Effective Ecosystem Management Research Articles

Optimizing Sampling Strategies for Estimating Riverine Nutrient Loads in the Yiluo River Watershed, China

Accurately estimating nutrient loads is crucial for effective management and monitoring of aquatic ecosystems. This study evaluated the uncertainty in different sampling frequencies and calculation methods for estimating total nitrogen (TN) and total phosphorus (TP) loads in the Yiluo River watershed, a tributary of the Yellow River in China. Using daily TN and TP concentration data from 2019 to 2020, we conducted a bootstrapping analysis to evaluate the accuracy of nine different load estimation methods at different sampling frequencies. Our results showed that Method 3 (M_3, constant concentration interpolation) and Method 7 (M_7, flow-weighted concentration method), when used with a biweekly sampling frequency, had the lowest Standard Deviation of the Percentage errors (STD) (7.70% and 8.60% for TN, 12.0% and 18.8% for TP, respectively) and Mean Relative Error (MRE) values (0.078% and −1.60% for TN, 0.305% and 2.33% for TP, respectively) on an annual scale. For monthly TN and TP load estimates, M_7 can control the MRE within ±20% at a biweekly sampling frequency. Furthermore, the uncertainty in TN and TP load estimates was generally larger during the summer months (June–September), emphasizing the important role of storm events in nutrient export. Extreme events (<10% of the time) contributed approximately 50% of the annual nutrient loads. The findings of this study provide a scientific basis for optimizing water quality monitoring schemes and management strategies in agricultural watersheds.

Benzoyl Chloride Derivatization Advances the Quantification of Dissolved Polar Metabolites on Coral Reefs.

Extracellular chemical cues constitute much of the language of life among marine organisms, from microbes to mammals. Changes in this chemical pool serve as invisible signals of overall ecosystem health and disruption to this finely tuned equilibrium. In coral reefs, the scope and magnitude of the chemicals involved in maintaining reef equilibria are largely unknown. Processes involving small, polar molecules, which form the majority components of labile dissolved organic carbon, are often poorly captured using traditional techniques. We employed chemical derivatization with mass spectrometry-based targeted exometabolomics to quantify polar dissolved phase metabolites on five coral reefs in the U.S. Virgin Islands. We quantified 45 polar exometabolites, demonstrated their spatial variability, and contextualized these findings in terms of geographic and benthic cover differences. By comparing our results to previously published coral reef exometabolomes, we show the novel quantification of 23 metabolites, including central carbon metabolism compounds (e.g., glutamate) and novel metabolites such as homoserine betaine. We highlight the immense potential of chemical derivatization-based exometabolomics for quantifying labile chemical cues on coral reefs and measuring molecular level responses to environmental stressors. Overall, improving our understanding of the composition and dynamics of reef exometabolites is vital for effective ecosystem monitoring and management strategies.

Phosphorus sorption–desorption changes phosphorus fraction dynamic in a desert revegetation chronosequence

AbstractUnderstanding the characteristics of soil phosphorus (P) sorption and desorption is essential for comprehending P biogeochemical cycling and effectively managing ecosystems in a desert revegetation chronosequence. The present study utilized the Freundlich model and enzymatic activity to characterize the features of P sorption–desorption, and microbial activity, which aims to elucidate the effect of P kinetics and microbial activity on P fractions in the soils of a desert revegetation chronosequence, consisting of 11, 31, 40, 57, and 65 years old revegetated deserts. The findings revealed that the 31 years old soil showed the highest alkaline phosphomonoesterase and phosphodiesterase activities, and the 40 years old displayed the highest inorganic pyrophosphatase activity. In revegetated desert soils, microbial activity changed P sorption–desorption kinetics by decreased or increased the parameters including sorption/desorption energy site, P sorption/desorption ability, and the maximum buffering capacity of P sorption/desorption. And in microbial activity soils of 31–40 years old, P desorption significantly decreased T‐P and A‐P concentrations (p < 0.05). P sorption process and enzyme activity explained 35.10% and 22.20% of P fraction variation, respectively; and P desorption process and enzyme activity explained 48.3% and 22.3% of P fraction variation, respectively. These findings provide valuable insights into the contribution of P kinetics coupled with microbial activity in desert ecosystems, aiding in the effective management of these fragile ecosystems.

Improving Satellite Chlorophyll-a Retrieval in the Turbid Waters of the Bay of Fundy, Canada

AbstractThe Bay of Fundy is a highly productive ecosystem within the Northwest Atlantic where extreme tides and strong currents result in a large gradient of sediment concentrations across and along the bay. We processed daily satellite data from the MODerate resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite from 2003 to 2021 at 300-m resolution to understand and quantify spatial and temporal trends in chlorophyll-a concentration (chl-a, a measure of phytoplankton biomass), and suspended particulate matter concentration (SPM) in the Bay of Fundy surface waters. To account for high sediment loading (up to 100’s g m−3) and moderate chl-a (median in situ chl-a of 1.5 mg m−3 from 2003 to 2021), coefficients of the OC3M chl-a algorithm were regionally tuned using in situ chl-a data, and satellite-derived SPM was incorporated within the chl-a retrieval algorithm to account for possible bias. The updated new algorithm was denoted as OCX-SPMCor. Chl-a computed using OCX-SPMCor showed better performance against in situ chl-a than the generic OC3M with a coefficient of determination that increased from 0.01 to 0.28 and a root mean square logarithmic error that decreased by 35%. Unlike previous remote sensing studies, OCX-SPMCor correctly predicted the particular chl-a seasonality in the Bay of Fundy, which does not follow the typical occurrence of spring/fall blooms as observed in the adjacent Gulf of Maine and Scotian Shelf. For the first time, satellite-predicted chl-a aligned with the phenology of in situ chl-a, where chl-a continually increased from April to June and remained high all summer, with a small secondary summer peak before decreasing in the fall. SPM seasonality followed an opposite trend where SPM reached a maximum in winter and a minimum in summer. A small number of matchups and high temporal variability on the hourly time scale precluded a robust assessment of the satellite-derived SPM. However, comparisons between time series of remotely sensed and in situ SPM demonstrated the ability of the satellite-derived SPM to capture temporal variations, though the absolute values may be slightly underestimated. Accurate maps of phytoplankton biomass and sediment concentrations are essential variables required for effective management and conservation of marine ecosystems in the Bay of Fundy.

Foraging habits of Northwest Atlantic hooded seals over the past 30 years: Future habitat suitability under global warming.

The Arctic is a global warming 'hot-spot' that is experiencing rapid increases in air and ocean temperatures and concomitant decreases in sea ice cover. These environmental changes are having major consequences on Arctic ecosystems. All Arctic endemic marine mammals are highly dependent on ice-associated ecosystems for at least part of their life cycle and thus are sensitive to the changes occurring in their habitats. Understanding the biological consequences of changes in these environments is essential for ecosystem management and conservation. However, our ability to study climate change impacts on Arctic marine mammals is generally limited by the lack of sufficiently long data time series. In this study, we took advantage of a unique dataset on hooded seal (Cystophora cristata) movements (and serum samples) that spans more than 30 years in the Northwest Atlantic to (i) investigate foraging (distribution and habitat use) and dietary (trophic level of prey and location) habits over the last three decades and (ii) predict future locations of suitable habitat given a projected global warming scenario. We found that, despite a change in isotopic signatures that might suggest prey changes over the 30-year period, hooded seals from the Northwest Atlantic appeared to target similar oceanographic characteristics throughout the study period. However, over decades, they have moved northward to find food. Somewhat surprisingly, foraging habits differed between seals breeding in the Gulf of St Lawrence vs those breeding at the "Front" (off Newfoundland). Seals from the Gulf favoured colder waters while Front seals favoured warmer waters. We predict that foraging habitats for hooded seals will continue to shift northwards and that Front seals are likely to have the greatest resilience. This study shows how hooded seals are responding to rapid environmental change and provides an indication of future trends for the species-information essential for effective ecosystem management and conservation.

Exploring spatiotemporal dynamics of NDVI and climate-driven responses in ecosystems: Insights for sustainable management and climate resilience

Understanding the intricate relationship between climate variables and the Normalized Difference Vegetation Index (NDVI) is essential for effective ecosystem management. This study focuses on the spatiotemporal dynamics of NDVI and its interaction with climate variables in the ecologically diverse Khyber Pakhtunkhwa (KPK) Province, Pakistan, from 2000 to 2022. The research methodology involves analyzing satellite images and meteorological datasets to examine NDVI and surface latent heat flux (SHF), total precipitation (TPP), temperature (T), soil temperature (ST), and total pressure (TP). KPK Province's ecological significance and complex climate-vegetation interactions drive the selection of this study area. The study uses multiple linear regression analysis to investigate how T, TPP, SHF, and TP influence NDVI. The Mann-Kendall test detects trends, with Sen's slope estimator quantifying trend magnitudes. Additionally, correlation coefficients provide insights into long-term changes and association strengths. The findings highlight a consistent upward trend in mean NDVI over the 23 years, revealing an overall increase in NDVI, particularly in vegetation-dense areas where it rose from 0.27 to 0.32. The research showed an annual growth rate of 0.84% in the entire area, with specific vegetated zones exhibiting a slightly lower rate of 0.80%. However, the average yearly increase in NDVI is higher in vegetation-specific zones (0.00237) compared to the whole area (0.00151). This increase in NDVI occurs alongside a statistically significant decrease in SHF and PPT, suggesting a complex adaptation of vegetation to changing climate conditions in the KPK Province. In contrast, SHF exhibits a statistically significant negative slope of −5.952e-06 (p < 0.05), indicating a pronounced downward trend. Similarly, Sen's slope estimate for precipitation demonstrates a significant negative trend of −0.0001 (p < 0.05), showing diminishing precipitation. The study uncovers intricate linkages between climate variables and vegetation dynamics within KPK Province. These insights have far-reaching implications, guiding decision-making in land management, conservation efforts, and global climate resilience strategies. Ultimately, the research underscores the critical role of data-driven approaches in shaping a greener and more sustainable future.

Realized thermal niche approach eliminates temperature bias in bioenergetic model estimates.

Bioenergetics models estimate ectotherm growth, production, and prey consumption - all key for effective ecosystem management during changing global temperatures. Based on species-specific allometric and thermodynamic relationships, these models typically use the species' lab-derived optimum temperatures (physiological optimum) as opposed to empirical field data (realized thermal niche) that reflect actual thermal experience. Yet, dynamic behavioral thermoregulation mediated by biotic and abiotic interactions may provide substantial divergence between physiological optimum and realized thermal niche temperatures to significantly bias model outcomes. Here, using the Wisconsin bioenergetics model and in-situ year-round temperature data, we tested the two approaches and compared the maximum attainable lifetime weight and lifetime prey consumption estimates for two salmonid species with differing life histories. We demonstrate that using the realized thermal niche is the better approach because it eliminates significant biases in estimates produced by the physiological optimum. Specifically, using the physiological optimum, slower-growing Salvelinus namaycush maximum attainable lifetime weight was underestimated, and consumption overestimated, while fast-growing Oncorhynchus tshawytscha maximum attainable weight was overestimated. While the physiological optimum approach is useful for theoretical studies, our results demonstrate the critical importance that models used by management utilize up-to-date system- and species-specific field data representing actual in-situ behaviors (i.e., realized thermal niche).

One- and Three-Dimensional Hydrodynamic, Water Temperature, and Dissolved Oxygen Modeling Comparison

Understanding and modeling water quality in a lake/reservoir is important to the effective management of aquatic ecosystems. The advantages and disadvantages of different water quality models make it challenging to choose the most suitable model; however, direct comparison of 1-D and 3-D models for lake water quality modeling can reveal their relative performance and enable modelers and lake managers to make informed decisions. In this study, we compared the 1-D model MINLAKE and the 3-D model EFDC+ for water temperature, ice cover, and dissolved oxygen (DO) simulation in three Minnesota lakes (50-m Carlos Lake, 23.5-m Trout Lake, and 5.6-m Pearl Lake). EFDC+ performed well for water temperature and DO simulation in the open water seasons with an average root mean square error (RMSE) of 1.32 °C and 1.48 mg/L, respectively. After analyzing the ice thickness with relevant data, it was found that EFDC+ calculates a shorter ice cover period and smaller ice thickness. EFDC+ does not consider snowfall for ice thickness simulation. The results also revealed that EFDC+ considers spatial variance and allows the user to select inflow/outflow locations precisely. This is important for large lakes with complex bathymetry or lakes having multiple inlets and outlets. MINLAKE is computationally less intensive than EFDC+, allowing rapid simulation of water quality parameters over many years under a variety of climate scenarios.

Temporal-Like Bivariate Fay-Herriot Model: Leveraging Past Responses and Advanced Preprocessing for Enhanced Small Area Estimation of Growing Stock Volume

Forest inventories are crucial for effective ecosystem management but often lack precision for smaller geographical units due to limited sample sizes. This study introduces an enhanced temporal-like bivariate Fay-Herriot model, improving upon its univariate counterpart. The model incorporates field data and auxiliary data, including canopy height metrics from WorldView stereo-imagery and past census data, sourced from the University Forest of Pertouli in Central Greece. The model aims to estimate the growing stock volume for 2008 and 2018, focusing on enhancing the precision of the 2018 estimates. The 2008 dependent variable is used as auxiliary information by the model for more reliable 2018 small area estimates. A novel preprocessing pipeline is also introduced, which includes outlier identification, cluster analysis, and variance smoothing. Compared to direct estimates and the standard univariate Fay-Herriot model, our bivariate approach shows a percentage variance reduction of 96.58% and 13.52%, respectively. The methodology not only offers more reliable estimates with reduced variance and bias but also contributes to more accurate decision-making for sustainable forest management.

Spatial relationship between ecosystem health and urbanization in coastal mountain city, Qingdao, China

Rapid urbanization and population growth have significantly impacted air and water quality, exerting adverse effects on both the natural environment and human health. While ecosystem health assessment is a crucial aspect of ecosystem management, the smaller-scale implications of urban development have often been overlooked. This paper addresses this gap by examining the relationship between ecosystem health and urbanization in Qingdao over the period 2000–2019. Utilizing the Vigor-Organization-Resilience-Service (VORS) model, we evaluated ecosystem health (ESH) while measuring the extent of urbanization through population dynamics, economic factors, and land size. Our findings indicate a declining trend in ESH over the studied period, particularly in Chengyang District and Huangdao District. Ecosystem vigor experienced the most significant decline, dropping from 0.730 to 0.639, followed by a decrease in ecosystem resilience from 0.422 to 0.394. Concurrently, the urbanization rate in Qingdao exhibited a steady increase, with high levels observed in Shinan District, Shibei District and Licang District. Our analysis reveals a negative impact of urbanization on ecosystem health, with population growth being the predominant factor from 2000 to 2005. Post-2005, the expansion of construction land emerged as a major contributing factor. Addressing ecological and environmental concerns and the effective management of urban ecosystems all depend on understanding and mitigating the negative impacts of urbanization on ecosystem health. These findings hold crucial implications for government departments tasked with managing the delicate balance between population growth and land expansion.

No generality in biodiversity-productivity relationships along elevation in temperate and subtropical forest landscapes

An improved understanding of biodiversity-productivity relationships (BPRs) along environmental gradients is crucial for effective ecosystem management and biodiversity conservation. The stress-gradient hypothesis suggests that BPRs are stronger in stressful environments compared to more favorable conditions. However, there is limited knowledge regarding the variation of BPRs along elevational gradients and their generality across different landscapes. To study how BPRs change with elevation, we harnessed inventory data on 6,431 trees from 152 plots surveyed twice in eight to ten year intervals in mountain forests of temperate Europe and subtropical Asia. We quantified the relationship between aboveground productivity and different biodiversity measures, including taxonomic, functional, and phylogenetic diversity. To elucidate the processes underlying BPRs, we studied the variation of different functional traits along elevation across landscapes. We found no general pattern of BPRs across landscapes and elevations. Relationships were neutral for all biodiversity measures in temperate forests, and negative for taxonomic and functional diversity in subtropical forests. BPRs were largely congruent between taxonomic, functional and phylogenetic diversity. We found only weak support for the stress-gradient hypothesis, with BPRs turning from negative to positive (effect not significant) close to the tree line in subtropical forests. In temperate forests, however, elevation patterns were strongly modulated by species identity effects as influenced by specific traits. The effect of traits such as community-weighted mean of maximum plant height and wood density on productivity was congruent across landscapes. Our study highlights the context-dependence of BPRs across elevation gradients and landscapes. Species traits are key modulating factors of BPRs and should be considered more explicitly in studies of the functional role of biodiversity. Furthermore, our findings highlight that potential trade-offs between conserving biodiversity and fostering ecosystem productivity exist, which require more attention in policy and management.

Alternating dominant effects of temperature and precipitation along elevational gradient on the alpine and subalpine vegetation activities in southwestern China

Elevation plays a pivotal role in modulating hydroclimatic dynamics, changing vegetation activity and shaping vegetation distribution patterns in alpine regions. Nevertheless, a conspicuous knowledge gap persists regarding the interaction between climate drivers on vegetation activity. In this study, we investigated the spatio-temporal patterns of the Normalized Difference Vegetation Index (NDVI), a proxy for vegetation activity, and examined its interactions with temperature (T) and precipitation (P) along elevational gradient (EG) in the Alpine and Sub-alpine Woodlands of Southwest China (ASWSC) during 2001–2018. We found that approximately 24% vegetation in ASWSC exhibited significant greening trend, as a result of regional warming and slight wetting during the study period. The greening and browning rates were both elevational asymmetric, with higher rates at lower elevations. We also illustrated an alternating domination of T - P on vegetation activity along EG. This suggested a roughly antagonistic effect between the two drivers within the whole vegetation elevation range except for a synergistic effect in the sub-alpine forests zone between 2300 - 4200 m. The antagonistic effect tended to be more pronounced in warm and dry years, while the synergistic effect was more evident in cold and wet years. Specifically for different vegetation types, we found an insignificant T - P interactive effect along EG in indigenous evergreen needleleaf forest (ENF) and evergreen broadleaf forest (EBF), in contrast to the significant synergistic effect in the regenerated deciduous broadleaf forest (DBF) and mixed forest (MF) and antagonistic effect in shrubland and grassland types. In summary, our study revealed alternating-dominant effects of temperature and precipitation on vegetation activity along EG. These findings will deepen our understanding of vegetation resistance and resilience to climate change and eventually contribute to establishing a scientific foundation for effective ecosystem management and conservation practices in alpine region.

Impacts of the Three Gorges Dam on riparian vegetation in the Yangtze River Basin under climate change

As the largest hydroelectric project in the world, the Three Gorges Dam (TGD) is expected to have significant environmental and ecological impacts on riparian vegetation in the Yangtze River Basin (YRB). However, existing studies have mainly focused on small segments of the YRB. In addition, few studies have quantified the responses of riparian vegetation to both climatic factors and dam construction. In this study, we investigated riparian vegetation dynamics over the entire YRB before, during, and after the construction of TGD from 1982 to 2015 using the normalized difference vegetation index (NDVI). Furthermore, the effects of climatic factors and dam construction on riparian vegetation were quantitatively analyzed using path analysis. The results demonstrate that the YRB has experienced a generally greening trend after TGD construction. The impacts of climate change on riparian vegetation have exhibited notable spatial heterogeneity and temperature is the main climatic factor that affects riparian vegetation growth. Moreover, TGD becomes the major contributor to riparian vegetation dynamics in the YRB after TGD construction. TGD has not only directly enhanced riparian vegetation but also indirectly affected riparian vegetation by regulating the microclimate. This study highlights the significance of anthropogenic interference when evaluating the relationships between riparian vegetation and climatic factors, providing useful insights for the effective management and conservation of large-scale riparian ecosystems.

Elevation filters bat, rodent and shrew communities differently by morphological traits

AbstractAimMountains are geographic features that provide sharp elevational gradients which can accommodate a diversity of terrestrial flora and fauna. In the face of climate change, many of these species are being pushed higher to escape ever‐increasing temperatures. Despite this, we have little understanding of how species distribute themselves across mountains. African mountains in particular are less studied than mountains elsewhere and the small mammal groups that inhabit them are also poorly studied when compared to other groups. In this study, we examined the responses of three functionally distinct small mammal taxonomic groups to changes in elevation across Africa.LocationAfrica.MethodsWe calculated four functional diversity metrics for 166, 97 and 153 communities of rodents, bats and shrews comprising 225, 183 and 109 species, respectively. We employed RLQ and fourth‐corner analyses to identify any associations between the functional traits of the small mammals and elevation and other climatic variables.ResultsWe show that the species richness of the three taxa responded differently to increases in elevation, with only rodents showing a mid‐elevational hump. The composition of rodent and bat communities differed significantly in upland versus lowland sites, but bat communities showed far more overlap across the elevational gradient. Functional diversity metrics responded differently for each taxon highlighting the importance of using different taxonomic groups when studying elevational patterns of functional diversity.Main ConclusionsOur study shows that functional divergence increases with elevation in all three taxa, indicating a pervasive and broadly applicable strong environmental filtering at higher elevations. Our findings suggest that species at higher elevations may be at higher risk due to specialization. These species are losing habitat due to ongoing climate change that will force them up the elevational gradient. At the same time, the human population in Africa is predicted to triple in size by the year 2100, which will also likely contribute to further habitat loss and fragmentation. As small mammals often play essential roles in ecosystems, from seed dispersal to soil aeration and predation, understanding the susceptibility of the specialization of species at higher elevations is crucial for the effective conservation and management of mountain ecosystems, especially in light of climatic change and human expansion.

Drought decreased annual cumulative carbon uptake in Southwest China mainly through its influence on phenology rather than physiology

Drought poses a significant threat to the sustainability of ecosystems, particularly in regions like Southwest China, where it has been observed to substantially reduce the annual cumulative carbon uptake (ACCU). Understanding the mechanisms driving this reduction is therefore crucial for effective ecosystem management. To address this issue, this study decomposed ACCU into three indicators, i.e., start of the growing season (SOS), end of the growing season (EOS), and peak gross primary productivity (GPPmax), through the Statistical Model of Integrated Phenology and Physiology (SMIPP), and explored the response of ACCU to drought. The results revealed that phenology (SOS and EOS) and physiology (GPPmax) components collectively captured 74% of the variation in ACCU, confirming the applicability of the SMIPP model in Southwest China. Among the three indicators, GPPmax contributes to ACCU more than the two phenological indicators. We also found that, from 2001 to 2020, drought decreased ACCU by 65.58 Tg C through delying SOS, by 21.47 Tg C through advancing EOS, but increased ACCU by 11.15 Tg C through increasing GPPmax, resulting in a net loss of 75.90 Tg C in ACCU. Our findings highlight the predominant negative impact of drought on ACCU, achieved primarily through alterations in phenology. Overall, this study quantified the respective contributions of phenology and physiology in the response of ACCU to drought, and would inform the prediction of ACCU of ecosystems under future drought in Southwest China.

Multi-habitat carbon stock assessments to inform nature-based solutions for coastal seascapes in arid regions

Coastal ecosystems are integral to global carbon cycling and are increasingly recognised for their role in mitigating climate change. Within these ecosystems, the dynamics of carbon storage are diverse, varying significantly across different habitats. However, existing management strategies often focus predominantly on vegetated habitats neglecting the contributions of non-vegetated areas. We address this knowledge gap by providing a quantitative spatial assessment of carbon storage across coastal seascapes varying in plant biomass. Our comprehensive multi-habitat inventory of carbon stocks in the United Arab Emirates confirmed that mangroves are the largest carbon-storing habitat per hectare (94.3 t/ha), followed by saltmarshes (63.6 t/ha), microbial mats (51.6 t/ha), mudflats (46.8 t/ha), seagrass (32.5 t/ha), and coastal sabkha (31.0 t/ha).Mean carbon content in the top 50 cm of mangrove soils (53.9 t/ha) was similar to saltmarshes (52.7 t/ha), microbial mats (51.6 t/ha), and mudflats (46.8 t/ha). We highlight the importance of including non-vegetated habitats in carbon accounting and management strategies. Our findings suggest that a more context-specific whole-system approach is essential for guiding effective ecosystem management and designing ecologically meaningful Nature-based Solutions (NbS). Adopting this broader perspective in NbS can ensure more comprehensive conservation and restoration outcomes, which not only protect and enhance blue carbon ecosystems but also contribute to broader ecological and social benefits. This approach is pivotal for advancing our understanding of interconnected coastal ecosystems and their role in climate change mitigation.

Ecological impacts of dam construction on epilithic diatom communities in estuaries: A case study of the Korean peninsula

This study, spanning 2016 to 2018, investigated diatom distribution in 324 Korean Peninsula estuaries, emphasizing the ecological impact of artificial dams. Examining environmental and biological variables, we focused on dam construction. OPEN estuaries exhibited higher urban/forest land cover and had more alkaline, saline, conductive, and oxygen-rich water. In CLOSE estuaries, agricultural farmland and nitrogen compound concentrations were higher. Dams in CLOSE estuaries correlated with lower pH, salinity, electrical conductivity, and dissolved oxygen. Regional variations were evident, with WEST OPEN estuaries showing higher salinity, turbidity, chemical oxygen demand, and total phosphorus. SOUTH estuaries displayed intermediate characteristics, while EAST OPEN estuaries had higher dissolved oxygen but lower temperature and turbidity.Diverse epilithic diatoms were identified, with OPEN estuaries displaying greater species richness, primarily dominated by Nitzschia inconspicua Grunow. CLOSE estuaries, conversely, exhibited higher richness with a different subdominant species. Indicator species analysis revealed taxa specific to estuaries and sea areas, with CLOSE ones exhibiting lower salinity and higher nitrogen/phosphorus concentrations. Nitzschia inconspicua dominated all estuaries, but subdominant species varied; N. fonticola (Grunow) Grunow in OPEN, N. paleaceae (Grunow) Grunow in CLOSE. CLOSE estuaries had higher species richness. In the West Sea, turbidity and TP levels affected diatom growth, with dams exacerbating turbidity and potentially disrupting the food chain.Results underscored intricate interactions between dams, land use, and diatom communities, offering foundational data for ecosystem management and biodiversity conservation in Korean Peninsula estuaries. Understanding the ecological consequences of artificial dams on diatom distribution is crucial for preserving estuarine health. Future research is recommended to explore additional factors influencing these ecosystems, particularly focusing on various organisms in West Sea estuaries for effective ecosystem management and conservation.

Performance evaluation of backscattering coefficients and polarimetric decomposition parameters for marsh vegetation mapping using multi-sensor and multi-frequency SAR images

Wetland vegetation is the basis for wetland ecosystems to regulate climate change, carbon sequestration and maintain biodiversity. Therefore, high-precision mapping and dynamic monitoring of wetland vegetation are essential for the effective management, restoration and sustainable development of wetland ecosystems. This study addressed to explore classification performance of backscattering coefficients and polarimetric decomposition parameters of multi-frequency SAR images, including single-polarimetric X-band TerraSAR (TS), full-polarimetric C-band Radarsat-2 (RS) and L-band ALOS PALSAR-2 (PS) for marsh vegetation mapping in Honghe National Nature Reserve, Northeast China. We proposed two transfer-learning strategies, and examined the feasibility of transfer-learning vegetation classifications between optical and SAR sensors, different frequencies SAR (X-, C- and L-band) and its derivative images, respectively. This paper further compared transfer-learning classification performance of marsh vegetation from polarimetric decomposition parameter images to backscattering coefficient images under the same SAR sensors. The results indicated that: (1) The three SAR images performed good classification ability in identifying marsh vegetation with the overall accuracies (OA) ranging from 0.74 to 0.88. For the same frequency SAR images, polarimetric decomposition parameters outperformed backscattering coefficients with an OA improvement ranging from 0.24 % to 2.41 %; (2) The longer wavelength SAR images produced better classification results, and L-band PS images realized the highest classification accuracy (OA = 0.871); (3) Full-polarimetric SAR images obtained the better transfer-learning classifications (OA > 0.8), and the transfer-learning classification ability of the same frequency SAR images outperformed the different frequencies; (4) The transfer learning classification results between SAR sensors outperformed that of between optical and SAR images. The results of this study provide a scientific basis for wetland change monitoring conservation and sustainable development.

Species Identification of Sea Bamboo (Isis hippuris) using COI-based DNA Barcoding

Conservation and effective management of marine ecosystems and biodiversity requires accurate species identification. This study classifies sea bamboo (Isis hippuris) specimens using DNA barcoding, a technique widely recognized for its speed, accuracy, and objectivity. This study examines the cytochrome c oxidase subunit I (COI) gene analysis for species identification. Isis hippuris was collected from two stations (coral and seagrass areas) of Tanjung Tiram Waters, South Konawe, Southeast Sulawesi. Genomic DNA was extracted from the base, main, and lateral stem of I. hippuris. Polymerase chain reaction (PCR) was used to amplify the mtDNA of I. hippuris with HCO2198 and LCO1490 primers. The highest quality PCR product based on the COI gene was chosen for sequencing analysis. The study revealed that COI gene analysis could only be performed on the base and main stem of the I. hippuris. Samples from coral and seagrass-coral areas on lateral stems were not further analyzed due to low concentration and purity values, which could potentially fail DNA sequencing. Each part of I. hippuris may have unique genetic differences. This study highlights the advantages of DNA sequencing in providing a unique genetic fingerprint for each species, enabling accurate species identification. This research provides insight into using DNA barcoding for sea bamboo species identification.

Assessment of habitat suitability in riverine wetland using genetical and physiological analysis of anurans (Pelophylax nigromaculatus)

Habitat suitability assessments are crucial for effective ecosystem management. We conducted genetic and physiological analyses of frog populations to assess the suitability of habitats in riverine wetlands, and compared populations in riverside areas between water channels and river levees, and protected lowlands between river levees and human living spaces. Our results showed unexpected genetic diversity in the riverside population but revealed differences in genetic structure between the two groups. Most physiological indicators were not significantly different, although some blood biochemical indicators revealed hepatic stress in frogs from the protected lowlands. The study suggests that frogs from riverside areas are not necessarily worse in terms of population size or health but may be genetically isolated due to levees. To address this issue, enhancing habitat connectivity is recommended. This study demonstrated the utility of genetic and physiological information for understanding complex habitats and population conditions in the context of ecosystem management.