of optical and radar imagery has shown promise in land use and land cover (LULC) mapping, only a handful of studies have attempted to study the dynamics of land changes in tropical montane forests by combining the two. In this study, we examined the usage of Sentinel-1 (S-1) and Sentinel-2 (S-2) and their fusion as input for LULC mapping with three modeling classifiers: traditional (maximum likelihood classification - MLC), machine learning techniques (random forest, k-nearest neighbor, and kd-tree nearest neighbor), and a deep learning approach (U-Net) in a TMF in the Philippines. Also, the deforestation was characterized in terms of proximity and topographic factors. The findings revealed that the combination of S-1 and S-2 provides LULC with high accuracy of image classification. In binary classification, traditional MLC supersedes other classifiers in correctly classifying the pixels of the input imagery (average overall accuracy (OA) = 95.22; Kappa index (KI) = 90.39). Random Forest (RF) stands out in machine learning classifiers (average OA = 94.49; KI = 88.8). However, U-Net deep learning loses in binary classification but proven more robust when LULC were classified into six complex classes with an OA of 86.77 and KI of 78.89. In addition, using deep learning modeling for LULC mapping of the research site, it was determined that from 2015 to early 2022, 417.93 km2 of the study area had been deforested. Further, this research reveals that the greater the proximity of a forest to a human settlement or agricultural zone, the greater the likelihood that it will be cleared for human habitation or agriculture. Deforestation also occurred in rural locations, far from roads and bodies of water. This analysis also supports the hypothesis that deforestation can occur even in high-elevation areas. The results of this study can be utilized by policy and law makers in order to better communicate the critical nature of implementing evidence- and science-based policies to strengthen protections, as well as developing conservation and management plan for tropical montane forests.

Ground surface temperature monitoring data analysis and applications to geothermal exploration in volcanic areas, Mount Meager, western Canada

The southern Mount Meager area has been studied for its geothermal resource potential for a half century. Although attempts to commercialize the resource were unsuccessful in the past, a large volume of surface and subsurface geoscience data have been collected and made publicly available, making the Mount Meager area a unique natural laboratory for testing new ideas or tools for geothermal exploration. This study investigates the potential of using a ground surface temperature (GST) monitoring network as a tool in geothermal resource exploration. Twenty-two temperature data loggers were deployed in, and surrounding, the core area of the geothermal prospect for nearly one year. The collected temperature time series were analyzed statistically, and machine learning methods such as hierarchical clustering and k-means classification, were applied to data interpretation. The temporal variation of measured temperature can be divided into four segments: 1) snow free, 2) snow affected, 3) snow curtain, and 4) snow melt seasons. The intensity of daily ground temperature variation in the snow free season shows clear environmental and topographic footprints and is complicated by soil properties. The sites with a short period of near zero GST during the snow curtain period is spatially coincident with high heat flow areas. The measured mean GST shows a close affinity with subsurface heat flow and shallow ground water circulation, suggesting that GST time series contain information indicative of subsurface geothermal anomalies and that a GST monitoring network could be an effective tool for geothermal resource exploration in high latitude and/or elevation areas with seasonal snow cover.

Spatiotemporal Evolution and Driving Forces of Vegetation Cover in the Urumqi River Basin.

It is important to determine long-term changes in vegetation cover, and the associated driving forces, to better understand the natural and human-induced factors affecting vegetation growth. We calculated the fractional vegetation coverage (FVC) of the Urumqi River basin and selected seven natural factors (the clay and sand contents of surface soils, elevation, aspect, slope, precipitation and temperature) and one human factor (land use type). We then used the Sen-Man-Kendall method to calculate the changing trend of the FVC from 2000 to 2020. We used the optimal parameters-based geographical detector (OPGD) model to quantitatively analyze the influence of each factor on the change in vegetation coverage in the basin. The FVC of the Urumqi River basin fluctuated from 2000 to 2020, with average values between 0.22 and 0.33. The areas with no and low vegetation coverage accounted for two-thirds of the total area, whereas the areas with a medium, medium-high and high FVC accounted for one-third of the total area. The upper reaches of the river basin are glacial and forest areas with no vegetation coverage and a high FVC. The middle reaches are concentrated in areas of urban construction with a medium FVC. The lower reaches are in unstable farmland with a medium and high FVC and deserts with a low FVC and no vegetation. From the perspective of the change trend, the areas with an improved FVC accounted for 62.54% of the basin, stable areas accounted for 5.66% and degraded areas accounted for 31.8%. The FVC showed an increasing trend in the study area. The improvement was mainly in the areas of urban construction and desert. Degradation occurred in the high-elevation areas, whereas the transitional zone was unchanged. The analysis of driving forces showed that the human factor explained more of the changes in the FVC than the natural factors in the order: land use type (0.244) > temperature (0.216) > elevation (0.205) > soil clay content (0.172) > precipitation (0.163) > soil sand content (0.138) > slope (0.059) > aspect (0.014). Apart from aspect, the explanatory power (Q value) of the interaction of each factor was higher than that of the single factor. Risk detection showed that each factor had an interval in which the change in the FVC was inhibited or promoted. The optimum elevation interval of the study area was 1300-2700 m and the greatest inhibition of the FVC was seen above 3540 m. Too much or too little precipitation inhibited vegetation coverage.

Bias correction of ERA-Interim reanalysis temperature for the Qilian Mountains of China

Air temperature is the primary indicator of climate change. Reanalysis temperature products are important datasets for temperature estimates over high-elevation areas with few meteorological stations. However, they contain biases in observations, so a bias correction is required to enhance the accuracy of modeling predictions. In this study, we used the temperature lapse-rate method to correct ERA-Interim reanalysis-temperature data in the Qilian Mountains of China from 1979 to 2017. These temperature lapse rates were based on observations (ΓObs) and on model internal vertical lapse rates derived from different ERA-Interim pressure levels (ΓERA). The results showed that the temperature lapse rates in warm periods were larger than those in cold periods. Both the original and corrected ERA-Interim temperature can significantly capture the warming trend exhibited by observations. In general, the temperature lapse rate method was reliable for correcting ERA-interim reanalysis-temperature data. Although ΓObs performed best in bias correction, it depends heavily on the density of ground observation stations and is not appropriate for remote areas with a low data coverage. Correction methods based on ΓERA were shown to be reliable for bias correction, and will be especially applicable to mountainous areas with few observation stations. Our results contribute to the improvement of quality of data products and enhance the accuracy of modeling of climate change effects and risks to the environment and human health.

Effect of snow cover on water and heat transfer in alpine meadows in the source region of Yellow River

Extreme snowfall events have been increasing in the Tibetan Plateau, causing greater variations in the snow cover conditions. However, the soil water-heat transfer under different snow conditions has rarely been characterized in detail. Here, by using the multi-source observation data of five years, we analyzed the influences of snow cover on water-heat transfer in alpine meadows of the source region of the Yellow River. The main findings are as follows: In the deep soil, the yearly warming rate from spring to summer was much faster than the cooling rate from autumn to winter, while in the shallow soil, conversely, the former was slower than the latter. Snow cover not only decreased the average soil temperature but also inhibited the occurrence of extremely low temperatures in the soil. The insulation effect of snow was mainly in the mid-frozen period. It was insufficient to balance out the heat lost by the high albedo during early and late frozen periods. In years with more snow, different depths of the soil featured similar thawing dates and plenty of soil voids due to small solid water content and high gravel content, together creating favorable conditions for the snowmelt infiltration, which passed through the frozen layer and infiltrated into the soil of 3.20 m or deeper. In years with less snow, the long-term freezing-thawing cycles aggravated the evaporation and loss of surface soil water in spring. Under different snow cover conditions, the difference in the sensible heat flux was much larger than the latent heat flux in winter and early spring. This study provides a refined physical image of soil water-heat transfer under extreme snow cover conditions in the Tibetan Plateau, which is expected to light the snow cover-frozen soil interaction in the mid-latitude and high-elevation areas.

Biogeographical events, not cospeciation, might be the main drivers in the historical association betweenNoctiliostreblaspecies (Streblidae) and their bulldog bat hosts

AbstractThe genus Noctiliostrebla Wenzel (Diptera: Streblidae) stands out for its high degree of specificity exhibited in relation to bat species of the genus Noctilio Linnaeus and provides an exciting system for understanding the history behind host–parasite associations. Here, we present a phylogeny of Noctiliostrebla based on an analysis of DNA sequences and morphological characters, along with cophylogenetic and biogeographical analyses. Our results strongly support the monophyly of Noctiliostrebla, but with uncertainties within the genus. With a low frequency of cospeciation events explaining the associations between hosts and parasites, cophylogenetic analyses did not show an overall congruence between the host and parasite phylogenies. Indeed, two parallel histories were recovered in the host–parasite associations, which might indicate that niche segregation is determined evolutionarily, facilitating the coexistence of parasites and promoting diversification. Biogeographical analysis showed a strong spatial congruence between disjunct distributions of Noctiliostrebla and major river basins in South America and with areas of higher elevation, which might be associated with the glacial periods throughout the Pliocene and Pleistocene. Overall, our findings suggest an agreement with the expectations of the ‘Stockholm paradigm’ framework, in which biogeographical events and ecological factors act as important components to explain the associations, instead of cospeciation events.