Variation In Cover Research Articles

Comparing methods to estimate cloud cover over the Baikal Natural Territory in December 2020

The paper addresses the issue of how much cloud cover data obtained using satellite and model-interpolation techniques are suitable for monitoring the transparency of the atmosphere and determining conditions for airglow observations at a local geophysical observatory. For this purpose, we compared the temporal dynamics of cloud cover from ECMWF’s ERA5 reanalysis and NOAA satellites with the night atmosphere transparency according to a digital camera. We considered the dynamics of the addressed parameters at the Geophysical Observatory of the Institute of Solar-Terrestrial Physics, located in the Baikal Natural Territory near the village of Tory (Republic of Buryatia, Russia), during December 2020. The comparative analysis showed a generally good agreement between cloud cover data from ECMWF’s ERA5 climate reanalysis and those observed with the camera. Disadvantages are the lack of information on rapid variations in cloud cover in the reanalysis and positive and negative delays in the dynamics of cloud fields that last about two hours. Due to irregular satellite data, large time gaps between passes and difficulties in estimating cloud cover at night, we could not come to reliable conclusions concerning the applicability of satellite data.

Сопоставление методов определения облачного покрова над Байкальской природной территорией в декабре 2020 г.

The paper addresses the issue of how much cloud cover data obtained using satellite and model-interpolation techniques are suitable for monitoring the transparency of the atmosphere and determining conditions for airglow observations at a local geophysical observatory. For this purpose, we compared the temporal dynamics of cloud cover from ECMWF’s ERA5 reanalysis and NOAA satellites with the night atmosphere transparency according to a digital camera. We considered the dynamics of the addressed parameters at the Geophysical Observatory of the Institute of Solar-Terrestrial Physics, located in the Baikal Natural Territory near the village of Tory (Republic of Buryatia, Russia), during December 2020. The comparative analysis showed a generally good agreement between cloud cover data from ECMWF’s ERA5 climate reanalysis and those observed with the camera. Disadvantages are the lack of information on rapid variations in cloud cover in the reanalysis and positive and negative delays in the dynamics of cloud fields that last about two hours. Due to irregular satellite data, large time gaps between passes and difficulties in estimating cloud cover at night, we could not come to reliable conclusions concerning the applicability of satellite data.

Vegetation cover change and restoration potential in the Ziwuling Forest Region, China

Since the implementation of “Grain for Green” program in 1999, remarkable changes have taken place in the vegetation of the Loess Plateau, China, especially in the forests. The Ziwuling Forest Region is an important ecological forest area in the central zone of the Loess Plateau. The spatiotemporal variation of the vegetation cover and vegetation restoration potential in the Ziwuling Forest Region was studied using the NDVI data, based on geographical spatial analysis technology, Hurst exponent analysis and statistical analysis. From 2001 to 2019, vegetation cover in forest region increased significantly. The average growth rate of vegetation cover was 6.49%, and NDVI increased significantly in 84.66% of the area (p < 0.05), with an average annual growth rate of 0.0045 a−1. In 2019, it reached the maximum value of 0.833, and the Hurst index indicates that 35.02% of the area will show a benign development trend in the future. The vegetation coverage was linear negatively correlated with the aridity index, and the fitting degree in steep slope area (R2 > 0.5) was better than that in gentle slope area (R2 > 0.4). The average vegetation restoration potential in the study area was 0.837. Of the regional vegetation coverage, 72.47% is close to or has exceeded the vegetation restoration potential, and the vegetation restoration degree in the northern and eastern regions is relatively high. The existing vegetation coverage and vegetation restoration potential in Ziwuling Forest Region are high, so the existing vegetation restoration measures should be maintained to avoid damage to the vegetation in the area. This study has important guiding significance for the implementation of vegetation restoration and ecological protection policies on the Loess Plateau.

Use of Remotely Sensed Data for the Evaluation of Inter-Row Cover Intensity in Vineyards

Information on vegetation cover and soil management is used in hydrological and soil erosion modeling, but in most cases, reference values are used solely based on land use classification without considering the actual spatial and temporal variation adopted at the field scale. This work focused on the adoption of satellite optical data from the Copernicus Sentinel-2 (S2) mission to evaluate both spatial and temporal variations of vineyard ground cover. First, on a wider scale, fields were mapped by photointerpretation, and a cluster analysis was carried out. Results suggest that vineyards can be classified according to different inter-row soil management, with the best results obtained using NDVI and NDWI. A pilot area in the municipality of Carpeneto, in the wine-growing area of Alto Monferrato, was also analyzed due to the availability of reference data on inter-row vegetation cover from experimental plots. Those are set on sloping areas and present different inter-row soil managements (conventional tillage—CT, and permanent grass cover—GC). Time series of different vegetation indices (VIs) have been obtained, and both S2 native bands and the derived VIs were evaluated to assess their capability of describing the vineyard’s inter-row coverage growth trends at plot level for the agrarian year 2017–2018. Results suggest that a seasonality effect may be involved in the choice of the most suitable band or index that better describes soil coverage development at a given moment of the year. Further studies on open-source remotely sensed (RS) data could provide specific inputs for applications in erosion risk management and crop modeling.

Improved estimation of vegetation water content and its impact on L-band soil moisture retrieval over cropland

Satellite-based soil moisture (SM) retrieval within agricultural regions is challenging due to pronounced vegetation and land cover variations during the growing season. Vegetation water content (VWC)–used to describe vegetation opacity in both the Soil Moisture Active Passive (SMAP) Dual Channel Algorithm (DCA) and V-polarization Single Channel Algorithm (SCA-V)–is approximated using a climatological Normalized Difference Vegetation Index (NDVI) time series. To understand the impact of VWC algorithms on SMAP SM retrievals, we investigated optimal vegetation indices for VWC estimation, and further evaluated the impact of VWC uncertainty on DCA and SCA-V SM retrievals. Besides NDVI, we applied four dynamic vegetation indices (VIs) acquired from Sentinel-2–including two red-edge VIs (Modified Chlorophyll Absorption Ratio Index (MCARI) and Inverted Red-edge Chlorophyll Index (IRECI)) and two non-red-edge VIs (Normalized Difference Water Index (NDWI1 and NDWI2)) to estimate growing-season corn VWC and the impact of different empirical relationships on VWC estimates. We find that climatological NDVI from Moderate Resolution Imaging Spectroradiometer (MODIS) significantly underestimates VWC, and therefore underestimates SM over croplands in Northwest China during the growing season, whereas dynamic VIs can improve the accuracy of VWC and SM retrievals. With respect to the choice of VI for VWC estimation, MCARI is more accurate during the peak growing season compared to its counterpart non-red-edge VIs; however, it also overestimates VWC during the early growing stage. In addition, the influence of VWC uncertainty on SM accuracy is shown to be higher in SCA-V than in DCA. The results of this study provide insight into preferred approaches for the accurate estimation of VWC and associated improvement in passive microwave algorithms for SM retrieval.

Effects of landscape characteristics, anthropogenic factors, and seasonality on water quality in Portland, Oregon

Urban areas often struggle with deteriorated water quality because of complex interactions between landscape factors and climatic variables. However, few studies have considered the effects of landscape variables on water quality at a sub-500-m scale. We conducted a spatial statistical analysis of six pollutants for 128 water quality stations in four watersheds around Portland, Oregon, using data from 2015 to 2021 for the wet season at two microscales (100m and 250m buffers). E. coli was associated with land cover, soil type, topography, and pipe length, while lead variations were best explained by topographic variables. Developed land cover and impervious surface explained variations in nitrate, while orthophosphate was associated with mean elevation. Models for zinc included land cover and topographic variables in addition to pipe length. Spatial regression models better explain variations in water quality than ordinary least squares models, indicating strong spatial autocorrelation for some variables. Our findings provide valuable insights to city planners and researchers seeking to improve water quality in metropolitan areas by manipulating city landscapes.

Spatial and temporal analyses of land use changes with special focus on seasonal variation in snow cover in District Chitral; a Hindu Kush mountain region of Pakistan

Snow and glacier changes and increase in temperature due to climate change in Hindu Kush Himalayas (HKH) and its impacts are important for water resource management in the world and specifically for Pakistan, which is a water-stressed country. Being a mountainous region, the people living in HKH are highly susceptible to the adverse impacts induced by climate change. This paper therefore mainly focused on monitoring snow cover changes in district Chitral using USGS satellite images (Landsat5-TM, Landsat7-ETM+, and Landsat8-OLI) for the years 2000, 2004, 2008, 2012, and 2016. The maximum likelihood method was used for Land Use Land Cover (LULC) classification. For a better understanding of the pattern of seasonal variation in snow cover over time, the total study period was distributed in four quadrennials, and the dataset for each period was taken only for early winter (Oct-Nov). A marked increase (266.7%) in the built-up area and 135.9 km2 of agriculture expansion in this remote and mountainous area is quite significant. Results of the current study showed that in the year 2000, more than half (51.6%) of the total land of District Chitral was covered with snow in early winter, but it drastically decreased to only 6.8% in the year 2008. During the first two quadrennials, 44.7% (5694.6 km2) of glaciated area exposed the barren rocks, while the overall changes in snow-cover areas are approximately 43.3% (5514.6 km2). The most significant impact of melting snow and glaciers is Glacial Lakes Outburst Floods (GLOFs). GLOFs may cause human deaths and injuries, while these are also a threat to agricultural land, forest, and residential areas. Based on the current study, it is recommended to enhance institutional capacity in the country to face different environmental hazards, including early warning systems on the local scale. Keeping in view the water stress and based agriculture-based economy of Pakistan, proper analysis and monitoring of snow should be carried out for the sack of water availability, drought or floods, and other environmental vulnerabilities.

50%, not great, not terrible: Pan-European gap-analysis shows the real status of the DNA barcode reference libraries in two aquatic invertebrate groups and points the way ahead

The essential key to routine molecular species identification (DNA barcoding/metabarcoding) is the existence of an error-free DNA barcode reference library providing full coverage of all species. Published studies generally state the need to produce more barcodes, and control their quality, but unfortunately, the number of barcoded species is still low. However, to initiate real progress, we need to know where the gaps lie, how big they are and why they persist. Our aims were to draw and understand the current state of knowledge regarding species diversity, distribution, and barcode coverage, and offer solutions for improvement. In this study, we used two groups of aquatic insects, beetles and true bugs. We have compiled and critically evaluated an essentially complete and up-to-date European list, containing 1527 species. The list served as a basis for the barcode gap analyses in the Barcode-of-Life-Data-System (BOLD) conducted in three subsequent years (2020–2022). The overall barcode coverage of the pan-European fauna was around 50 % in both groups. The lowest coverage was in the Mediterranean, the Balkans and South-eastern Europe. The coverage in each country depended significantly on the local diversity, the number of rare, endemic species and the similarity of its fauna to that of the most active barcoding European countries. Gap analyses showed a very small increase in species coverage (<1 % in European aquatic beetles) despite an ~25 % increase in the number of barcodes. Hence, it is clear that future barcoding campaigns must prioritise quality over quantity. To visibly improve reference libraries, we need to increase the involvement of taxonomic experts and focus on targeted studies and underexplored but biodiversity-rich areas.

Oceanic productivity and high-frequency temperature variability—not human habitation—supports calcifier abundance on central Pacific coral reefs

Past research has demonstrated how local-scale human impacts—including reduced water quality, overfishing, and eutrophication—adversely affect coral reefs. More recently, global-scale shifts in ocean conditions arising from climate change have been shown to impact coral reefs. Here, we surveyed benthic reef communities at 34 U.S.-affiliated Pacific islands spanning a gradient of oceanic productivity, temperature, and human habitation. We re-evaluated patterns reported for these islands from the early 2000s in which uninhabited reefs were dominated by calcifiers (coral and crustose coralline algae) and thought to be more resilient to global change. Using contemporary data collected nearly two decades later, our analyses indicate this projection was not realized. Calcifiers are no longer the dominant benthic group at uninhabited islands. Calcifier coverage now averages 26.9% ± 3.9 SE on uninhabited islands (compared to 45.18% in the early 2000s). We then asked whether oceanic productivity, past sea surface temperatures (SST), or acute heat stress supersede the impacts of human habitation on benthic cover. Indeed, we found variation in benthic cover was best explained not by human population densities, but by remotely sensed metrics of chlorophyll-a, SST, and island-scale estimates of herbivorous fish biomass. Specifically, higher coral and CCA cover was observed in more productive waters with greater biomass of herbivores, while turf cover increased with daily SST variability and reduced herbivore biomass. Interestingly, coral cover was positively correlated with daily variation in SST but negatively correlated with monthly variation. Surprisingly, metrics of acute heat stress were not correlated with benthic cover. Our results reveal that human habitation is no longer a primary correlate of calcifier cover on central Pacific island reefs, and highlight the addition of oceanic productivity and high-frequency SST variability to the list of factors supporting reef builder abundance.

Climate and elevation control snow depth and snow phenology on the Tibetan Plateau

Snowmelt from the Tibetan Plateau (TP) is the water source of many major Asian rivers, with significant importance for regional water supply and ecosystem services. The spatiotemporal variations of snow cover on the TP and its response to climate change at different altitudes are still unclear because of the lack of in situ observations on the western TP, and limitations of optical remote sensing due to clouds. Using a daily passive microwave remote sensing snow depth dataset from 1979 to 2020 across the TP, this study investigates the spatiotemporal variations of snow depth and snow phenology as well as their responses to climate change. The results showed that during the past 40 years, the maximum snow depth (SDmax) and the snow cover duration days (SCD) on the TP decreased significantly at a rate of 0.6 cm/decade and 2.9 d/decade, respectively. The snow cover starting date (SCS) was delayed at a rate of 1.1 d/decade, whereas the snow cover melt date (SCM) advanced at a rate of 1.1 d/decade. The decrease of SCD was driven by the advance of SCM, which was caused by the decrease of SDmax, whereas the decrease of SDmax was driven by the increase in snow accumulation season temperature (Ta). The TP showed significant elevation-dependent warming (EDW) (0.04 ℃ decade-1 km−1) and elevation-dependent decrease of SDmax (0.12 cm decade-1 km−1) and SCD (4.1 d decade-1 km−1). The EDW explains the elevation-dependent decrease of SDmax (r = −0.72, P < 0.05) and SCD (r = −0.83, P < 0.05). It is expected that the negative feedback effect of SDmax and SCD on EDW may further exacerbate the EDW of the TP, and the earlier snowmelt due to the continuous decrease of snow depth may increase the frequency of droughts and floods. Our findings support the enhancement of EDW on the TP, depletion of solid reservoirs, and intensification of the regional water crisis in a warmer future.

Large-scale spatial variability in urban tolerance of birds.

Quantifying intraspecific and interspecific trait variability is critical to our understanding of biogeography, ecology and conservation. But quantifying such variability and understanding the importance of intraspecific and interspecific variability remain challenging. This is especially true of large geographic scales as this is where the differences between intraspecific and interspecific variability are likely to be greatest. Our goal is to address this research gap using broad-scale citizen science data to quantify intraspecific variability and compare it with interspecific variability, using the example of bird responses to urbanization across the continental United States. Using more than 100 million observations, we quantified urban tolerance for 338 species within randomly sampled spatial regions and then calculated the standard deviation of each species' urban tolerance. We found that species' spatial variability in urban tolerance (i.e. standard deviation) was largely explained by the variability of urban cover throughout a species' range (R2 =0.70). Variability in urban tolerance was greater in species that were more tolerant of urban cover (i.e. the average urban tolerance throughout their range), suggesting that generalist life histories are better suited to adapt to novel anthropogenic environments. Overall, species differences explained most of the variability in urban tolerance across spatial regions. Together, our results indicate that (1) intraspecific variability is largely predicted by local environmental variability in urban cover at a large spatial scale and (2) interspecific variability is greater than intraspecific variability, supporting the common use of mean values (i.e. collapsing observations across a species' range) when assessing species-environment relationships. Further studies, across different taxa, traits and species-environment relationships are needed to test the role of intraspecific variability, but nevertheless, we recommend that when possible, ecologists should avoid using discrete categories to classify species in how they respond to the environment.

Intra-annual sediment dynamic assessment in the Wei River Basin, China, using the AIC functional-structural connectivity index

Hydrological and sediment dynamics have changed considerably on the Chinese Loess Plateau during the last six decades due to large scale land use changes and numerous water regulation actions. Understanding the mechanism of sediment transport change and its effects is of great importance to food and environmental security. Numerical approaches are useful to map and assess spatio-temporal patterns in sediment dynamics. This study evaluates monthly and annual sediment connectivity in the Wei River Basin (134,800 km2) at the basin and sub-basin scales using the aggregated index of sediment connectivity (AIC). For the first time, this index is applied on this relatively large regional scale. The two objectives were to (1) evaluate the performance of the AIC at the regional scale, addressing substantial differences among areas, and (2) analyze how each AIC sub-factor co-determines the monthly sediment and connectivity patterns. Results show that AIC has strong or moderate positive correlation with sediment yield from 15 out of 23 stations in the Wei and Jing sub-basin. The Jing sub-basin has the highest sediment connectivity due to degraded vegetation, while the Beiluo sub-basin has the lowest sediment connectivity on average due to better ecological restoration. Within the year, sediment connectivity is highest in April and lowest in January, due to the rainfall regime and intra-annual land cover variations. Among the AIC factors, the rainfall factor has the highest effect on sediment connectivity, implying that functional connectivity (graded by rainfall and soil cover) determines sediment dynamics more than structural connectivity (mainly determined by topography and soil permeability). This study provides one of the first large-scale estimates of spatial and temporal sediment connectivity from hillslopes to river stream and including large reservoirs, which can be further employed to implement regional ecological construction works and environmental catchment management.

Ecological determinants and risk areas of Striga hermonthica infestation in western Kenya under changing climate

AbstractStriga hermonthica (Del.) Benth is a parasitic weed that is damaging major cereal crops in sub‐Saharan Africa (SSA). Although Striga is recognised as an agricultural scourge, there is limited information available indicating the extent of its growth and spread as impacted by the changing climate in Kenya. This study investigated the impact of current climate conditions and projected future (2050) climate change on the infestation of Striga hermonthica in the western Kenya region. Specifically, the study aimed to predict Striga hermonthica habitat suitability in five counties in the western Kenya region through using the maximum entropy (MaxEnt) model and bioclimatic, soil, topographic and land use, and land cover (LULC) variables. Striga hermonthica geolocations were collected and collated and ecological niche models were developed to determine the habitat suitability. The results showed that approximately 1767 km2 (10% of the total study area) is currently highly suitable for Striga hermonthica occurrence. The future projections showed a range between 2106 km2 (19% of the total study area) and 2712 km2 (53% of the total study area) at the minimum carbon (RCP 2.6) and the maximum carbon emission scenarios (RCP 8.5) respectively. Elevation, annual precipitation, LULC, temperature seasonality and soil type were determined to be the most influential ecological predictor variables for Striga hermonthica establishment. The study revealed the importance of using climate, soil, topographic and LULC variables when evaluating agricultural production constraints such as Striga's prevalence. The methodology used in this study should be tested in other Striga affected areas.

The relative importance of forest cover and patch-level drivers for phyllostomid bat communities in the Amazonian Savannas

ContextAnalyze the multiple dimensions of biodiversity under a local and landscape lens in natural habitats, such as Amazonian savannas, is fundamental for the conservation of species and ecosystems.ObjectivesWe aim to explore how landscape forest cover and patch-level variables affect the patterns of species abundance, functional traits, and taxonomic, functional and phylogenetic α-diversity of Phyllostomid bats in forest patches of the Savannas of Amapá, in both the wet and dry seasons.MethodsWe used mist nets to survey bats in 26 forest patches. We also quantified forest cover in buffers of 500, 1000, 1500, 2000 and 2500 m around each patch, and tree height, basal area, canopy cover, and vegetation clutter in the understorey at the patch level. We used hierarchical partitioning to relate the different indices with our predictor variables.ResultsTaxonomic, functional and phylogenetic diversity in the wet season increased with the proportion of forest cover in the 2500 m buffer. Vegetation clutter was negatively related to taxonomic and functional diversity in the wet season. In the dry season, average tree height positively affected taxonomic and functional diversity. Patch-level variables were more important than forest cover in explaining the average functional traits in both seasons.ConclusionWe found seasonal variation in the relationships between components of bat diversity and different drivers. Since both forest cover in the landscape and patch-level variables are important for Phyllostomid bat diversity, conservation plans should consider forest conservation at the landscape level and maintenance of forest patch quality.

Long‐term proliferation of large annual thistles in dry Mediterranean rangelands

AbstractSpiny plants comprise a large, ecologically and economically important functional group in Mediterranean rangelands. The increasing abundance of large annual thistles in grazed grasslands entails major consequences for ecosystem services. This study aims to quantify the contribution of large annual spiny plants to rangeland vegetation cover and productivity and to identify management‐ and climate‐related drivers of spiny plant distribution and performance. Using a 15‐year dataset from an extensive herbaceous pasture experiment in northeastern Galilee, Israel, we examined the effects of livestock management and climate on the cover and biomass of two dominant annual thistle species, Scolymus maculatus and Carthamus glaucus. These thistles constitute a significant proportion of pasture productivity, contributing more than 50% and 25% under high and moderate stocking density, respectively. Despite the similarity in life‐form and life‐history characteristics, each demonstrates a distinct response to both management intensity and annual climatic parameters. High stocking density had a positive effect on both cover and biomass of S. maculatus. Conversely, C. glaucus biomass estimates were higher under moderate stocking density. Distance from feeding site had significant contrasting effects on each of the focal thistles. Relative humidity and temperature were the most sensitive climatic parameters in explaining the variation in cover and biomass of the two thistles. The directionality of the two species' responses suggests that S. maculatus attains higher biomass than C. glaucus under dry and warm conditions. The proliferation of both large thistles under variable stocking densities and climatic conditions increases productivity but reduces the palatable vegetation of Mediterranean rangelands by 27%–50%.

CHEOPS finds KELT-1b darker than expected in visible light

Recent studies based on photometry from the Transiting Exoplanet Survey Satellite (TESS) have suggested that the dayside of KELT-1b, a strongly irradiated brown dwarf, is significantly brighter in visible light than what would be expected based on Spitzer observations in the infrared. We observed eight eclipses of KELT-1b with CHaracterising ExOPlanet Satellite (CHEOPS) to measure its dayside brightness temperature in the bluest passband observed so far, and we jointly modelled the CHEOPS photometry with the existing optical and near-infrared photometry from TESS, LBT, CFHT, and Spitzer. Our modelling has led to a self-consistent dayside spectrum for KELT-1b covering the CHEOPS, TESS, H, Ks, and Spitzer IRAC 3.6 and 4.5 µm bands, where our TESS, H, Ks, and Spitzer band estimates largely agree with the previous studies. However, we discovered a strong discrepancy between the CHEOPS and TESS bands. The CHEOPS observations yield a higher photometric precision than the TESS observations, but they do not show a significant eclipse signal, while a deep eclipse is detected in the TESS band. The derived TESS geometric albedo of 0.36−0.13+0.12 is difficult to reconcile with a CHEOPS geometric albedo that is consistent with zero because the two passbands have considerable overlap. Variability in cloud cover caused by the transport of transient nightside clouds to the dayside could provide an explanation for reconciling the TESS and CHEOPS geometric albedos, but this hypothesis needs to be tested by future observations.

Spatio-temporal variation on land use and land cover and its drivers under watershed management activities in Becho, Central Highlands of Ethiopia

Abstract The study sought to understand the spatio-temporal variation of land use and land cover (LULC) and its drivers under watershed management activities in Becho district, in Ethiopia’s Central Highlands. To gain a better comprehension of the subject, two micro watersheds were chosen to test the effectiveness of watershed management activities (treated-Shankur Tareqo and untreated-Mende Tufessa). LULC changes were detected using aerial photography (1973), and satellite images from Landsat 5 TM (1990), Spot 5 (2005), and Landsat 8 OLI (2021) obtained from the Ethiopian Geospatial Information Institute and the United States Geological Survey. In addition, key informant interviews (KII) and focus group discussions (FGD) were used to elicit LULC drivers. Between 1973 and 2021, the total area of woodland, and cultivated and rural settlement land LULC classes in the treated micro-watershed decreased by 24.65% (171.9 ha) and 7.34% (759 ha), respectively. Though, grassland, forestland, and barrenland increased by 30.83% (179.52 ha), 1% (3 ha), and 183.14% (755.28 ha), respectively. The overall area of LULC class for woodland, grassland, forestland, and cultivated and rural settlement decreased by 50.36% (316.16 ha), 41.23% (196.46 ha), 2.43% (11.85 ha), and 1.35% (138.6 ha), respectively, in the untreated micro-watershed, while barrenland increased by 175.86% (666.55 ha). According to KII and FGD, the drivers of LULC changes were identified as the expansion of cultivated land, population pressure, and government policy. According to the findings, local-scale watershed management activities was not as effective as expected. As a result, in order to achieve the desired outcome, the concerned stakeholders should reconsider how watershed management activities is undertaken.

Effects of Transport Corridor Advancement on Agglomeration and Industrial Relocation – Dallas Fort Worth (US) case study

Abstract Cities serve as hubs for various activities that necessitate comprehensive transportation connectivity. This study examines the decadal urban agglomeration patterns from 2001 to 2020 and critically assesses the relationship between freeway developments, industrial relocation, and population density in the DFW (Dallas Fort Worth) metropolitan area. Landsat satellite imageries, US census, and open-source GIS datasets have been utilized in the study. The Maximum Likelihood Classification (MLC) algorithm helped generate the vector database, using which Land Use/Land Cover (LULC) variations were assessed. The calculated overall accuracies of the classified images for 2001, 2011, and 2020 were 93.12%, 91.87%, and 93.12%, respectively. Eventually, buffer generation techniques and summary statistics helped detect potential boom hotspots. Our results indicate that the highway advancement project lures industries, leading to population migration. The LULC variations suggest that the increase in highway infrastructure resulted in a surge in built-up and a decrease in open spaces in District-3 of DFW. From our study, we find that 79.16% of old industries are located near old freeways, while 78.84% of new industries are located near new freeways. Further, our industrial area to road area comparison clearly shows that industrial relocation was driven by transportation advancements over time. Our results also confirm that this relocation of industries fostered a massive population influx during the following decades.

Ecological niche modelling of Cantharellus species in Benin, and revision of their conservation status

Of the eight Cantharellus species known from Benin, seven have been encountered under similar macroecological conditions. The present work attempts to generate a more complete distribution of these seven species. Forty-eight occurrences of the target species and four explanatory variables including three bioclimatic variables and a land cover variable were used to build an ensemble model from five modelling approaches under the Biomod2 package of R software. Results showed a distribution restricted to the Bassila and Atacora mountain range phytogeographic districts with excellent statistical performance (TSS = 0.98, AUC = 0.99). This distribution is governed mainly by high soil moisture and high potential evapotranspiration, thus defining only gallery forests as the most suitable habitat for chanterelles in Sudano-guinean and Soudanese ecozones of Benin. Based on IUCN criterion B1 and sub-criteria B1a and B1c(i), these seven species were categorized under the Endangered (EN) threat category according to our results.

Effects of climate change and human activities on vegetation coverage change in northern China considering extreme climate and time-lag and -accumulation effects

Quantifying the contributions of climate change (CC) and human activities (HA) to vegetation change is crucial for making a sustainable vegetation restoration scheme. However, the effects of extreme climate and time-lag and -accumulation effects on vegetation are often ignored, thus underestimating the impact of CC on vegetation change. In this study, the spatiotemporal variation of fractional vegetation cover (FVC) from 2000 to 2019 in northern China (NC) as well as the time-lag and -accumulation effects of 15 monthly climatic indices, including extreme indices, on the FVC, were analyzed. Subsequently, a modified residual analysis considering the influence of extreme climate and time-lag and -accumulation effects was proposed and used to attribute the change in the FVC contributed by CC and HA. Given the multicollinearity of climatic variables, partial least squares regression was used to construct the multiple linear regression between climatic indices and the FVC. The results show that: (1) the annual FVC significantly increased at a rate of 0.0268/10a from 2000 to 2019 in all vegetated areas of NC. Spatially, the annual FVC increased in most vegetated areas (∼81.6 %) of NC, and the increase was significant in ∼54.6 % of the areas; (2) except for the temperature duration (DTR), climatic indices had no significant time-lag effects but significant time-accumulation effects on the FVC change. The DTR had both significant time-lag and -accumulation effects on the FVC change. Except for potential evapotranspiration and DTR, the main temporal effects of climatic indices on the FVC were a 0-month lag and 1–2-month accumulation; and (3) the contributions of CC and HA to FVC change were 0.0081/10a and 0.0187/10a in NC, respectively, accounting for 30.2 % and 69.8 %, respectively. HA dominated the increase in the FVC in most provinces of NC, except for the Qinghai and Neimenggu provinces.