Ecosystem Indicators Research Articles

Records of Odonata in the Riparian System of Andanan Watershed Forest Reserve, Philippines

The Odonata fauna is a good biological indicator of freshwater ecosystems. This research aims to provide a record inventory of both dragonflies and damselflies occurring in the riparian ecosystem of Andanan Watershed Forest Reserve. Field collection using sweep nets was done in three locations along the riparian area. Odonatans (n=79) were recorded belonging to 19 species, comprising 58% dragonflies and 42% damselflies. Out of 19 species recorded in the area, one species of dragonfly and six species of damselfly are endemic to the Philippines, with 36.84% endemicity in the area. All dragonflies documented are ground skimmers with a high tolerance for anthropogenic disturbances in freshwater systems. The genus Orthetrum Newman, 1833 is relatively abundant and obtained the highest number of species. On the other hand, the genus Euphaea Selys, 1840 in damselflies, was recorded to have the highest abundance. The genus Risiocnemis Cowley, 1934 has the highest species richness. All species of Risiocnemis were also reported endemic. Despite the high diversity (H’=2.77; H'/Hmax=0.94) of the Odonata fauna in Andanan Watershed Forest Reserve, human activities and intervention were still observed around the riparian ecosystem. The results shown in the current study may be utilized as primary information to allow local conservation efforts for odonatans found in the watershed and its tributaries.

Detecting the sensitivity of water content and deficiency rainfall during positive Indian Ocean Dipole events

This study aimed to detect the water content in peatland and cropland associated with rainfall deficiencies and positive Indian Ocean Dipole (IOD) events. The condition of water content is a biological indicator of peatland ecosystems that commonly contributes to hot spots in Sumatra. The water content and rainfall data were processed using the spatial average at two study areas, and the variabilities were analyzed with the Indian Ocean Dipole index (DMI). From 2015 until 2020, this study employed the Dipole Mode Index to evaluate five positive IOD events. The analysis of the water content conditions and deficiency rainfall correlated to positive IOD events. In the peatland, the water content was a sensitive parameter, and even though the value decreased by a small amount, it potentially inflamed. Even if the water content was low in cropland areas, it did not trigger forest fires. The effect of rainfall deficiency was related to land response to water content conditions. Different land types will have different sensitivities. Understanding the correlation between deficiency rainfall with water content can be helpful for an early warning system.

Cumulative effects of offshore renewables: From pragmatic policies to holistic marine spatial planning tools

To alleviate climate change consequences, the UK government is pioneering offshore renewable energy developments at an ever-increasing pace. The North Sea is a dynamic ecosystem with strong bottom-up/top-down natural and anthropogenic drivers facing rapid climate change impacts. To ensure the compatibility of such large-scale developments with nature conservation obligations, regulatory processes set out that all effects need to be evaluated through cumulative impact assessments (CIA). However, by excluding climate change impacts and bottom-up effects of renewable developments, the CIA lacks spatio-temporal baselines linking oceanic ecosystem indicators to population dynamics, leading to uncertain predictions at population levels. CIA is currently required in Europe under the Strategic Environmental Assessment and the Marine Strategy Framework Directive (MSFD), suggesting that these two policy areas should be more closely aligned. This study presents an overview of the current CIA policy framework, enabling an ecosystem-based approach linking lower ecosystem components to top-predator populations using the UK as a case study. At the UK level, CIA requirements mirror the EU ones under the Marine and Coastal Access Act, the UK Marine Policy Statement, and the UK National Policy Statement. Firstly, we show how CIA and MSFD requirements are integrated into the UK licensing and maritime planning frameworks. Secondly, we provide policy pathways embedding the MSFD as a baseline for CIAs with European and UK regulations. Thirdly, we propose a framework encompassing a shared monitoring effort, an ecosystem modelling approach connected with two existing online databases supported with funds from Contracts for Difference. This integrated approach will enable a holistic and pragmatic ecosystem-based framework for more accurate and rapid methods for producing CIAs for offshore renewable energy developments.

Spatiotemporal Variations in Fractional Vegetation Cover and Their Responses to Climatic Changes on the Qinghai–Tibet Plateau

The alpine vegetation of the Qinghai–Tibet Plateau (QTP) is extremely vulnerable and sensitive to climatic fluctuations, making it an ideal area to study the potential impacts of climate on vegetation dynamics. Fractional vegetation cover (FVC) is regarded as one of the key indicators in monitoring semiarid and arid ecosystems due to its sensitive responses to vegetation behavior under climatic changes. Although many studies have analyzed the responses of vegetation on the QTP to climatic change, limited information is available on the influence of climatic variables on FVC changes in this area. In this study, we used satellite images and meteorological data to investigate the spatiotemporal variations of FVC during the growing season (FVCGS) during 1998–2018 and evaluated the responses to changes in climatic variables. Results showed that FVCGS displayed an overall fluctuating rise of 0.01/10 a (p < 0.01) over the study period. The FVCGS variation was spatially heterogeneous, with a general trend of greening in the northern and browning in the southern QTP. Obvious correlations were observed between the average FVC, average temperature, and total precipitation of the growing season, with precipitation being the primary controlling factor for vegetation growth. Some regions in the northwestern and northeastern QTP showed greening trends due to the positive influence of precipitation. Some areas in the southwestern QTP experienced browning trends due to water shortages caused, probably, by the weakening of the Indian monsoon. Browning in the southeastern parts was likely caused by drought and permafrost degradation resulting from high temperature. The inconsistent trend of vegetation change on the QTP is relatively high considering the continuous warming and changing atmospheric circulation patterns. FVC in most regions of the QTP has 0–1 month temporal responses to precipitation and temperature. Moreover, the one-month lagged effects of temperature and precipitation had a greater influence on steppe and desert vegetation than on other vegetation types. This research provides new perspectives for understanding the QTP vegetation response to climatic changes and a basis for making reasonable vegetation conservation and management policies.

Ecotrophic perspective in fisheries management: a review of Ecopath with Ecosim models in European marine ecosystems

The aim of this work is to present the food web models developed using the Ecopath with Ecosim (EwE) software tool to describe structure and functioning of various European marine ecosystems (eastern, central and western Mediterranean Sea; Black Sea; Bay of Biscay, Celtic Sea and Iberian coast; Baltic Sea; North Sea; English Channel, Irish Sea and west Scottish Sea; and Norwegian and Barents Seas). A total of 195 Ecopath models based on 168 scientific publications, which report original, updated and modified versions, were reviewed. Seventy models included Ecosim temporal simulations while 28 implemented Ecospace spatiotemporal dynamics. Most of the models and publications referred to the western Mediterranean Sea followed by the English Channel, Irish Sea and west Scottish Sea sub-regions. In the Mediterranean Sea, the western region had the largest number of models and publications, followed by the central and eastern regions; similar trends were observed in previous literature reviews. Most models addressed ecosystem functioning and fisheries-related hypotheses while several investigated the impact of climate change, the presence of alien species, aquaculture, chemical pollution, infrastructure, and energy production. Model complexity (i.e., number of functional groups) increased over time. Main forcing factors considered to run spatial and temporal simulations were trophic interactions, fishery, and primary production. Average scores of ecosystem indicators derived from the Ecopath summary statistics were compared. Uncertainty was also investigated based on the use of the Ecosampler plug-in and the Monte Carlo routine; only one third of the reviewed publications incorporated uncertainty analysis. Only a limited number of the models included the use of the ECOIND plug-in which provides the user with quantitative output of ecological indicators. We assert that the EwE modelling approach is a successful tool which provides a quantitative framework to analyse the structure and dynamics of ecosystems, and to evaluate the potential impacts of different management scenarios.

When bioregionalisation emphasises the presence of vulnerable marine ecosystem indicator species in Nephrops fishing grounds: Evidence in the Bay of Biscay/Irish Sea continuum

Under the apparent homogeneity of soft-bottom ecosystems hides an heterogeneity of habitats driven by variations in sediment composition and environmental conditions.Using an extensive underwater video survey dataset, we explored the taxonomic diversity of soft-bottom Nephrops fishing grounds and their environmental drivers on a large latitudinal scale from the Bay of Biscay to the Irish Sea (Northeast Atlantic). Biogeographical network clustering highlighted indicator species of the different communities and a Between-Class Analysis characterised the abiotic factors influencing each community.Our analyses confirmed a biogeographical limit between the Bay of Biscay and the northern areas driven by a latitudinal temperature gradient and highlighting the distribution of Lusitanian and Boreal species. Mobile fish and crustaceans, and sessile filter-feeder assemblages differed along a depth, bottom current and fishing gradient. Some species assemblages covered the whole latitudinal range, implying a greater influence of optimal environmental surroundings rather than their geographical position. Vulnerable Marine Ecosystem indicator taxa such as Virgularia mirabilis and Pennatula phosphorea are potential indicator species of some clusters, while harvested species such as Nephrops norvegicus or mobile fish characterized other bioregions.Spatial knowledge produced in this study could be integrated as biodiversity layers together with fisheries activities layers in decision support tools such as Marine Spatial Planning in order to define compromise between conservational and fishing objectives. Outcomes of management scenarios would then consider the whole species stock (e.g. Nephrops) rather that local populations independently.

Zooplankton assemblages and indicator species in the Changjiang river estuary and its adjacent waters

Zooplankton is a vital biological indicator in estuarine ecosystems. In this study, the Changjiang River Estuary (CRE) was investigated in the dry (March) and wet seasons (July) of 2019 for spatial and temporal fluctuations of zooplankton based on the indicator value (IndVal) index method. A total of 172 zooplankton taxa (146 adult taxa and 26 larvae) were identified. Zooplankton composition, abundance, biodiversity, grouping, and indicator species all showed substantial seasonal changes. The hydrological environment of the CRE was affected by diluted water and current intrusions. Compared to the dry season, the wet season had a higher abundance and biodiversity of zooplankton. Zooplankton communities from the inside-mouth fresh-brackish, intermediate transition, and offshore neritic regions were distributed in a three-segment pattern (fresh-brackish, transitional and neritic) and were significantly impacted by Changjiang River discharge. In general, freshwater and brackish species shifted toward the ocean during the wet season, whereas during the dry season, when river flow decreased, marine species shifted toward the estuary. Sinocalanus sinensis and Mesocyclops spp. were indicators of the Changjiang Diluted Water. Temora turbinata and Flaccisagitta enflata were good indicators of Taiwan Warm Current invasion, while Calanus sinicus may represent the effect of the Yellow Sea Coastal Current in the northern CRE. This research contributes to a thorough understanding of pelagic ecosystem dynamics and seasonal succession patterns in the CRE, which has a complicated hydrological environment.

Mapping Tree Species Using CNN from Bi-Seasonal High-Resolution Drone Optic and LiDAR Data

As the importance of forests has increased, continuously monitoring and managing information on forest ecology has become essential. The composition and distribution of tree species in forests are essential indicators of forest ecosystems. Several studies have been conducted to classify tree species using remote sensing data and machine learning algorithms because of the constraints of the traditional approach for classifying tree species in forests. In the machine learning approach, classification accuracy varies based on the characteristics and quantity of the study area data used. Thus, applying various classification models to achieve the most accurate classification results is necessary. In the literature, patch-based deep learning (DL) algorithms that use feature maps have shown superior classification results than point-based techniques. DL techniques substantially affect the performance of input data but gathering highly explanatory data is difficult in the study area. In this study, we analyzed (1) the accuracy of tree classification by convolutional neural networks (CNNs)-based DL models with various structures of CNN feature extraction areas using a high-resolution LiDAR-derived digital surface model (DSM) acquired from a drone platform and (2) the impact of tree classification by creating input data via various geometric augmentation methods. For performance comparison, the drone optic and LiDAR data were separated into two groups according to the application of data augmentation, and the classification performance was compared using three CNN-based models for each group. The results demonstrated that Groups 1 and CNN-1, CNN-2, and CNN-3 were 0.74, 0.79, and 0.82 and 0.79, 0.80, and 0.84, respectively, and the best mode was CNN-3 in Group 2. The results imply that (1) when classifying tree species in the forest using high-resolution bi-seasonal drone optical images and LiDAR data, a model in which the number of filters of various sizes and filters gradually decreased demonstrated a superior classification performance of 0.95 for a single tree and 0.75 for two or more mixed species; (2) classification performance is enhanced during model learning by augmenting training data, especially for two or more mixed tree species.

Protected areas maintain neotropical freshwater bird biodiversity in the face of human activity

Because of their accessibility, freshwater ecosystems are particularly sensitive to deforestation and bank habitat fragmentation. Their responses to human activities in general, and specifically to small-scale extractive activities, are not well understood. Protected Areas (PAs) can be an effective tool to secure the conservation of freshwater animal assemblages. Given their ability to respond to changes in site quality and local resources, waterbirds could be suitable wetland ecosystem indicators. To examine the effectiveness of PAs in protecting neotropical biodiversity, we used repeated visual count surveys of freshwater and forest-associated birds, comparing species richness and abundance in protected oxbow lakes with lakes subject to gold mining and fishing activities. Bird community structure was predicted by the proportion of mined area in lake banks and water quality. Bird richness was reduced in unprotected oxbow lakes, and this pattern was stronger for aquatic species. Land protection was the most important predictor of bird abundance. Over half the species (53%) showed markedly reduced abundance in the unprotected sites. Our results provide evidence for the effectiveness of PAs in maintaining freshwater biodiversity and for the impacts of human activities on neotropical wetland bird assemblages. Our findings also suggest that water-associated species may be sensitive to the deterioration in hydrological processes promoted by these activities. By documenting the maintenance of elevated freshwater bird biodiversity within two PAs, our results inform the debate on their effectiveness. We recommend the extension of legal protections for freshwater ecosystems and their banks to prevent further degradation of essential habitats and animal communities, driven by expanding informal and illegal mining activities.

Studies on the diversity of macroinvertebrates in suburban and rural aquatic bodies of West Bengal: Implications of vector control

Biological assessment of the freshwater habitats aims to characterize and monitor the conditions of the aquatic resources. Assessment of species assemblage in these habitats will indicate the possible variations in the resource exploitation and trophic interactions. Macroinvertebrates are the best indicators of aquatic ecosystem and play an important role in freshwater ecosystem functioning through nutrient cycling, primary production, decomposition and biological control of mosquitoes.Observations revealed that the prey individuals of order Diptera were found to be highest (51.16%), however the cumulative predatory taxa including Coleoptera, Odonata, Hemiptera and Orthoptera accounted to 67.02% The values of diversity indices varied significantly across different sampling spots justifying the usage of those wetlands and potentiality of them towards conservation biological control. Based on the biotic index, rice fields at Panskura ranked ‘Good’ to ‘Fair’ while all others ranked ‘Fair’ or ‘Poor’.Irrespective of the classes and orders, the representative individuals were observed in high numbers during the post monsoon and the winter months which may be attributed to the fact that with the volume of water, the space available for the insects increases, thereby promoting population expansion and releasing the crowding effect. The result of three way factorial ANOVA on the number of macroinvertebrates considering the spots, sites and sampling months as explanatory variables, revealed significant differences across all the interactions. A correspondence of the taxonomic diversity with the functional role of the aquatic predatory insects of the order Coleoptera, Hemiptera and Odonata is well established, through their links with multiple prey species including mosquito and chironomid larvae. In an assorted species assemblage of both predator and prey species, conservation biological control may require habitat extension and modification to allow increment of niche width to sustain diverse species in the habitats. Therefore to comment on the chances of the potentials of conservation biological control, monitoring of the macroinvertebrate community becomes imperative.

Soil saprophytic fungi could be used as an important ecological indicator for land management in desert steppe

Soil microbes are among the most complex and diverse communities on Earth, actively participating in biogeochemical cycles while responding positively to environmental changes. Saprophytic fungi are important factors in soil carbon cycle, and the response and driving factors in grassland to forestland and grassland to farmland conversion in desert steppe are still poorly understood. Therefore, we analyzed the soil microbial community structure and saprophytic fungal communities in grasslands, shrub lands, and farmlands in typical desert grassland areas of northwest China. It was found that the cultivation of desert steppe plants/crops increased the proportion of silt in soil aggregates while decreasing soil salinity and increasing soil total carbon, nitrogen, and organic matter content. Proteobacteria, Actinobacteriota and Ascomycota were the dominant phyla in desert steppe soils, with Proteobacteria, Gemmatimonadota and Mucoromycota were more responsive to soil environment changes. The co-occurrence network relationship further characterized the process of niche sharing/competition between bacteria and fungi. The complexity of the co-occurrence network was deepened by land use, and fungi occupied more of the niche in shrub planting than in desert steppe and maize planting. Network relationships further characterized the process of niche sharing/competition between bacteria and fungi, and land use deepened the complexity of the co-occurrence network, with soil fungi occupying more ecological niches in shrub cultivation than in grassland and maize cultivation. In addition, saprophytic fungi are the main functional fungi in bacterial-fungal co-occurrence networks and are influenced by soil properties. Random forest analysis further explained the importance of saprophytic fungi in response to environmental changes in desert steppes. The enrichment of soil saprophytic fungi had an obvious correlation with soil aggregate stability, soil physical properties, and soil nutrients, especially in the background of shrub forestation in desert steppes. This study further highlights afforestation as one of the ways to benefit land management in desert steppes, while emphasizing the importance of saprophytic fungi as ecosystem indicators.

Effects of intra-annual precipitation patterns on grassland productivity moderated by the dominant species phenology.

Phenology and productivity are important functional indicators of grassland ecosystems. However, our understanding of how intra-annual precipitation patterns affect plant phenology and productivity in grasslands is still limited. Here, we conducted a two-year precipitation manipulation experiment to explore the responses of plant phenology and productivity to intra-annual precipitation patterns at the community and dominant species levels in a temperate grassland. We found that increased early growing season precipitation enhanced the above-ground biomass of the dominant rhizome grass, Leymus chinensis, by advancing its flowering date, while increased late growing season precipitation increased the above-ground biomass of the dominant bunchgrass, Stipa grandis, by delaying senescence. The complementary effects in phenology and biomass of the dominant species, L. chinensis and S. grandis, maintained stable dynamics of the community above-ground biomass under intra-annual precipitation pattern variations. Our results highlight the critical role that intra-annual precipitation and soil moisture patterns play in the phenology of temperate grasslands. By understanding the response of phenology to intra-annual precipitation patterns, we can more accurately predict the productivity of temperate grasslands under future climate change.

Mesophilic and thermophilic viruses are associated with nutrient cycling during hyperthermophilic composting

While decomposition of organic matter by bacteria plays a major role in nutrient cycling in terrestrial ecosystems, the significance of viruses remains poorly understood. Here we combined metagenomics and metatranscriptomics with temporal sampling to study the significance of mesophilic and thermophilic bacteria and their viruses on nutrient cycling during industrial-scale hyperthermophilic composting (HTC). Our results show that virus-bacteria density dynamics and activity are tightly coupled, where viruses specific to mesophilic and thermophilic bacteria track their host densities, triggering microbial community succession via top-down control during HTC. Moreover, viruses specific to mesophilic bacteria encoded and expressed several auxiliary metabolic genes (AMGs) linked to carbon cycling, impacting nutrient turnover alongside bacteria. Nutrient turnover correlated positively with virus–host ratio, indicative of a positive relationship between ecosystem functioning, viral abundances, and viral activity. These effects were predominantly driven by DNA viruses as most detected RNA viruses were associated with eukaryotes and not associated with nutrient cycling during the thermophilic phase of composting. Our findings suggest that DNA viruses could drive nutrient cycling during HTC by recycling bacterial biomass through cell lysis and by expressing key AMGs. Viruses could hence potentially be used as indicators of microbial ecosystem functioning to optimize productivity of biotechnological and agricultural systems.

Trophic structure using ecological relationships between five dominant commercial fish in Kolahi to Dargahan

AbstractThe purpose of this study was to determine the effects of frequent species population fluctuations and the impact of different rates of exploitation on other ecological links in the food web. The mass‐balanced Ecopath model represents the trophic interactions among the 31 defined functional groups in the Kolahi to Dargahan area, with five main species, including Trichiurus lepturus, Saurida tumbil, Nemipterus japonicus, Sillago sihama, and Cynoglossus arel (from April 2018 to April 2019). To investigate the effects of fishing and environmental disturbances, the Ecopath modeling approach combines software for analyzing ecosystem trophic‐level balances with population dynamic models. In the past 5 years, Hormozgan province has caught more than 45% of the benthic fish caught off the northern coasts of the Persian Gulf. From Kolahi to Dargahan, one of the most important fishing grounds in this province's southeast is located. Food web models are used to represent a marine system's current state, assess stock levels, and predict change over time. Over a year, the first five dominant fish in the study area, S. tumbil, S. sihama, C. arel, N. japonicus, and T. lepturus, were biometrically measured, and their population dynamics parameters as well as feeding ecology indices were analyzed. According to the trophic‐level index results, the five most common species studied in this study belonged to the third (N. Japonicas, S. sihama, and C. arel) and fourth (T. lepturus, and S. tumbil) trophic levels. The key species with the greatest impact on other groups of studied species were identified as S. tumbil and T. lepturus, respectively. The estimated ecosystem indicators were the system operational power (75846.797), the primary production/respiration ratio (0.034), the connectance index (0.159), and the system omnivory index (0.253). A pedigree index (PI) of 0.38 was estimated for the present model. Overexploitation of T. lepturus could disrupt the aquatic food web and adversely affect the long‐term sustainable use of aquatic resources, according to data. As a result, ecosystem‐based fisheries management should be implemented to find a more appropriate solution to sustainable exploitation in the studied habitat, an important fishing area in the Persian Gulf's north.

Deep sequencing reveals comprehensive insight into the prevalence, mobility, and hosts of antibiotic resistance genes in mangrove ecosystems

Mangrove receives aquaculture wastewater and urban sewage, and thus is a potential reservoir for antibiotic resistance genes (ARGs). However, there is a dearth of a comprehensive profile of ARGs in mangrove ecosystems. We used metagenomic techniques to uncover the occurrence, host range, and potential mobility of ARGs in six mangrove ecosystems in southeastern China. Based on deep sequencing data, a total of 348 ARG subtypes were identified. The abundant ARGs were associated with acriflavine, bacitracin, beta-lactam, fluoroquinolone, macrolide-lincosamide-streptogramin, and polymyxin. Resistance genes tetR, aac(6′)-Iae, aac(3)-IXa, vanRA, vanRG, and aac(3)-Ig were proposed as ARG indicators in mangrove ecosystems that can be used to evaluate the abundance of 100 other co-occurring ARGs quantitatively. Remarkably, 250 of 348 identified ARG subtypes were annotated as mobile genetic elements-associated ARGs, indicating a high potential risk of propagation of ARGs in mangrove ecosystems. By surveying the distribution of ARGs in 6281 draft genomes, more than 42 bacterial phyla were identified as the putative hosts of the ARGs. Among them, 21.97% were potentially multidrug-resistant hosts, including human and animal opportunistic pathogens. This research adds to our understanding of the distribution and spread of antibiotic resistomes in mangrove ecosystems, helping improve ARG risk assessment and management worldwide.

An anchovy ecosystem indicator of marine predator foraging and reproduction.

Forage fishes are key energy conduits that transfer primary and secondary productivity to higher trophic levels. As novel environmental conditions caused by climate change alter ecosystems and predator-prey dynamics, there is a critical need to understand how forage fish control bottom-up forcing of food web dynamics. In the northeast Pacific, northern anchovy (Engraulis mordax) is an important forage species with high interannual variability in population size that subsequently impacts the foraging and reproductive ecology of marine predators. Anchovy habitat suitability from a species distribution model (SDM) was assessed as an indicator of the diet, distribution and reproduction of four predator species. Across 22 years (1998-2019), this anchovy ecosystem indicator (AEI) was significantly positively correlated with diet composition of all species and the distribution of common murres (Uria aalge), Brandt's cormorants (Phalacrocorax penicillatus) and California sea lions (Zalophus californianus), but not rhinoceros auklets (Cerorhinca monocerata). The capacity for the AEI to explain variability in predator reproduction varied by species but was strongest with cormorants and sea lions. The AEI demonstrates the utility of forage SDMs in creating ecosystem indicators to guide ecosystem-based management.

A Novel Deep Learning Model for Mining Nonlinear Dynamics in Lake Surface Water Temperature Prediction

As one of the critical indicators of the lake ecosystem, the lake surface water temperature is an important indicator for measuring lake ecological environment. However, there is a complex nonlinear relationship between lake surface water temperature and climate variables, making it difficult to accurately predict. Fortunately, satellite remote sensing provides a wealth of data to support further improvements in prediction accuracy. In this paper, we construct a new deep learning model for mining the nonlinear dynamics from climate variables to obtain more accurate prediction of lake surface water temperature. The proposed model consists of the variable correlation information module and the temporal correlation information module. The variable correlation information module based on the Self-Attention mechanism extracts key variable features that affect lake surface water temperature. Then, the features are input into the temporal correlation information module based on the Gated Recurrent Unit (GRU) model to learn the temporal variation patterns. The proposed model, called Attention-GRU, is then applied to lake surface water temperature prediction in Qinghai Lake, the largest inland lake located in the Tibetan Plateau region in China. Compared with the seven baseline models, the Attention-GRU model achieved the most accurate prediction results; notably, it significantly outperformed the Air2water model which is the classic model for lake surface water temperature prediction based on the volume-integrated heat balance equation. Finally, we analyzed the factors influencing the surface water temperature of Qinghai Lake. There are different degrees of direct and indirect effects of climatic variables, among which air temperature is the dominant factor.

Calculation of Sustainability Indicators for Water Objects based on the Example of Water Use in the Arctic Basin of the Yenisei River

In the article, the fractal approach to the description of nonequilibrium water ecosystems in their exploitation conditions is considered. The article demonstrates clearly that, in these conditions, the management of the development of water objects should be a precautionary provision, which should furthermore be reduced to the management of potential anthropogenic risks arising from a violation of the coevolution of anthropogenic and natural processes equivalent to the disruption in sustainability of the ecosystem in its exploitation conditions. The fractal approach opens up new opportunities for the assessment of water management based on the calculation of the fractal sustainability indicator (anthropogenic transformation) for water ecosystems that is directly related to the maximum permissible environmental load (MPEL).

Distribution patterns and drivers of nonendemic and endemic glires species in China.

Spatial patterns and determinants of species richness in complex geographical regions are important subjects of current biogeography and biodiversity conservation research. Glires are small herbivorous mammal species with limited migratory ability that may serve as an indicator of biodiversity and ecosystems. Herein, we aimed to evaluate how multiple ecological hypotheses could explain the species richness patterns of glires in China. Initially, we constructed a mapping grid cell operating units of 80 × 80 km2 which covered China's land mass and mapped the distribution ranges of the 237 glires species that had recorded. The glires taxa were separated into three response variables based on their distribution: (a) all species, (b) nonendemic species, and (c) endemic species. The species richness patterns of the response variables were evaluated using four predictor sets: (a) hydrothermal characteristics, (b) climatic seasonality, (c) habitat heterogeneity, and (d) human factors. We performed regression tree analysis, multiple linear regression analysis, and variation partitioning analyses to determine the effects of predictors on spatial species patterns. The results showed that the distribution pattern of species richness was the highest in the Hengduan Mountains and surrounding areas in southwest China. However, only a few endemic species adapted to high-latitude environments. It was found that there are differences about the determinants between nonendemic and endemic species. Habitat heterogeneity was the most influential determinant for the distribution patterns of nonendemic species richness. Climatic seasonality was the best predictor to determine the richness distribution pattern of endemic species, whereas this was least affected by human factors. Furthermore, it should be noted that hydrothermal characteristics were not strong predictors of richness patterns for all or nonendemic species, which may be due to the fact that there are also more species in some areas with less precipitation or energy. Therefore, glires are likely to persist in areas with characteristics of high habitat heterogeneity and stable climate.

The red alga Hildenbrandia rivularis is a weak indicator of the good ecological status of riverine habitats

Our knowledge about the size of benthic red alga populations inhabiting European freshwater ecosystems is still insufficient. For many years, in Europe, Hildenbrandia rivularis (Rhodophyta, Hildenbrandiaceae) was believed to be a very rare species of crustaceous red algae, valuable for oligotrophic system biomonitoring. In this paper, we challenge this assumption and show the phenomenon of H. rivularis expansion (i.e., from mountains and highlands to lowlands) in Europe based on detailed data from Poland. We collected over 311 records of H. rivularis occurring in rivers, streams and lakes (not typical habitats for this alga) across the country, including historical data. Here, we show the detailed distribution of this endangered species in Poland, one of the largest European countries. To examine the mechanism of H. rivularis population expansion, physicochemical data from 122 aquatic ecosystems were investigated. A comparison between three subperiods (1860–1944, 1945–1999, and 2000–2019) revealed an increase in the average abundance of the H. rivularis population in the lowlands area. However, the studied species seems to be disappearing in mountain and upland ecosystems. We found altitude and water flow and quality (i.e., alkalinity, oxygenation and biogens) to be the main determinants of H. rivularis occurrence within the study area. The results indicate that this red alga can be described as an expansive species, and its occurrence does not always indicate good water quality and fast water flow. Surprisingly, in contrast to observations from the last century, the population of H. rivularis in Poland currently occurs mainly in habitats with eu- and hypertrophic waters. We point out here that in the zone with temperate climate influence, H. rivularis is no longer an obvious indicator for oligotrophic ecosystems. We suggest that climate warming and eutrophication–reoligotrophication may have contributed to the increased spread of H. rivularis in Europe over recent decades. In addition, we see no reason to classify H. rivularis as an endangered species in Poland. This species most often inhabits anthropogenic water systems and occurs at high abundance in waters with high concentrations of biogens. For these reasons, H. rivularis is more ubiquitous than a cosmopolitan species (i.e., with a wide range of occurrence but associated with only a specific type of habitat and specific environmental parameters). Thus, the value of H. rivularis as a bioindicator for oligotrophic water ecosystems is very low.