Variation In Biodiversity Research Articles

Freshwater fish diversity from Siberut Island, a small island in the western part of Sumatra, Indonesia

Abstract. Roesma DI, Tjong DH, Aidil DR, Prawira FDL, Saputra A. 2024. Freshwater fish diversity from Siberut Island, a small island in the western part of Sumatra, Indonesia. Biodiversitas 25: 836-845. Indonesia is an archipelagic country with thousands of islands, including small islands with a variety of biodiversity, such as freshwater fish. Data and information on the fish biodiversity of small islands in the western part of Sumatra are limited, including Siberut Island. A study on freshwater fish diversity in Siberut Island was carried out using morphological and molecular methods. The study was conducted on seven rivers in the North and South Siberut Districts, Siberut Island. The study obtained 676 individuals, including 34 species, 26 genera, 16 families, and 10 orders. Oxudecidae is the family with the largest species (8), and Rasbora jacobsoni has the highest number of individuals (341). Species richness ranged from 2 to 18 species per site and was highest in the Srilanggai River. Siberut Island has low-moderate freshwater fish diversity. As many as 90 DNA barcodes of individuals from 34 species have been submitted to the Barcode of Life Data System. Freshwater fish groups do not receive enough attention from local communities and the government because of the richness of marine fish on Siberut Island. Apart from functioning as evidence of species richness, the results of this study are also useful for local communities' education.

The Spatiotemporal Variation in Biodiversity and Its Response to Different Future Development Scenarios: A Case Study of Guilin as an Internationally Renowned Tourist Destination in China

The preservation of biodiversity is crucial for maintaining ecological balance and promoting the harmonious development of mankind and nature. To formulate a biodiversity conservation plan for Guilin in China and accurately evaluate the impact of conservation measures on regional biodiversity, this study combined the InVEST model (v 3.7.0), the GeoSOS-FLUS model (v 2.3), and the landscape pattern index, analyzing the spatiotemporal changes in biodiversity from 2000 to 2020 in Guilin and simulating biodiversity under different development scenarios in 2040. The results showed the following: (1) The biodiversity index in Guilin displayed a declining trend, with the average annual value decreasing from 0.875 in 2000 to 0.870 in 2020. The area experiencing a reduction in biodiversity was primarily concentrated around the city. (2) The biodiversity level of each district and county had a large spatiotemporal difference, with the overall distribution characteristics of “higher in the northwest, southwest, and east, and lower in the northeast, southeast and central”. (3) The biodiversity hotspots were identified as priority areas for conservation; woodland and wetland were effectively protected, and the expansion of construction land and arable land was limited under the ecological protection scenario compared with the natural development scenario. (4) The annual average value of the biodiversity index of Guilin could reach 0.872 in 2040 after the adoption of ecological conservation measures, which is 0.013 higher than the natural development scenario. The results of this study can provide guidance for the construction of a national sustainable development model city and land use planning in Guilin, as well as a scientific reference for the creation of biodiversity conservation policies.

Acoustic indices are responsive to local-scale but not landscape-scale agricultural land use

Agricultural land use shapes biodiversity patterns. In the literature, land use and land cover at both local and landscape scales has been shown to be important to understanding variation in biodiversity in agricultural systems including measures of occupancy, abundance, and diversity, with landscape scale processes moderating local patterns. The relative role of these processes in explaining variation in acoustic indices, an increasingly frequent measure of biological and environmental change, remains unknown. To address this gap, we recorded acoustic data by passive sampling for two months across 39 farms in central Kansas, USA with automated recording units. We used these data to calculate eight different acoustic indices. We found that acoustic indices were associated with local land use composition (within 100 m) but not landscape composition (within 1000 m). These data suggest that passive acoustic monitoring may be used explain how local land use shapes the soundscape and perhaps biodiversity, but future research should seek to understand the lack of response to landscape variation.

Short-term temporal variability in offshore benthic biodiversity across hydrographic regions at a sub-Antarctic archipelago

AbstractCommunity composition is one of the main factors influencing the ecological functioning of any given ecosystem, with a more diverse community providing a larger set of services. Benthic community composition can vary at spatial and temporal scales, with the dynamics of primary production and benthic food availability being key determinants of community structure of a given system. Studies have indicated shifts in benthic community composition at sub-Antarctic Islands over a period of 30 years, linked to variability in food availability driven by climate change. Here, we aim to evaluate possible short-term variability in benthic community composition at the sub-Antarctic archipelago Prince Edward Islands (PEIs), sampling stations across three hydrographically dynamic regions over two consecutive years, 2016–2017. The results indicated significantly higher species richness and abundance in 2017 than in 2016, with some taxa also showing variation among regions around the PEIs. Such effects can be linked to different substratum type or hydrographic regime. This study further contributes to understanding variability and changes in benthic communities in the near future, an essential information to develop efficient management strategies for this vulnerable marine system.

A theory-informed emotion regulation variability index: Bray-Curtis dissimilarity.

Emotion regulation (ER) variability refers to how individuals vary their use of ER strategies across time. It helps individuals to meet contextual needs, underscoring its importance in well-being. The theoretical foundation of ER variability recognizes two constituent processes: strategy switching (e.g., moving from distraction to social sharing) and endorsement change (e.g., decreasing the intensity of both distraction and social sharing). ER variability is commonly operationalized as the SD between strategies per observation (between-strategy SD) or within a strategy across time (within-strategy SD). In this article, we show that these SD-based approaches cannot sufficiently capture strategy switching and endorsement change, leading to ER variability indices with poor validity. We propose Bray-Curtis dissimilarity, a measure used in ecology to quantify biodiversity variability, as a theory-informed ER variability index. First, we demonstrate how Bray-Curtis dissimilarity is more sensitive than SD-based approaches in detecting ER variability through two simulation studies. Second, assuming that higher ER variability is adaptive in daily life, we test the relation between ER variability and negative affect in three experience sampling method data sets (total N = [70, 95, 200], number of moment-level observations = [5,040, 6,329, 14,098]). At both the moment level and person level, higher Bray-Curtis dissimilarity predicted lower negative affect more consistently than SD-based indices. We conclude that Bray-Curtis dissimilarity may better capture moment-level within-person ER variability and could have implications for studying variability in other multivariate dynamic processes. The article is accompanied by an R tutorial and practical recommendations for using Bray-Curtis dissimilarity with experience sampling method data. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The Role of Vegetation in Elevational Diversity Patterns of Tenebrionid Beetles in Central Italy

Vegetation tends to vary in a systematic fashion along elevational gradients, leading to the possibility of recognizing distinct vegetational belts, which are frequently used to describe and interpret elevational variations in biodiversity. However, anthropogenic changes can create landscapes dominated by secondary grasslands in areas formerly occupied by forests, thus altering the natural sequence of vegetation types. The present research illustrates how the distribution of tenebrionid beetles in central Italy is influenced by secondary vegetation. Classical schemes of vegetational belts were modified into a scheme of main vegetation types that include secondary vegetations. Tenebrionid species presence/absence in each vegetation type was then assessed. Species richness tended to decrease with elevation in both natural and secondary vegetations. Geophilous (ground-dwelling) species (which include many endemics) prevailed in natural and secondary grasslands, while xylophilous species (associated with trees) prevailed in the natural forests. Similarities in tenebrionid composition indicated the presence of two main groups: one associated with forests and the other with natural and secondary grasslands. Geophilous species prevailed among tenebrionids with Mediterranean distributions, whereas xylophilous species prevailed among species distributed mainly in Europe and the Palearctic. High values of richness, biogeographical complexity and proportion of endemics make secondary vegetations of high conservation concern.

Decomposing drivers in avian insectivory: Large‐scale effects of climate, habitat and bird diversity

AbstractAimClimate is a major driver of large‐scale variability in biodiversity, as a likely result of more intense biotic interactions under warmer conditions. This idea fuelled decades of research on plant‐herbivore interactions, but much less is known about higher‐level trophic interactions. We addressed this research gap by characterizing both bird diversity and avian predation along a climatic gradient at the European scale.LocationEurope.TaxonInsectivorous birds and pedunculate oaks.MethodsWe deployed plasticine caterpillars in 138 oak trees in 47 sites along a 19° latitudinal gradient in Europe to quantify bird insectivory through predation attempts. In addition, we used passive acoustic monitoring to (i) characterize the acoustic diversity of surrounding soundscapes; (ii) approximate bird abundance and activity through passive acoustic recordings; and (iii) infer both taxonomic and functional diversity of insectivorous birds from recordings.ResultsThe functional diversity of insectivorous birds increased with warmer climates. Bird predation increased with forest cover and bird acoustic activity but decreased with mean annual temperature and functional richness of insectivorous birds. Contrary to our predictions, climatic clines in bird predation attempts were not directly mediated by changes in insectivorous bird diversity or acoustic activity, but climate and habitat still had independent effects on predation attempts.Main ConclusionsOur study supports the hypothesis of an increase in the diversity of insectivorous birds towards warmer climates but refutes the idea that an increase in diversity would lead to more predation and advocates for better accounting for activity and abundance of insectivorous birds when studying the large‐scale variation in insect‐tree interactions.

A Critical Analysis of the Illegal Coal Mining Activities Inside Dihing Patkai National Park

The Dihing Patkai National Park, commonly referred to as the “Amazon of the East”, is a hub of rich and diverse biodiversity located in the Tinsukia and Dibrugarh districts of Assam. The coal mining operations in this region have a historical origin that can be traced back to the colonial era. During this period, the fuel resources extracted from this region were primarily utilized to power local enterprises. However, lately, it has been alleged that certain illegal coal mining activities carried out in this region have greatly affected the region surrounding the National Park and have sparked protests among the local population against such activities. This paper discusses the impact of illegal coal mining activities inside Dihing Patkai National Park. At the same time, it will also discuss the reasons why stopping all the coal mining operations near the region will also affect the development and employment in the region. The research also highlights the historical background of the mining of coal in the region surrounding Dihing Patkai National Park. And the various environmental impacts on the region due to coal mining activities as well as its effects on the local population. This research also discusses the doctrine of public trust along with some important Supreme Court decisions and the One- Man Enquiry Commission Report under retired Justice B. P. Katakey. Moreover, this research aims to maintain a balance between ecology and economy

Temporal variations of the multifaceted biodiversity and assembly mechanisms in lake fish assemblages

AbstractUnderstanding long‐term changes in fish diversity and community assembly rules is crucial for freshwater conservation. Growing evidence indicates that studying functional and phylogenetic diversity beyond purely taxonomic considerations can provide different but complementary information on community assembly. Here, the taxonomic, functional, and phylogenetic β‐diversity of fish communities, as well as the community assembly mechanisms, were explored in five impounded lakes of the China's South‐to‐North Water Diversion Project (SNWDP) from the 1980s to the 2010s. We found that (1) there was an obvious trend of species homogenization in the five impounded lakes, but the long‐term transformations of different dimensional β‐diversity were divergent; (2) water quality and land use variables have greater impacts on multidimensional β‐diversity; and (3) community assembly process in taxonomic and functional dimensions were dominated by random process in both periods, while shifting from limiting similarity to habitat filtering in the phylogenetic dimension. These results highlight that functional and phylogenetic diversity are important additional ecological indices for assessing the patterns of fish diversity in lakes.

Micro-Environmental Variation in Soil Microbial Biodiversity in Forest Frontier Ecosystems—Implications for Sustainability Assessments

Soil health indicators based on microbial biodiversity are increasingly used in agricultural sustainability assessments. However, little is known about how microbial communities vary within micro-environmental gradients across different land uses, which is crucial for designing field sampling and monitoring protocols. Our objective was to assess how soil microbial communities changed with soil depth and spatial distance across land-use types. We sampled soils in four spatial distances (within 0.1–70 m) and four depths (within 0–40 cm) in forests, grasslands, and horticultural lands, and combined 16S rRNA gene sequencing, DNA quantification and soil chemical characterization to explore micro-environmental variation in microbial biomass, α-β-diversity, and communities’ assembly processes. Depth and spatial distance had differential effects on microbial biodiversity within different land uses. Microbial biomass was most sensitive to depth, α-diversity to spatial distance, and β-diversity to both depth and spatial distance. Deterministic processes dominate microbial communities’ assembly along depth in all land uses, which is a promising result for developing soil quality indicators based on microbial biodiversity. Overall, our results suggest that collecting soil samples separated by at least 12 m is adequate to capture biodiversity changes across land uses. However, collecting randomly within the first 10 cm is recommended for native forests, while systematic sampling within the first 20 cm is advised for grasslands and horticultural lands. Our findings underscore the need for land use-specific sampling frameworks in soil life-based sustainability assessments for meaningful regional comparisons.

Putting space into trait ecology: Trait, environment and biodiversity relationships at multiple spatial scales

Abstract Ecological processes such as environmental filtering and biotic interactions that shape species' traits and community diversity often vary with geographic distance, potentially generating spatial structures in trait variation, covariation and biodiversity data. Understanding spatial structures of trait, environment and biodiversity, or the spatial link between those factors, is fundamental to identifying spatially explicit assembly processes or biodiversity distributions in spatially heterogeneous landscapes but remains unclear. To address the issue, we gathered individual‐level leaf and diameter traits data paired with environmental data from a 4.8 ha subtropical Chinese forest and divided the forest into 25, 100, 400 and 1936 m2 grids representing contrasting spatial grains. Using Moran's correlograms, we quantified the spatial structures of trait variation and covariation, environmental conditions and biodiversity. We assessed the links between those variables using path analyses. Most variables were spatially positively autocorrelated. However, trait mean was more autocorrelated than trait variation or covariation, and intraspecific trait variation was more autocorrelated than interspecific variation. Autocorrelations in those community properties were generally weak at the large grain. Path analyses indicated positive associations between interspecific trait variation and species diversity at a very small to medium scale and a positive association between intraspecific variation and small‐scale functional diversity. Trait covariation constrained biodiversity, and multi‐trait means were negatively linked to very small‐ to medium‐scale species diversity but positively to medium‐ and large‐scale functional diversity. Patterns regarding multi‐trait community structure–environment–biodiversity associations were generally held for individual traits. However, depending on the trait, spatial scale and plant ontogenic stage, the pattern's strength changed, or occasionally, their sign reversed. We attribute spatial patterns in multi‐trait mean and covariation to scale‐dependent variation in environmental heterogeneity and trait variation to scale‐dependent competition. Synthesis. Our study provides novel insights into spatial and scale‐dependent variability in functional community structure, environment and biodiversity, and their relationships. Our results demonstrate the usefulness of spatial trait analyses in identifying scale‐dependent assembly processes or finding the importance of processes to biodiversity distributions in spatially heterogeneous landscapes. A spatially explicit perspective is thus helpful for the progress of trait ecology.

Spatial patterns of β-diversity under cumulative pressures in the Western Mediterranean Sea

Understanding the spatial dynamics of biodiversity is an essential issue in marine ecology and requires combining information at local and regional scales. β-diversity is an important measure of biodiversity that informs on the differences in community composition between sites and, thus, in the species turnover in the community structure. In this study, we analysed and predicted the spatial patterns of β-diversity for fishes, invertebrates and the demersal assemblage along the Iberian Mediterranean coast. We used Bayesian Bootstrap Generalized Dissimilarity Models (BBGDMs) to study the effects of environment and human pressures on the β-diversity of invertebrate, fishes and the entire demersal assemblage from 1994 to 2015 using different time windows to account for temporal variability. Then, we used these relationships to predict the spatial patterns of β-diversity in the whole Iberian Mediterranean coast. Our results highlighted that the regional spatial patterns of β-diversity were best described by bathymetry and a cumulative index of coastal impacts. We identified specific regions with the highest β-diversity in the study area, which were complementary to hotspots of species richness and presented different degree of overlapping with existent marine protected areas. Overall, our study illustrates that by modelling spatial turnover using β-diversity we can better understand and predict spatial variation of biodiversity and the effects of particular variables, providing relevant information to end-users and policy makers for designing specific spatial conservation and management strategies.

Carbon Sequestration in Mangrove Finfish and Variation of Biodiversity and Immune Response Due to Ocean Acidification

Carbon Sequestration in Mangrove Finfish and Variation of Biodiversity and Immune Response Due to Ocean Acidification

Condition of Coral Reefs in the Ciletuh Geopark Area, SukabumiIndonesia

Ciletuh Geopark has unique natural resources, namely the natural beauty of the sea. Coral reefs are one of the most productive marine ecosystems with diverse biodiversity. Data and information regarding coral reefs in the south of Java Island, especially in the Ciletuh Geopark area, Sukabumi is still minimal, and their existence is rarely exposed. Therefore, we carry out research activities related to the condition of coral reefs using the underwater photo transect method. Data were taken at a depth of 6 meters with a transect length of 50 m and analyzed using CPCe 4.1 and Microsoft Excel 2010 software. Observations of the condition of coral reefs at Pasir Putih Beach in the Ciletuh Sukabumi Geopark area show that the percentage of cover is in the criteria of quite good (25-49.9%) and poor (0-24.9%). The observation results show that the percentage of coral reef cover at station I (28.88%) is quite good, station II (35.75%) is quite good, and station III (22.48%) is in the poor category. The highest diversity index (1.68) and Variety Index (0.25) was found at station II and the lowest was at station I with a diversity value of 1.07 and a diversity value of 0.16.

Assessing biodiversity's impact on stress and affect from urban to conservation areas: A virtual reality study

Biodiversity is the essential foundation of ecosystem stability and significantly influences human health. However, the specific impacts of broadly varied biodiversity levels across diverse greenspaces on mental well-being remain unclear. In this randomized controlled trial, immersive virtual reality (VR) auditory-visual simulations, emulating real biodiversity scenarios, were employed to investigate the effect of diverse biodiversity levels on stress and affect. After an induced stress phase, participants (N = 90) were randomly assigned to a ten-minute immersion in one of three settings: urban park, peri-urban park, or nature conservation area. Physiological responses were measured via skin conductance level (SCL) and significant skin conductance responses (nSCR), while psychological responses were evaluated using Positive Affect and Negative Affect Scale (PANAS). Additionally, the Perceived Restorativeness Scale (PRS) was employed to evaluate restoration potential. Repeated measures analysis of variance revealed that immersion in the peri-urban park and nature conservation area was associated with a significantly faster and more substantial decrease in SCL compared to the urban park. nSCR in the nature conservation area remained significantly lower than in the urban park. While immersion in all three natural environments significantly diminished negative affect, the nature conservation scenario was associated with a substantial decline in positive affect and received the lowest rating on the subjective restorativeness. A psychological benefit threshold related to biodiversity was observed, in contrast to the absence of a corresponding physiological threshold. This disparity suggests that an innate genetic affinity for high biodiversity may persists, unaffected by acquired experiences. Our study underscores the stress recovery benefits of high-value ecological environments, thereby fostering an avenue for further investigations into human-ecological health interconnections.

Towards interpretable learned representations for ecoacoustics using variational auto-encoding

Ecoacoustics is an emerging science that seeks to understand the role of sound in ecological processes. Passive acoustic monitoring is being used to collect vast quantities of soundscape audio recordings to study variations in acoustic community and monitor biodiversity. However, extracting relevant information from soundscape recordings is non-trivial. Recent approaches to machine-learned acoustic features appear promising but are limited by at least three issues: inductive biases, lack of interpretability and crude temporal integration. In this paper we introduce a novel self-supervised representation learning algorithm for ecoacoustics - a convolutional Variational Auto-encoder (VAE) - and directly address these shortcomings. Firstly, we train the network on soundscape recordings from temperate and tropical field sites along a gradient of ecological degradation to provide a more relevant inductive bias than prior approaches. Secondly, we present a new method that allows interpretation of the latent space for the first time, giving insight into the basis of classification. Thirdly, we advance existing methods for temporal aggregation of learned embeddings by encoding latent features as a distribution over time. Under our approach to increase interpretability, we provide insight into how learned features drive habitat classification for the first time: inspection of latent space confirms that varying combinations of biophony, geophony and anthrophony are used to infer sites along a degradation gradient. Our novel temporal encoding method increases sensitivity to periodic signals and improves on previous research that uses time-averaged representations for site classification. This approach also reveals the contribution of hardware-specific frequency response that create a potential bias; we demonstrate how a simple linear transformation can be used to mitigate the effect of hardware variance on the learned representation under our approach. Our novel approach paves the way for development of a new class of deep neural networks that afford more interpretable learned ecoacoustic representations to advance both fundamental and applied science and support global conservation efforts.

Deep Learning Untuk Klasifikasi Kematangan Buah Mangrove Berdasarkan Warna

Plants that live between land and sea, such as mangroves, are influenced by the tides and tides. Indonesia has the largest mangrove forest in the world and a variety of biodiversity and structure. People currently detect mangrove maturity by looking directly at the fruit. This study proposes to classify the maturity of mangrove fruit using artificial intelligence techniques, making it easier for farmers to determine the ripeness of the fruit. This proposal uses data from 200 images for mangroves taken directly from Lukit Village, Merbau District, Meranti Islands Regency. This research improves the Convolutional Neural Network (CNN) method to classify mangrove fruit maturity. The results obtained from this research were by classifying ripe and unripe fruit. Based on this research, accuracy reaches a maximum of 96%.

PEMULIHAN PERAIRAN TERCEMAR MENGGUNAKAN MAKROFITA AIR

Indonesia possesses a potential and diverse biodiversity of plants that can be utilized as phytoremediation agents. One of the ecosystems frequently encountering pollution is the aquatic ecosystem. Therefore, this research is conducted to identify the diversity of aquatic macrophytes with the potential for water remediation efforts. The method employed is qualitative descriptive based on literature review. The literature study revealed 30 species of aquatic macrophytes, with 15 species prominently utilized for environmental remediation. Among these, Ipomea aquatica and Scirpus grossus emerge as the most widely employed aquatic macrophytes.

Bottom-up global biodiversity metrics needed for businesses to assess and manage their impact.

Ensuring that companies can assess and manage their impacts on biodiversity will be crucial to solving the current biodiversity crisis, and regulatory and public pressure to disclose these impacts is increasing. Top-down intactness metrics (e.g., Mean Species Abundance) can be valuable for generating high-level or first-tier assessments of impact risk but do not provide sufficient precision or guidance for companies, regulators, or third-party assessors. New metrics based on bottom-up assessments of biodiversity (e.g., the Species Threat Abatement and Restoration metric) can accommodate spatial variation of biodiversity and provide more specific guidance for actions to avoid, reduce, remediate, and compensate for impacts and to identify positive opportunities.

Interpreting the Haor Eco-System through Sustainable Design: Haor (Wetland) Eco-Interpretation Center, Moulvibazar, Sylhet, Bangladesh

Wetlands, known as 'Haors' in Bangladesh, are vital ecosystems that provide essential ecological services and support diverse biodiversity. However, they face increasing threats due to extensive tourists visits, unawareness about environment preservation and unsustainable development practices. The "Haor Eco-Interpretation Center" in Moulvibazar, Sylhet, Bangladesh, emerges as a pioneering initiative to address these challenges by combining environmental education and sustainable design principles. This paper provides an overview of the Haor Eco-Interpretation Center's objectives, strategies, and significance. The center serves as a unique model for interpreting the Haor ecosystem while promoting sustainability through its architectural and operational features. The key elements of this initiative include visitor education, research facilities, and eco-sensitive design principles.