Ecological Indicators Research Articles

Egyptian sole Solea aegyptiaca Chabanaud 1927 as an eligible ecological indicator for Lake Qarun, Egypt

Egyptian sole Solea aegyptiaca Chabanaud 1927 as an eligible ecological indicator for Lake Qarun, Egypt

Dynamic monitoring and analysis of ecological quality based on RSEI: A case study of Akkulam-Veli Lake Basin of Thiruvananthapuram City, Kerala, India

ABSTRACT The world today is experiencing rapid urbanization, leading to prominent urban ecological problems. Evaluating urban ecological quality is crucial for monitoring environment-centered initiatives. The Akkulam-Veli Lake Basin, in Thiruvananthapuram, Kerala, India, is threatened by rapid urbanization. The present study proposes a comprehensive evaluation of the ecological quality by the Remote-Sensing Ecological Index (RSEI), based on the four indexes: greenness (NDVI), wetness (WET), dryness (NDSBI), and heat (LST), from 2000 to 2023. The interrelationship between RSEI and land use has been studied to properly analyze human activities’ effects on the study region’s ecological quality. Results indicated that the mean values of RSEI experienced a drastic decline from 0.733 in 2000 to 0.645 in 2015, and further declined to 0.611 in 2023, indicating an overall deterioration in the status of ecological quality in the Akkulam-Veli Lake Basin. Moreover, Moran’s I index of 0.556 in 2000, 0.554 in 2015, and 0.552 in 2023 show that the sample RSEI values have a strong positive autocorrelation with adjacent values in the study area. The study provides evidence for the need for systematic urban planning and serves as a scientific reference for policymakers to manage the ecological qulaity of urban areas effectively.

Assessment of Carbon Storage in a Multifunctional Landscape: A Case Study of Central Asia

The robust carbon storage (CS) capacity of terrestrial ecosystems is crucial in mitigating climate change and holds indispensable significance for global sustainable development. The diverse topography of Central Asia (CA), comprising oases, grasslands, forests, deserts, and glaciers, has fostered industries like animal husbandry, irrigation agriculture, and mining. However, the fragile arid ecosystems of CA render it highly sensitive to climate change and human activities, with their impact on the sustainable development of multifunctional landscapes in this region remaining ambiguous in the future. This study linked land use changes with multiple socio-economic and ecological indicators to predict the dynamics of land use and changes in CS in CA. The findings reveal a significant spatial heterogeneity in CS, with considerable variations among five countries driven by differences in landscape composition. Kyrgyzstan and Kazakhstan, characterized by grasslands, demonstrate higher CS per unit area, whereas Turkmenistan, dominated by barren land, exhibits the lowest CS per unit area. Strategies involving innovative development and improved biodiversity conservation have proven effective in augmenting CS. Meanwhile, high economic and population growth stimulates the expansion of cropland and urban land, reducing the CS capacity of ecosystems. This study contributes to a more precise assessment of CS dynamics in CA. Furthermore, by elucidating the interrelationships between future socio-economic development and environmental conservation in CA, it offers solutions for enhancing the conservation of multifunctional landscapes in CA.

Revealing the Eco-Environmental Quality of the Yellow River Basin: Trends and Drivers

The Yellow River Basin (YB) acts as a key barrier to ecological security and is an important experimental region for high-quality development in China. There is a growing demand to assess the ecological status in order to promote the sustainable development of the YB. The eco-environmental quality (EEQ) of the YB was assessed at both the regional and provincial scales utilizing the remote sensing-based ecological index (RSEI) with Landsat images from 2000 to 2020. Then, the Theil–Sen (T-S) estimator and Mann–Kendall (M-K) test were utilized to evaluate its variation trend. Next, the optimal parameter-based geodetector (OPGD) model was used to examine the drivers influencing the EEQ in the YB. Finally, the geographically weighted regression (GWR) model was utilized to further explore the responses of the drivers to RSEI changes. The results suggest that (1) a lower RSEI value was found in the north, while a higher RSEI value was found in the south of the YB. Sichuan (SC) and Inner Mongolia (IM) had the highest and the lowest EEQ, respectively, among the YB provinces. (2) Throughout the research period, the EEQ of the YB improved, whereas it deteriorated in both Henan (HA) and Shandong (SD) provinces. (3) The soil-available water content (AWC), annual precipitation (PRE), and distance from impervious surfaces (IMD) were the main factors affecting the spatial differentiation of RSEI in the YB. (4) The influence of meteorological factors (PRE and TMP) on RSEI changes was greater than that of IMD, and the influence of IMD on RSEI changes showed a significant increasing trend. The research results provide valuable information for application in local ecological construction and regional development planning.

Assessing the suitability of a surveillance fauna-monitoring program for detecting future changes in reptile occupancy

Context Ecological surveillance monitoring typically targets multiple taxonomic groups by using standardised sampling across large spatial scales. Although surveillance monitoring confers advantages over hypothesis-driven monitoring in its broad taxonomic and spatial scope, the approach has been criticised for its disconnect from ecological management and failure to provide insights on the drivers of ecological change Aims To assess the adequacy of a plot-based general fauna-monitoring program for sampling reptiles as indicators of ecosystem health in a semi-arid upland region of the Northern Territory, Australia. Methods We surveyed reptiles at 90 sites, stratified between major landform and vegetation types, and using standard fauna-sampling methods, across the 2568 km2 Tjoritja National Park in the MacDonnell Ranges. We compiled a full inventory of the reptile fauna of the study area and identified species with potential utility as ecological indicators. We then used single-season occupancy models and power analyses to evaluate the adequacy of sampling for detecting potential future changes in occupancy. Key results We detected 57 of the 68 reptile species known from the protected area, 17 of which are potentially useful indicators of ecological health, mostly related to fire management. There was insufficient power to detect moderate (50%) future changes in reptile occupancy for all but the single most detected species. For the two ecological indicator species with sufficient detections for occupancy modelling, a positive association with a keystone structure (dense spinifex grass) was confirmed. However, increasing detection probability or the number of surveys would result in only minor improvements in power to detect occupancy change in these species. Conclusions Although reptiles are potentially useful indicators of ecological health, particularly in relation to fire regimes, the number of sites required to detect future changes in reptile occupancy by using standardised plot-based monitoring in this protected area is prohibitively high. Implications Our results suggest that once ecological associations are understood, monitoring ecological health remotely by using techniques such as fire-scar mapping to track proportions of long-unburnt vegetation should be considered over labour-intensive surveillance monitoring for reptiles. Targeted monitoring of threatened and other reptile species of conservation or cultural concern may also be warranted.

Enhancing ecological uncertainty predictions in pollution control games through dynamic Bayesian updating

This study presents a dynamic Bayesian game model designed to improve predictions of ecological uncertainties leading to natural disasters. It incorporates historical signal data on ecological indicators. Participants, acting as decision-makers, receive signals about an unknown parameter-observations of a random variable’s realization values before a specific time, offering insights into ecological uncertainties. The essence of the model lies in its dynamic Bayesian updating, where beliefs about unknown parameters are refined with each new signal, enhancing predictive accuracy. The main focus of our paper is to theoretically validate this approach, by presenting a number of theorems that prove its precision and efficiency in improving uncertainty estimations. Simulation results validate the model’s effectiveness in various scenarios, highlighting its role in refining natural disaster forecasts.

Comprehensive assessment of water and sediment quality to support sustainable management practices and mitigate potential risks of trace metal pollution in the Johor River Basin, South Peninsular Malaysia

Human activities have caused concerns over the contamination of trace elements in aquatic systems due to their toxicity, long-lasting nature, and ability to accumulate in living organisms. This study evaluated the spatial pattern, environmental hazard, and potential health hazard of 13 trace metals in water and sediment samples collected from the Johor River basin using multivariate statistical techniques in order to identify the impact of both natural and human-related factors on the presence of trace metals in the area. The increased levels of metals in Station S1 indicated a significant impact from municipal, domestic, and industrial waste. The Geo-accumulation Index (Igeo) values for pollution and ecological indices in the sediment of the Johor River Basin ranged from -9.44 to 6.27. The Pollution Load Index (PLI) values ranged from 0.05 to 0.18, and the Potential Ecological Risk Assessment (RI) values ranged from 2.15 to 11.18. These results indicate that the sediments in the Johor River Basin have a low risk of contamination from trace metals. The water's hazard quotient (HQ) had an average value of 0.0001, while the hazard index (HI) had an average value of 0.0003. It is important to increase stakeholders' understanding and concerns regarding the potential long-term human health and ecological implications associated with trace metals in Johor River water. The results of this study offer essential initial information for government entities to implement sustainable management strategies, reducing the likelihood of future trace metal contamination issues in the Johor River basin and similar regions.

Response of chlorophyll-a to rainfall event in the basin of the South China sea: Statistical analysis

Chlorophyll-a (Chl-a) is an essential ecological indicator, and affected by processes such as typhoons, mesoscale eddies, and Rossby waves. However, the impact of more frequent and widespread precipitation events on Chl-a seems to be overlooked. This study utilized remote sensing data and reanalysis data to investigate the response of Chl-a to 240 precipitation events in the central South China Sea from 2005 to 2019. The results indicate that precipitation events have a significant impact on Chl-a concentration. Following a precipitation event in 2019, the Chl-a concentration in the affected area increased by approximately 0.22 mg m−³ from the 3rd to the 7th day. The reasons for the increase in Chl-a concentration were the vertical mixing induced by wind stirring and the upwelling caused by wind stress curl, which transported nutrients to the euphotic zone, lowering the sea surface temperature and triggering a proliferation of phytoplankton. Additionally, dissolved nutrients in precipitation provided a nutrient source for Chl-a growth. The contributions of nutrient supply, wind speed, and wind stress curl to the increase in Chl-a concentration during precipitation events were 18%, 37%, and 45%, respectively. Precipitation events enhanced marine primary productivity, playing a crucial role in deepening our understanding of ocean-atmosphere interactions and their impact on marine ecosystem.

Spatial and Temporal Heterogeneity of Eco-Environmental Quality in Yanhe Watershed (China) Using the Remote-Sensing-Based Ecological Index (RSEI)

The long-term impacts of climate change and human activities have resulted in the Yanhe watershed, a typical watershed in the Loess Plateau region, exhibiting a high degree of vulnerability and significant heterogeneity in ecological environmental quality. This has led to environmental degradation and complex socio-ecological challenges. Consequently, there is an urgent need to carry out research on the spatial and temporal differentiation patterns of ecological environment quality. By utilizing remote sensing data spanning 21 years, this study evaluated the evolutionary trends and consistency of ecological environment quality (EEQ) within the Yanhe watershed based on the remote-sensing-based ecological index (RSEI). Furthermore, it examined global and local spatial autocorrelation of the RSEI by constructing a hexagonal grid, thereby revealing the spatiotemporal characteristics of EEQ at different scales within the Yanhe watershed. The results were as follows: (1) The EEQ has exhibited an overall upward trend in the past two decades, while it has displayed significant fluctuations; (2) the Global Moran’s I values for the years 2000, 2010, and 2020 were 0.18, 0.32, and 0.21, respectively, indicating a presence of spatial autocorrelation within the RSEI; (3) the overall EEQ of the Yanhe watershed will continue to improve, although the ecological quality in certain areas remains unstable due to local natural conditions and human activities. This research not only contributes to the technical framework for analyzing the spatiotemporal heterogeneity of EEQ but also provides actionable insights for ecosystem restoration and sustainability within the Loess Plateau watershed. Our work advances the understanding of ecological dynamics in semi-arid regions and offers a model for assessing ecological quality in similar environmental contexts.

Spatial–Temporal Variations of the Gross Ecosystem Product under the Influence of the Spatial Spillover Effect of Urbanization and Ecological Construction in the Yangtze River Delta Region of China

Rapid development of urbanization and intense human activities had a profound influence on the ecosystem service functions. As an integrated monetary index for the evaluation of final ecosystem services, the gross ecosystem product (GEP) is widely used in the quantification of ecosystem service value (ESV). This study initially assessed and analyzed the spatial distribution of the GEP at the county-level scale using multisource data spanning 2000, 2005, 2010, 2015, and 2020. Then, the spatial transfer characteristics of the GEP were measured. Finally, the study employed spatial panel econometric models and the geographically weighted regression (GWR) model to investigate the spatial effect of urbanization and ecological construction on the GEP. The results indicated that: (1) In 2020, the GEP in the Yangtze River Delta Region was RMB 15.24 trillion, and the GEP per unit area was RMB 42.58 million per square kilometer. It exhibited a cumulative decrease of RMB 298.72 billion from 2000 to 2020. (2) The spatial transfer efficiency of the GEP in urban agglomerations showed a clear decline trend. During the period of 2000–2020, over 96% of county-level units exhibited a decline with RMB 90,076,103.17/km2, indicating a consistent downward trend from the central regions towards the periphery. (3) Based on the decomposition effects of the spatial Durbin mode, urbanization and the ecological construction indicator showed spatial spillover effects on the GEP, but their impact mechanisms varied substantially. Among them, the urbanization rate (UR), population density (PD), and the proportion of impervious land (ILP) had the largest negative effect on the GEP, and a 1% rise in ILP locally resulted in a 0.044% decline in the local GEP and a 0.078% rise in the GEP of neighboring units. And the area of ecological land had a positive effect on the GEP of both local and neighboring areas. Those conclusions can offer evidence in favor of encouraging ecologically responsible building practices and sustainable growth in urban agglomerations.

Research on provincial water resources carrying capacity and coordinated development in China based on combined weighting TOPSIS model

With the continuous development of the economy and society, along with the sustained population growth, the issue of water resources carrying capacity in China has attracted increasing attention. This paper constructs a model for evaluating the provincial water resources carrying capacity in China from four dimensions: water, economy, society, and ecology. Utilizing this model, we analyze the spatiotemporal variations in water resources carrying capacity among 31 provinces in China from 2005 to 2021. Additionally, we delve into the coupling coordination and influencing factors of water resources carrying capacity. The study reveals an overall increasing trend in China’s water resources carrying capacity index, with the ecological indicator exhibiting the most significant growth while the water resources sub-indicator lags behind. There are notable regional differences, with higher water resources carrying capacity observed in the eastern coastal areas and relatively lower capacity in the western regions. The ecological criterion becomes a core factor constraining water resources carrying capacity from 2005 to 2015, gradually giving way to the prominence of the social criterion since 2015. The coordination degree is relatively higher in the eastern regions, more scattered in the western regions, and relatively stable in the central regions. Based on the research findings, a series of recommendations are proposed, including strengthening environmental protection policies, optimizing water resources management mechanisms, improving water use efficiency, and promoting economic structural diversification. These suggestions aim to facilitate the sustainable development of water resources carrying capacity in China.

Study on the Spatial and Temporal Trends of Ecological Environment Quality and Influencing Factors in Xinjiang Oasis

Human activities and climate change have profound impacts on the ecological environment of oases in Xinjiang, and it is of great significance to explore the spatial and temporal evolution patterns of ecological environment quality in this region for the sustainable development of Xinjiang. The remote sensing ecological index (RSEI) was extracted from the Google Earth Engine (GEE) platform from 2000 to 2020, and the coefficient of variation and Hurst index were used to reveal the spatial and temporal characteristics and stability of the ecological environment quality of the artificial oasis and natural oasis in Xinjiang. The key factors affecting the ecological environment quality are explored through correlation analysis and geoprobes. The results show that the distribution of the ecological environment in Xinjiang oases is high in the north and low in the south, and the overall quality shows a fluctuating downward trend from 0.210 to 0.189. Artificial oases have higher RSEI values, stability, and sustainability than natural oases. The RSEI in the study area was mainly influenced by humidity, followed by greenness and heat, and dryness had the least influence on the RSEI model. Based on the geodetector, the top three highest contributors were found to be precipitation (PRE) (0.83) > relative humidity (RHU) (0.82) > evapotranspiration (ET) (0.57). Climate is the main factor affecting the ecological quality of oases, and the RSEI can be improved by increasing the proportion of artificial oases. The study aims to provide a scientific basis for the sustainable development of oases in arid zones.

Coastal ecological security assessment in Laizhou Bay, China: from the perspective of demographic-social-economic-natural complex ecosystem.

Assessment of ecological security is essential for understanding the status of bay ecosystem and developing appropriate management strategy. Based on the driving force-pressure-state-impact-response (DPSIR) model, the demographic, economic, social, and ecological data of Laizhou Bay and its three neighboring counties were selected for the period from 2015 to 2021. An ecological security evaluation index system of Laizhou Bay containing 26 indicators was established, and the weights of each indicator were determined by the methods of AHP and EWM, and a comprehensive evaluation of the ecological security of Laizhou Bay was carried out by ESI. Correlations between indicators were analyzed by the Spearman's rank coefficient of correlation. The results showed that there were significant correlations between marine conditions and indicators such as population size in the surrounding area, mariculture area, industrial and domestic wastewater discharge, and treatment rate. Overall, from 2015 to 2021, the ecological security of Laizhou Bay showed a favorable trend, from a relatively unsafe level to a generally safe level, and then to a relatively safe level. Through the comprehensive evaluation of the ecological security of Laizhou Bay, we can recognize the utilization of marine resources and ecological carrying capacity, guide the rational development and utilization of marine resources, and promote the sustainable development of the marine economy.

Analysis of the evolution and influencing factors of ecological environment quality after the transformation of resource-exhausted cities based on GEE and RSEI: a case study of Xuzhou City, China

ABSTRACT This study used Google Earth Engine (GEE) to get and process Landsat images of Xuzhou from 2008 to 2020, and built remote sensing ecological indices (RSEI). This study analyzed the spatiotemporal features and drivers of ecological environment quality after Xuzhou’s transformation using landscape pattern index, spatial autocorrelation, and geographic detector methods. The results showed that: (1) The ecological environment quality of Xuzhou improved steadily but unevenly from 2008 to 2020; the west and central urban areas had poor but improving quality, while the east had the opposite trend; (2) The landscape pattern indices of ecological environment quality in different regions of Xuzhou did not change consistently from 2008 to 2020; (3) The spatial distribution of ecological environment quality had significant autocorrelation, with high-high clusters in the east and low-low clusters in the center and the urban areas of each district and county; (4) NDVI is the component index that has the greatest impact on the changes in the RSEI. Among the single factors, land use conditions have the strongest influence on ecological environmental quality. After the interaction of dual factors, the explanatory power is stronger than that of any single factor. The research results can support urban planning and design, ecological environment protection, etc. in Xuzhou, and offer insights for monitoring and evaluation of ecological environment quality after the transformation of resource-exhausted cities.

Analysis of the spatiotemporal dynamics and driving factors of ecosystem quality in Inner Mongolia from 2005 to 2020

Enhancing ecosystem quality is a necessary part of establishing of ecological civilization. The study of ecosystem quality requires the development of comprehensive evaluation indices. The existing simple remote sensing ecological indices are insufficient for achieving a comprehensive and systematic evaluation of the ecosystem quality. Therefore, we constructed an ecosystem quality index based on the landscape pattern, ecosystem stability, and ecosystem services. The spatiotemporal dynamics of the ecosystem quality in Inner Mongolia were analyzed over the period from 2005 to 2020. Moreover, a geographically weighted regression model was used to investigate the factors influencing the spatiotemporal variations in the ecosystem quality. The main results are as follows. (1) The spatial distribution of ecosystem quality in Inner Mongolia exhibited a gradual decline from the northeast to the southwest. In contrast, temporal analysis revealed a general increase in ecosystem quality from 2005 to 2020. (2) Climate was a significant factor influencing the spatial heterogeneity and temporal variability of the ecosystem quality. Socioeconomic factors, population density and livestock numbers had notable impacts on the spatial heterogeneity and temporal variability of ecosystem quality, respectively. (3) In Inner Mongolia, temperature and ecosystem quality showed a positive correlation in the northeastern region, but a negative correlation in the central and western regions. The findings offer valuable support for local policymakers in making informed decisions regarding targeted ecosystem management. Furthermore, our results provide local governments with valuable insights for enhancing the quality of regional ecosystems by taking into account the specific conditions of the area.

Predictive modeling of green water availability: The role of annual plants as an ecological indicator in dryland ecosystems

Green water is primarily associated with the appearance of annual plants and plays a significant role in biomass production in both arid and semi-arid ecosystems. Herein, we aim to estimate the optimal threshold for determining the presence or absence of annual plants and use them as an ecological indicator to assess potential green water areas in Kuwait as a case study. We integrate remote sensing techniques and MaxEnt modeling. The AUC for the annual plant distribution with all examined factors is 0.847, and the standard deviation is 0.050. The results demonstrated that potential locations with high levels of green water cover <20% of the country. The annual plant distribution was significantly correlated with several types of perennial plants, maximum temperature, precipitation, and sandy soils. It was also found that annual plants are controlled by the spring and winter temperature decline and the timing of precipitation occurrence, especially the pattern and amount of rainfall received in November. Sandy loam and loam soils were found to be ideal for annual plants, although land depressions and soil types are crucial factors in determining annual plant distribution. Additionally, annual plants enhanced the growth of several perennial communities. To reiterate, our study's model helped to comprehend the significance of annual plants as an ecological indicator in sustaining soil moisture over a prolonged period, as well as factors controlling the distribution of annual plants. The developed model and indicators could support decision-makers in determining appropriate locations with adequate levels of green water for revegetation planning in arid landscapes.

Ecological boundaries and their regional exceedance in China

Planetary boundaries have received considerable attention since they were first proposed, but applying various downscaling methods to the regional scale has certain limitations due to regional heterogeneity. The concept of ecological boundaries (EB) extends and complements planetary boundaries at a regional scale. However, previous studies have not considered the EB of multiple regions and the impact of interregional ecosystem service value (ESV) flows on EB. In this study, we optimized the EB accounting method and quantified the EB of 30 provinces in China from 2002 to 2017, then assessed the ecosystem unsustainability, and determined the impact of demand for goods and services on the consumption of local natural resources by each province in China using an ESV-extended multiregional input-output model. We found that EB increased in all provinces of China. The ecological unsustainability index of all 30 provinces was larger than 1, indicating a serious environmental unsustainability, but the magnitude of the index tends to decrease. Furthermore, the regions that have the greatest impact on exceeding EB in each province were concentrated in Guangdong and Henan. Guangdong had the highest total net imports in 2012 and 2015 (665.08 and 641.70 billion yuan, respectively), while Henan had the highest total net imports in 2017 (611.58 billion yuan). For the role of net exports, the rankings of the provinces differed in terms of the direct ESV and the boundary-exceeding ESV indicators. Our results reveal EB across provinces in China, underscoring the importance of considering the flow of ESV between regions in assessing the impact of exceeding EB. This study can assist policymakers in better allocating ecological resources within EB, which is critical for alleviating ecological pressures.

Identification and classification of urban employment centers based on big data: A case study of Beijing.

The layout, scale and spatial form of urban employment centers are important guidelines for the rational layout of public service facilities such as urban transportation, medical care, and education. In this paper, we use Internet cell phone positioning data to identify the workplace and residence of users in the Beijing city area and obtain commuting data of the employed to measure the employment center system in Beijing. Firstly, the employment density distribution is generated using the data of the working places of the employed persons, and the employment centers are identified based on the employment density of Beijing. Then, we use the business registration data of employment centers to measure the industrial diversity within the employment centers by using the ecological Shannon Wiener Diversity Index, and combine the commuting links between employment centers and places of residence to measure the energy level of each employment center, analyze the hinterland and sphere of influence of each center, and finally using the industrial diversity index of employment centers and the average commuting time of employed persons, combined with the K-Means clustering algorithm, to classify the employment centers in Beijing. The employment center identification and classification method based on big data constructed in this study can help solve the limitations of the previous employment center system research in terms of center identification and commuting linkage measurement due to large spatial units and lack of commuting data to a certain extent. The study can provide reference for the regular understanding and technical analysis of employment centers and provide help for the employment multi-center system in Beijing in terms of quantifying the employment spatial structure, guiding the construction of multi-center system, and adjusting the land use rules.

Avifaunal Diversity of Cantonment Area, Lucknow, Uttar Pradesh, India

Birds have always fascinated mankind with their naturally attractive plumage, harmonious songs and creative behavior. Avifaunal Diversity is one of the most important ecological indicators, displays the environmental quality of an area, its pollution level, safety and accessibility of food and habitat. Cantonment area is one of the distinctive locations represents a sub-urban area of Lucknow. Cantonment area is an abundant green area around 23.43 square kilometer, preferred by number of bird species at its different types of habitat like shaded trees, bushes, grasses, grounds some parks and buildings etc. They provide food and shelter for the urban terrestrial bird’s community. The study was performed in Cantonment area for six months from February, 2022 to July, 2022. Bird surveys were carried out using the Line transect method across four different transects at this area. As a result of six months observation, 55 bird species were recorded belonging to 15 orders and 29 families. Majority of species were observed in the order Passeriformes and family Muscicapidae. Data analysis showed that 29 avian species were Common, 12 were Fairly Common, 6 were Uncommon and 8 were Rare, whereas 52 avian species were residents and 3 avian species were migrants.

Diversity and Ecological Assessment of Grasslands Habitat Types: A Case Study in the Calabria Region (Southern Italy)

Grasslands differ in many types depending on the diversity of climatic conditions and substrates. Due to the great wealth of species found in semi-natural grasslands, they conserve an essential part of the biodiversity of the European Union (EEC 43/92), defined as habitats of community interest. Using the region of Calabria (southern Italy) as a case study, this study aims to evaluate how species assemblages and a set of indicators applied to them can be used to analyse and characterize the diversity, ecological features and conservation status of grassland habitats. Vegetation analysis was carried out using the phytosociological method, and habitat ecological characteristics were defined by Ellenberg’s ecological indicator adapted to the Italian flora. Multivariate analysis of the surveys by means of cluster analysis and Principal Components Analysis (PCA) made it possible to define eight habitat groups according to EEC Directive 43/92: 6110 Rocky or basophilous calcareous grasslands of the Alysso-Sedion albi, 6170 Alpine and subalpine calcareous grasslands, 6220*a Pseudo-steppe with grasses and annuals of the Thero-Brachypodietea dominated by a Lygeum spartum, 6220*b Pseudo-steppe with grasses and annuals of the Thero-Brachypodietea dominated by Hyparrhenia hirta, 6210* Semi-natural dry grasslands and scrub facies on calcareous substrates (Festuco-Bromometalia) (*important orchid sites), 6230* Species-rich Nardus grasslands, on siliceous substrates in mountain areas (and submountain areas, in Continental Europe), 6410 Molinia meadows on calcareous, peaty or clayey-siltladen soils (Molinion caeruleae), 6420 Mediterranean tall humid herb grasslands of the Molinio-Holoschoenion, 6430 Hydrophilous tall herb fringe communities of plains and of the montane to alpine levels. Temperature (T) and oisture (U) are the most statistically significant ecological factors in differentiating different habitat types. Analysis of diversity, assessed through Shannon and Evenness indices, showed that it is strongly correlated with habitat diversity as soil moisture increases. The study of ecological characteristics, correlated with biodiversity indices, helps to characterize grassland habitats, providing guidance for the implementation of active conservation policies for these habitats.