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15 pages, 1850 KiB  
Article
Genetic Variation of Growth Traits and Seed Production in a Patagonian Native Pasture in Semiarid Rangelands Under Different Environmental Settings
by Aldana Soledad López, Nicolás Nagahama, Alejandro Aparicio, María Marta Azpilicueta, Verónica Guidalevich, Juan Pablo Angeli and Paula Marchelli
Plants 2025, 14(5), 736; https://doi.org/10.3390/plants14050736 - 27 Feb 2025
Viewed by 198
Abstract
Rangelands play a crucial socioeconomic and environmental role worldwide. In South America, desertification and overgrazing has led to their deterioration and declining productivity. Breeding programs that use native forage species of economic and ecological importance, such as Festuca pallescens (St. Yves) Parodi, may [...] Read more.
Rangelands play a crucial socioeconomic and environmental role worldwide. In South America, desertification and overgrazing has led to their deterioration and declining productivity. Breeding programs that use native forage species of economic and ecological importance, such as Festuca pallescens (St. Yves) Parodi, may provide locally adapted germplasm that enhances productivity without threatening local biodiversity. These programs may even promote the conservation of native species. To this end, we characterized the phenotypic variation of nondestructive variables (growth and reproductive traits) related to forage and seed production during spring and early summer (growth and reproductive periods). Plants from ten populations were grown under common garden conditions in two environmental settings (sites) over two years. By early summer of the second year, most populations maintained a consistent relative performance with higher values for basal diameter, height and synflorescence production at site 2. This suggests more favorable environmental conditions for the species and highlights their potential for enhancing both seed and forage production. The growth and reproductive traits were probably largely influenced by micro-environmental cues (i.e., soil type and moisture), showing predominantly plastic patterns. The populations displaying phenotypic plasticity and above-average values for both traits were selected for further evaluation in breeding programs. Full article
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<p>Growth traits (basal diameter and height) of the ten populations in each site, growth period, and year. Panels (<b>a</b>–<b>d</b>) show data from the first (<b>a</b>,<b>b</b>) and second (<b>c</b>,<b>d</b>) growth periods of 2018, while panels (<b>e</b>–<b>h</b>) display the same for 2019. Specifically, panels (<b>a</b>,<b>c</b>,<b>e</b>,<b>g</b>) represent basal diameter, and panels (<b>b</b>,<b>d</b>,<b>f</b>,<b>h</b>) represent height. The populations including symbol and number labels are in panel (<b>a</b>), and details about the growth measurements (basal diameter and height) are explained in the upper left of panel (<b>b</b>). Bars indicate the upper and lower limits of the confidence interval for the adjusted mean values of basal diameter and height calculated using linear mixed models for each population at each site. Sub-figure in panel b shows an illustration of the measurements.</p>
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<p>Reproductive traits of the ten populations at each site during the reproductive periods: Percentage of plants producing synflorescences in 2018 (<b>a</b>) and 2019 (<b>c</b>), and synflorescence production as the mean number of synflorescences produced by each population in 2018 (<b>b</b>) and 2019 (<b>d</b>) at each site. The bars represent the upper and lower limits of the confidence interval for the adjusted mean of each reproductive trait, calculated using linear mixed models for each population at each site.</p>
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<p>Graphical interpretation of the variation in basal diameter and synflorescence production at the end of the evaluated period across sites and populations using Multidimensional Scaling. Dotted lines indicate the average values for each variable.</p>
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<p>Maps showing the locations of the sampled populations and sites (<b>A</b>). Daily accumulated precipitation (DAP) and mean annual temperature (MAT) from 2017 to 2020 in site 1 (EEA Bariloche, <b>B</b>) and site 2 (CEAT, <b>C</b>) during the period of experimentation for both locations. Black lines indicate mean annual temperature, with upper and lower dotted lines representing mean maximum (MxT) and minimum (MnT) temperatures, respectively (right <span class="html-italic">y</span>-axis). The blue discontinuous line represents accumulated precipitation (DAP; left <span class="html-italic">y</span>-axis). Data provided by the Centre of Meteorological Information, National Meteorological Service, Defence Ministry, Argentina. Images illustrating the trial and basal diameter measurement using a digital caliper (top left), as well as synflorescence production (bottom left) at site 1 (<b>D</b>).</p>
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13 pages, 18607 KiB  
Communication
Updating the Distribution and Conservation Status of the Endemic Nabatean Thyme (Thymbra nabateorum)
by Ayman Abdulkarem, Ahmed Elgharib, Mohammed Darwish, Abdulaziz Assaeed, Ali Alenezi, Lourens Van Essen and Alaaeldin Soultan
Conservation 2025, 5(1), 9; https://doi.org/10.3390/conservation5010009 - 18 Feb 2025
Viewed by 482
Abstract
Nabatean thyme (Thymbra nabateorum (Danin & Hedge) Bräuchler) is a perennial herb species under the Lamiaceae family, first described in 1998. The species is thought to be endemic to Jordan with only six known records. However, recent fieldwork has uncovered new patches [...] Read more.
Nabatean thyme (Thymbra nabateorum (Danin & Hedge) Bräuchler) is a perennial herb species under the Lamiaceae family, first described in 1998. The species is thought to be endemic to Jordan with only six known records. However, recent fieldwork has uncovered new patches of Nabatean thyme in northwestern Saudi Arabia. This study aimed to determine the global conservation status and update the distribution of Nabatean thyme. To achieve this, we conducted extensive fieldwork and used the collected occurrences to calculate species Extent of Occurrence (EOO) and Area of Occupancy (AOO). We recorded Nabatean thyme in sandstone grooves within open plains at altitudes of 850 to 1350 m, with its largest population occurring outside its historical range, rendering it endemic to northwest Arabia. The primary threats to Nabatean thyme across its range include overgrazing, excessive harvesting for medicinal purposes, and habitat fragmentation. Nabatean thyme has an EOO of 47,585 km² and an AOO of 136 km². Accordingly, we recommend considering Nabatean thyme as an Endangered species under the B2ab(iii) and C2a(ii) IUCN criteria. We recommend integrating both in situ and ex situ conservation programs to improve the conservation status and ensure the sustainability of Nabatean thyme. Full article
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<p>The typical habitat of <span class="html-italic">Thymbra nabateorium</span> species.</p>
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<p>The map shows the study area and where Nabatean thyme was recorded.</p>
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<p>Population size of Nabatean thyme recorded during the field survey.</p>
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<p>Thymbra nabateorium shoot system (<b>left</b>), the stem (<b>top right</b>), axillary flowering node (<b>middle right</b>), flower (<b>bottom right</b>).</p>
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<p>Camel grazing was recorded within Nabatean thyme habitat during the survey.</p>
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<p>Individual Nabatean thyme experiencing drought pressure.</p>
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<p>Nabatean thyme individual experiencing grazing pressure.</p>
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16 pages, 6130 KiB  
Article
Prescribed Burns Reduce Early-Stage Shrub Encroachment in Semi-arid Grassland
by Teresa Alfaro-Reyna, Carlos Alberto Aguirre-Gutierrez, Juan Carlos de la Cruz Domínguez, Miguel Luna Luna, Dulce Flores-Rentería and Josué Delgado-Balbuena
Fire 2025, 8(2), 71; https://doi.org/10.3390/fire8020071 - 10 Feb 2025
Viewed by 511
Abstract
Wildfire is a key factor in regulating ecological processes in grassland ecosystems; however, changes in land use/cover have modified the intensity and frequency of fires as they occurred naturally. Different factors have caused a rise in woody vegetation in these ecosystems, leading to [...] Read more.
Wildfire is a key factor in regulating ecological processes in grassland ecosystems; however, changes in land use/cover have modified the intensity and frequency of fires as they occurred naturally. Different factors have caused a rise in woody vegetation in these ecosystems, leading to changes in species composition, diversity, and biogeochemical cycles. Prescribed burns are a tool for controlling and eradicating shrubs; however, their effectiveness depends on vegetation composition, biomass availability, and the objectives of restoration. We evaluated the effectiveness of fire as a shrub controller in a semi-arid grassland ecosystem. We measured several shrub dasometric parameters and the percentage of damage in ten 2000 m² plots three months after a prescribed burning was performed. Both crown height and width and total height were the main variables that explained the percentage of shrub damage by fire. Individuals with a height greater than 1.6 m and wide crowns did not suffer damage. Moreover, even though 97% of the total shrubs presented some fire damage, 86% recovered after the rain period. Our results show that fire could be an effective strategy to control early-growing shrubs, but on overgrazed arid lands it would be difficult to have enough biomass to implement burning programs. Full article
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<p>Location map of the study area in the Llanos de Ojuelos, Jalisco, Mexico. The study site is marked in yellow, while the sampling plots are shown in green.</p>
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<p>Changes in shrub abundance in the experimental site. Images correspond to the years 2011 (<b>a</b>) and 2022 (<b>b</b>; Google, s.f.). Aereal view of one of the four sites before (<b>c</b>) and after (<b>d</b>) the burning treatment. The black contour in the left image is the protection line, which was made one week before the prescribed burning.</p>
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<p>Environmental and soil water content (SWC) conditions observed in the two years of the prescribed burnings. Vertical dashed lines stand for dates of fire application; black and gray for sites 1 and 2, respectively, in 2021, and black and gray for sites 3 and 4, respectively, in 2022. Maximum and minimum temperatures (Tmax and Tmin, respectively) and precipitation (PPT).</p>
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<p>(<b>a</b>) Soil temperature at 1, 3, 5, and 10 cm depth during the burning treatments, and (<b>b</b>) soil temperature at three depths five days after fire treatment. The air temperature at three different heights over soil (<b>c</b>), and the temperature over the grass tussocks during the fire treatment (<b>d</b>). The shaded areas stand for 1 standard deviation of the mean.</p>
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<p>Fitted functions (normalized units) of relationships between fire response and dasometric variables (crown area, base diameter (diameter at 30 cm), and total height). Number of resprouts for <span class="html-italic">Mimosa biuncifera</span> (<b>a</b>–<b>c</b>) and for <span class="html-italic">Vachelia schaffneri</span> (<b>d</b>–<b>f</b>), and the percentage of fire damage for <span class="html-italic">V</span>. <span class="html-italic">schaffneri</span> (<b>g</b>–<b>i</b>). Dashed lines stand for thresholds of the response in the number of resprouts and fire damage.</p>
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16 pages, 1357 KiB  
Article
Mitigating Water Loss in Arid Lands: Buffelgrass as a Potential Replacement for Alfalfa in Livestock Feed
by Mouna Ghorbel, Ahmad Alghamdi, Faical Brini, Abdalmenem I. M. Hawamda and Khalil Mseddi
Agronomy 2025, 15(2), 371; https://doi.org/10.3390/agronomy15020371 - 30 Jan 2025
Viewed by 640
Abstract
In the dry regions of the Arabian Peninsula, such as Saudi Arabia, rangeland degradation and the decline of pasture species have significantly reduced phytomass production. The scarcity of grazing pastures has led to an expansion of alfalfa-irrigated fields, exacerbating the risk of water [...] Read more.
In the dry regions of the Arabian Peninsula, such as Saudi Arabia, rangeland degradation and the decline of pasture species have significantly reduced phytomass production. The scarcity of grazing pastures has led to an expansion of alfalfa-irrigated fields, exacerbating the risk of water shortages. This study is the first to systematically evaluate the adaptability and production potential of Cenchrus ciliaris accessions in the arid environment of Saudi Arabia. The objective of this study is to evaluate the potential of buffelgrass (C. ciliaris) as an alternative to alfalfa in irrigated crop systems for livestock production and to assess its suitability for reintroduction into degraded rangelands to enhance forage production. For this purpose, accessions of C. ciliaris were collected from five different sites in northern Saudi Arabia (Aja, Jameen, Zaitoun, Gaed, and Industrial zone) to select the most vigorous ecotypes to be introduced in the degraded lands and/or to be used as irrigated forage crop. This study shows that under full irrigation (2500-3000 mm year−1), alfalfa can produce 11.9 t ha−1 to 22.6 t ha−1 with a five-year average of 17 t ha−1. However, C. ciliaris can produce 9.3–18.4 t ha−1 with less water consumption than alfalfa (water supply is estimated at 400–500 mm year−1). The average was about 14.1 t ha−1. Our comparative study of these accessions showed that the Aja accession seemed to be the most salt tolerant, whereas the Jameen accession was the most well-developed, productive (18.4 t ha−1), and overgrazing resistant accession (940.3 g plant−1 after 3 cuts). Therefore, the Jameen accession is recommended for rangeland rehabilitation. In terms of chemical composition, C. ciliaris was less protein rich than alfalfa, but this can be compensated for by its high digestibility, estimated by neutral detergent fiber (NDF of 69.6%). This study identifies the Gaed and Jameen accessions as the most productive and grazing resistant, exhibiting drought and salt tolerance, making them suitable for use in irrigated systems to produce high green- and dry-matter yields or for reintroduction to rehabilitate degraded rangelands for rehabilitation purposes. Full article
(This article belongs to the Section Grassland and Pasture Science)
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<p>Localities of the accessions of <span class="html-italic">Cenchrus ciliaris</span> in Hail region, Saudi Arabia.</p>
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<p>Effect of salt concentrations on the germination of different accessions of <span class="html-italic">Cenchrus ciliaris</span> in Saudi Arabia (Hail Region).</p>
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17 pages, 9263 KiB  
Article
Mapping Vegetation Changes in Mongolian Grasslands (1990–2024) Using Landsat Data and Advanced Machine Learning Algorithm
by Mandakh Nyamtseren, Tien Dat Pham, Thuy Thi Phuong Vu, Itgelt Navaandorj and Kikuko Shoyama
Remote Sens. 2025, 17(3), 400; https://doi.org/10.3390/rs17030400 - 24 Jan 2025
Viewed by 971
Abstract
Grassland ecosystems provide a range of services in semi-arid and arid regions. However, they have significantly declined due to overgrazing and desertification. In the current study, we employed Landsat time series data (TM, OLI, OLI-2) spanning from 1990 to 2024, combined with vegetation [...] Read more.
Grassland ecosystems provide a range of services in semi-arid and arid regions. However, they have significantly declined due to overgrazing and desertification. In the current study, we employed Landsat time series data (TM, OLI, OLI-2) spanning from 1990 to 2024, combined with vegetation indices such as NDVI and SAVI, along with NDWI and digital elevation models (DEMs), to analyze land cover dynamics in the Ugii Lake watershed area, Mongolia. By integrating multisource remote sensing data into the advanced XGBoost (extreme gradient boosting) machine learning algorithm, we achieved high classification accuracy, with overall accuracies exceeding 94% and Kappa coefficients greater than 0.92. The results revealed a decline in montane grasslands (−6.2%) and an increase in other grassland types, suggesting ecosystem redistribution influenced by climatic and anthropogenic factors. Cropland exhibited resilience, recovering from a significant decline in the 1990s to moderate growth by 2024. Our findings highlight the stability of barren land and underscore pressures from ecological degradation and human activities. This study provides up-to-date statistical data to support decision-making in the conservation and sustainable management of grassland ecosystems in Mongolia under changing climatic conditions. Full article
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<p>Location map of the study area at Ugii Lake in Mongolia.</p>
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<p>Proposed flowchart used to monitor vegetation changes in this study.</p>
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<p>Maps of vegetation and grassland types between 1990 and 2024.</p>
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<p>Land cover types as percentages of the total land.</p>
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<p>Sankey diagrams showing land cover changes from 1990 to 2024.</p>
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<p>Vegetation dynamics at Ugii Lake, Mongolia.</p>
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24 pages, 6160 KiB  
Article
Transboundary Impacts of NO2 on Soil Nitrogen Fixation and Their Effects on Crop Yields in China
by Jinhui Xie, Peiheng Yu and Xiangzheng Deng
Agriculture 2025, 15(2), 208; https://doi.org/10.3390/agriculture15020208 - 18 Jan 2025
Viewed by 920
Abstract
Nitrogen dioxide (NO2) impacts climate, air quality, soil nitrogen fixation, and crop production, yet its transboundary impacts remain unclear. This study combines 15 global datasets to assess nitrogen’s transboundary impacts on crop yields and soil health. We use machine learning to [...] Read more.
Nitrogen dioxide (NO2) impacts climate, air quality, soil nitrogen fixation, and crop production, yet its transboundary impacts remain unclear. This study combines 15 global datasets to assess nitrogen’s transboundary impacts on crop yields and soil health. We use machine learning to develop yield prediction models for major grain crops (maize, rice, soybean, and wheat) affected by NO2. Our findings indicate stable soil nitrogen fixation in China from 2015 to 2020, although overgrazing and deforestation may cause declines. Increasing soil total nitrogen content by 0.62–2.1 g/kg can reduce NO2 by 10–30%. Our research indicates that the current agricultural environments for major grain crops (58.5–94.2%) have already exceeded the NO2 concentration range that crops can tolerate, particularly in regions near northern urban clusters. This highlights the need for regional interventions, such as precision nitrogen fertilizer management, to enhance both soil nitrogen fixation and crop yields. Scenario analysis suggests that NO2 control can boost maize and rice yields in a greener context, while increasing total nitrogen content improves wheat and soybean yields. This provides a solution for advancing sustainable agriculture by linking nitrogen cycle management with improved crop yields and environmental sustainability. Full article
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<p>Framework of data collection and statistical modeling process. Phenological data included evapotranspiration (ET), average surface temperature (AT), leaf area index (LAI), normalized difference vegetation index (NDVI), precipitation (Precip. Soil data included silt, clay, bulk density (bdod), total nitrogen content (nitrogen), pH in H<sub>2</sub>O (pHH<sub>2</sub>O), sand, cation exchange capacity at pH7 (cec), soil organic carbon (soc). Terms in parentheses refer to key soil and environmental metrics. The crop yield data is from Spatial Production Allocation Model (SPAM) database 2020 v1.0.</p>
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<p>Major grain-producing regions and the distribution of total nitrogen density in croplands of China. (<b>a</b>) Distribution of arable land in the major grain-producing regions of rice and its total soil nitrogen density, mainly in (<b>1</b>) the three northeastern provinces, and (<b>2</b>) the southern provinces. (<b>b</b>) Distribution of cultivated land and soil total nitrogen density in major wheat-producing areas is primarily located in the (<b>3</b>) north, (<b>4</b>) southwest, and (<b>5</b>) northern regions. (<b>c</b>) Distribution of cultivated land and soil total nitrogen density in major maize-producing areas, including (<b>6</b>) the three northeastern provinces, (<b>7</b>) Sichuan, Yunnan, Guizhou regions, Inner Mongolia, the North China Plain, and the (<b>8</b>) Xinjiang region. (<b>d</b>) Distribution of cultivated land and soil total nitrogen density in soybean-producing areas is mainly concentrated in (<b>9</b>) the northeast, (<b>10</b>) the southwest, and (<b>11</b>) parts of the North China Plain. The division of major grain-producing regions was based on the 2020 national statistics of crop production; spatial distribution data for cultivated land were sourced from the 30 m resolution land use dataset of CNLUCC [<a href="#B32-agriculture-15-00208" class="html-bibr">32</a>] in 2020; total nitrogen concentration data were derived from the Basic Soil Property dataset of high-resolution China Soil Information Grids [<a href="#B33-agriculture-15-00208" class="html-bibr">33</a>].</p>
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<p>The overall trend of soil TNC and its variation across different land types. (<b>a</b>) Flow chart of the land transfer matrix in China from 2015 to 2020. (<b>b</b>) Statistical analysis of the TNC of different land types. (<b>c</b>) Evolution of TNC during urbanization in China. The land transfer matrix was plotted using the CNLUCC dataset, total soil nitrogen content data were obtained from SoilGrids, corresponding land types were referred to MODIS land classification data.</p>
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<p>Linear regression analysis between TNC and NO<sub>2</sub> for major grain crops. (<b>a</b>) The scatter plot of the linear relationship between TNC and NO<sub>2</sub> for total sample points (R = −0.76). (<b>b</b>) Linear relationship of TNC and NO<sub>2</sub> for 202 maize sample points (R = −0.76). (<b>c</b>) Linear relationship of TNC and NO<sub>2</sub> for 267 rice sample points (R = −0.70). (<b>d</b>) Linear relationship of TNC and NO<sub>2</sub> for 224 soybean sample points (R = −0.84). (<b>e</b>) Linear relationship of TNC and NO<sub>2</sub> for 165 wheat sample points (R = −0.68).</p>
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<p>RFR bias dependence and SHAP scatter plots for the yields of major grain crops under influence of NO<sub>2</sub>. (<b>a</b>) RFR bias dependence and SHAP scatter plots for maize yields under influence of NO<sub>2</sub>. (<b>b</b>) RFR bias dependence and SHAP scatter plots for rice yields under influence of NO<sub>2</sub>. (<b>c</b>) RFR bias dependence and SHAP scatter plots for soybean yields under influence of NO<sub>2</sub>. (<b>d</b>) RFR bias dependence and SHAP scatter plots for wheat yields under influence of NO<sub>2</sub>.</p>
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<p>Spatial distribution of the optimal NO<sub>2</sub> concentration range for major grain crops in China. (<b>a</b>) Spatial distribution of the optimal NO<sub>2</sub> concentration range for maize in major maize-producing areas. (<b>b</b>) Spatial distribution of the optimal NO<sub>2</sub> concentration range for rice in major rice-producing areas. (<b>c</b>) Spatial distribution of the optimal NO<sub>2</sub> concentration range for soybean in major soybean-producing areas. (<b>d</b>) Spatial distribution of the optimal NO<sub>2</sub> concentration range for wheat in major wheat-producing areas. The legend shows the extent of NO<sub>2</sub> impact on different crops, with colors ranging from blue (low impact) to red (high impact). The red areas highlight regions where crops are more vulnerable to the adverse effects of NO<sub>2</sub>. The basemap is from Google Earth.</p>
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<p>Impact of all feature variables on major grain crops in XGBoost yield prediction models. (<b>a</b>) Impact of all feature variables on maize yield prediction models. (<b>b</b>) Impact of all feature variables on rice yield prediction models. (<b>c</b>) Impact of all feature variables on soybean yield prediction models. (<b>d</b>) Impact of all feature variables on wheat yield prediction models. The impact of different variables on crop yield is represented by SHAP values, and the magnitude of the variables’ eigenvalues is indicated by color.</p>
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<p>Crop yield predictions at different nitrogen fixation levels for SRES in 2030 and 2050. (<b>a</b>) Maize yield predictions at different nitrogen fixation levels for SRES in 2030 and 2050. (<b>b</b>) Rice yield predictions at different nitrogen fixation levels for SRES in 2030 and 2050. (<b>c</b>) Soybean yield predictions at different nitrogen fixation levels for SRES in 2030 and 2050. (<b>d</b>) Wheat yield predictions at different nitrogen fixation levels for SRES in 2030 and 2050. The nitrogen fixation levels include basic as usual (BAU), high nitrogen (HN), and low nitrogen (LN). The two SRES scenarios from the Intergovernmental Panel on Climate Change (IPCC) are A1 AIM (balanced) and B1 IMAGE (clean energy), in 2030 and 2050.</p>
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<p>Scatter plot of predicted vs. observed yields at BAU nitrogen fixation levels under different SRES. (<b>a</b>–<b>d</b>) Scatter plot of predicted vs. observed maize yield under the A1 AIM and B1 IMAGE scenarios. (<b>e</b>–<b>h</b>) Scatter plot of predicted vs. observed rice yield under the A1 AIM and B1 IMAGE scenarios. (<b>i</b>–<b>l</b>) Scatter plot of predicted vs. observed soybean yield under the A1 AIM and B1 IMAGE scenarios. (<b>m</b>–<b>p</b>) Scatter plot of predicted vs. observed wheat yield under the A1 AIM and B1 IMAGE scenarios.</p>
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<p>The dual dependence plots of TNC and NO<sub>2</sub> for the yields of major grain crops. (<b>a</b>) Partial dependence of NO<sub>2</sub> and TNC on maize yield. (<b>b</b>) Partial dependence of NO<sub>2</sub> and TNC on rice yield (kg/ha). (<b>c</b>) Partial dependence of NO<sub>2</sub> and TNC on soybean yield (kg/ha). (<b>d</b>) Partial dependence of NO<sub>2</sub> and TNC on wheat yield (kg/ha).</p>
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15 pages, 2123 KiB  
Article
The Effect of Goat Grazing on the Biodiversity of Pannonian Dry Grassland
by Karoly Penksza, Ferenc Pajor, Andrea Kevi, Zsombor Wagenhoffer, Laszló Sipos, Eszter Salata-Falusi, Peter Penksza, Peter Poti, Jozsef Berke, Denes Salata, Marta Bajnok and Szilard Szentes
Diversity 2025, 17(1), 13; https://doi.org/10.3390/d17010013 - 26 Dec 2024
Viewed by 593
Abstract
In this study, we analyzed the phytosociological data from four sample sites located in the Pannonian region. The study areas, ranging from 2.4 to 2.5 hectares, have been subjected to goat grazing and mowing for 24 years. N1: Nagyréde, an overgrazed pasture with [...] Read more.
In this study, we analyzed the phytosociological data from four sample sites located in the Pannonian region. The study areas, ranging from 2.4 to 2.5 hectares, have been subjected to goat grazing and mowing for 24 years. N1: Nagyréde, an overgrazed pasture with 24 goats; N2: Nagyréde, a mown field; C1: Csokvaomány, a lightly grazed pasture with 12 goats; and meadow C2: Csokvaomány, a site that is both mown and grazed. Six phytosociological surveys were conducted randomly in each area. We also considered the conservation value, biomass production, and forage values. Phytosociological data were processed using hierarchical cluster analysis and the non-parametric Kruskal–Wallis test. The overgrazed pasture (N1) exhibited the most degraded vegetation community, dominated by weeds and disturbance-tolerant species. The overgrazed (N1) pasture had a low forage value because of the different timing of treatments. Even in the lightly grazed pasture (C1), the proportion of species indicative of degradation was significant. The species composition of the areas indicated that the mown and subsequently grazed area (C2) had outstanding values. The species richness of C2 was twice that of the mown field (N2). Based on the present study, a combination of light grazing pressure and mowing is the most suitable approach for managing and economically utilizing these grasslands. Full article
(This article belongs to the Special Issue Ecology and Restoration of Grassland)
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<p>The location of the sample sites in Hungary (1: Nagyréde; 2: Csokvaomány).</p>
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<p>Classification of quadrats from the studied areas (N1: Overgrazed pasture in Nagyréde; N2: Hayfield in Nagyréde; C1: Pasture with low grazing pressure in Csokvaomány; C2: Meadow in Csokvaomány).</p>
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<p>Significant differences in grass (<b>A</b>) and leguminous (<b>B</b>) species at the sample sites, based on statistical evaluation and Dunn’s post hoc test with Bonferroni correction (N1: Overgrazed pasture in Nagyréde; N2: Hayfield in Nagyréde; C1: Pasture with low grazing pressure in Csokvaomány; C2: Meadow in Csokvaomány).</p>
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<p>Mean coverage (mean, standard deviation) and significant differences in weeds (<b>A</b>) and other species (<b>B</b>) at the sample sites, based on statistical evaluation and Dunn’s post hoc test with Bonferroni correction (N1: Overgrazed pasture in Nagyréde; N2: Hayfield in Nagyréde; C1: Pasture with low grazing pressure in Csokvaomány; C2: Meadow in Csokvaomány, *: significant difference).</p>
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<p>Mean coverage (mean, standard deviation) and significant differences in various plant categories: (<b>A</b>) Toxic species (-1); (<b>B</b>) Neutral, low-value species (0); (<b>C</b>) Low-value forage plants (1, 2, 3); (<b>D</b>) Useful forage plants (4, 5, 6); (<b>E</b>) Forage-improving species (7, 8), based on statistical evaluation and Dunn’s post hoc test with Bonferroni correction (N1: Overgrazed pasture in Nagyréde; N2: Hayfield in Nagyréde; C1: Pasture with low grazing pressure in Csokvaomány; C2: Meadow in Csokvaomány, *: significant difference).</p>
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<p>Distribution of species based on Pignatti’s life form types across the sample areas (N1: Overgrazed pasture in Nagyréde; N2: Hayfield in Nagyréde; C1: Pasture with low grazing pressure in Csokvaomány; C2: Meadow in Csokvaomány). (<span class="html-italic">H scap</span>: species with ascending stems; <span class="html-italic">H caesp</span>: tussock-forming species; <span class="html-italic">H ros</span>: rosette-forming perennials; <span class="html-italic">H rept</span>: perennials with stolons, runners, or rhizomes, <span class="html-italic">H bienn</span>: biennial species, <span class="html-italic">G bulb</span>: geophytes with bulbs; <span class="html-italic">G rhiz</span>: rhizomatous, creeping geophytes; <span class="html-italic">T scap</span>: annual species with ascending stems; <span class="html-italic">T ros</span>: rosette-forming annual species; <span class="html-italic">T caesp</span>: annual tussock species; <span class="html-italic">Ch rept</span>: creeping-stem dwarf shrubs; <span class="html-italic">Ch succ</span>: succulent dwarf shrubs).</p>
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<p>Shannon’s and Simpson’s diversity values of the examined sample areas. (N1: Overgrazed pasture in Nagyréde; N2: Hayfield in Nagyréde; C1: Pasture with low grazing pressure in Csokvaomány; C2: Meadow in Csokvaomány).</p>
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<p>Rényi diversity profiles of the investigated areas based on the species that occur. (N1: Overgrazed pasture in Nagyréde; N2: Hayfield in Nagyréde; C1: Pasture with low grazing pressure in Csokvaomány; C2: Meadow in Csokvaomány).</p>
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<p>The Rényi diversity profiles of the investigated areas are only based on <span class="html-italic">Fabaceae</span> species. (N1: Overgrazed pasture in Nagyréde; N2: Hayfield in Nagyréde; C1: Pasture with low grazing pressure in Csokvaomány; C2: Meadow in Csokvaomány).</p>
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20 pages, 15646 KiB  
Article
A New Grazing–Vegetation Tradeoff and Coordination Indicator: The Grazing Intensity and Vegetation Cover Harmonization Index (GVCI)
by Qinyi Huang, Jianjun Chen, Xinhong Li, Hucheng Li, Zizhen Chen, Yanping Lan, Ming Ling, Haotian You and Xiaowen Han
Agriculture 2025, 15(1), 27; https://doi.org/10.3390/agriculture15010027 - 26 Dec 2024
Viewed by 531
Abstract
Overgrazing typically leads to grassland vegetation degradation and reduction, which in turn triggers a series of ecological problems. Therefore, it is crucial to understand the effects of different Grazing Intensities (GIs) on the Vegetation Ecosystem (VE) to achieve sustainable grazing development. This study [...] Read more.
Overgrazing typically leads to grassland vegetation degradation and reduction, which in turn triggers a series of ecological problems. Therefore, it is crucial to understand the effects of different Grazing Intensities (GIs) on the Vegetation Ecosystem (VE) to achieve sustainable grazing development. This study proposes a new quantitative index, the Grazing Intensity and Vegetation Cover Harmonization Index (GVCI), based on multiple indicators such as fractional vegetation cover (FVC), net primary productivity (NPP), and GI. The GVCI was used to quantify the “Harmonization and Conflict” status between GI and the VE in 39 Prefecture-Level Cities (PLCs) of the Qinghai-Tibet Plateau (QTP) and to evaluate the sustainable development level of grazing in different regions. In addition, the Random Forest (RF) model was used to simulate the GVCI development trend of various PLCs from 2015 to 2040. The results showed the following: (1) The GVCI can effectively quantify the response relationship between GI and the VE. The overall GVCI of the QTP was in the “Harmonization” state, with the proportion of areas in the “Harmonization” state fluctuating upwards. (2) The level of economic development intuitively affects the harmonization between grazing and the VE. Gross Domestic Product (GDP) is one of the important indicators of economic development level. PLCs with higher GDP levels exhibited a strong positive correlation between the GVCI and regional GDP. (3) The simulation results indicate that an increasing number of PLCs on the QTP will shift toward a “Harmonization” state. However, some PLCs in the western regions were still in an “Overload” state, and there is a need for close monitoring of their grazing activities and VE dynamics. The GVCI proposed in this study provides a novel methodology for quantifying the complex relationship between GI and the VE. It offers important scientific support for the sustainable development of grazing in ecologically fragile areas such as the QTP. The research results can be a robust scientific basis for the government to formulate reasonable grazing plans. Full article
(This article belongs to the Section Digital Agriculture)
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<p>Location of study area (numbers in <a href="#agriculture-15-00027-f001" class="html-fig">Figure 1</a> represent different PLCs).</p>
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<p>Research methodology flowchart.</p>
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<p>Spatial and temporal patterns of GI in different PLCs from 1990 to 2015.</p>
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<p>Spatial and temporal variation patterns of QTP GVCI in different PLCs during 1990–2015; (<b>a</b>–<b>e</b>) GVCIs of PLCs in different periods of QTP; (<b>f</b>) land area ratio transfer matrix of QTP “Harmonization” and “Conflict” relationship state from 1990 to 2015.</p>
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<p>Correlation coefficient of GVCI and GDP; (<b>a</b>) spatial distribution of correlation between GVCI and GDP; (<b>b</b>) PLC with high negative correlation, and changes of FVC, NPP, and GI in 1990–2015; (<b>c</b>) PLC with high positive correlation, and changes of FVC, NPP, and GI in 1990–2015.</p>
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<p>GVCI fitting forecast results of PLCs from 2015 to 2040.</p>
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16 pages, 5793 KiB  
Article
RITA® Temporary Immersion System (TIS) for Biomass Growth Improvement and Ex Situ Conservation of Viola ucriana Erben & Raimondo
by Piergiorgio Capaci, Fabrizio Barozzi, Stefania Forciniti, Chiara Anglana, Helena Iuele, Rita Annunziata Accogli, Angela Carra, Marcello Salvatore Lenucci, Loretta L. del Mercato and Gian Pietro Di Sansebastiano
Plants 2024, 13(24), 3530; https://doi.org/10.3390/plants13243530 - 18 Dec 2024
Viewed by 731
Abstract
Viola ucriana Erben & Raimondo is a rare and endangered taxon, endemic to a limited area on Mount Pizzuta in northwestern Sicily, Italy. Its population is significantly threatened by anthropogenic activities, including fires, overgrazing, and habitat alterations. Temporary immersion systems (TISs) have proven [...] Read more.
Viola ucriana Erben & Raimondo is a rare and endangered taxon, endemic to a limited area on Mount Pizzuta in northwestern Sicily, Italy. Its population is significantly threatened by anthropogenic activities, including fires, overgrazing, and habitat alterations. Temporary immersion systems (TISs) have proven effective for large-scale propagation in various protected species, offering potential for ex situ conservation and population reinforcement of V. ucriana. This study aimed to establish a bioreactor-based micropropagation protocol for shoot multiplication and compare the efficacy of a TIS with that of conventional solid culture medium (SCM). Three different plant growth regulators (PGRs) were also compared: 6-benzylaminopurine (BA), zeatin, and meta-topolin-9-riboside (mTR). The starting material originated from seeds collected from mother plants in their natural environment. The best growth outcomes (in terms of shoot multiplication, shoot length, and relative growth rate) were achieved using THE RITA® TIS, with BA (0.2 mg/L) and mTR (0.5 or 0.8 mg/L) outperforming SCM. Anomalous or hyperhydric shoots were observed with all zeatin treatments (especially with 0.8 mg/L) in both the TIS and SCM, suggesting that this cytokinin is unsuitable for V. ucriana biomass production. The rooting phase was significantly improved by transferring propagules onto rockwool cubes fertilized with Hoagland solution. This approach yielded more robust roots in terms of number and length compared to the conventional agar-based medium supplemented with indole-3-butyric acid (IBA). Flow cytometry analysis confirmed the genetic fidelity of the regenerants from the optimal PGR treatments, showing that all plantlets maintained the diploid ploidy level of their maternal plants. Over 90% of the in vitro derived plantlets were successfully acclimatized to greenhouse conditions. This paper represents the first report of V. ucriana biomass multiplication using a RITA® bioreactor. The stability of the regenerants, confirmed by nuclei quantification via cytofluorimetry, provides guidance in establishing a true-to-type ex situ population, supporting conservation and future reinforcement efforts. Full article
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<p>Effect of culture system and PGR (0.2–0.5–0.8 mg/L BA, 0.2–0.5–0.8 mg/L <span class="html-italic">m</span>TR, 0.2–0.5–0.8 mg/L zeatin) on shoot multiplication and shoot length of <span class="html-italic">V. ucriana</span> after 4 weeks of culture. (<b>A</b>) Differences in number of shoots produced in SCM and RITA® TIS with different PGR concentrations. (<b>B</b>) Differences in shoot length produced in SCM and RITA® TIS with different PGR concentrations. (<b>C</b>) Selection of images showing morphological appearance of shoot multiplication and shoot length after 4 weeks of culture with best treatment (0.2 mg/L BA, 0.5 mg/L <span class="html-italic">m</span>TR, 0.8 mg/L <span class="html-italic">m</span>TR) and worst treatment (0.8 mg/L zeatin). Scale bar = 25 mm. Statistical analysis with two-way ANOVA with Tukey’s post hoc test (<span class="html-italic">p</span> &lt; 0.001). Different letters within bars indicate significant differences. Data presented as mean values ± standard error of three replications of 30 explants each for both culture systems.</p>
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<p>Effect of culture system and PGR (0.2–0.5–0.8 mg/L BA, 0.2–0.5–0.8 mg/L <span class="html-italic">m</span>TR, 0.2–0.5–0.8 mg/L Zeatin) on relative growth rate (RGR) of <span class="html-italic">V. ucriana</span> after 4 weeks of culture. (<b>A</b>) Differences in RGR index in SCM and RITA® TIS with different PGR concentrations. (<b>B</b>) Comparison between biomass produced with SCM and RITA® TIS with the best treatment (0.2 mg/L BA, 0.5 mg/L <span class="html-italic">m</span>TR, 0.8 mg/L <span class="html-italic">m</span>TR) and the worst one (0.8 mg/L zeatin) in terms of hyperhydric and unviable explants. Biomass appearance after 4 weeks of culture. Scale bar = 25 mm. Statistical analysis was conducted with two-way ANOVA with Tukey’s post hoc test (<span class="html-italic">p</span> &lt; 0.001). Different letters within bars indicate significant differences. Data are presented as mean values ± standard error of three replications of 30 explants each for both culture systems.</p>
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<p>Differences in number and length of roots grown (<b>A</b>) in rooting plugs with rockwool cubes and (<b>B</b>) in ½ MS medium with 2 mg/L IBA after 5 weeks. (<b>C</b>) Plantlets 3 months after potting up from rooting plugs (<b>C1</b>, <b>C2</b>) and from MS medium with 2 mg/L IBA (<b>C3</b>, <b>C4</b>) located int the Unisalento Botanical Garden greenhouse. Scale bars (<b>A</b>,<b>B</b>) = 10 mm. Scale bar (<b>C</b>) = 25 mm.</p>
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<p>Optimization of nuclei isolation method using leaves of <span class="html-italic">V. ucriana</span>. (<b>A</b>) Leaves were digested for 18 h using a digestive solution. (<b>B</b>) Protoplasts were separated from debris (mucilage, phenolic compounds, DNAse, RNAse, etc.), and the solution was washed with W5 buffer. (<b>C</b>) Nuclei were extracted from protoplasts using nuclei isolation buffer. (<b>D</b>) Nuclei were stained with propidium iodide (PI) before being analyzed with flow cytometry. Representative CLSM micrographs showing <span class="html-italic">V. ucriana</span> nuclei. BF and red channel (propidium iodide: λex 543 nm, λem 570–700 nm). Scale bars: 10 μm.</p>
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<p>Flow cytometry analysis for the determination of DNA ploidy level. Nuclei were stained with PI indicating the DNA content from <span class="html-italic">A. thaliana</span> (<b>A</b>) and <span class="html-italic">V. ucriana</span> originating from (<b>B</b>) mother plants, (<b>C</b>) 0.2 mg/L BAP, (<b>D</b>) 0.5 mg/L <span class="html-italic">m</span>TR, (<b>E</b>) 0.8 mg/L <span class="html-italic">m</span>TR. In all histograms, peaks represent 2C DNA content of plant materials.</p>
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26 pages, 6096 KiB  
Article
Evolution of Vegetation Coverage in the Jinan Section of the Basin of the Yellow River (China), 2008–2022: Spatial Dynamics and Drivers
by Dongling Ma, Zhenxin Lin, Qian Wang, Yifan Yu, Qingji Huang and Yingwei Yan
Forests 2024, 15(12), 2219; https://doi.org/10.3390/f15122219 - 16 Dec 2024
Viewed by 753
Abstract
The Yellow River Basin serves as a critical ecological barrier in China. However, it has increasingly faced severe ecological and environmental challenges, with soil erosion and overgrazing being particularly prominent issues. As an important region in the middle and lower reaches of the [...] Read more.
The Yellow River Basin serves as a critical ecological barrier in China. However, it has increasingly faced severe ecological and environmental challenges, with soil erosion and overgrazing being particularly prominent issues. As an important region in the middle and lower reaches of the Yellow River, the Jinan section of the Yellow River Basin is similarly affected by these problems, posing significant threats to the stability and sustainability of its ecosystems. To scientifically identify areas severely impacted by soil erosion and systematically quantify the effects of climate change on vegetation coverage within the Yellow River Basin, this study focuses on the Jinan section. By analyzing the spatio-temporal evolution patterns of the Normalized Difference Vegetation Index (NDVI), this research aims to explore the driving mechanisms behind these changes and further predict the future spatial distribution of NDVI, providing theoretical support and practical guidance for regional ecological conservation and sustainable development. This study employed the slope trend analysis method to examine the spatio-temporal variation characteristics of NDVI in the Jinan section of the Yellow River Basin from 2008 to 2022 and utilized the FLUS model to predict the spatial distribution of NDVI in 2025. The Optimal Parameters-based Geographical Detector (OPGD) model was applied to systematically analyze the impacts of four key driving factors—precipitation (PRE), temperature (TEM), population density (POP), and gross domestic product (GDP) on vegetation coverage. Finally, correlation and lag effect analyses were conducted to investigate the relationships between NDVI and TEM as well as NDVI and PRE. The research results indicate the following: (1) from 2008 to 2022, the NDVI values during the growing season in the Jinan section of the Yellow River Basin exhibited a significant increasing trend. This growth suggests a continuous improvement in regional vegetation coverage, likely influenced by the combined effects of natural and anthropogenic factors. (2) The FLUS model predicts that, by 2025, the proportion of high-density NDVI areas will rise to 55.35%, reflecting the potential for further optimization of vegetation coverage under appropriate management. (3) POP had a particularly significant impact on vegetation coverage, and its interaction with TEM, PRE, and GDP generated an amplified combined effect, indicating the dominant role of the synergy between socioeconomic and climatic factors in regional vegetation dynamics. (4) NDVI exhibited a significant positive correlation with both temperature and precipitation, further demonstrating that climatic conditions were key drivers of vegetation coverage changes. (5) In urban areas, NDVI showed a certain time lag in response to changes in precipitation and temperature, whereas this lag effect was not significant in suburban and mountainous areas, highlighting the regulatory role of human activities and land use patterns on vegetation dynamics in different regions. These findings not only reveal the driving mechanisms and influencing factors behind vegetation coverage changes but also provide critical data support for ecological protection and economic development planning in the Yellow River Basin, contributing to the coordinated advancement of ecological environment construction and economic growth. Full article
(This article belongs to the Section Forest Ecology and Management)
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<p>Study area. (<b>a</b>) China, (<b>b</b>) The Yellow River Basin, and (<b>c</b>) The Jinan Section of the Yellow River Basin.</p>
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<p>Flow chart of the study.</p>
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<p>Temporal variation characteristics of NDVI.</p>
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<p>The percentage of NDVI change trend during the planting season.</p>
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<p>Spatial distribution of NDVI trends. (<b>a</b>) 2008–2012, (<b>b</b>) 2013–2017, (<b>c</b>) 2018–2022, and (<b>d</b>) 2008–2022.</p>
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<p>Comparison of NDVI Distribution Between 2022 and 2025. (<b>a</b>) 2022, (<b>b</b>) 2025.</p>
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<p>Percentage Distribution of NDVI in 2022 and 2025.</p>
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<p>NDVI Conversion Relationships.</p>
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<p>Explanatory power of interactive detection of driving factors. (<b>a</b>) 2008, (<b>b</b>) 2013, (<b>c</b>) 2018, and (<b>d</b>) 2022.</p>
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<p>Percentage of correlation between NDVI and rainfall.</p>
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<p>Spatial distribution of the correlation analysis between NDVI and PRE. (<b>a</b>) 2008–2012, (<b>b</b>) 2013–2017, (<b>c</b>) 2018-2022, and (<b>d</b>) 2008–2022.</p>
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<p>Percentage of correlation between NDVI and TEM.</p>
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<p>Spatial distribution of the correlation analysis between NDVI and TEM. (<b>a</b>) 2008–2012, (<b>b</b>) 2013–2017, (<b>c</b>) 2018–2022, and (<b>d</b>) 2008–2022.</p>
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<p>Spatial distribution of the lagged relationship between NDVI and TEM in summer. (<b>a</b>) Current Month, (<b>b</b>) One Month Prior, and (<b>c</b>) Two Month Prior.</p>
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<p>Spatial distribution of the lagged relationship between NDVI and TEM in summer. (<b>a</b>) Current Month, (<b>b</b>) One Month Prior, and (<b>c</b>) Two Month Prior.</p>
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14 pages, 597 KiB  
Article
The “Ruined Landscapes” of Mediterranean Islands: An Ecological Framework for Their Restoration in the Context of SDG 15 “Life on Land”
by Reeya Ghose Roy, Leanne Camilleri and Sandro Lanfranco
Sustainability 2024, 16(22), 9771; https://doi.org/10.3390/su16229771 - 8 Nov 2024
Viewed by 885
Abstract
The “ruined landscapes” of the Mediterranean littoral are a consequence of millennia of human impact and include abandoned agricultural lands, deforested areas, and degraded coastal areas. One of the drivers is the historical pattern of land use, which has resulted in the clearing [...] Read more.
The “ruined landscapes” of the Mediterranean littoral are a consequence of millennia of human impact and include abandoned agricultural lands, deforested areas, and degraded coastal areas. One of the drivers is the historical pattern of land use, which has resulted in the clearing of vegetation, soil erosion, and overgrazing. These have caused significant damage to natural ecosystems and landscapes leading to soil degradation, loss of biodiversity, and the destruction of habitats. The UN Sustainable Development Goal 15 “Life on Land” recommends a substantial increase in afforestation (SDG 15.2). Whilst this goal is certainly necessary in places, it should be implemented with caution. The general perception that certain ecosystems, such as forests, are inherently more valuable than grasslands and shrublands contributes to afforestation drives prioritising quick and visible results. This, however, increases the possibility of misguided afforestation, particularly in areas that never supported forests under the present climatic conditions. We argue that in areas that have not supported forest ecosystems, targeted reinforcement of existing populations and recreation of historical ones is preferable to wholesale ecosystem modification disguised as afforestation. We present a possible strategy for targeted reinforcement in areas that never supported forests and that would still achieve the goals of SDGs 15.5 and 15.8. Full article
(This article belongs to the Special Issue Advances in Sustainability Research at the University of Malta)
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<p>Flowchart illustrating the structured workflow for vegetation restoration and/or reinforcement.</p>
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17 pages, 786 KiB  
Article
Early Desertification Risk in Advanced Economies: Summarizing Past, Present and Future Trends in Italy
by Marco Maialetti, Rares Halbac-Cotoara-Zamfir, Ioannis Vardopoulos and Luca Salvati
Earth 2024, 5(4), 690-706; https://doi.org/10.3390/earth5040036 - 26 Oct 2024
Cited by 1 | Viewed by 1085
Abstract
Being located in the middle of Southern Europe, and thus likely representing a particularly dynamic member of Mediterranean Europe, Italy has experienced a sudden increase in early desertification risk because of multiple factors of change. Long-term research initiatives have provided relatively well-known examples [...] Read more.
Being located in the middle of Southern Europe, and thus likely representing a particularly dynamic member of Mediterranean Europe, Italy has experienced a sudden increase in early desertification risk because of multiple factors of change. Long-term research initiatives have provided relatively well-known examples of the continuous assessment of the desertification risk carried out via multiple exercises from different academic and practitioner stakeholders, frequently using the Environmentally Sensitive Area Index (ESAI). This composite index based on a large number of elementary variables and individual indicators—spanning from the climate to soil quality and from vegetation cover to land-use intensity—facilitated the comprehensive, long-term monitoring of the early desertification risk at disaggregated spatial scales, being of some relevance for policy implementation. The present study summarizes the main evidence of environmental monitoring in Italy by analyzing a relatively long time series of ESAI scores using administrative boundaries for a better representation of the biophysical and socioeconomic trends of interest for early desertification monitoring. The descriptive analysis of the ESAI scores offers a refined representation of economic spaces in the country during past (1960–2010 on a decadal basis), present (2020), and future (2030, exploring four different scenarios, S1–S4) times. Taken as a proxy of the early desertification risk in advanced economies, the ESAI scores increased over time as a result of worse climate regimes (namely, drier and warmer conditions), landscape change, and rising human pressure that exacerbated related processes, such as soil erosion, salinization, compaction, sealing, water scarcity, wildfires, and overgrazing. Full article
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<p>The spatial distribution of the ESAI scores observed all over Italy at the beginning (1960, <b>left</b>) and the end (2020, <b>right</b>) of the observation period.</p>
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<p>A mean-to-dispersion plot depicting the relationship over time (1960–2030) between the average ESAI score and its coefficient of variability across the Italian provinces by geographical macro-region ((<b>a</b>): Northern Italy; (<b>b</b>): Central Italy; (<b>c</b>): Southern Italy; (<b>d</b>): Italy. 2030 indicates the mean value of ESAI score and its variability across the four scenarios, from S1 to S4).</p>
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22 pages, 5341 KiB  
Article
Multi-Annual Study of Eriogaster catax (Linnaeus, 1758) (Lepidoptera, Lasiocampidae) Oviposition Strategy in Transylvania’s Largest Population: Key Insights for Species Conservation and Local Land Management
by Cristian Sitar, Geanina Magdalena Sitar, Angela Monica Ionică, Vladimír Hula, Lukáš Spitzer, Alina Simona Rusu and László Rakosy
Insects 2024, 15(10), 794; https://doi.org/10.3390/insects15100794 - 12 Oct 2024
Viewed by 849
Abstract
This study provides new insights into the oviposition strategy of Eriogaster catax (Linnaeus, 1758) (Lepidoptera, Lasiocampidae), an endangered species of moth found in semi-natural habitats within agricultural landscapes. Protected under various European directives and listed as Data Deficient by the IUCN, E. catax [...] Read more.
This study provides new insights into the oviposition strategy of Eriogaster catax (Linnaeus, 1758) (Lepidoptera, Lasiocampidae), an endangered species of moth found in semi-natural habitats within agricultural landscapes. Protected under various European directives and listed as Data Deficient by the IUCN, E. catax inhabits warmer regions of the Western Palearctic. Despite noted geographic variations in its ecological preferences, few studies have statistically significant data on its ecology. Our six-year study, conducted within the largest known population of E. catax. in Romania, reveals critical data on its oviposition preferences, including the species’ tendency to utilize Prunus spinosa L. and Crataegus monogyna Jacq. shrubs at an average height of 80.48 ± 34.3 cm, with most nests placed within the 41–80 cm range and containing an average of 186 ± 22 eggs. The study also addresses the species’ vulnerability to human activities such as bush trimming, agricultural burning, and uncontrolled grazing, particularly due to its low oviposition height. These findings underscore the negative impact of overgrazing and burning practices, particularly when conducted on a large scale, on the conservation of E. catax. The detailed ecological requirements identified in this study are essential for developing effective conservation strategies and habitat management practices. Furthermore, the study highlights the importance of local community involvement and public education in raising awareness about biodiversity and the conservation of endangered species. Full article
(This article belongs to the Section Insect Ecology, Diversity and Conservation)
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<p><span class="html-italic">Eriogaster catax</span> L. adults: (<b>A</b>) male; (<b>B</b>) female. Specimens from the Zoological Museum of Babeș-Bolyai University.</p>
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<p>(<b>A</b>,<b>B</b>) Eggs; (<b>C</b>) First instar larvae; (<b>D</b>) Second instar larvae; (<b>E</b>) Third instar larvae; (<b>F</b>) Fourth instar larvae; (<b>G</b>) Fifth instar larvae; (<b>H</b>) Pupa and Cocoon. Photos taken in situ in the study area—Natura 2000 site The Eastern Hills of Cluj.</p>
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<p>(<b>A</b>) Study area in the Eastern Hills of Cluj County. (<b>B</b>) Habitat in the study area exhibiting a mosaic structure, characterized by dense clusters of shrubs interspersed with isolated bushes. This spatial arrangement highlights the heterogeneity of vegetation within the landscape.</p>
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<p>Abundance of <span class="html-italic">Prunus spinosa</span> L. and <span class="html-italic">Crataegus monogyna</span> Jacq. shrubs within the study area [<a href="#B70-insects-15-00794" class="html-bibr">70</a>].</p>
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<p>Preference for the cardinal orientation.</p>
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<p>(<b>A</b>) Oviposition on <span class="html-italic">Crataegus monogyna</span> Jacq. (<b>B</b>) Oviposition on <span class="html-italic">Prunus spinosa</span> L. Box plots showing the distribution of the oviposition heights (grey) and the host plant heights (orange) from 2011 to 2016. For each year, the oviposition height and host plant height are displayed side by side. The boxes represent the interquartile range (IQR), with the median indicated by the horizontal line and the mean by an “X”. Whiskers extend to the minimum and maximum values within 1.5 times the IQR, and outliers are shown as circles. Across all years, moths predominantly laid eggs at lower heights compared to the overall height of the host plants, with consistent trends in oviposition height despite increasing host plant variability over time.</p>
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<p>(<b>A</b>) Dynamics of <span class="html-italic">Eriogaster catax</span> L. nest numbers from 2011 to 2015. (<b>B</b>) The direct impact of the fire. (<b>C</b>) The direct impact of the fire. (<b>D</b>) Coverage of the study area by shrubs exceeding 20% in 2012. (<b>E</b>) By 2016, only a few larger shrubs remained, indicated by blue arrows.</p>
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20 pages, 19130 KiB  
Article
Spatiotemporal Analysis of Land Use and Land Cover Dynamics of Dinderesso and Peni Forests in Burkina Faso
by Alphonse Maré David Millogo, Boalidioa Tankoano, Oblé Neya, Fousseni Folega, Kperkouma Wala, Kwame Oppong Hackman, Bernadin Namoano and Komlan Batawila
Geomatics 2024, 4(4), 362-381; https://doi.org/10.3390/geomatics4040019 - 4 Oct 2024
Cited by 1 | Viewed by 1153
Abstract
The sustainable management of protected areas has increasingly become difficult due to the lack of updated information on land use and land cover transformations caused by anthropogenic pressures. This study investigates the spatiotemporal dynamics of the Dinderesso and Peni classified forests in Burkina [...] Read more.
The sustainable management of protected areas has increasingly become difficult due to the lack of updated information on land use and land cover transformations caused by anthropogenic pressures. This study investigates the spatiotemporal dynamics of the Dinderesso and Peni classified forests in Burkina Faso from 1986 to 2022. First, a data driven method was adopted to investigate these forests degradation dynamics. Hence, relevant Landsat images data were collected, segmented, and analyzed using QGIS SCP plugin Random Forest algorithm. Ninety percent of the overall adjusted classification accuracies were obtained. The analysis also showed significant degradation and deforestation with high wooded vegetation classes such as clear forest and wooded savannah (i.e., tree savannah) converging to lower vegetation classes like shrub savannah and agroforestry parks. A second investigation carried out through surveys and field trips revealed key anthropogenic drivers including agricultural expansion, demographic pressure, bad management, wood cutting abuse, overexploitation, overgrazing, charcoal production, and bushfires. These findings highlight the critical need for better management to improve these protected areas. Full article
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<p>Dinderesso and Peni classified forest location.</p>
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<p>Landsat land use land cover assessment and household heads survey flowchart.</p>
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<p>Land uses land cover classes in Dinderesso and Peni classified forests.</p>
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<p>Land use land cover map of Dinderesso classified forest in 1986, 2006, 2010, 2016, and 2022.</p>
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<p>Land use land cover map of Peni classified forest in 1986, 2006, 2010, 2016, and 2022.</p>
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<p>Land use land cover change in the classified forest of Dinderesso in 1986, 2006, 2010, 2016, and 2022.</p>
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<p>Land use land change in the classified forest of Peni in 1986, 2006, 2010, 2016, and 2022.</p>
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<p>Anthropogenic drivers of Dinderesso and Peni classified forests degradation and deforestation.</p>
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<p>Dinderesso classified forest degradation and deforestation drivers.</p>
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<p>Peni classified forest degradation and deforestation drivers.</p>
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19 pages, 1518 KiB  
Article
Assessing Ecological Compensation Policy Effectiveness: A Case Study in the Inner Mongolia Autonomous Region, China
by Yiwen Lu, Xining Yang and Yichun Xie
Sustainability 2024, 16(18), 8094; https://doi.org/10.3390/su16188094 - 16 Sep 2024
Viewed by 1209
Abstract
As a vital component of the terrestrial ecosystem, grassland accounts for one-third of the global vegetation system. Grassland degradation has been exacerbated due to extreme overgrazing in China’s Inner Mongolia Autonomous Region (IMAR). While conservation was carried out via the Ecological Subsidy and [...] Read more.
As a vital component of the terrestrial ecosystem, grassland accounts for one-third of the global vegetation system. Grassland degradation has been exacerbated due to extreme overgrazing in China’s Inner Mongolia Autonomous Region (IMAR). While conservation was carried out via the Ecological Subsidy and Award Program (ESAP) to mitigate grassland degradation, little is known about its effectiveness in improving the biophysical conditions of grassland. This paper integrates the conceptual frameworks of total socio-environmental systems (TSESs) to assess how ecological systems respond to the ESAP, investigate the spatial heterogeneity of the ESAP, and explore the meddling effects of socio-environmental interactions on the ESAP. We integrated ecological, climate, and socioeconomic data and developed several hierarchical linear mixed models (HLMMs) to investigate how these factors interact with the ESAP in the IMAR. Our findings prove that the above-ground biomass between 2011 and 2015 responds significantly to variations in socioeconomic conditions and ecological communities. Available land resources, hospital and medical facilities, and net farmer and herdsman income are the most critical factors positively related to grassland productivity. Primary industries like mining, total consumer retail value, farming, forestry, animal husbandry, fishery productions, and GDP are the most damaging factors affecting biomass. Our study recommends a regionally or locally tailored ecological recovery policy, instead of a generalized one, in future efforts to conserve grassland. Full article
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<p>Study area: Inner Mongolia Autonomous Region of China and 26 counties.</p>
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<p>The flow chart of the analysis.</p>
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<p>The graph that ranks the random effects at the county level.</p>
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<p>Spatial heterogeneity of the HLMM model. The figure is a map of residual interpolations in 26 counties.</p>
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