Ecosystem Indicators Research Articles

Release capacity of Portunus trituberculatus enhancement in coastal waters: A case study in the marine ranching area of Haizhou bay

In recent years, the community structure of fishery resources in offshore waters has undergone significant changes, and the resources of traditional commercial fish have gradually declined; as a result, crustaceans have become the main catch. To prevent the loss of resources, it is necessary to carry out ecological stock enhancement and scientifically prevent and control the ecological risks of released species. In this study, based on the Ecopath with Ecosim model, the areas of marine ranching and adjacent waters in Haizhou Bay were used as a case study to construct a temporal dynamic model of Portunus trituberculatus, one of the typical crustacea released in offshore water of China. The ecological carrying capacity (ECC) of P. trituberculatus was assessed, and its impact on other functional groups and ecosystems was predicted. The results showed that the ECC of P. trituberculatus is 42.458 t km−2, and the entire ecosystem would become imbalanced if this value is exceeded. Under the four simulation scenarios, each ecosystem indicator showed positive responses to different degrees, with total system respiration (R) and total system biomass (B) increasing by 244.66% and 236.90%, respectively. We believe that the maturity of the ecosystem in Haizhou Bay is not high, and the marine organisms are mostly in trophic levels Ⅱ to Ⅲ. Therefore, there is still room for the stock enhancement of P. trituberculatus. The model framework provides a method for assessing the ECC of P. trituberculatus in offshore water and offers a scientific reference and practical basis for stock enhancement activities, resource management, and fishing strategies for P. trituberculatus in the offshore waters of China.

Ensemble analysis and forecast of ecosystem indicators in the North Atlantic using ocean colour observations and prior statistics from a stochastic NEMO–PISCES simulator

Abstract. This study is anchored in the H2020 SEAMLESS project (https://www.seamlessproject.org, last access: 29 January 2024), which aims to develop ensemble assimilation methods to be implemented in Copernicus Marine Service monitoring and forecasting systems, in order to operationally estimate a set of targeted ecosystem indicators in various regions, including uncertainty estimates. In this paper, a simplified approach is introduced to perform a 4D (space–time) ensemble analysis describing the evolution of the ocean ecosystem. An example application is provided, which covers a limited time period in a limited subregion of the North Atlantic (between 31 and 21∘ W, between 44 and 50.5∘ N, between 15 March and 15 June 2019, at a 1/4∘ and a 1 d resolution). The ensemble analysis is based on prior ensemble statistics from a stochastic NEMO (Nucleus for European Modelling of the Ocean)–PISCES simulator. Ocean colour observations are used as constraints to condition the 4D prior probability distribution. As compared to classic data assimilation, the simplification comes from the decoupling between the forward simulation using the complex modelling system and the update of the 4D ensemble to account for the observation constraint. The shortcomings and possible advantages of this approach for biogeochemical applications are discussed in the paper. The results show that it is possible to produce a multivariate ensemble analysis continuous in time and consistent with the observations. Furthermore, we study how the method can be used to extrapolate analyses calculated from past observations into the future. The resulting 4D ensemble statistical forecast is shown to contain valuable information about the evolution of the ecosystem for a few days after the last observation. However, as a result of the short decorrelation timescale in the prior ensemble, the spread of the ensemble forecast increases quickly with time. Throughout the paper, a special emphasis is given to discussing the statistical reliability of the solution. Two different methods have been applied to perform this 4D statistical analysis and forecast: the analysis step of the ensemble transform Kalman filter (with domain localization) and a Monte Carlo Markov chain (MCMC) sampler (with covariance localization), both enhanced by the application of anamorphosis to the original variables. Despite being very different, the two algorithms produce very similar results, thus providing support to each other's estimates. As shown in the paper, the decoupling of the statistical analysis from the dynamical model allows us to restrict the analysis to a few selected variables and, at the same time, to produce estimates of additional ecological indicators (in our example: phenology, trophic efficiency, downward flux of particulate organic matter). This approach can easily be appended to existing operational systems to focus on dedicated users' requirements, at a small additional cost, as long as a reliable prior ensemble simulation is available. It can also serve as a baseline to compare with the dynamical ensemble forecast and as a possible substitute whenever useful.

Automated zooplankton size measurement using deep learning: Overcoming the limitations of traditional methods

Zooplankton size is a crucial indicator in marine ecosystems, reflecting demographic structure, species diversity and trophic status. Traditional methods for measuring zooplankton size, which involve direct sampling and microscopic analysis, are laborious and time-consuming. In situ imaging systems are useful sampling tools; however, the variation in angles, orientations, and image qualities presented considerable challenges to early machine learning models tasked with measuring sizes.. Our study introduces a novel, efficient, and precise deep learning-based method for zooplankton size measurement. This method employs a deep residual network with an adaptation: replacing the fully connected layer with a convolutional layer. This modification allows for the generation of an accurate predictive heat map for size determination. We validated this automated approach against manual sizing using ImageJ, employing in-situ images from the PlanktonScope. The focus was on three zooplankton groups: copepods, appendicularians, and shrimps. An analysis was conducted on 200 individuals from each of the three groups. Our automated method's performance was closely aligned with the manual process, demonstrating a minimal average discrepancy of just 1.84%. This significant advancement presents a rapid and reliable tool for zooplankton size measurement. By enhancing the capacity for immediate and informed ecosystem-based management decisions, our deep learning-based method addresses previous challenges and opens new avenues for research and monitoring in zooplankton.

Historical and projected response of Southeast Asian lakes surface water temperature to warming climate

The temperature of surface and epilimnetic waters, closely related to regional air temperatures, responds quickly and directly to climatic changes. As a result, lake surface temperature (LSWT) can be considered an effective indicator of climate change. In this study, we reconstructed and investigated historical and future LSWT across different scenarios for over 80 major lakes in mainland Southeast Asia (SEA), an ecologically diverse region vulnerable to climate impacts.Five different predicting models, incorporating statistical, machine and deep learning approaches, were trained and validated using ERA5 and CHIRPS climatic feature datasets as predictors and 8-day MODIS-derived LSWT from 2000 to 2020 as reference dataset. Best performing model was then applied to predict both historical (1986–2020) and future (2020–2100) LSWT for SEA lakes, utilizing downscaled climatic CORDEX-SEA feature data and multiple Representative Concentration Pathway (RCP). The analysis uncovered historical and future thermal dynamics and long-term trends for both daytime and nighttime LSWT.Among 5 models, XGboost results the most performant (NSE 0.85, RMSE 1.14 °C, MAE 0.69 °C, MBE -0.08 °C) and it has been used for historical reconstruction and future LSWT prediction. The historical analysis revealed a warming trend in SEA lakes, with daytime LSWT increasing at a rate of +0.18 °C/decade and nighttime LSWT at +0.13 °C/decade over the past three decades. These trends appeared of smaller magnitude compared to global estimates of LSWT change rates and less pronounced than concurrent air temperature and LSWT increases in neighbouring regions. Projections under various RCP scenarios indicated continued LSWT warming. Daytime LSWT is projected to increase at varying rates per decade: +0.03 °C under RCP2.6, +0.14 °C under RCP4.5, and +0.29 °C under RCP8.5. Similarly, nighttime LSWT projections under these scenarios are: +0.03 °C, +0.10 °C, and +0.16 °C per decade, respectively. The most optimistic scenario predicted marginal increases of +0.38 °C on average, while the most pessimistic scenario indicated an average LSWT increase of +2.29 °C by end of the century.This study highlights the relevance of LSWT as a climate change indicator in major SEA's freshwater ecosystems. The integration of satellite-derived LSWT, historical and projected climate data into data-driven modelling has enabled new and a more nuanced understanding of LSWT dynamics in relation to climate throughout the entire SEA region.

Application of a One Welfare‐Based Ecosystem Model to assess wild collection for public aquariums

Abstract1. Public aquariums are organizations that offer their visitors an opportunity to engage with, gain knowledge of, and contribute to the conservation of species and ecosystems. Unfortunately, the ways many aquariums maintain their populations include primarily sourcing marine species from the wild. This creates the potential for negative impacts to stressed aquatic environments and a need for a holistic approach to quantify the impacts of aquarium population management. 2. The objective of this study was to implement a developed One Welfare‐Based Ecosystem Model to predict impacts of aquarium population management on humans, animals, and the environment. Ecosystem indicators were selected and grouped into physical–chemical, biological, and socio‐economic categories. Data included measurements of environmental and animal indicators at field sites frequently visited by aquariums to collect animals from, aquarium visitor surveys, and publicly available data. Model development included comparing field data to reference information and then adding weightings based on indicator significance and alpha‐testing of the model. 3. At model completion, each institution was allocated a One Welfare status. Confidence ratings of measured indicators and reference data occurred for each field site to determine the appropriateness of use of the model for each aquarium. 4. Findings included a positive One Welfare status, with collaborating institutions scoring in the good and excellent categories (81.92/100 and 92.51/100). Confidence ratings showed positive results (62/100 and 78/100) for model applicability for the field sites studied as well as future use by other institutions assessing similar parameters. 5. To maintain their recognition as leaders in conservation, public aquariums must objectively assess their direct and indirect influence on marine ecosystems moving forward.

The value of improving freshwater ecosystem services: South Carolina residents’ willingness to pay for improved water quality

Riverine ecosystems play a crucial role in providing essential services such as drinking water, food, recreation, and other aquatic resources. Yet, their capacity to deliver ecosystem services is threatened by rapid land use which modifies their ecological functions. While freshwater monitoring and restoration programs became more robust with technological advancement, the technical ecosystem indicators monitored by experts do not typically resonate with the public. Since public sentiments and preferences are crucial in conservation planning, we quantified households' mean willingness to pay (WTP) for riverine ecosystem services in South Carolina (SC) using a payment card approach. This technique in conducting a contingent valuation method allowed us to estimate mean WTP for five aquatic indicators. Findings revealed that households’ monthly mean WTP is higher for indicators that can enhance recreational benefits, such as fish catch ($5.89- $6.58), species richness ($6.28- $6.72) and access ($6.75) compared to IBI ($5.74- $6.26) and instream flow quality ($5.34–6.06). When extrapolated to entire SC, the improvement of each indicator would translate to total benefits ranging between $131 to $165 million annually. The values computed from this study could serve as inputs for the computation of benefit-cost ratios of proposed freshwater programs. By incorporating households' WTP in the policy analysis, decision makers can prioritize programs that offer the greatest public benefit, while enhancing freshwater quality across the state.

Cumulative trophic curves elucidate tropical coral reef ecosystems

There are few generalizable patterns in ecology, with widespread observations and predictability. One possible generalizable pattern is the cumulative trophic theory, which consistently exhibits S-curves of cumulative biomass over trophic level (TL) for over 200 different marine ecosystems. But whether those cumulative biomass patterns persist in some of the more distinct marine ecosystems, coral reefs, is unclear. Coral reefs are unique among marine ecosystems, representing global biodiversity hotspots and providing crucial ecosystem services. They are subject to many pressures, including both global (e.g., climate and ocean changes, warming, acidification) and local (e.g., overexploitation/overfishing, increase in turbidity, bleaching, habitat destruction, invasive species) stressors. The analysis of emergent ecosystem features, such as cumulative biomass S-curves, could represent a useful and new analytical option that can also be implemented for coral reefs. The cumulative biomass approach was applied to 42 U.S. Pacific islands (Guam and the Commonwealth of Northern Mariana Islands, American Samoa, the Pacific Remote Islands Areas, and the Northwestern and Main Hawaiian Islands), using data collected from fish surveys. Results show that coral reef ecosystems do indeed follow the S-curve patterns expected from cumulative trophic theory, which is not trivial for tropical reef systems that tend to be less widely examined and strongly dominated by structuring organisms like corals. The curve parameters results are also consistent with both fish assemblage diversity indexes and the benthic substrate ratio, which suggests this measure could serve as a useful ecosystem indicator to measure the ecological status of reefs. Moreover, the curve shape was consistent with what one would expect for different levels of perturbation, with the areas more densely inhabited showing less pronounced S-curves, in contrast to those observed in low human population density islands. All this is reflected in the curve parameters, particularly inflection point of the TL and steepness, generally showing a negative response to both natural and anthropogenic disturbances. Cross-archipelago differences have also been detected with the Hawaiian Island chain tending to have lower inflection points for biomass and TL than other regions. Collectively our findings demonstrate the potential application of the cumulative biomass approach to evaluate coral reef ecosystems.

Prokaryotic Community Composition and Diversity in Sediments from Choctafaula, Uphapee, and Cubahatchee Creeks in the Lower Tallapoosa River Basin, Macon County, Alabama: An Observational Study

Sedimentary prokaryotes are primarily responsible for metabolic activity in rivers. They are subjected to a variety of natural and anthropogenic pressures, allowing us to use the composition and diversity of their communities as indicators of ecological health. For our investigation, we looked at sediments from three ecologically critical streams in the Lower Tallapoosa River Basin (Choctafaula, Uphapee, and Cubahatchee Creeks). The prokaryotic community was characterized using molecular approaches, and elemental concentrations were determined by inductively coupled plasma atomic emission spectrometry. This research demonstrated that Proteobacteria (45.02–80.73%), Bacteroidetes (1.98–26.52%), Firmicutes (1.36–50.67%), Actinobacteria (1.55–16.81%), and Acidobacteria (0.13–8.77%) were the most prevalent phyla. Key physicochemical parameters, core communities at multiple taxonomic levels, and several pathogenic genera shifted radically between streams. Weighted and unweighted unifrac distance metrics based PCoA plots indicated the structural and membership similarity of samples from specific creek ecosystems. Based on our research findings, it is evident that the composition and diversity of prokaryotic communities in sediment could serve as significant indicators in stream ecosystems. Further investigation and application of these indicators could prove valuable in assessing the health of streams, particularly in light of the accelerated changes resulting from climate change within a condensed timeframe.

ВИРУСЫ ЛЕТУЧИХ МЫШЕЙ, ОБЛАДАЮЩИХ ЗООНОЗНЫМ ПОТЕНЦИАЛОМ

In recent years, the study of bat viruses has become particularly relevant in light of the coronavirus pandemic and other major outbreaks of viral diseases, such as Ebola fever and the Zika virus. Bats are important reservoirs for many pathogens that can cause diseases in humans and animals. These mam-mals not only serve as primary sources of various infections but also play a key role in their transmission, making them a subject of increased interest for virologists and epidemiologists.This article attempts to systematize information about the most common viruses associated with bats on a global scale. It examines the main viral families circulating among bats, as well as their pathogenic properties and mechanisms of interaction with the host. Additionally, the article presents an overview of current research conducted in Kazakhstan regarding bat viruses. The relevance of these studies is ana-lyzed in the context of public health and the potential for preventing future outbreaks of viral diseases.Thus, this work emphasizes the significance of bats as biological indicators of ecosystem and human health, as well as their role in the epidemiology of infectious diseases.

Habitat status of the Smooth-coated Otter (Lutrogale perspicillata) in Geruwa-Khaurahi River, Bardia National Park, Nepal

Smooth-coated Otter (SCO), a top predator and health indicator of the aquatic ecosystem is included as vulnerable on the IUCN red list and listed in Appendix I. Geruwa-Khaurahi River (GKR) was observed to determine the habitat status of SCO between Bardiya National Park (BNP) and Khata Corridor (KC), and to evaluate factors affecting the SCO habitat, data on habitat parameters and SCO signs were collected in each transect of 500 m. Principal component analysis was used for the most probable habitat parameter selection. An SCO group of eight was observed at Lalmati on the broad, shallow, and fast-flowing GKR with a sandy island and a flat stone bank with a vast escape distance. All signs were found on the sandy shoreline of the riverine forest with nearby tall Saccharum coverage over a narrow escape cover with a gentle bank slope. Diversions of water from the Geruwa River to the narrow and shallow Khaurahi River resulted in fast-flowing water where SCO pugmarks were found abundant. But at KC, human disturbances, over-fishing, river mining, and infrastructures have made the river unsuitable for SCO. SCO preferred dense riverine forests where the gentle riverbank has sand and/or tall Saccharum in between a narrow escape distance. Also, the narrow river with shallow depth and slow flow of good water quality was preferred by SCO. Lastly, with minimal human disturbance, further study on feeding ecology and population dynamics is requisite to conserve the suitable habitat of the SCO.

Assessment of pollutants in coastal waters, sediments, and biota of marine ecosystems in Algeria, North Africa

This study aims to assess the chemical and ecological quality of the marine ecosystem in Algerian central coastal zone (Bay of Algiers (AB) and Bou-Ismail Bay (BIB)) by examining several quality indicators of the marine ecosystem: water, sediment, and biota. Except for stations near the mouths of wadis and industrial and urban discharges released without prior treatment, the study of the physicochemical water quality in the different sampling stations revealed a more or less normal variation in temperature and salinity. According to nutrient salt analysis, all studied stations (in AB and BIB) have high nitrogen levels, such as ammonium and nitrate. However, low levels of phosphate were detected, indicating that this element is scarce in the Algerian coastal marine waters. Three trace metals were also analyzed in the sediments of both bays. Pb ranged from 21.15 to 52.69 μg g–1 dry weight (dw), Zn from 19.32 to 175.1 μg g–1 dw and Cd between 0.87 and 2.031 μg g–1 dw. Contamination factors ranged from 0.62 to 1.55 for Pb, 0.2 to 1.85 for Zn and 1.74 to 4.04 for Cd. Analysis of these three metals in sediment samples reveals their presence at most stations studied. The contamination index calculation shows a moderate anthropogenic intake that requires continuous monitoring to protect the study area’s ecosystem. Crucially, the analysis of fish products revealed a lack of chemical risk concerning trace metals, known for their detrimental health effects. However, this conclusion does not dismiss the potential for subtle contamination, warranting persistent environmental surveillance. Consequently, sustained efforts in environmental monitoring are imperative to ensure the preservation of the marine ecosystem amidst escalating anthropogenic pressures.

Species Distribution and Conservation Status of Dragonflies and Damselflies (Odonata) in Antananarivo City, Madagascar

Dragonflies are iconic freshwater and excellent indicators of freshwater ecosystems' environmental health and quality. The knowledge of Madagascar's Odonata is not advanced, and inventories are needed to increase the information on the distribution and conservation of these species. Here, we assessed the Odonata fauna occurring in Antananarivo City. Through opportunistic observations from October 2020 to September 2021 in 13 pond areas, we recorded 32 species of Odonata (22 Anisoptera and 10 Zygoptera). Endemic species represent a high proportion of the samples (69.70%). Few exotic species have been recorded (15.15%) and do not represent a real threat to the native species. Based on the International Union on Conservation of Nature criteria, most of the species are classified as a Least Concern (81.82%). River and the lake represent the main breeding sites for these species. The rice fields surrounding the Capital are excellent for breeding but contain fewer species. Interaction predator-prey should be initiated to assess Odonata's role in controlling malaria vectors such as Anopheles arabiensis.

Ecosystem indicators: predicting population responses to combined climate and anthropogenic changes in shallow seas

Crowded seas are becoming a pressing management problem with the increased development of offshore renewable energy (ORE) to combat climate change. Marine ecosystems are complex and varied; therefore, we need new tools to help rapidly increase our understanding of how they are likely to change with both climate and anthropogenic changes. This study uses a pragmatic data‐driven Bayesian network approach to capture the patterns of ecosystem complexity and reveal trends of ecosystem drivers (i.e. indicators) important to ecosystem functioning across space and over time. The ecosystem approach assessed physical and biological indicators and their influence on population (abundance/productivity) trends in four regions with contrasting habitats of the North Sea within the last 30 years (1990–2019). What‐if scenarios were conducted to examine species/functional group responses to physical (temperature and stratification) representing climate and large‐scale ORE development effects, as well as anthropogenic (fishing) changes. Clear patterns were revealed, including temporal trends of the dynamic nature of bottom‐up effects driven by physical change versus top‐down effects driven by fishing across trophic levels and habitat types. All four regions are influenced by both effects; however, the dominance of effects was dependent on region: Shetland and Orkney (bottom‐up driven), southern North Sea (top‐down driven). In general, regions with stronger bottom‐up effects showed increasing population trends whereas those with stronger top‐down effects, decreasing trends. Our findings also suggest that some species are much better indicators of either bottom‐up (e.g. zooplankton), top‐down effects (e.g. fish) or both (e.g. grey seal), but the strength of indicator is dependent on habitat type. The habitat‐specific results provide better understanding of what type of ecosystem change they are indicating (physical or biophysical) and therefore indicators that assess both ecosystem status and resilience, ensuring a more strategic and integrated evaluation of trade‐offs for future sustainable management of our shallow seas.

Patterns and Predictors of Phytoplankton Assemblage Structure in a Coastal Lagoon: Species-Specific Analysis Needed to Disentangle Anthropogenic Pressures from Ocean Processes

Phytoplankton are dominant primary producers and key indicators in aquatic ecosystems. Understanding the controlling factors on the structure of phytoplankton assemblages is fundamental, but particularly challenging at the land–ocean interface. To identify the patterns and predictors of phytoplankton assemblage structure in the Ria Formosa coastal lagoon (south Portugal), this study combined phytoplankton abundance along a transect between the discharge point of a wastewater treatment plant and a lagoon inlet, over two years, with physico-chemical, hydrographic, and meteo-oceanographic variables. Our study identified 147 operational taxonomic units (OTUs), and planktonic diatoms (60–74%) and cryptophyceans (17–25%) dominated the phytoplankton in terms of abundance. Despite strong lagoon hydrodynamics, and the lack of spatial differences in the phytoplankton abundance and most diversity metrics, the multivariate analysis revealed differences in the assemblage structure between stations (p < 0.001) and seasons (p < 0.01). Indicator analysis identified cryptophyceans as lagoon generalists, and 11 station-specific specialist OTUs, including Kryptoperidinium foliaceum and Oscillatoriales (innermost stations) and potentially toxigenic species (Pseudo-nitzschia and Dinophysis; outer lagoon station, p < 0.05). Water temperature, pH, and nutrients emerged as the variables that best explained the changes in the phytoplankton assemblage structure (p < 0.001). Our findings provide insight into the relevance of local anthropogenic and natural forcings on the phytoplankton assemblage structure and can be used to support the management of RF and other coastal lagoons.

Macroalgae diversity and its relationship with environmental conditions in polluted waters of Seribu Islands, Jakarta Bay, Indonesia

Abstract. Handayani S, Widhiono I, Widyartini DS. 2023. Macroalgae diversity and its relationship with environmental conditions in polluted waters of Seribu Islands, Jakarta Bay, Indonesia. Biodiversitas 24: 6291-6298. Macroalgae are one of the important marine primary producers because they support the life of other organisms at a higher trophic level in aquatic ecosystems. This study aimed to determine the species diversity and composition of macroalgae and its relationship with local aquatic environmental conditions. This research was conducted in Seribu Islands, Jakarta Bay, and consisted of Pramuka Island, Semak Daun Island, Kotok Besar Island, Karang Bongkok Island, Kongsi Island, and Pari Island as sampling sites. This research used the transect method with quadratic sampling and the data was analyzed using the Shannon-Wiener Diversity Index, Dominance Index, and Evenness. Diversity parameter calculations were carried out using PAST4.0 software. The relationship between diversity and water quality was analyzed using PCA software. Across the six sampling sites, there were 41 species of macroalgae belonging to 3 divisions, namely Chlorophyta (19 species), Phaeophyta/Ochrophyta (10 species), and Rhodophyta (12 species). The species richness among islands showed that Karang Bongkok Island had the highest species with 28 species and the lowest was Semak Daun Island and Kongsi Island with only 15 species. The Diversity Index was the highest in Karang Bongkok Island with 2.679 and the lowest was in Kongsi Island with 1.907. The species with the largest number of individuals were Halimeda macroloba with 930 individuals, followed by Sargassum binderi with 648 individuals, and Corallina officinalis. with 257 individuals. The diversity of macroalgae species on the six islands is classified as moderate and can be used as an indicator of marine ecosystems. Physicochemical parameters that affect macroalgae diversity in the Seribu Islands waters are temperature, depth, currents, salinity, Total Dissolved Solids (TDS), pH, Dissolved Oxygen (DO), Cu, and Phosphate. The finding of this study implies that despite the high pollution in Seribu Islands waters, it is still good for the growth of macroalgae.

Zooplankton as ecosystem indicators and their effects on eutrophication in Lake Arekit (Ethiopia) – implication for freshwater habitat management

This paper examines the zooplankton abundance and composition along with various environmental factors in Lake Arekit – a shallow freshwater habitat in Ethiopia’s rift valley system. Zooplankton samples and specific environmental data were collected by a seasonal campaign (rainy season: June to August) and dry season: March to May 2023) from three sites: inlet area (IA), pelagic area (PA), and macrophyte area (MA). In total, 11 zooplankton taxa from four different groups – rotifera (7 taxa), cladocera (2 taxa), copepod (1 taxa), and ostracoda (1 taxa) – were identified in Lake Arekit. Large-bodied copepoda and cladocera comprised 90% of the zooplankton density in the lake, but small-bodied rotifers dominated the zooplankton diversity. The most noticeable zooplankton in the lake were Mesocyclops aequatorialis, Daphnia barbata, and Cypridopsis vidua. Seasonal difference in the total zooplankton abundance was evident (p < 0.01): being high during the rainy season which was accompanied by an increase in the lake’s water temperature and nutrient levels. At MA, where D. barbata predominated, chlorophyll a was relatively low. Chlorophyll a had a strong negative correlation with the abundance of grazing zooplankton, especially with D. barbata (r = −0.563) and C. vidua (r = −0.518). The zooplankton composition and abundance of Lake Arekit reveal a low Shannon diversity index (H’) (1.03) and a predominance of a few species, indicating heavy contamination of the lake’s water. Moreover, Lake Arekit was determined to be hypertrophic (TSI > 70) using Carlson’s trophic index (TSI), which took into account the lake’s water transparency, total phosphorus, and chlorophyll a. Our results indicated that high densities of Daphnia should be the goal of biomanipulation since they can achieve filtration potentials high enough to enhance the water’s clarity in hypereutrophic lake. Even though high D. barbata concentrations cannot address the underlying cause of eutrophication, grazing can assist by lengthening the clear-water stages in a hypertrophic lake – Lake Arekit. The sources of pollution for the lake are the discharge of wastewater from nearby water bottling companies and possibly high nutrient levels from the lake’s geological history. Stopping the discharge of wastewater from the nearby commercial industries (the major source of contaminant) into heavily washed open areas and establishing a buffer zone may help manage the water quality of Lake Arekit.

Integrated Assessment and Restoration Pathways for Holistic Ecosystem Health in Anxi County, China

Different types of ecosystems form a complex community of life. Hence, ecosystem protection and restoration should not focus solely on a single ecosystem. Ecosystem health assessments should consider the integrity and systematicity of interrelated ecosystems to inform rational environmental planning and management. In this study, the key characteristic indicators of major ecosystems (mountain, water, forest, and cropland) and ecosystem service capacity indicators in Anxi County, China, were selected to construct an integrated assessment system of ecosystem health that led to integrated ecosystem restoration pathways that addressed the county’s ecological problems. The results revealed that ecosystem health was higher in the western and lower in the eastern parts of the county. Throughout the county, “medium” and “poor” ecosystem health levels predominated, revealing that overall ecosystem sustainability was weak. Ecosystem restoration programmes should be tailored to each health level. Where there was “excellent” and “good” ecosystem health ratings, those healthy ecosystem functions should be strengthened and maintained. In the “medium” health areas, the control and prevention of ecological problems should be strengthened. “Poor” health areas require immediate integrated ecological restoration projects that ensure the connectivity and coordination of restoration tasks in fragile ecosystems. This then will enhance holistic ecosystem stability and sustainability.

Ecological niche modelling of two water-dependant birds informs the conservation needs of riverine ecosystems outside protected area network in the Eastern Himalaya, India.

Common species often play vital roles in ecosystem functions and processes. Globally, conservation strategies are mostly focused on threatened species and rarely explored the potential of using common species as indicators of critical ecosystems. The Himalayan mountains have unique riverine ecosystems harbouring high diversity of specialist river birds. Ecological niche modelling provides effective tools to predict suitable habitats of a species and identify habitats for conservation. We used two common water-dependent bird species, Blue Whistling Thrush and White-capped Water Redstart as indicators of riverine ecosystems within the Sikkim Himalayan region and predicted their suitable habitats using an ensemble modelling approach. We selected six predictor variables for the final model including three bioclimatic and three topographic variables. For both species, bioclimatic variables such as mean annual temperature and precipitation were the most important factors compared to topographic variables. At least 70 percent of the most suitable habitats are distributed below 2000 m elevation alongside major drainages. Also, most of their potential habitats are distributed outside the protected area networks in the region. This habitat suitability pattern may be applied to other sympatric species in the region. Since major water bodies in Sikkim are largely affected by developmental activities and climate change, these riverine birds might face threats of losing suitable habitats. We recommend a dynamic approach to evaluate the habitat quality of riverine birds, especially outside protected area networks in the region to plan conservation strategies. This approach will ensure habitat conservation of many water-dependent birds and other taxa associated with the riverine ecosystems of the Eastern Himalaya.

Bathymetric segregation among demersal benthos and its contributions to the differences in the bycatches on bottom fisheries in the Emperor Seamounts area, Northwestern Pacific Ocean

The need for the management of commercially targeted species and surrounding ecosystems has become more apparent in conjunction with the thriving commercial exploration of open seas. Despite the growing global interest in how fishing activity impacts seamount ecosystems, data regarding to the fishing impacts of gillnets on seamount ecosystems are scarce, and quantitative comparisons between trawls and gillnets are surprisingly limited. Our quantitative comparative studies using observer data collected at the southern Emperor Seamounts area revealed that the quantity and quality of bycatches of four key demersal benthos, denoted as Vulnerable marine ecosystem (VME) indicator taxa designated in the convention text of The North Pacific Fisheries Commission (three orders of dominant corals, Antipatharia, Scleractinia, and “Gorgonian” (Alcyonacea with solid axis), and Porifera), were not inherently different between the gear types, and operational tactics, such as depth or positions, might be prior factors largely affecting bycatches of benthic assemblages in the fishing activities carried out at Emperor Seamounts. Additionally, assessments of multiyear operational data revealed temporal shifts in the species composition of cold-water coral bycatches. Overall, the synthesis of bycatch occasions provided by scientific observers enabled us to reveal (1) the variations in bathymetric distributions and the contribution of local topographies toward demersal benthic organisms and (2) fishing operational features, such as operation positions and depth, which may strongly affect bycatches.

Sacred river of Pune: boon or bane for the diversity of aquatic beetles (Insecta: Coleoptera)

Aquatic beetles are potential indicators of freshwater ecosystem and play an important role in food web and nutrient cycling. Parameters like pH, temperature, conductivity, total dissolved solids, salinity, and dissolved oxygen, are important water quality parameters. The present study is focused on the diversity of aquatic beetles and assessing water quality parameters of the sacred Indrayani River from various sites namely Valvan, Kamshet, Warangwadi, Begadewadi, Moshigaon, Alandi, Dhanore, and Tulapur. A total of 94 examples of aquatic beetles belonging to 31 species under 19 genera and four families from Indrayani River were recorded along with water quality parameters.