Ecological Quality Assessment Research Articles

Assessment and Simulation of Urban Ecological Environment Quality Based on Geographic Information System Ecological Index

The urban ecological environment is crucial to the quality of life of residents and the sustainable development of the region, and the assessment and prediction of the ecological environment quality can provide a scientific guidance for ecological environment management and improvement. We proposed a novel approach to assess and simulate the urban ecological environment quality using the Geographic Information System Ecological Index (GISEI). First, we calculated the remote sensing ecological index (RSEI) for Xi’an in 2020. Second, we selected land use data, mean annual temperature, and mean annual relative humidity as ecological indicators. We regressed these indicators on the RSEI to obtain the GISEI of Xi’an in 2020. Finally, we simulated the GISEI of Xi’an in 2030 by predicting the ecological indicators and analyzed the changes in the ecological environment quality. The results of the study show that the ecological environment quality in Xi’an in 2020 is better overall. By 2030, most of the ecological environment quality in Xi’an will be worse, and the proportion of the excellent area will decrease from 42.8% to 3.8%. The more serious ecological degradation is mainly located in the regions bordering the Qinling Mountains and the Guanzhong Plain, and the ecological environment quality in most areas of the Qinling Mountains will deteriorate from excellent to good.

Vertical variations and environmental heterogeneity drove the symphony of periphytic protozoan fauna in marine ecosystems

Periphytic protozoa are esteemed icons of microbial fauna, renowned for their sensitivity and role as robust bioindicators, pivotal for assessing ecosystem stress and anthropogenic impacts on water quality. Despite their significance, research exploring the community dynamics of protozoan fauna across diverse water columns and depths in shallow waters has been notably lacking. This is the first study that examines the symphony of protozoan fauna in different water columns at varying depths (1, 2, 3.5 and 5 m), in South China Sea. Our findings reveal that vertical changes and environmental heterogeneity plays pivotal role in shaping the protozoan community structure, with distinct preferences observed in spirotrichea and phyllopharyngea classes at specific depths. Briefly, diversity metrics (i.e., both alpha and beta) showed significantly steady patterns at 2 m and 3.5 m depths as well as high homogeneity in most of the indices was observed. Co-associations between environmental parameters and protozoan communities demonstrated temperature, dissolved oxygen, salinity, and pH, are significant drivers discriminating species richness and evenness across all water columns. Noteworthy variations of the other environmental parameters such as SiO3–Si, PO4−-P, and NO2––N at 1 m and NO3−–N, and NH4+–N, at greater depths, signal the crucial role of nutrient dynamics in shaping the protozoan communities. Moreover, highly sensitive species like Anteholosticha pulchara, Apokeronopsis crassa, and Aspidisca steini in varying environmental conditions among vertical columns may serve as eco- indicators of water quality. Collectively, this study contributes a thorough comprehension of the fine-scale structure and dynamics of protozoan fauna within marine ecosystems, providing insightful perspectives for ecological and water quality assessment in ever-changing marine environments.

Using the Heavy Metal and Biotic Indices to Assess Ecological Quality in the Central Area of the East Sea, South Korea

With the rapid development of the South Korean economy, human activities have extensively affected Korea’s coastal environment. A precise ecological quality assessment remains paramount despite the relatively lower impact of human activities on the East Sea compared to the West and South Seas of South Korea. Accurate ecological quality assessments can provide valuable marine environmental protection and management references. In our study, we employed seven indices based on heavy metals and macrobenthos to comprehensively assess ecological quality. Our results indicated the final ecological quality in the central East Sea of South Korea was acceptable at most stations; however, the ecological quality in winter marginally falls short compared to that in spring. The concentration of heavy metals emerges as a significant determinant of the final ecological quality, underscoring the need for subsequent studies to investigate the origins of heavy metals in the central East Sea of South Korea and the influence of anthropogenic activities on heavy metal concentrations. Furthermore, employing a single biotic index proves challenging for accurately assessing ecological quality in the East Sea of South Korea.

Urban Ecological Quality Assessment Based on Google Earth Engine and Driving Factors Analysis: A Case Study of Wuhan City, China

Ecological quality is a critical factor affecting the livability of urban areas. Remote sensing technology enables the rapid assessment of ecological quality (EQ), providing scientific theoretical support for the maintenance and management of urban ecology. This paper evaluates and analyzes the EQ and its driving factors in the city of Wuhan using remote sensing data from five periods: 2001, 2006, 2011, 2016, and 2021, supported by the Google Earth Engine (GEE) platform. By employing principal component analysis, a Remote Sensing Ecological Index (RSEI) was constructed to assess the spatiotemporal differences of EQ in Wuhan City. Furthermore, the study utilized the optimal parameter-based geographical detector model to analyze the influence of factors such as elevation, slope, aspect, population density, greenness, wetness, dryness, and heat on the RSEI value in 2021 and further explored the impact of changes in precipitation and temperature on the EQ in Wuhan. The results indicate that (1) principal component analysis shows that greenness and wetness positively affect Wuhan’s EQ, while dryness and heat have negative impacts; (2) spatiotemporal analysis reveals that from 2001 to 2021, the EQ in Wuhan showed a trend of initial decline followed by improvement, with the classification grades evolving from poor and average to good and better; (3) the analysis of driving factors shows that all nine indicators have a certain impact on the EQ in Wuhan, with the influence ranking as NDVI > NDBSI > LST > WET > elevation > population density > GDP > slope > aspect; (4) the annual average temperature and precipitation in Wuhan have a non-significant impact on the EQ. The EQ in Wuhan has improved in recent years, but comprehensive management still requires enhancement.

Spatial-temporal characteristics analysis and ecological environment quality evaluation of forest health care bases in Yunnan, Guizhou and Sichuan provinces

As the forest health care in China is still in the early stage of development, the construction standards of forest health care base are not unified yet, resulting in large differences in the evaluation criterion for the ecological environment of forest health care bases. So, it is urgent to develop a new forest health care ecological environment quality assessment method. Yunnan, Guizhou and Sichuan provinces of China were selected as the study area, the previous 6 batches of 165 national forest health care pilot construction bases were selected as the main data source. This study explored the spatial and temporal distribution characteristics of forest health care bases in the study area using standard deviation ellipses, kernel density estimation method and cold and hot spot analysis. Furthermore, this study evaluated the ecological environment quality of the forest health care bases with a new ecological environment quality evaluation index model, which assembled Fraction Vegetation Coverage (FVC), Wetness (WET), Evapotranspiration (ET), Land Surface Temperature (LST) and Normalized Difference Bare Soil Index (NDBSI). The results are as follows: (1) the forest health bases in the study area are mainly located by the east of the Hu Line with a northeast-southwest distribution direction characteristics, and gradually expanded into a shape of “high in the east and low in the west, multi-point development”. (2) the area with ecological environment quality in excellent, good and medium grade accounts for about 87.73 % in the study area, indicating that most of the study area is suitable for the construction of forest health care base. These results can provide a practical guidance for the further rational layout and balanced development of forest health care bases in the study area.

Spatial-temporal Evolution and Driving Factors Analysis of Ecological Environment Quality in Daihai Basin based on AWRSEI

Watersheds are an important ecological security barrier and social and economic development area. In order to evaluate the ecological environment quality of arid and semi-arid watersheds more objectively and accurately, based on the remote sensing ecological index (RSEI), the salinity index was introduced to construct a remote sensing ecological index (AWRSEI) suitable for arid and semi-arid watersheds, and the Daihai watershed was taken as an example to analyze its applicability. Based on the AWRSEI model, four phases of Landsat TM/OLI composite images were used to quantitatively evaluate the ecological and environmental quality of the Daihai Basin from 2001 to 2020. The spatio-temporal evolution of the ecological and environmental quality of the Daihai Basin was analyzed using the coefficient of variation and spatial autocorrelation, and the cause analysis and driving factor explanation power analysis were carried out using geographic detectors. The results showed that:① the average correlation coefficient between AWRSEI and various ecological factors was 0.860, which was more representative than that of a single index component. The load positive and negative values and ranking of the first principal component were consistent with those of RSEI, the contribution rate of eigenvalues was 3.69% higher than those of RSEI, and the evaluation results were closer to the real surface conditions, which is suitable for the ecological environment quality assessment of arid watersheds. ② The annual average of the AWRSEI index in the Daihai Basin from 2001 to 2020 was 0.427, which indicated a poor ecological environment quality basis. During the study period, the average of AWRSEI showed a fluctuating trend and reached the highest value of 0.502 in 2020. The overall ecological environment quality improved significantly, the deterioration area decreased by 20.51%, and the improvement area increased by 12.71%. In terms of spatial distribution, the ecological environment quality of forest land in the southern and northwestern high-altitude areas of the Daihai Basin was good, whereas that in the northern and southern mid-altitude areas was poor, and that in the northern area was better than that in the southern area. ③ The average variation coefficient of AWRSEI in the Daihai Basin was 0.280, the ecological environment quality was stable, and the overall change fluctuation was small; the high fluctuation was mainly concentrated in the southern part of the lake and the residential area. There was a significant spatial autocorrelation in the ecological environment quality of the Daihai Basin, and the high-high agglomeration area was mainly distributed in the forest area at high altitude and the cultivated land area at low altitude. Low-low concentration areas were scattered in the middle altitude area. ④ The improvement of the ecological environment in Daihai Basin from 2001 to 2020 was mainly due to the increase in NDVI and the decrease in NDBSI and NDSI. NDVI and NDBSI were the combination with the strongest interaction and the strongest interpretation of the ecological environment. Land use was the dominant factor of AWRSEI and had the strongest explanatory power. The combination of land use and meteorological factors was the strongest interaction, and the relationship between each driving factor was enhanced.

Spatio-temporal dynamics of ecological, bacteriological, and overall water quality of the Damodar River, India.

Assessing river water quality is crucial for human and ecological needs because of the deterioration of the river and escalated water pollution under the threats of anthropogenic activities. In order to assess river water quality, the Damodar River water was evaluated from the perspectives of spatio-temporal dynamics of ecological (organic pollution index or OPI and eutrophication index or EI), bacteriological (coliform count and comprehensive bathing water quality index or CBWQI), and overall water quality assessments (water quality index or WQI and comprehensive pollution index or CPI). The OPI reveals that 44.66% of water samples have heavy organic pollution; however, EI depicts that almost all water samples of Damodar River have severe eutrophication, especially in the pre- and post-monsoon seasons. Moreover, the fecal coliform count and CBWQI indicate the unsuitability of river water for bathing. The overall WQI portrays that 21.56%, 33.59%, and 22.47% of water samples have heavy pollution in pre-monsoon, monsoon, and post-monsoon, respectively. Moreover, 73.39% of water samples have low CPI indicating slight comprehensive pollution. This study also reveals that the pollution level in the Damodar River downstream of the Durgapur barrage is high among the other stations. The major reasons behind the severe contamination of Damodar River water are urban-industrial and agricultural effluents mixing into the river that lead to higher concentrations of BOD, DO, fecal coliform, COD, fluoride TSS, and turbidity in the river water. Thus, this study carries appreciated information on policy recommendations for the different stakeholders of the Damodar River basin including regional planners, agri-engineers, and ecological river engineers for sustainable river management.

Spatiotemporal Pattern, Evolutionary Trend, and Driving Forces Analysis of Ecological Quality in the Irtysh River Basin (2000–2020)

Considering climate change and increasing human impact, ecological quality and its assessment have also received increasing attention. Taking the Irtysh River Basin as an example, we utilize multi-period MODIS composite imagery to obtain five factors (greenness, humidity, heat, dryness, and salinity) to construct the model for the amended RSEI (ARSEI) based on the Google Earth Engine platform. We used the Otsu algorithm to generate dynamic thresholds to improve the accuracy of ARSEI results, performed spatiotemporal pattern and evolutionary trend analysis on the results, and explored the influencing factors of ecological quality. Results indicate that: (1) The ARSEI demonstrates a correlation exceeding 0.88 with each indicator, offering an efficient approach to characterizing ecological quality. The ecological quality of the Irtysh River Basin exhibits significant spatial heterogeneity, demonstrating a gradual enhancement from south to north. (2) To evaluate the ecological quality of the Irtysh River Basin, the ARSEI was utilized, exposing a stable condition with slight fluctuations. In the current research context, the ecological quality of the Irtysh River Basin watershed area is projected to continuously enhance in the future. This is due to the constant ecological protection and management initiatives carried out by countries within the basin. (3) Precipitation, soil pH, elevation, and human population are the main factors influencing ecological quality. Due to the spatial heterogeneity, the driving factors for different ecological quality classes vary. Overall, the ARSEI is an effective method for ecological quality assessment, and the research findings can provide references for watershed ecological environment protection, management, and sustainable development.

Ecological environment quality assessment and spatial autocorrelation of northern Shaanxi mining area in China based-on improved remote sensing ecological index

The northern Shaanxi coal mining area is an important coal production base in China and an ecologically fragile area, and it is of great significance to explore the ecological environment quality and spatial evolution trend of the mining area. Based on Sentinel-2 and MODIS image data, an improved remote sensing ecological index was constructed by principal component analysis method: normalized difference vegetation index, normalized difference water index, normalized differential buildup and bare soil index, and net primary productivity. The ecological environment quality of the northern Shaanxi coal mining area and its influencing factors, as well as the spatial autocorrelation analysis of ecological environment quality, were discussed. The results showed that: 1) The vegetation coverage in the study area showed an overall increasing trend, but it was greatly affected by the average annual temperature. The NDVI index at the mine area is higher than the NDVI index at the non-mine area. 2) The water area gradually decreases with the year, which has a certain negative correlation with the total raw coal production. 3) The NDBB index showed a decreasing trend with the year, and compared with the non-mining area. 4) The coupling of year-by-year precipitation and temperature leads to interannual fluctuation of NPP value. 5) The change of ecological environment quality in the study area is the result of the comprehensive effect of natural factors and human factors. The implementation of ecological protection projects such as geological environmental protection and land reclamation in mining areas also has a certain impact on the trend of ecological environment quality. 6) There was a significant spatial autocorrelation in the quality of the ecological environment in the study area. There are significant “High-High” gathering areas of ecological environment quality within the coal mining area.

Development of a macroinvertebrate-based biotic index to assess water quality of rivers in Niger State, North Central Ecoregion of Nigeria.

The increasing pollution of lotic ecosystems in sub-Saharan Africa, particularly in Nigeria, poses a threat to water quality, public health and biodiversity. It is therefore essential to develop appropriate tools and methods for monitoring these rivers, particularly in heavily affected areas, where these water resources are vital to the surrounding communities that are heavily dependent on them. To fill this gap, we propose to develop a multimetric index based on macroinvertebrates for the assessment of ecological quality of rivers in Niger State (NSRBI). Eighty-eight metrics were evaluated through a step-by-step statistical process (namely, range test and stability, redundancy test and relationship with abiotic variables), in which metrics that did not meet the conditions were excluded. At the end of this process, only four metrics (%Hemiptera, Diptera richness, Pielou equitability and % of very large individuals (size > 40 mm)) fulfilling all criteria were included in the index. These metrics were then scored on a continuous scale and divided into four water quality classes: "very poor", "poor", "fair" and "good". Evaluation of the performance of the index on test sites showed a correspondence of 90% between index result and environmental-based classification. Therefore, the NSRBI could be a valuable tool for monitoring and assessing the ecological conditions of rivers in Niger State and the North Central Nigeria ecoregion predominantly in urban and agricultural landscapes.

Environmentally friendly assessment of ecological quality of watercourses based on banded demoiselle, Calopteryx splendens

AbstractDragonflies and damselflies are excellent bioindicators of the quality of both aquatic and terrestrial ecosystems. In our study, we assessed the usefulness of metric and meristic morphological traits as environmentally friendly and cost‐effective indicators of the integrative ecological quality of watercourses. Our study species of choice was the damselfly banded demoiselle, Calopteryx splendens (Harris) (Odonata: Calopterygidae). Adult C. splendens specimens were collected at three study sites along the trophic gradient of the Tisza River in Hungary and Ukraine. Body and abdomen length, head width, and distances between wing landmarks were assessed as metric traits, and the number of wing cells as meristic traits. The concentration of chlorophyll‐a was used to classify the three study sites into having a low, intermediate, and high trophic condition based on earlier studies. Significant differences were found along the trophic gradient based on the measured metric and meristic traits. Especially, insects from the site with the highest trophic condition had the largest body length, head width, and distances between wing landmarks, as well as the highest number of cells in the fore wings. There were also differences between males and females, but we did not find differences in fluctuating asymmetry (FA), i.e., differences between the left and the right wings. These results indicated that the morphological traits of adult banded demoiselles could be indicative of the environmental quality of a watercourse.

Standardization of ALEX index for the ecological quality assessment under European Framework Directives in Mediterranean sensitive habitats affected by biological invasions

Abstract This paper aims at providing a standardized procedure to assess the ecological quality of Mediterranean marine habitats in relation to biological invasions by macroalgae through the employment of the ALEX index. Available data from previous ALEX applications were used to optimize the sampling design and to propose a standardized procedure. The procedure was applied to the main Mediterranean sensitive habitats, coralligenous reefs and meadows of the endemic seagrass Posidonia oceanica, at two sites in the north‐western Mediterranean Sea. A total of 73 native macroalgal taxa and four introduced taxa (the Chlorophyta Caulerpa cylindracea and the turf forming Rhodophyta Acrothamnion preissii, Womersleyella setacea and Asparagopsis spp.) were identified. Coralligenous reefs exhibited a higher abundance of both C. cylindracea and introduced turf species, while P. oceanica meadows were mostly affected by W. setacea and A. preissii. The application of ALEX for different years on coralligenous reefs highlighted the consistency of the index over time in the absence of further invasions. The use of ALEX index with other ecological quality indices showed similar patterns in both habitats. The concurrent assessment of the ecological quality of ecosystems by generic indices and the level of invasion through ALEX index may be a useful approach for answer to requirements of the European Directives and to plan even more complete and effective conservation programmes.

Assessment of optimal seasonal selection for RSEI construction: a case study of ecological environment quality assessment in the Beijing-Tianjin-Hebei region from 2001 to 2020

Timely and objective assessment of the optimal season for the construction of remote sensing ecological index (RSEI) is of great significance for accurate and effective assessment of ecological environment quality. We manipulated RSEI in to monitor seasonal variations in ecological environment quality (EEQ) in the Beijing-Tianjin-Hebei (JJJ) region from 2001 to 2020. First, we evaluated image quality across all four seasons and filled in missing observations through liner interpolation. Second, Seasonal RSEI was constructed using MODIS and compared across different years. Third, temporal and spatial variations within the same seasons in EEQ. Additionally, Moran’s I was utilized to evaluate spatial autocorrelation of EEQ, and the stability of the correlation between RSEI and four indicators seasonal indicators was compared. The results showed that: 1) the PC1 component concentrates most of the characteristics of the four indicators, especially in summer (over 71%); 2) the Moran’ I in the summer of 2001, 2006, 2011, 2016 and 2020 are 0.909, 0.898, 0.917, 0.921 and 0.892, respectively, which indicated that the EEQ has a strong positive spatial correlation. 3) the correlation between the four indicators and summer RSEI showed high correlation in different years, and the standard deviation of the correlation between the four indicators and RSEI fluctuated most slightly in summer, which the std of NDVI, WET, LST and, NDBSI were 0.005, 0.052, 0.026 and 0.017, respectively. This study theoretically demonstrates that summer is the optimal season for constructing RSEI, filling the research gap in previous studies regarding the rationale for selecting images from periods of vigorous vegetation growth for RSEI construction, which can provide a reference for selecting the optimum season for the ecological quality monitoring of urban in the future.

Non-Indigenous Freshwater Fishes as Indicators of Ecological Quality in Running Waters

The European Union Water Framework Directive (WFD) is a comprehensive initiative guiding river basin water management, addressing pressures such as pollution from diffuse and point sources, and hydromorphological alterations. However, pressures that can deteriorate the ecological quality of water bodies through biotic changes (i.e., by the introduction of non-indigenous species) are not rigorously addressed by the WFD. This study explores associations between conventional ecological quality indices based on physicochemical and biotic quality elements (fish and macroinvertebrates) against the presence and densities of non-indigenous freshwater fish species (NIFS) in lotic ecosystems of Greece, aiming to unravel the potential usage of NIFS in future ecological assessments. The dataset comprises 277 samplings at 115 sites, covering physicochemical and biotic (fish and macroinvertebrate) quality indices, and anthropogenic pressure variables. Based on our findings, the occurrence and densities of four NIFS (Lepomis gibbosus, Pseudorasbora parva, Gambusia holbrooki, and Carassius gibelio) were highly associated with the ecological quality assessments of the applied indices. Higher occurrences and densities of these NIFS were related to samplings of lower ecological quality. In addition, NIFS exhibited a positive association with anthropogenic pressures, likely due to their adaptability to less optimal environmental conditions or higher tolerance to pollution and other stressors. Our findings underscore the need for a paradigm shift in ecological quality assessments, emphasizing the use of NIFS either as a potential indicator of ecosystem health or as a pressure that deteriorates ecological quality.

Anthropogenic nutrients and phytoplankton diversity in Kenya's coastal waters: An ecological quality assessment of sea turtle foraging sites

We assessed ecological quality status (EQS) of coastal waters following claims of increasing sea turtle fibro-papillomatosis (FP) infections in Kenya, a disease hypothesized to be associated with ‘poor’ ecological health. We established widespread phosphate (P) and silicate (Si) limitation, dissolved ammonium contamination and an increase in potential harmful algal blooming species. Variations in the EQS was established in the sites depending on the indicators used and seasons. Generally, more sites located near hotels, tidal creeks, and estuarine areas showed ‘poor’, and ‘bad’ EQS during rainy period compared to dry season. Additionally, 90.1 % of the sites in ‘poor’ and ‘bad’ EQS based on dissolved inorganic nitrogen. Low dissolved oxygen, elevated temperature, salinity and ammonium, ‘poor’ EQS based on DIN, and potential bio-toxin-producing phytoplankton species characterized the FP prevalent areas, specifically during the dry season suggesting environmental stress pointing to the hypothesized connection between ecological and sea turtle health.

Multi-Scale Remote Sensing Assessment of Ecological Environment Quality and Its Driving Factors in Watersheds: A Case Study of Huashan Creek Watershed in China

The Huashan Creek watershed is the largest water source and the main production area of honeydew in Pinghe County, whose extensive cultivation of honeydew has exacerbated soil and water pollution. However, the spatial application of remote sensing ecological index (RSEI) in this watershed and key driving factors are not clear considering the applicability of data quality and the diversity of methodological scales. To explore the RSEI and driving factors at distinct scales in Huashan Creek watershed, this study constructed the RSEI based on the environmental balance matrix at seven scales in 2020, revealed its spatial response characteristics at different scales, and analyzed the key drivers. The results show that the 240 m grid as well as rural and watershed scale convergence analyses satisfy the assessment of RSEI, whose Moran indexes are 0.558, 0.595, and 0.146, respectively. The RSEIs at different scales have significant spatial aggregation characteristics, but the overall status is moderate. The central town–riparian area with poor RSEI contrasts with the western mountainous area, which has comparatively better quality. Population has a major influence on RSEI at multiple scales (0.8), with elevation and patch index acting significantly at the village and grid scales, respectively. These findings help to identify the spatial distribution of quality and control mechanisms of RSEI in the Huashan Creek watershed and provide new insights into key scales and drivers of ecological restoration practices in the watershed.

Ecological quality assessment: A framework to report ecosystems quality and their dynamics from reference conditions

AbstractWorldwide, ecosystems are suffering important taxonomic and functional modifications in response to anthropogenic disturbances, operating at multiple spatial and temporal scales. Awareness on biodiversity losses has led to the adoption of conservation policies and the development of programs devoted to the conservation and the restoration of terrestrial, freshwater, and marine ecosystems. The assessment of the ecological health of ecosystems requires measuring and characterizing restoration or degradation dynamics and their consequences on the ecological quality with respect to reference conditions defined pragmatically as conservation targets. Methodological innovations, in terms of data collection, analysis, and visualization, have an important influence on the ability of ecologists to understand biodiversity changes. The assessment of the quality of ecosystems with respect to reference conditions requires to address, notably, three main challenges: the definition of reference conditions, the assessment of the degree of achievement of conservation objectives, and the qualitative and quantitative characterization of recovering and departing patterns. We propose here the ecological quality assessment (EQA) framework as a data‐driven approach to track ecological quality focusing on the distance of the tested stations with respect to a chosen reference envelope using fuzzy logic and trajectory analysis. We take advantage of those analytical tools to propose a general and flexible multivariate framework by quantifying the achievement of reference conditions, measuring restoration and degradation dynamics when temporal series are available, and representing and synthesizing this information. To take into account the natural spatiotemporal variability of sites considered as reference, we gave two variants to our framework: a state‐based variant when no temporal replications are available and a trajectory‐based variant specially devoted to compare whole trajectories to a trajectory reference envelope defined by a set of reference trajectories. These two complementary approaches were illustrated through two terrestrial and marine ecological applications using the R package “ecotraj” in order to evidence ecological observations that meet conservation objectives from those that do not meet them. EQA constitutes a flexible framework for the assessment and reporting of ecosystem quality, including restoration and degradation dynamics adaptable to multiple questions in the different fields of ecology and conservation.

Mapping Forest Abrupt Disturbance Events in Southeastern China—Comparisons and Tradeoffs of Landsat Time Series Analysis Algorithms

Forest change monitoring is a fundamental and routine task for forest survey and planning departments, and the resulting forest change information acts as an underlying asset for sustainable forest management strategy development, ecological quality assessment, and carbon cycle research. The traditional ground-based manual monitoring of forest change has the disadvantages of high time and labor costs, low accessibility, and poor timeliness over wide regions. Remote sensing technology has become a popular approach for multi-scale forest change monitoring due to its multiple available spatial, spectral, temporal, and radiometric resolutions and wide coverage. Particularly, the free access policy of long time series archive data of Landsat (around 50 years) has triggered many automated analysis algorithms for landscape-scale forest change analysis, such as VCT, LandTrendr, BFAST, and CCDC. These automated algorithms differ in their principles, parameter settings, execution complexity, and disturbance types to be detected. Thus, selecting a suitable algorithm to satisfy the particular forest management demands is an urgent and challenging task for forest managers in a given forested area. In this study, Lishui City, Zhejiang Province, a typical plantation forest region in Southern China where forest disturbance widely and frequently exists, was selected as the study area. Based on the GEE platform, the algorithmic adaptability of VCT, LandTrendr, and CCDC in monitoring abrupt forest disturbance events was compared and assessed. The results showed that the kappa coefficients of the abrupt disturbance events detected by the three algorithms were at 0.704 (LandTrendr), 0.660 (VCT), and 0.727 (CCDC), and the corresponding overall accuracies were at 0.852, 0.830, and 0.862, respectively. The validated disturbance occurrence time consistency reached nearly 80% for the three algorithms. In light of the characteristics of forest disturbance occurrence in southeastern China as well as the algorithmic complexity, efficiency, and adaptability, LandTrendr was recommended as the most suitable one in this region or other similar regions. Overall, the forest change monitoring process based on GEE is becoming more simplified and easily implemented, and the comparisons and tradeoffs in this study provide a reference for the choice of long time series forest monitoring algorithms.

Taxonomic and functional diversity of nematode fauna: two sides of the same coin in the ecological quality assessment of transitional environments

The spatiotemporal variation in taxonomic indices and functional traits of the nematode fauna was investigated along two major environmental (salinity and organic matter enrichment) gradients in the Cabras Lagoon (Sardinia, Italy). We aimed to assess, for the first time in a transitional system of western Mediterranean Sea, how taxonomic and functional components of nematode assemblage respond to such environmental factors. The taxonomic structure was the most sensitive metric to document changes in the nematode assemblage, showing significant differences in relation to all the factors and their interactions. All the taxonomic and functional nematode features, except for the maturity index (MI), proved salinity and organic enrichment to be the primary drivers of nematode distribution. The lack of significant variation in the MI is quite interesting and can be interpreted because of the marked adaptation of nematodes to highly dynamic environmental conditions of brackish and confined habitats. Temperature mainly affected faunal composition, abundance, and diversity, due to its influence on fecundity and biological cycles on almost all species. Integrating the taxonomic and functional components of nematodes as “two-sides of the same coin”, the Shannon diversity index, the percentage of coloniser–persisters and the MI were used together to assess the Ecological Quality Status (EQS) of the study sites, which ranged from poor to bad. Nematodes proved to be good indicators of the environmental variations in the investigated lagoon ecosystem. Importantly, the joint use of taxonomic and functional approaches provided integrative knowledge of nematode response to environmental gradients. We conclude that combining nematode-based taxonomic and functional indicators represent a valuable tool to assess the environmental quality of lagoonal ecosystems and may provide complementary information to macrofauna.

Ecological quality assessment of five smart cities in India: a remote sensing index-based analysis

Ecological quality assessment of five smart cities in India: a remote sensing index-based analysis