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15 pages, 1137 KiB  
Article
Breeding Season Habitat Selection of the Eurasian Collared Dove in a Dry Mediterranean Landscape
by Alan Omar Bermúdez-Cavero, Edgar Bernat-Ponce, José Antonio Gil-Delgado and Germán Manuel López-Iborra
Birds 2024, 5(4), 737-751; https://doi.org/10.3390/birds5040050 - 24 Nov 2024
Viewed by 399
Abstract
Birds select habitats to optimize resources and maximize fitness, with some species recently colonizing new areas, like the Eurasian collared dove (ECD) in the Iberian Peninsula. The ECD spread across Europe in the early 20th century from South Asia. This study reanalyzes data [...] Read more.
Birds select habitats to optimize resources and maximize fitness, with some species recently colonizing new areas, like the Eurasian collared dove (ECD) in the Iberian Peninsula. The ECD spread across Europe in the early 20th century from South Asia. This study reanalyzes data from the Atlas of Breeding Birds in the Province of Alicante (SE Spain) to identify macrohabitat-level environmental variables related to its occurrence and abundance in this semi-arid Mediterranean landscape during the breeding season. We performed Hierarchical Partitioning analyses to identify important environmental variables for the species associated with natural vegetation, farming, topography, hydrographical web, urbanization, and climate. Results show that ECD has a higher occurrence probability near anthropic areas (isolated buildings, suburban areas), water points (medium-sized ponds), larger crop surfaces (total cultivated area), and warmer localities (thermicity index). The species avoids natural habitats like pine forests and scrublands. Abundance is positively linked to anthropic features like larger suburban areas and urban-related land uses. These findings can help predict its expansion in regions with a Mediterranean climate in South America, North America, or Australia, and its continuous natural expansion and population increase within the Mediterranean basin and Europe. Full article
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<p>Map of Alicante province and its location in SE Spain. The 10 × 10-km UTM grid is shown (thin line) along with the 2 × 2 squares that were randomly selected for the fieldwork of the <span class="html-italic">Atlas of Breeding Birds in the Province of Alicante</span> [<a href="#B34-birds-05-00050" class="html-bibr">34</a>,<a href="#B35-birds-05-00050" class="html-bibr">35</a>].</p>
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<p>Relationships of the most relevant environmental variables, according to the HP analyses, showing a positive relationship for the presence (blue line: (<b>A</b>–<b>E</b>)) and abundance (red line: (<b>F</b>,<b>G</b>)) of the Eurasian collared dove in SE Spain.</p>
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9 pages, 96135 KiB  
Interesting Images
Urban Nature Preserves as Habitats for Rare and Endemic Flora in a Scrubland and Pine Flatwoods Region of the Southeastern United States
by Mary G. Lusk
Diversity 2024, 16(11), 705; https://doi.org/10.3390/d16110705 - 20 Nov 2024
Viewed by 320
Abstract
Florida, USA, has 215 endemic or near-endemic plant species, most of which are found in scrubland and pine flatwood habitats and some of which are globally threatened or endangered. Florida is also one of the most rapidly urbanizing states in the United States, [...] Read more.
Florida, USA, has 215 endemic or near-endemic plant species, most of which are found in scrubland and pine flatwood habitats and some of which are globally threatened or endangered. Florida is also one of the most rapidly urbanizing states in the United States, and natural lands are being rapidly replaced by urban development in this state. Conservation easements and nature preserves are two tools for sustaining biodiversity in urbanizing landscapes. This collection of images documents observational research on rare and endemic wildflower species in the nature preserves of Hillsborough County, Florida (population of 1.5 million), part of the larger Tampa metropolitan area (population of 3.2 million). A two-year survey of wildflowers in 27 nature preserves dispersed throughout the county’s total 3.3 km2 area observed 410 species across 97 families. Of these 410 species, there were 19 species endemic to Florida, including the critically globally endangered Florida goldenaster (Chrysopsis floridana). Each of these endemic species relies on the unique soil and hydrologic conditions of the Florida scrubland and flatwood ecosystems, and preservation of these lands amidst urban development is critical for their conservation. The objective of this work is to document the role of the nature preserves as habitats for rare and endemic wildflower species, with the goal of providing science-based support for maintaining preserve land within and near urbanizing areas. Full article
(This article belongs to the Section Biodiversity Conservation)
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<p>Endemic species from the Asteraceae family described in <a href="#diversity-16-00705-t001" class="html-table">Table 1</a>. Species are Scrubland goldenaster (<b>A</b>), Tracy’s silkgrass (<b>B</b>), Feay’s Palafox (<b>C</b>), Florida greeneyes (<b>D</b>), and Florida false sunflower (<b>E</b>).</p>
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<p>Endemic species and subspecies of the Asteraceae family, continued, as described in <a href="#diversity-16-00705-t001" class="html-table">Table 1</a>. Species are Florida goldenaster (<b>A</b>), Leavenworth’s tickseed (<b>B</b>), rose rush (<b>C</b>), and pineland purple (<b>D</b>).</p>
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<p>Endemic species from the Fabaceae family described in <a href="#diversity-16-00705-t001" class="html-table">Table 1</a>. Species are Florida Alicia (<b>A</b>), pineland butterfly pea (<b>B</b>), and Tampa prairie clover (<b>C</b>).</p>
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<p>Endemic species from the Lamiaceae family described in <a href="#diversity-16-00705-t001" class="html-table">Table 1</a>. Species are flatwoods bluecurls (<b>A</b>) and Florida scrub skullcap (<b>B</b>).</p>
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<p>Endemic species from the Campanulaceae, Commelinaceae, and Apocynaceae families described in <a href="#diversity-16-00705-t001" class="html-table">Table 1</a>. Species are bay lobelia (<b>A</b>), Florida milkweed (<b>B</b>), and scrub roseling (<b>C</b>).</p>
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<p>Endemic species from the Cactaceae, Euphorbiaceae, and Annonaceae families described in <a href="#diversity-16-00705-t001" class="html-table">Table 1</a>. The species are netted pawpaw (<b>A</b>), Florida pricklypear (<b>B</b>), and Lesser Florida spurge (<b>C</b>).</p>
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<p>Different phenological stages of the Florida goldenaster. The white sandy surface soil that characterizes much of its habitat can be seen easily in the left image.</p>
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<p>The endangered giant orchid (<span class="html-italic">Orthochilus ecristatus</span>) (both images).</p>
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<p>The pine lily is a rare species observed in these nature preserves.</p>
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<p>Other rare species in the nature preserves. The species are Florida coastal bluecurls (<b>A</b>), Florida milkweed (<b>B</b>), and bushy aster (<b>C</b>).</p>
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13 pages, 3447 KiB  
Article
Assessing Land-Cover Changes in the Natural Park ‘Fragas do Eume’ over the Last 25 Years: Insights from Remote Sensing and Machine Learning
by Paula Díaz-García and Adrián Regos
Land 2024, 13(10), 1601; https://doi.org/10.3390/land13101601 - 1 Oct 2024
Viewed by 907
Abstract
The ‘Fragas do Eume’ Natural Park includes one of the best-preserved Atlantic forests in Europe. These forests are part of the Natura 2000 Network. This scientific study focuses on analysing land-cover changes in the ‘Fragas do Eume’ Natural Park (NW Spain) over a [...] Read more.
The ‘Fragas do Eume’ Natural Park includes one of the best-preserved Atlantic forests in Europe. These forests are part of the Natura 2000 Network. This scientific study focuses on analysing land-cover changes in the ‘Fragas do Eume’ Natural Park (NW Spain) over a 25-year period, from 1997 to 2022, using machine learning techniques for the classification of satellite images. Several image processing operations were carried out to correct radiometry, followed by supervised classification techniques with previously defined training areas. Five multispectral indices were used to improve classification accuracy, and their correlation was evaluated. Land-cover changes were analysed, with special attention to the transitions between eucalyptus plantations and native deciduous forests. A significant increase in eucalyptus plantations (48.2%) (Eucalyptus globulus Labill.) was observed, while native deciduous forests experienced a decrease in their extent (17.6%). This transformation of the landscape affected not only these two habitats, but also cropland and scrubland areas, both of which increased. Our results suggest that the lack of effective conservation policies and the economic interest of fast-growing tree plantations could explain the loss of native deciduous forests. The results highlight the need to implement pro-active and sustainable management measures to protect these natural forest ecosystems in the ‘Fragas do Eume’ Natural Park. Full article
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<p>Map showing the location of ‘Fragas do Eume’. The orange area indicates the extent of the Natural Park.</p>
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<p>Correlation diagram between multispectral indices. Top right: March 1997, top left: August 1997, bottom right: March 2022, and bottom left: July 2022.</p>
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<p>Boxplot of the overall accuracy data of the algorithms for the summer maps (Summer), summer and winter maps (Summer + Winter), and summer, winter, and indices maps (Summer + Winter + Index) in the years 1997 and 2022. The line dividing the box represents the median, the box represents 50% of the data, the lines represent 25% of the data, and the points are outliers.</p>
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<p>This Sankey diagram illustrates the transitions between different land use types over time. The categories include croplands (yellow), deciduous forest (red), evergreen forest (green), shrubland (light green), and water (blue). The flow lines between the source (left) and target (right) nodes represent the changes in land use, measured in hectares, highlighting the dynamic nature of land cover transitions within the study area. The thickness of each line corresponds to the magnitude of change, facilitating the visualisation of how land use categories have evolved.</p>
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<p>Bar plot of land data by land type and year.</p>
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<p>Maps of land cover habitat classes for 1997 (<b>top</b>) and 2022 (<b>bottom</b>) in the ‘Fragas do Eume’ Natural Park. Coordinates are in the UTM coordinate system, WGS84 Zone 29N.</p>
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20 pages, 4165 KiB  
Article
Identifying Conservation Priority Areas of Hydrological Ecosystem Service Using Hot and Cold Spot Analysis at Watershed Scale
by Srishti Gwal, Dipaka Ranjan Sena, Prashant K. Srivastava and Sanjeev K. Srivastava
Remote Sens. 2024, 16(18), 3409; https://doi.org/10.3390/rs16183409 - 13 Sep 2024
Viewed by 648
Abstract
Hydrological Ecosystem Services (HES) are crucial components of environmental sustainability and provide indispensable benefits. The present study identifies critical hot and cold spots areas of HES in the Aglar watershed of the Indian Himalayan Region using six HES descriptors, namely water yield (WYLD), [...] Read more.
Hydrological Ecosystem Services (HES) are crucial components of environmental sustainability and provide indispensable benefits. The present study identifies critical hot and cold spots areas of HES in the Aglar watershed of the Indian Himalayan Region using six HES descriptors, namely water yield (WYLD), crop yield factor (CYF), sediment yield (SYLD), base flow (LATQ), surface runoff (SURFQ), and total water retention (TWR). The analysis was conducted using weightage-based approaches under two methods: (1) evaluating six HES descriptors individually and (2) grouping them into broad ecosystem service categories. Furthermore, the study assessed pixel-level uncertainties that arose because of the distinctive methods used in the identification of hot and cold spots. The associated synergies and trade-offs among HES descriptors were examined too. From method 1, 0.26% area of the watershed was classified as cold spots and 3.18% as hot spots, whereas method 2 classified 2.42% area as cold spots and 2.36% as hot spots. Pixel-level uncertainties showed that 0.57 km2 and 6.86 km2 of the watershed were consistently under cold and hot spots, respectively, using method 1, whereas method 2 identified 2.30 km2 and 6.97 km2 as cold spots and hot spots, respectively. The spatial analysis of hot spots showed consistent patterns in certain parts of the watershed, primarily in the south to southwest region, while cold spots were mainly found on the eastern side. Upon analyzing HES descriptors within broad ecosystem service categories, hot spots were mainly in the southern part, and cold spots were scattered throughout the watershed, especially in agricultural and scrubland areas. The significant synergistic relation between LATQ and WYLD, and sediment retention and WYLD and trade-offs between SURFQ and HES descriptors like WYLD, LATQ, sediment retention, and TWR was attributed to varying factors such as land use and topography impacting the water balance components in the watershed. The findings underscore the critical need for targeted conservation efforts to maintain the ecologically sensitive regions at watershed scale. Full article
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<p>Map showing location of the study area. The inset diagram (<b>a</b>) represents the Indian Himalayan Range (IHR) in Indian subcontinent. The inset diagram (<b>b</b>) highlights the IHR states in yellow with precise location of Aglar watershed (in red) in Uttarakhand. The inset diagram (<b>c</b>) showcases the land use type in the Aglar watershed.</p>
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<p>PCA plots showing (<b>a</b>) relative contribution of the individual HES variable (<b>b</b>,<b>c</b>) relative contribution of each variable considered under regulating and supporting services categories, respectively.</p>
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<p>Hot and cold spot areas in Aglar watershed derived from four approaches along with their median under two distinct methods. (<b>a</b>) Method-1: Considering HES descriptors as an individual entity. (<b>b</b>) Method-2: Considering HES descriptors under broad ESs categories.</p>
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<p>Hot and cold spot areas in Aglar watershed derived from four approaches along with their median under two distinct methods. (<b>a</b>) Method-1: Considering HES descriptors as an individual entity. (<b>b</b>) Method-2: Considering HES descriptors under broad ESs categories.</p>
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<p>Pixel-level uncertainty in hot and cold spot maps based on mode values obtained from method 1 and 2.</p>
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<p>Pearson correlation coefficients between HES descriptors.</p>
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17 pages, 2291 KiB  
Article
Density and Home Range of Cats in a Small Inhabited Mediterranean Island
by Sara Molina-Bernabeu and Germán M. López-Iborra
Animals 2024, 14(16), 2288; https://doi.org/10.3390/ani14162288 - 6 Aug 2024
Viewed by 1256
Abstract
There is growing concern about effectively controlling cat populations due to their impact on biodiversity, especially on islands. To plan this management, it is essential to know the cat population size, sterilization rates, and space they use. Small inhabited islands can have very [...] Read more.
There is growing concern about effectively controlling cat populations due to their impact on biodiversity, especially on islands. To plan this management, it is essential to know the cat population size, sterilization rates, and space they use. Small inhabited islands can have very high cat densities; thus, this study aimed to evaluate cat density and home range on a small tourist island in the Spanish Mediterranean. Surveys in the urban area identified individual cats using a photographic catalog, and camera trapping was conducted in the scrubland area. GPS devices were fitted on three urban cats. The overall cat density was estimated to be 308 cats/km2, varying between the urban area (1084 cats/km2) and the uninhabited scrubland (27 cats/km2). Urban cats had smaller average home ranges (0.38 ha or 1.25 ha, depending on the estimation method) compared to scrubland cats (9.53 ha). Penetration of scrubland cats into the urban area was not detected. These results indicate that the urban area acts as a source of cats for the scrubland. Although the total sterilization rate was high (90.3%), the large cat population implies that the density would take over a decade to decrease to acceptable levels. Therefore, complementary measures for managing this cat population are recommended. Full article
(This article belongs to the Section Ecology and Conservation)
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<p>Location of Tabarca Island. The area marked by the red rectangle in an image outlines the area that appears enlarged in the next one. The yellow line delineates the urban area of the island.</p>
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<p>Location of the feeding points of the cat colony (triangles in the urban area) and the 27 camera trap points distributed across 9 north-south oriented transects (circles in the scrubland area) on Tabarca Island. In the latter, the first number identifies the transect, and the second indicates the position. The points within the same transect, where the cameras operated simultaneously, are shown in the same color. The cameras were moved from east to west.</p>
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<p>Heat map of the intensity of use of the urban area of Tabarca by cats. The numbers indicate the locations of official feeding points.</p>
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<p>Home ranges of cats in the urban area of Tabarca estimated using two methods. Upper map: MCP calculated from records of cats with at least five locations obtained during the surveys. Lower map: The home range was estimated as KDE 95% (blue line), and core areas were estimated as KDE 50% (pink line) for the three neutered male cats equipped with GPS. The blue dots show the locations used for the calculations. The numbers in both maps indicate the cats listed in <a href="#animals-14-02288-t001" class="html-table">Table 1</a>.</p>
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<p>Home ranges of cats in the scrubland area of Tabarca Island, estimated using MCP from locations obtained through camera trapping. Cats are identified by the same number as in <a href="#animals-14-02288-t002" class="html-table">Table 2</a>.</p>
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17 pages, 2915 KiB  
Article
Application of Soil Multiparametric Indices to Assess Impacts of Grazing in Mediterranean Forests
by Picazo Córdoba Marta Isabel, García Saucedo Francisco, Wic Baena Consolación, García Morote Francisco Antonio, López Serrano Francisco Ramón, Rubio Eva, Moreno Ortego José Luis and Andrés Abellán Manuela
Land 2024, 13(4), 411; https://doi.org/10.3390/land13040411 - 23 Mar 2024
Viewed by 940
Abstract
In this study, the effects of different stocking rates were quantified in three study areas in a Mediterranean forest (Cuenca, Spain) by applying a multiparametric soil quality index (SQI) developed from undisturbed forest soils (>40 years). The main objective was to advance the [...] Read more.
In this study, the effects of different stocking rates were quantified in three study areas in a Mediterranean forest (Cuenca, Spain) by applying a multiparametric soil quality index (SQI) developed from undisturbed forest soils (>40 years). The main objective was to advance the development and application of multiparametric indices that allow for soil condition assessment. To fulfill this objective, the effectiveness of the developed multiparametric soil quality index (SQI) was analyzed as an indicator of livestock impacts on soil in the Mediterranean forest. The control areas without livestock activity were forest stands of different ages (a thicket forest stand of <30 years; a high-polewood forest stand of 30–60 years; and an old-growth forest stand of >60 years), which were compared with areas subjected to various grazing intensities (areas with permanent livestock passage: a sheepfold that had been inactive for 2–3 years and an active sheepfold; areas with intermittent livestock passage: a bare-soil area, a pine stand and a scrubland). The applied multiparametric soil quality index (SQI) was sensitive to changes in forest ecosystems depending on the stocking rates. However, to obtain greater precision in the assessment of the effects of stocking rates, the multiparametric index was recalibrated to create a new index, the Soil Status Index by Livestock (SSIL). The correlation between the quality ranges obtained with both indices in different study areas suggests that the SSIL can be considered a livestock impact reference indicator in Mediterranean forest soils. Full article
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Graphical abstract
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<p>Study areas and sampling plots.</p>
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<p>Mean soil quality index (<b>SQI</b>) value in each study area. <b>Ash</b>, active sheepfold; Ish, inactive sheepfold; <b>BS</b>, bare soil; <b>Scr</b>, scrubland; <b>Pst</b>, pine stand; <b>Tfst</b>, thicket forest stand; <b>Hfst</b>, high-polewood forest stand; and <b>Ofst</b>, old-growth forest stand (n = 168, units shown on the planes of the axes).</p>
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<p>(<b>a</b>) Diagram showing the eigenvectors for each one of the twelve parameters (shown as lines) on the first two principal component axes. Longer lines indicate parameters that relate strongly to the axes, and the closer they are plotted, the stronger the correlations between the parameters (n = 168, units shown on the planes of the axes). (<b>b</b>) Scatter plot of the principal component scores of the standardized data. Abbreviations: Ash, active sheepfold; Ish, inactive sheepfold; BS, bare soil; Scr, scrubland; Pst, pine stand; Tfst, thicket forest stand; Hfst, high-polewood forest stand; Ofst, old-growth forest stand; TOC, total organic carbon; N, total nitrogen; M, moisture; pH, soil acidity; BR, basal soil respiration; MBC, microbial biomass carbon; APA, phosphatase activity; β-GLU, β-glucosidase activity. (<b>c</b>) Principal component analysis (2PCA) performed using the eight selected parameters. The eigenvector for each of the eight parameters is plotted on the plane. (<b>d</b>) Principal component analysis (3PCA) performed using the eight selected parameters, with axes 3PC1 and 3PC2. M, moisture; pH, soil acidity; MBC, microbial biomass carbon; UA, urease activity.</p>
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<p>Average value of <b>SSI<sub>L</sub></b> (Soil Status Index by Livestock) in each study area. <b>Ash</b>, active sheepfold; <b>Ish</b>, inactive sheepfold; <b>BS</b>, bare soil; <b>Scr</b>, scrubland; <b>Pst</b>, pine stand; <b>Tfst</b>, thicket forest stand; <b>Hfst</b>, high-polewood forest stand; and <b>Ofst</b>, old-growth forest stand (n = 168, units shown on the planes of the axes).</p>
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<p>Ranges for <b>RSQI</b> and <b>RSSI<sub>L</sub></b> in each study area. <b>Ash</b>, active sheepfold; <b>Ish</b>, inactive sheepfold; <b>BS</b>, bare soil; <b>Scr</b>, scrubland; <b>Pst</b>, pine stand; <b>Tfst</b>, thicket forest stand; <b>Hfst</b>, high-polewood forest stand; and <b>Ofst</b>, old-growth forest stand (n = 168, units shown on the planes of the axes).</p>
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20 pages, 5250 KiB  
Article
Validation of NWCG Wildfire Directional Indicators in Test Burns in Coastal California
by Keith Parker and Vytenis Babrauskas
Fire 2024, 7(1), 5; https://doi.org/10.3390/fire7010005 - 21 Dec 2023
Viewed by 2273
Abstract
One of the primary tools used for determining the origin of a wildfire is analyzing burn patterns formed during the fire progression. These patterns, called fire pattern indicators, are interpreted and used to document the direction of fire movement at specific points, creating [...] Read more.
One of the primary tools used for determining the origin of a wildfire is analyzing burn patterns formed during the fire progression. These patterns, called fire pattern indicators, are interpreted and used to document the direction of fire movement at specific points, creating a directional map back to the specific area of origin. This concept was first set forth in 1978 by a U.S. governmental organization, the National Wildfire Coordinating Group (NWCG). Their recommendations are currently (2016) in the third edition, and in our study, we examine these indicators. Specifically, the objective was to perform a validation exercise where controlled burns were conducted of natural vegetation plots but augmented with 32 identical sets of staged artifacts which would provide additional opportunities for fire movement to create observable directional fire pattern indicators. Three adjacent plots were burned, each using a single point ignition, all located on level, scrubland terrain. The burns were conducted in the fall season, under low to moderate burning conditions. The research was structured as a preliminary study, since only mild terrain and weather conditions were encompassed. The actual fire movements were documented by drone videos, additional ground-based videos, and still photography. Within the three burn plots, a total of 12 data sites out of 32 data sites were selected: each one containing 7 to 12 individual artifacts. Each artifact was photographically documented post-fire, and the actual fire movement direction at that location was established. Assessment entailed the use of four experienced wildland fire investigators, with each one independently assessing the direction and type of fire spread at each artifact using the photographic site evidence. An analysis was then conducted to make a statistical comparison between the actual fire movement direction and the direction estimates provided by the experts analyzing the photographic evidence and the limited information on conditions provided. The results indicate an average error of 103°. These results indicate that additional efforts are needed to study the scientific basis of the indicators and to evolve improvements in both the indicators and in the accompanying guidance to investigators. Full article
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<p>Vortex flame wrap (Photo: Simeoni et al. [<a href="#B7-fire-07-00005" class="html-bibr">7</a>]; © Simeoni et al., published by Sage Publications).</p>
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<p>Overall view of the three burn plots; (<b>A</b>–<b>C</b>) are identified in the views above.</p>
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<p>Propane torch used to ignite vegetation at Plot B.</p>
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<p>Google Earth Pro Map with field GPS locations.</p>
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<p>Matterport scans (Provided by Envista Forensics).</p>
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<p>Example data site photograph supplied to evaluators.</p>
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<p>Example data site photograph supplied to evaluators.</p>
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<p>Example data site photograph supplied to evaluators.</p>
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<p>Example data site photograph supplied to evaluators.</p>
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<p>Example data site photograph supplied to evaluators.</p>
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27 pages, 4164 KiB  
Article
Altering Natural Ecosystems Causes Negative Consequences on the Soil Physical Qualities: An Evidence-Based Study from Nilgiri Hill Region of Western Ghats, India
by M. Jagadesh, Duraisamy Selvi, Subramanium Thiyageshwari, Cherukumalli Srinivasarao, Pushpanathan Raja, Udayar Pillai Surendran, Nadhir Al-Ansari and Mohamed A. Mattar
Land 2023, 12(10), 1869; https://doi.org/10.3390/land12101869 - 3 Oct 2023
Viewed by 1408
Abstract
Land use change (LUC) has direct and indirect consequences on soil quality. To gain insight into how LUC influences the physical properties of soil, it can be advantageous to compare undisturbed ecosystems with those that have naturally evolved over time, as well as [...] Read more.
Land use change (LUC) has direct and indirect consequences on soil quality. To gain insight into how LUC influences the physical properties of soil, it can be advantageous to compare undisturbed ecosystems with those that have naturally evolved over time, as well as to use soil quality indices to pinpoint the sensitivity of each ecosystem and land use change (LUC). A soil survey was carried out in the six major ecosystems of the Nilgiri Hill Region: cropland (CL), deciduous forest (DF), evergreen forest (EF), forest plantation (FP), scrubland (SL), and tea plantation (TP), with those having an establishment for over 50 years being selected and analyzed for soil physical parameters. In addition, soil quality indices were also derived to pinpoint the vulnerability of each ecosystem to LUC. The results reveal that the changes in land use significantly altered the soil physical properties. The content of clay was higher in EF and DF and increased with the soil profile’s depth, whereas the sand content was higher in CL and TP and decreased with the depth increment. BD and PD were significantly lower in EF, DF, SL, and FP, whereas they were higher in CL and TP. PS and ASM followed a similar trend to BD and PD. Owing to undisturbed natural settings, an abundance of litter input, and higher carbon concentrations, the HC was higher in EF, DF, SL, and FP, whereas, in the case of anthropogenic-influenced ecosystems such as CL and TP, it was lower. We discovered that LUC has altered Ag S, WSA, and MWD. Due to tillage and other cultural practices, Ag S, WSA, and MWD were significantly lower in CL and TP. However, the results confirm that native ecosystems (EF and DF) with a higher carbon content prevent such degradation, thereby resulting in good Ag S, WSA, and MWD. Full article
(This article belongs to the Special Issue Soil Legacies, Land Use Change and Forest and Grassland Restoration)
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<p>Distribution of the 214 sample sites across the NHR’s various ecosystems: (<b>a</b>) India, (<b>b</b>) Tamil Nadu map showing study region, (<b>c</b>) sampling points. (See <a href="#app1-land-12-01869" class="html-app">Table S1</a> for a full description of sampling sites in NHR.)</p>
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<p>Soil physical properties under different ecosystems of Nilgiri Hill Region (NHR). The figure displays the impact of land use change on the percentages of sand, silt, clay, and bulk density (BD) (Mg m<sup>−3</sup>) in several NHR ecosystems. According to DMRT, histograms with distinct letters differ significantly (<span class="html-italic">p</span> &lt; 0.01).</p>
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<p>Soil physical properties under different ecosystems of Nilgiri Hill Region (NHR). The figure displays how changing land use has an impact on particle density (PD) (Mg m<sup>−3</sup>), pore space (PS) (%), available soil moisture (ASM) (%), hydraulic conductivity (HC) (cm hr<sup>−1</sup>), aggregate stability (Ag S) (%), mean weight diameter (MWD) (mm), and water-stable aggregates (WSA) (%) in different ecosystems of the NHR. According to DMRT, histograms with distinct letters differ significantly (<span class="html-italic">p</span> &lt; 0.01).</p>
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<p>Soil organic matter (%) under different ecosystems of Nilgiri Hill Region (NHR). The figure displays how changing land use has an impact on soil organic matter (%) in different ecosystems of the NHR. According to DMRT, histograms with distinct letters differ significantly (<span class="html-italic">p</span> &lt; 0.01).</p>
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<p>Principal component analysis of soil physical properties and soil organic matter in different ecosystems. [Available soil moisture (ASM), hydraulic conductivity (HC), pore space (PS), particle density (PD), aggregate stability (Ag S), bulk density (BD)].</p>
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<p>Distribution of soil physical properties and soil organic matter under different ecosystems, and the correlation values with * specify significant correlations (significant levels: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1).</p>
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<p>Influence of soil physical properties on soil organic matter. (Values and effects are collinear. Values embedded in each soil properties represent the individual effect, whereas the values directed toward the soil organic matter (SOM) represent the effect of each parameters on soil organic matter.) [Available soil moisture (ASM), hydraulic conductivity (HC), pore space (PS), particle density (PD), aggregate stability (Ag S), bulk density (BD)].</p>
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32 pages, 7770 KiB  
Article
Study of the Ecosystem Service Value Gradient at the Land–Water Interface Zone of the Xijiang River Mainstem
by Yang Huang, Junling Deng, Min Xiao, Yujie Huang, Hui Li, Yinyin Xiao and Yiting Huang
Appl. Sci. 2023, 13(18), 10485; https://doi.org/10.3390/app131810485 - 20 Sep 2023
Cited by 1 | Viewed by 1440
Abstract
The ecosystem service value (ESV) gradient-evolution pattern of a river basin’s land and water-intertwined zones has a variety of ecosystem service values, such as biodiversity conservation, water conservation, water purification, etc. The study of the ecosystem service value (ESV) gradient-evolution pattern of a [...] Read more.
The ecosystem service value (ESV) gradient-evolution pattern of a river basin’s land and water-intertwined zones has a variety of ecosystem service values, such as biodiversity conservation, water conservation, water purification, etc. The study of the ecosystem service value (ESV) gradient-evolution pattern of a river basin’s land and water-intertwined zones will provide a scientific basis for the construction and protection of the ecological security pattern of the river basins. In this study, we combined the unit area equivalent factor method and geographically weighted regression (GWR) model to classify and analyze the gradient change pattern of ESV upstream, downstream, and along the river of the Guangdong mainstream section of the Xijiang River in China, and the conclusions are as follows: (1) The corresponding ESV share of each land use type was in the following order: water bodies > broad-leaved forest > artificial wetland > scrub > paddy field > coniferous forest > natural wetland > grassland. The level of each type of ESV does not depend entirely on the size of the area but is determined by the ecosystem service functions it can provide and the level of ESV per unit area; (2) the relationship between land use types along both sides of the river in the Guangdong section of the Xijiang River Basin shows a tendency to shift from water ecosystems to terrestrial ecosystems, and the ESV gradually decreases with the increase in distance from the water. (3) The upstream to the downstream area showed a trend of changing from terrestrial ecosystems to aquatic ecosystems, such as broad-leaved forests, scrublands, water bodies, artificial wetlands, etc., and the mean land ESV showed a general trend of undulating change and decline with the reduction in the distance from the downstream area. (4) Natural factors, such as the topography and geomorphology of the basin and the socio-economic factors of power consumption, influence the spatial distribution characteristics of the ESV in the region; among them, socio-economic factors, such as total power consumption, industrial exhaust gas emissions, industrial wastewater emissions, etc., in the economically developed areas of the Xijiang River Basin are the determinants of the changes in ESV, which are generated by human living and production activities, and these indirectly affect the magnitude of the ESV by influencing the factors of temperature and gas. Full article
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<p>Map showing the location of the water–land ecotone of the Guangdong section of the Xijiang River.</p>
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<p>Land use type map of a 1–10 km stretch along the river of a land and water interface zone of the Guangdong section of the Xijiang River Basin, as well as the profiles of the study subarea lines.</p>
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<p>The change trends of ecosystem service value per square kilometer and area of land use types with lateral gradient.</p>
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<p>Variation trend of each ecosystem and total service value with the lateral gradient.</p>
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<p>Distribution of service value at the different lateral gradient levels in eight ecosystems.</p>
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<p>Variation in the trends for the mean ESV of land with the upstream and downstream gradient.</p>
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<p>Ecosystem service values provided by different ecosystems in 10 zones along the river.</p>
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<p>Fitting results of the geographically weighted regression (GWR) model: (<b>a</b>) goodness-of-fit (R<sup>2</sup>); (<b>b</b>) fit constant t results.</p>
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<p>Spatial distribution of regression coefficients between each driving factor and ecosystem service in the Guangdong section of the Xijiang River.</p>
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15 pages, 3146 KiB  
Article
The Composition and Assembly of Soil Microbial Communities Differ across Vegetation Cover Types of Urban Green Spaces
by Yangyi Zhou and Jiangping Wang
Sustainability 2023, 15(17), 13105; https://doi.org/10.3390/su151713105 - 31 Aug 2023
Cited by 2 | Viewed by 1662
Abstract
Soil microorganisms play an important role in urban green spaces by providing ecological functions. However, information on the structure and assembly of microbial communities and the public risk of pathogenic bacteria in urban green spaces remains elusive. Here, we conducted a field survey [...] Read more.
Soil microorganisms play an important role in urban green spaces by providing ecological functions. However, information on the structure and assembly of microbial communities and the public risk of pathogenic bacteria in urban green spaces remains elusive. Here, we conducted a field survey on soil organisms in different vegetation cover types of urban green spaces (e.g., grasslands, shrublands, and woodlands) based on 16 S rRNA gene amplicon sequencing. We found that soil microbial communities in grasslands were dominated by Pseudomonadota, Acidobacteriota, Actinomycetota, and Chloroflexota. The diversity and niche breadth of the microbial communities in grasslands showed differences compared to shrublands and woodlands. Stochastic processes, which contribute to community assembly in grasslands, were lower compared to shrublands and woodlands, dominating the soil microbial community assembly of urban green spaces. Compared with soil microbial communities in scrublands and woodlands, the network of soil microbial communities in grasslands was simpler and had a weaker stability. Furthermore, the value of the microbial index of pathogenic bacteria in the observed green spaces was 0.01, which means that the risk of potential pathogens in green spaces was low. This study provides crucial information for the sustainable management of urban green spaces by regulating soil microorganisms, offering novel insights into the public health risks associated with potential pathogenic bacteria in these green spaces. Full article
(This article belongs to the Section Soil Conservation and Sustainability)
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<p>The characteristics of soil microbial communities in urban greenspaces. (<b>a</b>) The composition of soil microbial communities at the phylum level; (<b>b</b>) the alpha diversity of soil microbial communities; (<b>c</b>) the niche breadth of the microbial communities; (<b>d</b>) the generalists and specialists in different categories of taxa.</p>
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<p>Impact of environmental variables on soil microbial communities. (<b>a</b>) Non-metric multidimensional scaling (NMDS) analysis of the relationship between the environmental variables and microbial communities; (<b>b</b>) the importance of the major parameters assessed using multiple linear regression models of alpha diversity.</p>
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<p>Co-occurrence networks of soil microbial taxa and community stability analysis. (<b>a</b>) Co-occurring network of microorganisms in soil communities. Each dot represents an ASV, and each edge correlation, with R &gt; 0.5. The dot size corresponds to the ASV’s relative abundance. (<b>b</b>) the relationship between the major network’s module for the grasslands, shrublands, and woodlands and environmental variables; (<b>c</b>) Network-based negative/positive cohesions in the three types of greenspaces; (<b>d</b>) Robustness analysis displaying the relationship between the proportion of removed nodes and natural connectivity. Larger shifts in the same proportion indicate that there is less robustness or stability within microbial networks. Asterisks indicate statistical significance (** <span class="html-italic">p</span> &lt; 0.01; * <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Soil microbial community assembly in grasslands, shrublands, and woodlands.</p>
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<p>The composition of putative pathogens and the microbial index of pathogenic bacteria in urban green spaces. (<b>a</b>) Composition of animal, plant, and zoonotic pathogens in urban green spaces; (<b>b</b>) comparison of MIP among grasslands, shrublands, and woodlands; (<b>c</b>) canonical correspondence analysis (CCA) of the environmental variables’ relative contributions to pathogens.</p>
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19 pages, 3002 KiB  
Article
Multitemporal Land Use and Cover Analysis Coupled with Climatic Change Scenarios to Protect the Endangered Taxon Asphodelus bento-rainhae subsp. bento-rainhae
by Alice Maria Almeida, Fernanda Delgado, Natália Roque, Maria Margarida Ribeiro and Paulo Fernandez
Plants 2023, 12(16), 2914; https://doi.org/10.3390/plants12162914 - 10 Aug 2023
Cited by 1 | Viewed by 1468
Abstract
Climate change and land use and land cover (LULC) change are impacting the species’ geographic distribution, causing range shifts and reducing suitable habitats. Asphodelus bento-rainhae subsp. bento-rainhae (AbR) is an endangered endemic plant restricted to Serra da Gardunha (Portugal), and knowledge of those [...] Read more.
Climate change and land use and land cover (LULC) change are impacting the species’ geographic distribution, causing range shifts and reducing suitable habitats. Asphodelus bento-rainhae subsp. bento-rainhae (AbR) is an endangered endemic plant restricted to Serra da Gardunha (Portugal), and knowledge of those changes will help to design conservation measures. MaxEnt was used to model AbR’s current distribution and project it into the future, 2050, using the Shared Socioeconomic Pathway SSP3-7. The Portuguese LULC maps from 1951–1980, 1995, 2007, and 2018 were used to assess and quantify LULC changes over time. The results showed that the AbR current predicted distribution matches its actual known distribution, which will not be affected by future predicted climate change. The significant LULC changes were observed during the study periods 1951–1980 to 2018, particularly between 1951–1980 and 1995. Scrubland and Agriculture decreased by 5% and 2.5%, respectively, and Forests increased by 4% in the study area. In the occurrence area, Agriculture increased, and Forests decreased between 1980 and 2018, due to Orchard expansion (34%) and declines in Chestnut (16.9%) and Pine (11%) areas, respectively. The use of species distribution models and the LULC change analysis contributed to understanding current and future species distribution. The LULC changes will have a significant impact on future species distribution. To prevent the extinction of this endemic species in the future, it is crucial to implement conservation measures, namely species monitoring, replantation, and germplasm conservation, in addition to guidelines for habitat conservation. Full article
(This article belongs to the Section Plant Ecology)
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<p>The response curves of predicted suitability values for the selected environmental variables. Mean diurnal range (<b>a</b>), Temperature seasonality (<b>b</b>), Temperature annual range (<b>c</b>), Annual precipitation (<b>d</b>), Precipitation seasonality (<b>e</b>), Aspect (<b>f</b>), and Soil type (<b>g</b>). The soil type description is in <a href="#plants-12-02914-t0A1" class="html-table">Table A1</a>.</p>
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<p>Predicted habitat suitability: Current (<b>a</b>) and Future—2050 (<b>c</b>). Presence-absence maps: Current (<b>b</b>) and Future—2050 (<b>d</b>). Suitability areas (%) in the present and for the future (2050) (<b>e</b>). Absence/Presence areas (%) (<b>f</b>). Suitability class range: [0.0–0.2[, non-suitable area; [0.2–0.4[, low-suitability area; [0.4–0.6[, regular-suitability area; [0.6–0.8[, medium-suitability area; and [0.8–1.0], high-suitability area.</p>
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<p>The LULC changes in the study area from 1951–1980 to 2018. MAF1951-80 (<b>a</b>), COS1995 (<b>b</b>), COS2007 (<b>c</b>), and COS2018 (<b>d</b>). The LULC class description for the study area (SA) is in <a href="#plants-12-02914-t0A2" class="html-table">Table A2</a>.</p>
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<p>The LULC changes in the study area between two consecutive periods: 1951–1980–1995, 1995–2007, and 2007–2018.</p>
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<p>The LULC changes in occurrence area from 1951–1980 to 2018. MAF1951–1980 (<b>a</b>), COS1995 (<b>b</b>), COS2007 (<b>c</b>), and COS2018 (<b>d</b>). The LULC class description for the occurrence area (OA) is in <a href="#plants-12-02914-t0A2" class="html-table">Table A2</a>.</p>
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<p>The LULC changes between two consecutive periods: 1951–1980–1995, 1995–2007, and 2007–2018, in the species’ occurrence area.</p>
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<p>The LULC changes between 1951–1980 and 2018 in species occurrence area (<b>a</b>). The LULC inter-class transitions: Agriculture (<b>b</b>); Fruit orchards (<b>c</b>); Other oaks (<b>d</b>); Chestnut (<b>e</b>); and Pine woods (<b>f</b>).</p>
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<p>Location of the study area (SA—black line). Serra da Gardunha Regional Protected Landscape (red line). Spatial distribution of AbR occurrences (Gray dots) and the corresponding occurrence area (OA—green line).</p>
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<p>The soil type in the study area and species occurrences. The soil type description and codes as in <a href="#plants-12-02914-t0A1" class="html-table">Table A1</a>.</p>
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16 pages, 3824 KiB  
Article
Modeling Hydrological Responses to Land Use Change in Sejnane Watershed, Northern Tunisia
by Manel Mosbahi, Zeineb Kassouk, Sihem Benabdallah, Jalel Aouissi, Rihab Arbi, Mouna Mrad, Reginald Blake, Hamidreza Norouzi and Béchir Béjaoui
Water 2023, 15(9), 1737; https://doi.org/10.3390/w15091737 - 30 Apr 2023
Cited by 4 | Viewed by 2351
Abstract
Land use change is a crucial driving factor in hydrological processes. Understanding its long-term dynamics is essential for sustainable water resources management. This study sought to quantify and analyze land use change between 1985 and 2021 and its impacts on the hydrology of [...] Read more.
Land use change is a crucial driving factor in hydrological processes. Understanding its long-term dynamics is essential for sustainable water resources management. This study sought to quantify and analyze land use change between 1985 and 2021 and its impacts on the hydrology of the Sejnane watershed, northern Tunisia. Remote sensing and a SWAT model using the SUFI-2 algorithm to identify the most sensitive parameters were used to achieve this objective. Land use maps were developed for 1985, 2001 and 2021. For the last 37 years, the watershed experienced a slight decrease in forest, scrubland and forage crops, a significant reduction in grassland, and a conspicuous expansion of olive trees and vegetable crops. Given the scarcity of observed discharge data, a SWAT model was calibrated for the period 1997–2010 and validated for 2011–2019. Model performance was good for both calibration (NSE = 0.78, PBIAS = −6.6 and R2 = 0.85) and validation (NSE = 0.70, PBIAS = −29.2 and R2 = 0.81). Changes in land use strongly affected the water balance components. Surface runoff and percolation were the most influenced, showing an increase in runoff and a decrease in percolation by 15.5% and 13.8%, respectively. The results revealed that the construction of the Sejnane dam, the extension of irrigated perimeters and olive tree plantations were the major contributors to changes in hydrology. Full article
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<p>Location of the Sejnane river basin.</p>
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<p>Slope classes (<b>a</b>) and soil map (<b>b</b>) of the Sejnane river basin.</p>
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<p>The methodological framework for model calibration and land use change assessment.</p>
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<p>Land use yearly maps of the study area for 1985, 2001 and 2021.</p>
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<p>Percentage of land use classes for 1985, 2001 and 2021.</p>
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<p>Measured and simulated monthly streamflow for the calibration period.</p>
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<p>Measured and simulated monthly streamflow for the validation period.</p>
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<p>Mean monthly water balance components for different land use conditions. (<b>a</b>) Water yield, (<b>b</b>) surface runoff, (<b>c</b>) Lateral flow and (<b>d</b>) Evapotranspiration.</p>
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<p>Spatial and temporal change in evapotranspiration (<b>a</b>), surface runoff (<b>b</b>) and percolation (<b>c</b>) in the watershed between 1985 and 2021.</p>
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18 pages, 7666 KiB  
Article
Characterization of Polylepis tarapacana Life Forms in the Highest-Elevation Altiplano in South America: Influence of the Topography, Climate and Human Uses
by Victoria Lien López, Lucia Bottan, Guillermo Martínez Pastur, María Vanessa Lencinas, Griet An Erica Cuyckens and Juan Manuel Cellini
Plants 2023, 12(9), 1806; https://doi.org/10.3390/plants12091806 - 28 Apr 2023
Cited by 3 | Viewed by 2773
Abstract
In the upper vegetation limit of the Andes, trees change to shrub forms or other life forms, such as low scrubs. The diversity of life forms decreases with elevation; tree life forms generally decrease, and communities of shrubs and herbs increase in the [...] Read more.
In the upper vegetation limit of the Andes, trees change to shrub forms or other life forms, such as low scrubs. The diversity of life forms decreases with elevation; tree life forms generally decrease, and communities of shrubs and herbs increase in the Andean highlands. Most of treeline populations in the northwestern Argentina Altiplano are monospecific stands of Polylepis tarapacana, a cold-tolerant evergreen species that is able to withstand harsh climatic conditions under different life forms. There are no studies for P. tarapacana that analyze life forms across environmental and human impact gradients relating them with environmental factors. This study aims to determine the influence of topographic, climatic, geographic and proxies to human uses on the occurrence of life forms in P. tarapacana trees. We worked with 70 plots, and a new proposal of tree life form classification was presented for P. tarapacana (arborescent, dwarf trees, shrubs and brousse tigrée). We describe the forest biometry of each life form and evaluate the frequency of these life forms in relation to the environmental factors and human uses. The results show a consistency in the changes in the different life forms across the studied environmental gradients, where the main changes were related to elevation, slope and temperature. Full article
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<p>Classification of life forms in <span class="html-italic">P. tarapacana.</span> Ar: Arborescent; Dt: Dwarf tree; Sh: Shrubs; Bt: Brousse tigrée. The red line in the photo indicates the vertical cut that is observed in the graph on the left.</p>
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<p>Kruskal–Wallis test for the diameter, height, tree crown and crown spread ratio of <span class="html-italic">P. tarapacana</span> life forms. Different letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.05) by Conover–Iman test.</p>
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<p>Topographic, climatic and human use factors classified by the frequency of life forms. Relationship among topographic variables ((<b>A</b>) Elevation and slope, (<b>B</b>) Aspects), climatic ((<b>C</b>) temperature and precipitation) and human use ((<b>D</b>) human footprint and distance to towns). Bars indicate the standard deviation of each axis. Elevation in m a.s.l.; Slope in degree; S|N: North Aspect; W|E: East aspect. The aspects factors were calculated as sine and cosine functions, where sine values range from −1 (west) to 1 (east), while cosine values range from −1 (south) to 1 (north). AMT: Annual mean temperature in °C; AP: Annual precipitation in mm.yr<sup>−1</sup>; HF: Human footprint; DTT: Distance to towns in km. Ar: Arborescents; Sh: Shrubs; Dt: Dwarf trees; Bt: Brousse tigrée; M: Multiple forms.</p>
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<p>Distribution of <span class="html-italic">Polylepis tarapacana</span> forests (green) in the study area (Altiplano, Argentina), showing plots (red circles), towns (black circles) and contour lines, at 4000 m a.s.l. (narrow line), 4500 m a.s.l. (medium line) and 5000 m a.s.l. (tick line). Modified from López et al. [<a href="#B23-plants-12-01806" class="html-bibr">23</a>].</p>
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<p>Determination of the height, diameter at the base, crown diameter of the maximum axis and of the axis at 90 degrees for each life forms in <span class="html-italic">P. tarapacana</span>. H: height; DAB: diameter at the base of the tree; Ar: Arborescent; Dt: Dwarf tree; Sh: Shrubs; Bt: Brousse tigrée.</p>
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22 pages, 19768 KiB  
Article
Quantifying the Unvoiced Carbon Pools of the Nilgiri Hill Region in the Western Ghats Global Biodiversity Hotspot—First Report
by M. Jagadesh, Cherukumalli Srinivasarao, Duraisamy Selvi, Subramanium Thiyageshwari, Thangavel Kalaiselvi, Aradhna Kumari, Santhosh Kumar Singh, Keisar Lourdusamy, Ramalingam Kumaraperumal, Victor Allan, Munmun Dash, P. Raja, U. Surendran and Biswajit Pramanick
Sustainability 2023, 15(6), 5520; https://doi.org/10.3390/su15065520 - 21 Mar 2023
Cited by 6 | Viewed by 2189
Abstract
Accelerating land-use change (LUC) in the Nilgiri Hill Region (NHR) has caused its land to mortify. Although this deterioration has been documented, the destruction of buried gem soil has not been reported. Therefore, this study was conducted to assess the impact of LUC [...] Read more.
Accelerating land-use change (LUC) in the Nilgiri Hill Region (NHR) has caused its land to mortify. Although this deterioration has been documented, the destruction of buried gem soil has not been reported. Therefore, this study was conducted to assess the impact of LUC on soil-carbon dynamics in the six major ecosystems in the NHR: croplands (CLs), deciduous forests (DFs), evergreen forests (EFs), forest plantations (FPs), scrublands (SLs), and tea plantations (TPs). Sampling was conducted at selected sites of each ecosystem at three depth classes (0–15, 15–30, and 30–45 cm) to quantify the carbon pools (water-soluble carbon, water-soluble carbohydrates, microbial biomass carbon, microbial biomass nitrogen, dehydrogenase, and different fractions of particulate organic carbon). We found that the LUC significantly decreased the concentration of carbon in the altered ecosystems (49.44–78.38%), with the highest being recorded at EF (10.25%) and DF (7.15%). In addition, the effects of the LUC on the aggregate size of the organic carbon were dissimilar across all the aggregate sizes. The relatively high inputs of the aboveground plant residues and the richer fine-root biomass were accountable for the higher concentration of carbon pools in the untouched EFs and DFs compared to the SLs, FPs, TPs, and CLs. The results of the land-degradation Index (LDI) depicted the higher vulnerability of TP (−72.67) and CL (−79.00). Thus, our findings highlight the global importance of LUC to soil quality. Henceforth, the conservation of carbon pools in fragile ecosystems, such as the NHR, is crucial to keep soils alive and achieve land-degradation neutrality. Full article
(This article belongs to the Section Soil Conservation and Sustainability)
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<p>Distribution of sampling sites in different ecosystems of NHR.</p>
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<p>Soil-carbon pools under different ecosystems of NHR. The figure represents the effect of land-use change on water-soluble organic carbon (WSOC) mg kg<sup>−1</sup>, water-soluble carbohydrates (WSC) mg kg<sup>−1</sup>, dehydrogenase μg TPF g<sup>−1</sup>day<sup>−1</sup>, microbial biomass carbon (MBC) mg kg<sup>−1</sup>, and microbial biomass nitrogen (MBN) mg kg<sup>−1</sup> in different ecosystems of the Nilgiri Hill Region (NHR). Histograms with distinct letters are significantly different (<span class="html-italic">p</span> &lt; 0.01) according to DMRT. At depths between 0–15 cm and 15–30 cm, there was a slight drop in WSC in EF, FP, and CL compared to DF, SL, and TP.</p>
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<p>Aggregate-size organic carbon (ASOC) (g kg<sup>−1</sup>) in NHR. The figure represents the effect of land-use change on aggregate-size organic carbon (ASOC) ((2 mm), (0.25 mm), (0.053 mm), and (&lt;0.053 mm)) (g kg<sup>−1</sup>) under different ecosystems in Nilgiri Hill Region (NHR). Histograms with distinct letters are significantly different (<span class="html-italic">p</span> &lt; 0.01) according to DMRT.</p>
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<p>Distribution of total organic carbon and carbon pools under different ecosystems in NHR. The correlation values with * = significant correlations. Significant codes: 0 “***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1). Water-soluble organic carbon (WSOC) mg kg<sup>−1</sup>; water-soluble carbohydrates (WSC) mg kg<sup>−1</sup>; dehydrogenase (μg TPF g<sup>−1</sup>day<sup>−1</sup>); microbial biomass carbon (MBC) (mg kg<sup>−1</sup>); microbial biomass nitrogen (MBN) (mg kg<sup>−1</sup>); aggregate-size organic carbon (ASOC) (2 mm, 0.25 mm, 0.053 mm, &lt;0.053 mm) g kg<sup>−1</sup>.</p>
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<p>Principal component analysis of carbon pools indifferent ecosystems in NH. The PCA depicts the impact of land-use change on soil-carbon status. ASOC (2 mm), TOC, dehydrogenase, MSC, WSCarb, and WSC accounted for 58.7% of variability, whereas the ASOC (0.25 mm, 0.053 mm, &lt;0.053 mm) contributed 13.9% of variability among the different ecosystems in NHR. The principal components (1 and 2) with variable clustering at the left end of the biplot make the evergreen and deciduous forest unique, due to its high concentration of TOC and carbon pools. In both dimensions (1 and 2), the cropland and tea plantation with minimal TOC and carbon pools were far away from the evergreen and deciduous-forest ecosystems. Total organic carbon (TOC), water-soluble organic carbon (WSC), water-soluble carbohydrates (WS Carb), microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), aggregate-size organic carbon (ASOC) (2 mm, 0.25 mm, 0.053 mm, &lt;0.053 mm).</p>
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19 pages, 4517 KiB  
Article
Status of Ecosystem Services in Abandoned Mining Areas in the Iberian Peninsula: Management Proposal
by María González-Morales, Mª Ángeles Rodríguez-González and Luis Fernández-Pozo
Toxics 2023, 11(3), 275; https://doi.org/10.3390/toxics11030275 - 17 Mar 2023
Cited by 1 | Viewed by 1482
Abstract
An abandoned sphalerite mining area in the southwest (SW) of the Iberian Peninsula was studied to evaluate the impact that the presence of metal(loid)s has on soil and ecosystem health. Five zones were delimited: sludge, dump, scrubland, riparian zone, and dehesa. Critical total [...] Read more.
An abandoned sphalerite mining area in the southwest (SW) of the Iberian Peninsula was studied to evaluate the impact that the presence of metal(loid)s has on soil and ecosystem health. Five zones were delimited: sludge, dump, scrubland, riparian zone, and dehesa. Critical total levels of lead (Pb), zinc (Zn), thallium (Tl), and chromium (Cr), well above the limit indicative of toxicity problems, were found in the areas close to the sources of contamination. Pb-Zn concentrations were very high in the riparian zone, reaching values of 5875 mg/kg Pb and 4570 mg/kg Zn. The whole area is classifiable as extremely contaminated with Tl, with concentrations above 370 mg/kg in the scrubland. Cr accumulation mainly occurred in areas away from the dump, with levels up to 240 mg/kg in the dehesa. In the study area, several plants were found growing luxuriantly despite the contamination. The measured metal(loid)s content is the cause of a significant decrease in ecosystem services, resulting in unsafe soils for food and water production, so the implementation of a decontamination program is advisable. The plant species Retama sphaerocarpa, present in the sludge, scrubland, riparian zone, and dehesa, is postulated as suitable for use in phytoremediation. Full article
(This article belongs to the Special Issue Phytotoxicity of Heavy Metals in Contaminated Soils)
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<p>Location of the San Rafael mine (Azuaga, Spain).</p>
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<p>General map of the study area and sampling points: (1) mining sludge, (2) dump, (3) shrubland, (4) riparian zone and (5) dehesa.</p>
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<p>Total mean concentrations of the metals studied versus values for the NGR (Generic Reference Levels) in each of the zones. Mining sludge (n = 3), shrubland (n = 4), riparian (n = 12), dehesa (n = 21), control (n = 3).</p>
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<p>Pollution distribution according to the I<sub>geo</sub> in the study area: (1) mining sludge, (2) dump, (3) shrubland, (4) riparian zone, and (5) dehesa. Soil (n = 37).</p>
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<p>Vegetation cover.</p>
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<p>Average concentration of metal(loid)s in vegetation. Mining sludge (n = 4), riparian (n = 29), dehesa (n = 49), shrubland (n = 8).</p>
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