With the purpose of knowing the phytosocilogy of weeds associated to a carrot crop (Daucus carota L.) under conditions of the municipalities of Ventaquemada and Jenesano-Boyacá, one lot per municipality destined to carrot cultivation was selected and a W-shaped layout was made covering an area of 500 m². Relative density, relative frequency, relative dominance and the importance value index (IVI) were calculated, as well as the Alpha and Beta diversity indices for the sampled areas. A total of 6 families and 11 species were counted, of which 63.64% were represented by annual plants and 36.36% by perennial plants. The class Liliopsida (Monocotyledon) was represented by the Poaceae family. The Magnoliopsida class (Dicotyledon) was represented by the following families: Asteraceae, Brassicaceae, Boraginaceae, Leguminosaceae, Polygonaceae, the last one being the one with the highest number of species. The species R. crispus and P. nepalense were the ones with the highest values of Importance Value Index (IVI) with 0.953 and 0.959, respectively. According to the Shannon-Wiener diversity and Simpson’s dominance indices, the evaluated areas presented a low species diversity and a high probability of dominant species. The results obtained can serve as a basis and tool for carrot growers in the evaluated areas to define management plans for the associated weeds and thus optimize yields in this crop.

In order to evaluate the temporal changes in tree diversity of forest vegetation in Xishuangbanna, Yunnan Province, the study collected tree diversity data from four main forest vegetation in the region through a quadrat survey including tropical rainforest (TRF), tropical coniferous forest (COF), tropical lower mountain evergreen broad-leaved forest (TEBF), tropical seasonal moist forest (TSMF). We extracted the distribution of four forest vegetation in the region in four periods of 1992, 2000, 2009, and 2016 in combination with remote sensing images, using simp son Shannon Wiener and scaling species diversity indexes compare to the differences of tree evenness of four forest vegetation and use the scaling ecological diversity index and grey correlation evaluation model to evaluate the temporal changes of forest tree diversity in the region in four periods. The results show that: (1) The proportion of forest area has a trend of decreasing first and then increasing, which is shown by the reduction from 65.5% in 1992 to 53.42% in 2000, to 52.49% in 2009, and then to 54.73% in 2016. However, the tropical rainforest shows a continuous decreasing trend. (2) There are obvious differences in the contributions of the four kinds of forest vegetation to tree diversity. The order of evenness is tropical rainforest > tropical mountain (low mountain) evergreen broad-leaved forest > warm coniferous forest > tropical seasonal humid forest, and the order of richness is tropical rainforest > tropical mountain (low mountain) evergreen broad-leaved forest > tropical seasonal humid forest > warm coniferous forest, The order of contribution to tree diversity in tropical rainforest > tropical mountain (low mountain) evergreen broad-leaved forest > tropical seasonal humid forest > warm tropical coniferous forest. (3) The tree diversity of tropical rainforests and tropical seasonal humid forests showed a continuous decreasing trend. The tree diversity of forest vegetation in Xishuangbanna in four periods was 1992 > 2009 > 2016 > 2000. The above results show that economic activities are an important factor affecting the biodivesity of Xishuangbanna, and the protection of tropical rainforest is of great significance to maintain the biodiversity of the region.

A topic of current interest in forestry science concerns the regeneration of degraded forests and areas. Within this topic, an important aspect refers to the time that different forests take to recover their original levels of diversity and other characteristics that are key to resume their functioning as ecosystems. The present work focuses on the premontane rainforests of the central Peruvian rainforest, in the Chanchamayo valley, Junín, between 1,000 and 1,500 masl. A total of 19 Gentry Transects of 2 × 500 m, including all woody plants ≥2.5 cm diameter at breast height were established in areas of mature forests, and forests of different ages after clear-cutting without burning. Five forest ages were considered, 5-10, 20, 30, 40 and ≥50 years. The alpha-diversity and composition of the tree flora under each of these conditions was compared and analyzed. It was observed that, from 40 years of age, Fisher’s alpha-diversity index becomes quite similar to that characterizing mature forests; from 30 years of age, the taxonomic composition by species reached a similarity of 69–73%, like those occurring in mature forests. The characteristic botanical families, genera and species at each of the ages were compared, specifying that as the age of the forest increases, there are fewer shared species with a high number of individuals. Early forests, up to 20 years of age, are characterized by the presence of Piperaceae; after 30 years of age, they are characterized by the Moraceae family.

In light of swift urbanization and the lack of precise land use maps in urban regions, comprehending land use patterns becomes vital for efficient planning and promoting sustainable development. The objective of this study is to assess the land use pattern in order to catalyze sustainable township development in the study area. The procedure adopted involved acquiring the cadastral layout plan of the study area, scanning, and digitizing it. Additionally, satellite imagery of the area was obtained, and both the cadastral plan and satellite imagery were geo-referenced and digitized using ArcGIS 9.2 software. These processes resulted in reasonable accuracy, with a root mean square (RMS) error of 0.002 inches, surpassing the standard of 0.004 inches. The digitized cadastral plan and satellite imagery were overlaid to produce a layered digital map of the area. A social survey of the area was conducted to identify the specific use of individual plots. Furthermore, a relational database system was created in ArcCatalog to facilitate data management and querying. The research findings demonstrated the approach's effectiveness in enabling queries for the use of any particular plot, making it adaptable to a wide range of inquiries. Notably, the study revealed the diverse purposes for which different plots were utilized, including residential, commercial, educational, and lodging. An essential aspect of land use mapping is identifying areas prone to risks and hazards, such as rising sea levels, flooding, drought, and fire. The research contributes to sustainable township development by pinpointing these vulnerable zones and providing valuable insights for urban planning and risk mitigation strategies. This is a valuable resource for urban planners, policymakers, and stakeholders, enabling them to make informed decisions to optimize land use and promote sustainable development in the study area.

Monitoring marine biodiversity is a challenge in some vulnerable and difficult-to-access habitats, such as underwater caves. Underwater caves are a great focus of biodiversity, concentrating a large number of species in their environment. However, most of the sessile species that live on the rocky walls are very vulnerable, and they are often threatened by different pressures. The use of these spaces as a destination for recreational divers can cause different impacts on the benthic habitat. In this work, we propose a methodology based on video recordings of cave walls and image analysis with deep learning algorithms to estimate the spatial density of structuring species in a study area. We propose a combination of automatic frame overlap detection, estimation of the actual extent of surface cover, and semantic segmentation of the main 10 species of corals and sponges to obtain species density maps. These maps can be the data source for monitoring biodiversity over time. In this paper, we analyzed the performance of three different semantic segmentation algorithms and backbones for this task and found that the Mask R-CNN model with the Xception101 backbone achieves the best accuracy, with an average segmentation accuracy of 82%.

The reduction of biodiversity and the decline in wildlife populations are urgent environmental issues with devasting consequences for ecosystems and human health. As a result, the protection of wildlife and biodiversity has emerged as one of humanity’s greatest goals, not only for protecting and maintaining human health but also for environmental, economic, and social well-being. In recent years, people have become increasingly aware of the importance and effectiveness of wildlife conservation efforts alongside environmental protection measures, sustainable agricultural practices and non-harmful production procedures and services. This study describes the development and implementation of a labeling scheme for wildlife and biodiversity protection for products or services. The label is designed to encourage the adoption of sustainable and environmentally friendly production methods and services that will contribute to biodiversity conservation and the harmonic coexistence of human-wildlife. Moreover, using a case study approach, the research presents an innovative information system designed to streamline the label-awarding process, ensuring transparency and efficiency. The established system evaluates the sustainability practices and measures implemented by businesses, with a focus on honey production in this case. Additionally, the study explores the broader social implications of the label, particularly its potential to engage consumers and promote awareness of biodiversity conservation.