Dense Cover Research Articles

ASSESSMENT OF THE ROLE OF GUM ARABIC PRODUCERS’ ASSOCIATIONS (GAPAS) IN REHABILITATION OF GUM ARABIC BELT: CASE OF NORTH AND WEST KORDOFAN STATES, SUDAN

The research aimed to investigate the involvement of Gum Arabic Producers' Associations (GAPAs) in the rehabilitation of the gum Arabic belt in North and West Kordofan States, Sudan. Data were collected through social surveys of household heads, interviews, and observations, as well as remote sensing images from 1998, 2009, and 2020. Secondary data were obtained from different literature sources. The data were analysed using SPSS and ERDAS software. The results of the social survey showed that the establishment of GAPAs coincided with an increase in gum-producing trees, but GAPAs did not directly contribute to the rehabilitation process. Instead, the rehabilitation efforts were carried out through collaborations between the Forests National Corporation (FNC), multi-donor projects, and GAPAs. The remote sensing results showed changes in vegetation cover over the study period, with an increase in dense, moderate, and sparse vegetation cover classes. The research concluded that GAPAs have a significant impact on the enhancement of vegetation cover. External institutions played a role in the restocking of gum trees. It was recommended that GAPAs be strengthened through capacity building and the adoption of technology to improve gum production. FNC should encourage micro-financial institutions to support rehabilitation projects, utilise mapping to protect the gum gardens, and monitor the rehabilitation processes.

Monitoring solutions for remote locations: A data gathering approach for remote nature-based solution sites

Nature-based solutions have gained popularity as an approach to tackling hydro-meteorological hazards (HMHs) in both urban and rural settings. Despite this popularity, challenges persist regarding the evidence base for their effectiveness and data scarcity at the feature or site scale. Flood modelling is a common approach to quantifying the effectiveness of NbS; however, the accuracy of these models heavily depends on the accuracy of the DEM, land cover, and hydraulic/hydrological data utilised. Remote and rural settings often face data scarcity due to the challenging nature of data collection, and insufficient funding for monitoring. Additionally, NbS features vary in size and scale, with many being small (<1 m in width), posing challenges for accurate representation in national LiDAR datasets. Technological advancements in remote sensing technologies, such as unmanned aerial vehicles, handheld LiDAR, and GPS-GNSS, offer opportunities to gather high-resolution, high-accuracy data in these challenging locations. This article proposes a methodological framework for collecting elevation data at remote NbS sites that can tackle areas affected by both sparse and dense vegetation cover. This approach proves valuable in both pre-NbS implementation, through facilitating NbS opportunity and environmental risk identification, and post-NbS implementation, through aiding in geo-spatial feature location, improving existing DEM data for flood modelling, and monitoring temporal changes.

Enhanced observations from an optimized soil-canopy-photosynthesis and energy flux model revealed evapotranspiration-shading cooling dynamics of urban vegetation during extreme heat

Previousstudies on the cooling of urban vegetation mainly focused on its transpiration or shading effect separately, neglecting to explore the combined evapotranspiration-shading cooling. Further, accurate quantification of evapotranspiration-shading cooling remains challenging due to heterogeneity of urban landscapes, which limits understanding of its high-resolution spatiotemporal patterns. Here, we integrate high-precision remote sensing data and the Soil-Canopy-Observations of Photosynthesis and Energy Fluxes (SCOPE) model to propose an optimized quantitative approach. The approach was used to investigate changes in evapotranspiration-shade cooling during extreme heat.Taking Shanghai metropolitan as case, the results show: (1) The cooling capacity of urban vegetation in nighttime (18:00–6:00) is enhanced during extreme heat, which is attributed to accumulated effect of shading and enhanced evapotranspiration due to elevated vapor-pressure deficit. (2) In densely built-up areas with limited vegetation, there is a significant lack of thermal regulation, especially in the early morning (7:00) and late evening (17:00), thus exacerbating thermal stress. (3) At midday (11:00–13:00) there was a slight decrease in evaporative cooling, probably caused by the behaviour of the stomatal closure at high temperatures. Concurrently, high radiation causes the shading effect of vegetation to become more prominent, amplifying the cooling contrast between areas with dense and sparse vegetation cover. Moreover, the study also highlights that grassland with >50% cover can provide cooling effects similar to that of forest land. Overall, our study not only enhances the understanding of urban vegetation's cooling effects but also underscores the importance of strategic urban vegetation planning in mitigating urban heat, particularly under the escalating frequency and intensity of heat waves.

Age, origin and tectonic controls on rapid recent exhumation of the Sibela Mountains, Bacan, Indonesia

The Sibela Mountains of the island of Bacan in eastern Indonesia contain one of the Earth’s youngest metamorphic complexes that is now exposed at elevations up to 2000 m. New mica 40Ar/39Ar and apatite (U–Th–Sm)/He data from metamorphic and igneous rocks indicate that these rocks were rapidly exhumed in the Pleistocene (c. 0.7 Ma). Exhumation of the metamorphosed Permo-Triassic basement (c. 249–257 Ma) was accompanied by metamorphism (recorded by schists) as well as partial melting (recorded by c. 1.4 Ma granitic dykes). These processes must have occurred at extremely high cooling and exhumation rates. The rapid exhumation on land was associated with significant subsidence in adjacent basins offshore that reach depths up to 2.4 km. Neogene metamorphic core complexes and other metamorphic complexes are well-known from eastern Indonesia, but they usually record much higher exhumation rates than those reported from older classic metamorphic core complexes found in other parts of the world and require a different formation mechanism. Unlike classic metamorphic core complexes that are characterized by low-angle detachment faults, the Bacan metamorphic rocks were exhumed on steep bounding normal faults forming a rectilinear block pattern. We suggest such complexes are termed metamorphic block complexes (MBC). The Bacan MBC is exceptionally young and like the other east Indonesian complexes was rapidly exhumed during subduction rollback. A flexure formed during arc-arc collision as the Sangihe forearc loaded the Halmahera forearc which reactivated steeply-dipping faults in a rectilinear chocolate block pattern.Graphical abstractThe Sibela Mountains of the island of Bacan in eastern Indonesia are formed by one of the Earth’s youngest metamorphic complexes. a Dense rain forest cover and steep flanks of the Sibela Mountains which rise from sea level to more than 2000 m. b Quaternary collision between the Sangihe and Halmahera arcs. Loading of the Halmahera forearc formed a flexure that reactivated steeply-dipping faults, which exhumed the Sibela Mountains metamorphic block. c Rapid cooling paths during exhumation of the Sibela metamorphic complex

LCZ framework and landscape metrics: Exploration of urban and peri-urban thermal environment emphasizing 2/3D characteristics

Rapid urbanization has altered the environment and climate, necessitating a thorough grasp of urban thermal dynamics for sustainable development. The lack of detailed urban information poses a considerable challenge. This study employs the Local Climate Zone (LCZ) framework to delve into the intricate relationship between land surface temperature (LST) zones and both 2/3D urban characteristics. The LCZ map for Bojnourd city, Iran, was prepared, consisting of eleven classes categorized into five built types and six land cover types. The mean LST in the summer of 2021 was derived from Landsat8 using the split-window algorithm (SWA) and divided into seven thermal zones. The research reveals distinctive spatial patterns of LCZs across various Land LST zones. Notably, LCZ2 (Compact mid-rise) and LCZ 3 (Compact low-rise), despite differing heights, share the same thermal zone (Zone3), suggesting influences beyond height on thermal zoning. In contrast, LCZ5 (Open midrise), situated in a cooler thermal zone (Zone2), features more vegetation and taller trees, exhibiting a lower LST range compared to LCZ2 and LCZ3. Class-level metrics (AREA_MN and LPI) offer a similar description of LCZ spatial patterns, while landscape-level metrics like SHDI and IJI provide a more insightful depiction of spatial patterns. The study found that the most appropriate spatial pattern for improving urban thermal conditions involves considering a set of factors such as vegetation presence, land cover proximity, height, and density. This ensures sustainable and green urban development that is in tune with climate change and promotes balanced and harmonious thermal patterns in the urban environment.

Growth-climate relationships of four tree species in the subtropical evergreen broad-leaved forests in Southwest China

Subtropical forests are an important carbon sink, yet our understanding on tree growth response to inter-annual climate variability remains limited. This study investigated the growth-climate relationships of four evergreen broad-leaved tree species (Stewartia pteropetiolata W. C. Cheng, Schima noronhae Reinw. ex Bl. Bijdr, Machilus gamblei King ex J. D. Hooker, and Machilus yunnanensis Lec) in the subtropical evergreen broad-leaved forests (EBFs) in the Ailao Mountains of Yunnan province, southwest China. We constructed tree ring-width residual chronologies for each species and correlated them with daily and monthly climate data. Ring-width chronologies of S. pteropetiolata and S. noronhae were positively correlated with precipitation, relative humidity, and self-calibrated Palmer drought index (scPDSI) during autumn of the previous year and spring-to-early summer of the current year, indicating that these two Theaceae species were sensitive to moisture availability. Tree radial growth of two Machilus species was primarily limited by excessive precipitation and dense cloud cover during the rainy season in this middle montane cloud forest. Moving correlations between climate variables and radial growth of all species were temporally unstable, with a weakening response to climate variability in recent decades. We highlight the dendroclimatic potential of evergreen broad-leaved tree species in moist subtropical forests. The findings offer a pertinent perspective, emphasizing the necessity of separately considering distinct ecological indicators for trees in order to obtain a comprehensive understanding of climate-growth responses within highly diverse subtropical forests.

The relative influence of landscape features on maternity roost and hibernaculum selection in temperate bats

Many animal life-history stages center around residences (nests, roosts, etc.) where the availability of resources within an optimal range can affect fitness. Understanding factors influencing residence selection is fundamental for efficient management or recovery plans. Many bat species use permanent roosts during different periods of the year, and while most conservation plans aim to protect these roosts, the availability of suitable habitat near the roosts (e.g., foraging habitat) is also critical to consider. We evaluated the importance of landscape features at multiple scales surrounding seasonal bat roosts in two regions (north and south) of Québec (Canada), using data from participatory science and government databases. In the human-altered environment of south Québec, bats selected maternity roosts with high anthropogenic cover and water edge density at the 150 m and 2 km scales, respectively. Conversely, roost selection in north Québec, a forested area, could not be explained by any landscape features. In winter, fewer bats used hibernacula located in heavily human-modified landscapes—opposite to the trend observed with maternity roost selection. Our study demonstrates how considering landscape features at the appropriate temporal and spatial scales can promote more efficient conservation for bats.

Evaluation of the microshear bond strength of resin cement to zirconia treated by different nanomaterials using the dip coating technique

Aim: Using a dip-coating technique, this study evaluated the microshear bond strength of resin cement to zirconia surfaces coated with nanosilica and nanoalumina. Methods: Zirconia blocks (n = 56) were categorized into seven groups based on surface treatment: untreated (control), tribochemical silica coating (positive control), dip coating with pure nanosilica, pure nanoalumina, and nanosilica-nanoalumina mixtures at 75:25, 50:50, and 25:75 volume ratios. The coated surfaces underwent characterization using a Scanning Electron Microscope (SEM), Energy Dispersive Spectroscopy (EDS), X-ray Diffraction (XRD), and Atomic Force Microscopy (AFM). Resin cylinders were cemented onto the treated zirconia surfaces, and microshear bond strength testing was performed. Differences in bond strength between groups were analyzed using One-way ANOVA and Tukey’s post-hoc test (p &lt; 0.05). Results: SEM revealed that nanosilica coatings formed island-like agglomerations, nanosilica-nanoalumina produced porous layers, and nanoalumina formed a dense cover layer. XRD detected only the tetragonal phase in coated zirconia, indicating no phase transformation compared to tribochemical silica coating. Microshear bond strength was higher for all coating groups than for controls (p &lt; 0.05). The 75:25 nanosilica-nanoalumina demonstrated greater bond strength than other ratios. Conclusion: Dip-coating proved effective in enhancing resin-zirconia bonding without causing surface damage. Among the various ratios, the 75:25 nanosilica-nanoalumina mixture exhibited optimal bond strength.

Density-dependent facilitation and inhibition between submerged and free-floating plants

This study aimed at testing the hypothesis that free-floating plants may facilitate the growth of submerged plants under hypertrophic conditions and intermediate plant density. The effects of Lemna presence on the growth of two submerged plants (Elodea nuttallii and Ceratophyllum demersum) over a nitrogen gradient were experimentally investigated. This was complemented with analysing the presence of C. demersum and E. nuttallii in Hungary and in Germany in relation to the density of free-floating plants. Results showed a negative exponential pattern between underwater light intensity and Lemna cover. Ceratophyllum and Elodea relative growth rate decreased with increasing nitrogen concentrations and additional low Lemna density stimulated Ceratophyllum and suppressed Elodea. Elodea decreased linearly with Lemna density while Ceratophyllum showed a unimodal response. Total algal biomass (epiphytic and planktonic) was higher in Ceratophyllum than in Elodea treatments and decreased rapidly with increasing Lemna density. The field studies showed a positive relationship between Ceratophyllum and a negative one between Elodea and free-floating plant cover. This study clearly showed that free-floating plants can have either facilitating or inhibiting impact on the growth of submerged plants depending on cover density and macrophyte species. The facilitating effect on Ceratophyllum is most likely due to suppressing epiphytic algal growth.

Green Oases in the Concrete Desert: Combatting Beijing’s Heat with Urban Greenery

In the face of rapid urbanization, Beijing confronts the escalating challenge of the Urban Heat Island (UHI) effect, characterized by significantly higher temperatures in urban areas compared to their rural surroundings. This phenomenon not only exacerbates the thermal discomfort in city environments but also poses a substantial risk to public health and well-being. Amidst this urban climate crisis, the potential of green spaces emerges as a crucial mitigative and adaptive strategy. This comprehensive study embarks on an in-depth exploration of the multifaceted role that urban greenery plays in combatting the UHI effect and bolstering the well-being of Beijing’s residents. Employing a triangulated research methodology, the study harnesses high-resolution satellite imagery to delineate the thermal footprint of green spaces within the urban matrix of Beijing. Through detailed temperature analysis, it meticulously quantifies the extent to which parks, gardens, and tree-lined avenues contribute to cooling urban environments. Complementing this quantitative analysis, the study engages with the urban populace through extensive surveys, capturing perceptions and lived experiences of the thermal environment and the subjective well-being associated with access to green spaces. The findings reveal a significant cooling effect attributed to urban greenery, with marked temperature reductions in areas with dense vegetation cover. Beyond the thermal benefits, the research uncovers a positive correlation between access to green spaces and improvements in residents’ physical and psychological health, highlighting the critical role of green spaces in promoting urban livability and sustainability. This study advances the discourse on urban planning and public health by providing empirical evidence of the benefits of integrating green spaces into the urban fabric of Beijing. It underscores the urgency of adopting green infrastructure as a standard in urban development projects, not only as a countermeasure to the UHI effect but also as a foundational element for enhancing the quality of life in densely populated urban centers. The research concludes with strategic recommendations for urban policymakers, advocating for the expansion and optimization of green spaces as indispensable assets for achieving a resilient and health-promoting urban environment in Beijing.

High-resolution remotely sensed data characterizes indices of avifaunal habitat on private residential lands in a global metropolis

Urban ecosystems are dominated by private lands which poses a significant hurdle to performing field-based assessment of wildlife. An alternative approach is to characterize indices of animal habitat in difficult-to-access areas using data from airborne remote sensing platforms. Characterizing indices of wildlife habitat using remotely sensed data is common in natural systems but has received less attention within urban ecosystems. We tested the utility of using remotely sensed data from high-resolution airborne sensors, including LiDAR, a measure of vertical habitat structure, NDVI, a measure of greenness, image texture, a measure of horizontal habitat structure, and parcel level land-cover data, along with field-based street-tree measurements to predict bird abundance and richness across Greater Los Angeles, California, USA. We surveyed birds and gathered street-tree data on public lands of residential neighborhoods and processed the remote sensing data in 50-m and 300-m circular buffers of bird survey locations to capture data primarily on private, residential land across three winter field seasons (2016–18, 2019/20) at 23 locations along a tree-canopy cover gradient. Data from LiDAR processed as an index for the density of trees summarized in the 50-m and 300-m extents were the strongest univariate predictors of avifaunal abundance and richness explaining 75 % and 74 % of the likelihood in fitted models. NDVI, image texture, land cover, and street-tree density measures were weaker univariate predictors than models fitted with LiDAR data. Models including LiDAR and ground-based street-tree measurements accounted for upwards of 80 % of the variability in avifaunal abundance and richness, particularly for bird species associated with trees and shrubs. We recommend the prioritization of high-resolution remote sensing data, particularly LiDAR, in combination with field-based habitat measures e.g., street trees, to characterize indices of avifaunal habitat on public and private lands of cities, which could help to improve our understanding of the distribution of birds across urban areas.

Complex characteristics of landscape components affected by the disaster at the Ka-hovka Hydropower Plant

The paper provides an in-detail analysis of the flooding in Kherson and Mykolaiv oblasts as a result of the explosion at the Kahovka Hydropower Plant (HPP). We considered the possibility of using a combined analysis of the data of on-ground and remote monitoring of the course and consequences of the flooding. Based on the materials of the Ukrainian Hydometeorological Center of the State Service of Ukraine, we determined control points of chronology of the events and the dynamics of the main hydrometric indicators. The flooding began on 05/06/2023, the water returning back to the regular levels on average on 26/06/2023. The highest levels of water were observed in the period between June 7 and June 9, 2023. The synchronicity of the satellite surveillance of the territory during this time is representative. Based on the parameters of spatio-temporal resolution and degree of cloud cover, we chose the satellite images from Landsat 9 as the basic materials for our study. Using a modified normalized water index, we identified changes in the water area in the indicated time period. Using a digital model of the territory’s relief, we elaborated the zone of spread of the water surface in areas with dense vegetative cover. We found flooded zones where the water was much higher than the maximal levels recorded at the hydrological-monitoring checkpoints. The elucidation of estimations of the flooding zone revealed the components of natural landscapes that have been affected by the techogenic catastrophe. The flooding pummeled the azonal landscape complexes and complexes of above-floodplain terraces and coastal plains. The results of our study are an important step towards assessing the degradation of the downstream-Dnipro ecosystem. They will lay the groundwork for designing plans to liquidate the aftermath of the emergency and adaptation measures in the conditions of increasing risk of devastating technogenic events.

Spatio-Temporal Changes and Habitats of Rare and Endangered Species in Yunnan Province Based on MaxEnt Model

Biodiversity is crucial for ecosystem functioning, but it is rapidly declining due to human activities and climate change. Protecting biodiversity has become a key priority for global environmental conservation actions. Rare and endangered species have a great impact on the ecosystem, yet due to their limited survival capacity, they are more prone to extinction, thus exerting a significant impact on biodiversity. However, current research reveals a lack of information concerning the potential distribution and changes of these species. This study used the maximum entropy model to predict the present and future potential habitats of rare and endangered species in Yunnan Province. After superimposing model results, four richness regions are divided by the natural breakpoint method and analyzed. Existing protected areas are compared with hotspots, and the land-use composition of hotspots is also analyzed. The results revealed that, in both current and future scenarios, rare and endangered species in Yunnan Province are primarily found in the western mountainous region, the Xishuangbanna–Wenshan high temperature area, and the Kunming–Qujing dense vegetation cover area. These species are also expanding their distribution towards the western mountainous area. However, under the low carbon emission scenario (RCP2.6), these species will spread from the high abundance regions to the low altitude hotspots by 2070. In the high carbon emissions scenario (RCP8.5), there will be fewer high abundance areas in 2070 than in 2050. The transfer matrix analysis reveals regional richness variations over time. Furthermore, the analysis revealed significant conservation gaps and found that existing hotspot areas were heavily affected by human activities. To improve conservation efficiency, it is necessary to enhance the protection of existing hotspots in Yunnan Province. Climate change plays a significant role in species migration, with precipitation levels being a key factor. The necessary actions should be taken to address the insufficient protection, resolve conflicts between human activities and land use in critical areas, and formulate effective strategies for adapting to future climate changes. Yunnan Province, with its rich species resources, has the potential to become a global innovator in biodiversity conservation by implementing improved conservation strategies.

Forest and Natural Vegetation Cover Loss Over 2000 to 2020 in Sri Lanka; A Canopy Density Base Analysis

As one of the most important biodiversity hotspot, forest and natural vegetation areas play an essential role in the global ecosystem. It provides an uncountable number of ecosystem services while controlling the adverse impacts of climatic changes. With the expansion of civilization and fulfilling the infinite needs of man, forests and natural vegetation areas were destroyed, especially for agricultural purposes, development projects and timber. Due to this, the accelerated growth of deforestation and loss of natural vegetation can be observed in Sri Lanka in the past few decades. This study aimed to identify the forest and natural vegetation area loss from 2000 to 2020 with a particular focus on the Canopy Density (CD) of tree cover (&gt;25%, &gt;50% and &gt;75%) in Sri Lanka. The satellite estimated data (30 mx30 m resolution) was downloaded from the 2000 to 2020 time period from the Global Forest Watch (GFW) online platform conducted by the World Resource Institute were used. Spatial and temporal changing patterns of the forest and natural vegetation areas have been identified using descriptive analysis methods (percentage) using MS Excel 2019 software. Results of the study found that in 2000, 61.38 percent of the country was covered with above 25% tree cover CD, while 53.86 percent and 39.76 percent of areas have covered with the tree cover CD above 50% and 75%, respectively. However, when it has come to 2020, these areas have decreased by 52.78 percent (&gt;25% CD), 44.27 percent (&gt;50% CD) and 28.65 percent (&gt;75% CD). During this period, 8.6 percent (&gt;25% CD), 9.59 percent (&gt;50% CD) and 11.11 percent (&gt;75% CD) of the forest and natural vegetation areas of Sri Lanka have lost the country. Throughout this period, 2016 can be identified as a year at risk for deforestation due to its annual deforestation rate (&gt;8.8 percent). The total area of forest cover lost in 2016 is 17799 ha (&gt;25% CD), 15583 ha (&gt;50% CD) and 9865 ha (&gt;75% CD). This is nearly 13 percent of forest cover loss for all three types of CD tree cover areas. According to the calculations of the forest areas that have &gt;75% of CD, Anuradhapura (12.06%), Kurunegala (9.82%), and Monaragala (8.49%) districts are the areas that contributed to forest cover loss in the country during 2000 to 2020. According to the study, the annual deforestation rate is still very high. Hence should be needed to monitor and take action to stop deforestation and achieve sustainability in natural resource management in Sri Lanka. &#x0D; Keywords: Deforestation, Canopy density, Tree cover, Natural resource management, Sri Lanka

Corrigendum to ''Integrate Terrain Variables and Rapid Eye Satellite in Vegetation Indices, for Identifying Forest Cover Area and Density: A Case Study in Mountainous Iraqi Kurdistan Region (IKR)'' [Volume 6, Issue 1, 107-114

Corrigendum to ''Integrate Terrain Variables and Rapid Eye Satellite in Vegetation Indices, for Identifying Forest Cover Area and Density: A Case Study in Mountainous Iraqi Kurdistan Region (IKR)'' [Volume 6, Issue 1, 107-114

Integrate Terrain Variables and RapidEye Satellite in Vegetation Indices, for Identifying Forest Cover Area and Density: A Case Study in Mountainous Iraqi Kurdistan Region (IKR)

Integrate Terrain Variables and RapidEye Satellite in Vegetation Indices, for Identifying Forest Cover Area and Density: A Case Study in Mountainous Iraqi Kurdistan Region (IKR)

Estimating the Colored Dissolved Organic Matter in the Negro River, Amazon Basin, with In Situ Remote Sensing Data

Dissolved organic matter (DOM) is a crucial component of continental aquatic ecosystems. It plays a vital role in the carbon cycle by serving as a significant source and reservoir of carbon in water. DOM provides energy and nutrients to organisms, affecting primary productivity, organic composition, and the food chain. This study presents empirical bio-optical models for estimating the absorption of colored dissolved organic matter (aCDOM) in the Negro River using in situ remote sensing reflectance (Rrs) data. Physical–chemical data (TSS, DOC, and POC) and optical data (aCDOM and Rrs) were collected from the Negro River, its tributaries, and lakes and empirical relationships between aCDOM at 440 nm, single band, and the ratio bands of Rrs were assessed. The analysis of spectral slope shows no statistically significant correlations with DOC concentration or aCDOM absorption coefficient. However, strong relationships were observed between DOC and aCDOM (R2 = 0.72), aCDOM and Rrs at 650 nm (R2 &gt; 0.80 and RMSE &lt; 1.75 m−1), as well as aCDOM and the green/red band ratio (R2 &gt; 0.80 and RMSE &lt; 2.30 m−1). aCDOM displayed large spatial and temporal variations, varying from 1.9 up to 20.1 m−1, with higher values in rivers of the upper course of the Negro basin and lower values in rivers with total solids suspended &gt; 10 mg·L−1. Environmental factors that influence the production of dissolved organic matter include soil type, dense forest cover, high precipitation, and low erosion rates. This study demonstrated that aCDOM can serve as an indicator of DOC, and Rrs can serve as an indicator of aCDOM in the Negro basin. Our findings offer a starting point for future research on the optical properties of Amazonian black-water rivers.

Comparative analysis between spectral indices obtained in the Guangüiltagua metropolitan park in Quito – Ecuador, using remote sensing

The article presents an exhaustive comparative analysis of NDVI, SAVI and NDWI spectral indices, extracted from satellite images of the Guangüiltagua Metropolitan Park in Quito. The relevance of remote sensing, using satellites such as Sentinel-2, in the monitoring of biodiversity and environmental conditions is highlighted. The research emphasizes the importance of vegetation indices, especially NDVI, to assess vegetation health and detect changes in vegetation cover. The study discusses in detail vegetation sensitivity, water identification, water stress response, soil effect compensation, and specific applications of NDVI, SAVI, and NDWI. The ability of these indices to provide crucial information on ecosystem health, water presence, and potential water stress conditions in Metropolitan Park is highlighted. The methodology applied involves the use of the Copernicus platform and the Sentinel-2 satellite, with radiometric and geometric correction procedures, as well as atmospheric correction. The results obtained reveal high NDVI values, indicating a dense vegetation cover, while NDWI suggests potential areas of water scarcity. The comparative analysis between the indices offers a deeper understanding of the relationship between vegetation and water in the park.

Land cover preferences and spatiotemporal associations of ungulates within a Scottish mammal community.

In the degraded and modified environment of the Scottish Highlands, novel ungulate communities have arisen following local extinctions, reintroductions, and the introduction of non-native species. An understanding of the dynamics and interactions within these unique mammal communities is important as many of these mammals represent keystone species with disproportionate impacts on the environment. Using a camera trap survey, we investigated land cover preferences and spatiotemporal interactions within a Scottish ungulate community: the sika deer (Cervus nippon), the roe deer (Capreolus capreolus), the red deer (Cervus elaphus), and the wild boar (Sus scrofa). We used generalised linear models to assess land cover preferences and the effect of human disturbance; spatiotemporal interactions were characterised using time interval modelling. We found that sika deer and roe deer preferred coniferous plantations and grasslands, with sika deer additionally preferring woodland. For red deer, we found a slight preference for wetland over woodland; however, the explained variance was low. Finally, wild boar preferred grassland and woodland and avoided coniferous plantations, heathland, and shrubland. Contrary to our expectations, we found no evidence that human disturbance negatively impacted ungulates' distributions, potentially because ungulates temporally avoid humans or because dense vegetation cover mitigates the impacts of humans on their distributions. Furthermore, we detected a spatiotemporal association between sika deer and roe deer. Although the underlying cause of this is unknown, we hypothesise that interactions such as grazing facilitation or an anti-predator response to culling could be driving this pattern. Our work provides a preliminary analysis of the dynamics occurring within a novel ungulate community and also highlights current knowledge gaps in our understanding of the underlying mechanisms dictating the observed spatiotemporal associations.

Improving forest connectivity assessments using tree cover density maps

Forests are vital for sustaining biodiversity and regulating climate. However, the fragmentation of these critical ecosystems poses a serious threat to their ecological integrity and the myriad of organisms they support. In this paper we compare the degree of forest connectivity derived via the traditional approach of using a binary forest cover map with a new approach using a grayscale tree cover density map. Because connectivity is scale-dependent, the comparison is repeated for a series of analysis scales. We find that exploiting the additional information on tree cover density improves the precision of forest connectivity estimates. The degree of connectivity was on average 21% lower when using the tree cover density map compared to using the binary forest cover map. Additional benefits of using tree cover density maps are the detection and quantification of subtle temporal changes (gains and losses) and a more refined assessment of hotspots in forest connectivity that cannot be detected with binary maps. Improved assessment and monitoring capabilities can be instrumental to enhancing the design and assessing the efficacy of landscape management and restoration policies to improve forest connectivity. The generic conceptual approach is exemplified using the 2018 Copernicus Tree Cover Density dataset with all assessment tools available in open-source software packages.