Leksono AS, Yanuwiadi B, Afandhi A, Farhan M, Zairina A. 2020. The abundance and diversity of grasshopper communities in relation to elevation and land use in Malang, Indonesia. Biodiversitas 21: 5614-5620. Ecological factors include interactions of the community members with numerous biotic and abiotic factors such as temperature, humidity, precipitation, light intensity, and seasonality show an altitudinal gradient. Most grasshopper species play a role as herbivores and are a good source of protein for other animals such as amphibians, small reptiles, birds, and small mammals. This study aimed to analyze variations in the abundance, richness, and diversity of grasshopper species along an altitudinal gradient. This research was conducted in five locations in Malang District, East Java, Indonesia, namely Bantur, Sumber Pujung Lawang, Pujon, and Poncokusumo. Grasshopper sampling was carried out by the sweeping method using an insect net. Sweepings were carried out on four plots with each plot size of 2 x 10 m2. Sampling was conducted four times from June to August 2020. The data were analyzed using the Shannon Wiener index (diversity analysis) and the Bray-Curtis index. The differences between locations were tested by one-way analysis of variance. Land use was analyzed by ArcGIS, using Landsat imagery 8. The abundance of grasshoppers had a significant negative correlation with elevation. That correlation was positive to species richness and diversity of grasshoppers. That with species diversity was significant, while that with species richness was not significant. The greatest abundance of the grasshopper was found in the middle elevation in Lawang (19.39 ± 2.12). In contrast, the highest species richness and diversity were found in the highest elevation in Poncokusumo (richness = 15.75 ± 1.60 and H '= 2.58 ± 0.11). Land use variation was not significant on abundance, species, richness, and diversity of grasshoppers. Interestingly, the high similarity of the grasshopper compositions in low elevation habitats was detected, indicating that land use in the low land area was remarkable. The abundance of grasshopper had a significant positive correlation with temperature but negatively correlated with humidity. There was no significant correlation among species richness, species diversity with temperature and humidity.

Malang Indonesia is an area prone to landslides, resulting in the need to model soil reinforcement to determine the vegetation’s slope stability using the roots of five species. One of the methods to improve the stability of slopes prone to landslides is adequate vegetation preservation. Soil strengthening with vegetation roots is environmentally friendly and an inexpensive alternative to reduce the vulnerability of slopes along mountainous slopes and the risk of shallow erosions. Therefore, this study aims to evaluate the vegetation arrangement on the slopes in Malang Regency, Indonesia, with a view of geotechnical engineering on the role of its root characteristics. Slope stability was analyzed by modeling the distribution of vegetation roots as an equivalent cohesion approach, where the factor of safety (FoS) is calculated using the PLAXIS-2D version 86 software. Soil and root parameters were obtained through direct shear testing and examining five plant species’ tensile strength. The results showed that the highest stability is achieved when the position of the vegetation on the slope’s surface is compared to the top. The factor of safety (FoS) increased from 23% to 30% and from 28% to 31% for slopes with uniform and combined species. Of the five plant species, P. merkusii demonstrated some advantages in maintaining stability because it has better root mechanical properties, among others. However, the combined species, such as C. arabica, had better performance because they possess vertical and lateral root systems, which act as an anchor in penetrating and griping the soil. This means combining vegetation species is a preferable preventive measure to increase slope stability. The analysis results also demonstrated the significance of vegetation on slope stability. The results show that the FoS decreases when the slope angle increases and reaches its maximum when the species are combined. The mechanical effect of the plant root matrix system can increase the shear strength of the soil, thereby raising the slope stability. The density of roots in the soil mass and the tensile strength contribute to the soil’s ability to withstand shear stresses.

Small islands have unique ecosystems and are vulnerable to land degradation and ecological threats. Integrating spatial and landscape ecology approaches greatly influences the effectiveness and efficiency of environmental monitoring and future environmental management planning. Uncontrolled land conversion, extreme climate conditions, high biophysical land constraints, and anthropogenic and political factors contribute to biodiversity pressures. This study aimed to measure the impact of land use and land cover changes on the LST, NDVI, and NDWI as well as changes in landscape patterns and structures for environmental monitoring and ecological sustainability on Kapota Island. The LST values in 1990 ranged from 21.50°C to 25.40°C, and from 22.63°C to 32.56°C in 2020. In contrast, the NDVI values in 1990 ranged from -0.765 to 0.754 and from -0.241 to 0.514 in 2020. The surface temperature increased in vegetated areas with low density, as well as in non-vegetated areas and settlements. Habitat fragmentation was relatively high, as indicated by the SHDI value closer to 1. Moving forward, future research should delve deeper into the specific drivers of biodiversity pressures, including uncontrolled land conversion, extreme climate conditions, biophysical constraints, and anthropogenic and political factors. Moreover, efforts should be directed toward maintaining a green cover exceeding 30%, enhancing vegetation density, minimizing land-clearing activities, and encouraging the cultivation of crops with good water storage capabilities. This research lays the foundation for a more nuanced understanding of the intricate dynamics at play on small islands and sets the stage for informed conservation and management strategies.

Complex interactions between environmental, social, and urban density factors drive Urban Heat Island (UHI) dynamics. The current study synthesizes multidimensional metrics, including normalized difference indices, such as vegetation (NDVI), water (NDWI), moisture (NDMI), and social parameters (population density), such as urban morphology metrics (UDI) and built-up index (NDBI) to predict UHI intensity using remote sensing data and Support Vector Regression (SVR). Landsat-8, Sentinel-2A, and NASA-SRTM data from 2014 to 2023 were used to analyze Land Surface Temperature (LST) trends and spatially identify UHI hotspots in Malang City, Indonesia. The SVR model demonstrated robust performance, achieving an R² of 0.78, an RMSE of 0.23, and a MAPE of 0.46%. Results indicate that increasing urban density (UDI and NDBI) and population density significantly amplify LST, while higher NDVI values mitigate UHI effects. Temporal and spatial analyses reveal a steady expansion of UHI hotspots from central districts (e.g. Klojen) to peripheral areas (e.g. Sukun and Kedungkandang), driven by vegetation loss and urban sprawl. These findings underscore the potential of synthesizing multidimensional metrics for UHI prediction and highlight the value of integrating remote sensing data with machine learning models. The study provides actionable insights for urban planners to design targeted interventions, such as urban greening and density management, to mitigate UHI effects and enhance urban sustainability.