Ecosystem Changes Research Articles

Ecosystem water limitation shifts driven by soil moisture in the Loess Plateau, China

In the context of climate change, the functionality of ecosystems is primarily influenced by the availability of water and energy supply. However, there is limited research that comprehensively uses energy indicators to explore how climate change affects the water and energy limiting states of ecosystems. Here we evaluated the historical and future water and energy limitations using the Ecosystem Limitation Index (ELI) derived from evapotranspiration (ET), soil moisture (SM), net radiation (Rn), and air temperature (Ta), and conducted an in-depth analysis of the dominant factors. The results indicate that: (1) The degree of water limitation deepened initially and then weakened. Over 68 % of the region became drier initially, while over 83 % became wetter later. (2) In terms of area, soil moisture emerged as a critical factor influencing the variations in water and energy constraints within the Loess Plateau. Further research revealed the range of critical soil moisture (CSM) for the transition of water-energy limitation state is 0.286 mm3mm−3, and it varies with changes in temperature, soil texture, vegetation cover, and season. (3) Future projections suggest a transition towards heightened water limitations across the Loess Plateau. These findings underscore the efficacy of ELI in assessing and predicting dynamic ecosystem changes, offering valuable insights into the impacts of climate change on water and energy cycles within semi-arid ecosystems.

Climate change and disturbance interact to alter landscape reflectivity (albedo) in boreal forests across a large latitudinal gradient in Siberia

Boreal forests form the largest terrestrial biome globally. Climate change is expected to induce large changes in vegetation of high latitude ecosystems, but there is considerable uncertainty about where, when, and how those changes will occur. Such vegetation change produces major feedback to the climate system, including by modifying albedo (reflectivity). Our study used the LANDIS-II forest landscape model to project forest dynamics on four representative landscapes (1 M ha) for 280 years into the future under a range of climate scenarios across a broad latitudinal gradient in Siberia. The model estimated the albedo of the vegetation and any snow on each landscape grid-cell through time to quantify surface albedo change in response to climate change and disturbances. We found that the shortening of the snow-covered season (winter) decreased annual average albedo dramatically, and climate change facilitated the invasion of tundra by boreal trees in the northernmost landscape (reducing albedo in all seasons). However, in other landscapes, albedo increased in summer due to disturbances (fire, wind, insects, harvest), eliminating or reducing leaf area in the short-term, and in the mid-term by promoting more reflective forest types (deciduous, light conifers). This increased albedo was somewhat ephemeral and under climate change was overwhelmed by the shortening of the snow-covered season that greatly reduced albedo. We conclude that the primary driver of the overall reflectivity of boreal ecosystems is not vegetation, but rather, the length of the snow-covered season. Because climate change is likely to dramatically shorten the snow season, the concurrent reduction of albedo has the potential to act as a powerful positive feedback for climate change. Managing natural and anthropogenic disturbances may be the only tool with potential to mitigate the reduction of albedo by climate change in boreal ecosystems because management to encourage more reflective forest types has relatively small effect.

Climate-smart forestry: an AI-enabled sustainable forest management solution for climate change adaptation and mitigation

AbstractClimate change is the most severe ecological challenge faced by the world today. Forests, the dominant component of terrestrial ecosystems, play a critical role in mitigating climate change due to their powerful carbon sequestration capabilities. Meanwhile, climate change has also become a major factor affecting the sustainable management of forest ecosystems. Climate-Smart Forestry (CSF) is an emerging concept in sustainable forest management. By utilizing advanced technologies, such as information technology and artificial intelligence, CSF aims to develop innovative and proactive forest management methods and decision-making systems to address the challenges of climate change. CSF aims to enhance forest ecosystem resilience (i.e., maintain a condition where, even when the state of the ecosystem changes, the ecosystem functions do not deteriorate) through climate change adaptation, improve the mitigation capabilities of forest ecosystems to climate change, maintain high, stable, and sustainable forest productivity and ecosystem services, and ultimately achieve harmonious development between humans and nature. This concept paper: (1) discusses the emergence and development of CSF, which integrates Ecological Forestry, Carbon Forestry, and Smart Forestry, and proposes the concept of CSF; (2) analyzes the goals of CSF in improving forest ecosystem stability, enhancing forest ecosystem carbon sequestration capacity, and advocating the application and development of new technologies in CSF, including artificial intelligence, robotics, Light Detection and Ranging, and forest digital twin; (3) presents the latest practices of CSF based on prior research on forest structure and function using new generation information technologies at Qingyuan Forest, China. From these practices and reflections, we suggested the development direction of CSF, including the key research topics and technological advancement.

A multi-scale integrative approach to study the impact of a common pesticide, the dimethoate, on a mangrove fiddler crab Tubuca urvillei.

At land-sea interface, mangroves are likely to be exposed to pesticides due to agricultural run-offs. In Mayotte Island (Comoros archipelago, Mozambique Channel), dimethoate (DMT) is found in high concentrations in tomatoes, but no data confirm its presence in mangroves. We aimed at screening the presence of DMT in three mangroves of Mayotte at different levels (highest point above crops, village, upstream mangrove, downstream mangrove) and assessing the impact of DMT coupled with reduced salinity on mangrove crab physiology. To do so, we performed 24-h exposures at sublethal concentrations (10 and 100µg L-1) corresponding to 100 × and 1000 × the environmental standard (no data exist on environmental concentrations), in seawater (SW) and diluted SW (dSW). We exposed male fiddler crab Tubuca urvillei, one of the most common fiddler crabs living in mangrove areas regularly flooded and exposed to agricultural run-offs. Different physiological endpoints were considered: behaviour, acetylcholinesterase (AChE) activity, muscle energy metabolism, DNA oxidative damage and osmoregulatory capacity using hemolymph samples, posterior gills and claw muscle. We confirmed the presence of DMT in one mangrove and the effect of pesticide exposure at the different endpoints. Changes in behavioural and physiological parameters highlighted in this study could warn us of recent pesticide use upstream and help us understand past or future community-level changes in mangrove ecosystems affected by pesticide inputs.

Study the Dynamics of the Transformation Processes for Nitrogen and Phosphorus Compounds in the Ecosystem of the Vistula Lagoon of the Baltic Sea using the Methods of Mathematical Modeling

By using mathematical modeling methods, a systematic study of the interaction of hydrobiological, hydrochemical, hydrological and hydrophysical processes that occur in the ecosystem of the Vistula Lagoon (VL) of the Baltic Sea was carried out, taking into account the processes in the active layer of bottom sediments (BS). The features of the dynamics of nitrogen and phosphorus compounds, the turnover time and the components of the balance of compounds of biogenic elements in the VL ecosystem, as well as the degree of their temporal variability have been analyzed. It is shown that the variability of nitrogen and phosphorus compounds in the aquatic environment increases in spring and autumn periods. This is due to an increase in river flow into the lagoon and an increase in the level of external biogenic load on the water area of the VL. Model calculations of matter fluxes allow us to state that the inputs of dissolved organic and suspended matter into the lagoon from external sources and the removal to the Baltic Sea are important processes that significantly affect their content in the VL ecosystem. It has been established that under strong winds the process of sedimentation of suspensions can be largely blocked, and the intensity of BS resuspension can increase significantly. An analysis of the main qualitative and quantitative features of the nature of the temporal dynamics of the DON and DOP turnover times, as well as the mineral compounds of nitrogen and phosphorus, indicates a close conjugation of the processes of transformation of dissolved organic and inorganic substances in the water of the VL. A quantitative assessment of the processes of consumption and excretion of compounds of biogenic elements by different groups of aquatic organisms has been performed, and the important role of heterotrophic bacterioplankton and protozoa in the processes of transformation of compounds of nutrients in the VL ecosystem has been shown. The model can be used to perform scenario modeling and analysis of possible changes in the VL ecosystem under changing climatic and anthropogenic conditions.

The Functional Response of Estuarine Fish Communities to Hydrologic Change in a Semi-Arid Ecosystem

Functional assessment approaches were used to identify the responses of fish to environmental change in the San Antonio Bay System (Texas, USA). Using a 26-year coastal fisheries dataset (1993–2018), multivariate analyses revealed relationships between functional group abundance and freshwater inflows in the upper segments (Hynes Bay and Guadalupe Bay), but the patterns were decoupled from inflows in the lower bay segments (San Antonio Bay, Ayres Bay and Espiritu Santo Bay). In Hynes and Guadalupe Bays, freshwater migrant carnivores accounted for a significant fraction of the community irrespective of the gear, year or flow. Freshwater stragglers (omnivores and carnivores) were often present in the upper reaches of the bay. In the lower reaches, marine migrant omnivores were present during high and low flows in Espiritu Santos Bay, but only during low flows in Ayres Bay. Marine migrant carnivores were more important in gill nets irrespective of the flow conditions. The five most abundant fish were estuarine resident carnivores and omnivores, accounting for 53.5% of the community. Declines in the abundance of functional groups occurred during the 2011–2014 drought, with rebounds in 2015–2018. Functional methodologies provide insights into estuarine ecosystems and can serve as management tools to assess changes in fish assemblages.

Monitoring bay-scale ecosystem changes in bivalve aquaculture embayments using flow cytometry.

Bay-scale empirical evaluations of how bivalve aquaculture alters plankton composition, and subsequently ecological functioning and higher trophic levels, are lacking. Temporal, inter- and within-bay variation in hydrodynamic, environmental, and aquaculture pressure complicate plankton monitoring design to detect bay-scale changes and inform aquaculture ecosystem interactions. Here, we used flow cytometry to investigate spatio-temporal variations in bacteria and phytoplankton (< 20 μm) composition in four bivalve aquaculture embayments. We observed higher abundances of bacteria and phytoplankton in shallow embayments that experienced greater freshwater and nutrient inputs. Depleted nutrient conditions may have led to the dominance of picophytoplankton cells, which showed strong within-bay variation as a function of riverine vs marine influence and nutrient availability. Although environmental forcings appeared to be a strong driver of spatio-temporal trends, results showed that bivalve aquaculture may reduce near-lease phytoplankton abundance and favor bacterial growth. We discuss confounding environmental factors that must be accounted for when interpreting aquaculture effects such as grazing, benthic-pelagic coupling processes, and microbial biogeochemical cycling. Conclusions provide guidance on sampling considerations using flow cytometry in aquaculture sites based on embayment geomorphology and hydrodynamics.

Combining APCS-MLR model to evaluate the distribution and sources of rare earth elements in a large catchment

Rare earth elements (REEs), functioning as indicators for environmental tracking, revealing the impacts of human activities on changes in aquatic ecosystems. However, systematic research on the geochemical characteristics of REEs in large river basins remains relatively scarce. Therefore, this research investigates the geochemical properties of REEs within the Yangtze River basin, analyzing the quantity and spatial distribution of REEs in surface aquatic environments across the upstream, midstream, and downstream segments of the Yangtze River, and quantitatively assessing their sources. Results indicate that the REE concentration in the upstream and downstream areas are significantly higher than in the midstream, with average concentrations of 0.69 μg/L, 0.56 μg/L, and 0.39 μg/L, respectively. REEs in the Yangtze River basin are enriched in light rare earth elements (LREEs), exhibiting a slight negative cerium (Ce) anomaly and a pronounced positive europium (Eu) anomaly. The Ce anomaly correlates with pH levels, and the Eu anomaly is largely attributed to the selective chemical decomposition and solubilization of feldspar minerals. Correlation analysis indicates that REE sources are related to manganese (Mn). Utilizing the Absolute Principal Component Scores-Multiple Linear Regression (APCS-MLR) model, the principal sources of REEs are further determined to be mineral sources (36.80%), industrial sources (45.61%), and mixed sources (17.59%). Further analysis suggests that mining and dissolution of Mn-bearing feldspar minerals, along with the discharge of industrial wastewater, considerably influence REE concentrations in the basin. This study reveals the anthropogenic and natural factors influencing the distribution of REEs in the Yangtze River basin, laying a foundational framework for investigating how human activities affect the dispersion of REEs in aquatic environments.

Ecosystem transition due to deer overabundance: Insights from long‐term studies and future considerations

AbstractThe overabundance of certain deer species is emerging as a critical issue in many forested regions across the Northern Hemisphere, including those in Japan. In the field of deer impact studies, the prevailing notion has been that overabundant deer populations could cause drastic changes of ecosystem states. This study comprises a review of the historical discussion surrounding ecosystem changes caused by deer overabundance, from theoretical frameworks to in situ observations and experiments. The synthesis highlights the potential for state transitions, shifting ecosystems from forest to nonforest states, and in some scenarios to a so‐called alternative stable states. However, detecting these transitions poses challenges due to the enduring impacts of past deer activity and the nonequilibrium nature of forest dynamics. Furthermore, this study reveals additional multifield complexities arising from the interactive effects of deer overabundance and global changes on future forest dynamics. To address these challenges, new avenues for research are proposed, emphasizing the importance of sustained efforts in conducting valuable long‐term studies.

Climate‐driven shifts in plant–soil feedback of a perennial grass species

Abstract Plant–soil feedback (PSF) plays a key role in determining the composition of plant communities, and understanding the impact of the ongoing climate change on PSF is thus crucial for predicting the consequences of climate change for ecosystems. Here, we conducted a growth‐chamber experiment to examine possible climate‐driven shifts in PSF of a perennial grass, Festuca rubra, originating from two climatically distinct sites, by using all factorial combinations of soil biota origin, plant origin, and cultivation climate. Soil biota generated more negative PSF effects when grown under the climatic conditions of their origin. This observation suggests that soil biota, especially soil pathogens, are well adapted to their local climate, exhibiting greater efficiency in suppressing plant growth within their climatic conditions. All plants, regardless of their origin, exhibited less negative PSF (expressed as relative performance in live vs. sterilized soil) when grown under warmer climate than under colder climate, likely due to positive effects of increased activity of soil decomposers and enhanced nutrient cycling. Plants showed negative PSF when grown with local soil biota under home climate, and the negative PSF disappeared when plants were grown with foreign biota or in away climates. This suggests that any disruption of the established plant‐soil‐climate interactions may lead to the release of plants from negative PSF, potentially destabilizing plant communities. Synthesis. Our results highlight the adaptions of soil biota to their native climate as key drivers of plant–soil feedback interactions and suggest that climate change could significantly alter these interactions, potentially leading to new plant community dynamics. These findings emphasize the need for further investigations to unravel the mechanisms driving these responses and evaluate their consequences for ecosystem resilience in the face of climate change.

Towards Better Comprehension of Breaking Changes in the NPM Ecosystem

Code evolution is prevalent in software ecosystems, which can provide many benefits, such as new features, bug fixes, security patches, etc., while still introducing breaking changes that make downstream projects fail to work. Breaking changes cause a lot of effort to both downstream and upstream developers: downstream developers need to adapt to breaking changes and upstream developers are responsible for identifying and documenting them. In the NPM ecosystem, characterized by frequent code changes and a high tolerance for making breaking changes, the effort is larger. For better comprehension of breaking changes in the NPM ecosystem and to enhance breaking change detection tools, we conduct a large-scale empirical study to investigate breaking changes in the NPM ecosystem. We construct a dataset of explicitly documented breaking changes from 381 popular NPM projects. We find that 95.4% of the detected breaking changes can be covered by developers’ documentation, and 19% of the breaking changes cannot be detected by regression testing. Then in the process of investigating source code of our collected breaking changes, we yield a taxonomy of JavaScript and TypeScript-specific syntactic breaking changes and a taxonomy of major types of behavioral breaking changes. Additionally, we investigate the reasons why developers make breaking changes in NPM and find three major reasons, i.e., to reduce code redundancy, to improve identifier names, and to improve API design, and each category contains several sub-items. We provide actionable implications for future research, e.g., automatic naming and renaming techniques should be applied in JavaScript projects to improve identifier names, future research can try to detect more types of behavioral breaking changes. By presenting the implications, we also discuss the weakness of automatic renaming and breaking change detection approaches, such as the lack of support for public identifiers and various types of breaking changes.

Linking Vegetation Phenology to Net Ecosystem Productivity: Climate Change Impacts in the Northern Hemisphere Using Satellite Data

With global climate change, linking vegetation phenology with net ecosystem productivity (NEP) is crucial for assessing vegetation carbon storage capacity and predicting terrestrial ecosystem changes. However, there have been few studies investigating the relationship between vegetation phenology and NEP in the middle and high latitudes of the Northern Hemisphere. This study comprehensively analyzed vegetation phenological changes and their climate drivers using satellite data. It also investigated the spatial distribution and climate drivers of NEP and further analyzed the sensitivity of NEP to vegetation phenology. The results indicated that the average land surface phenology (LSP) was dominated by a monotonic trend in the study area. LSP derived from different satellite products and retrieval methods exhibited relatively consistent responses to climate. The average SOS and POS for different retrieval methods showed a higher negative correlation with nighttime temperatures compared to daytime temperatures. The average EOS exhibited a higher negative correlation with daytime temperatures than a positive correlation. The correlations between VPD and the average SOS, POS, and EOS showed that the proportion of negative correlations was higher than that of positive correlations. The average annual NEP ranged from 0 to 1000 gC·m−2. The cumulative trends of NEP were mainly monotonically increasing, accounting for 61.04%, followed by monotonically decreasing trends, which accounted for 17.95%. In high-latitude regions, the proportion of positive correlation between VPD and NEP was predominant, while the proportion of negative correlation was predominant in middle-latitude regions. The positive and negative correlations between soil moisture and NEP (48.08% vs. 51.92%) were basically consistent in the study area. The correlation between SOS and POS with NEP was predominantly negative. The correlation between EOS and NEP was overall characterized by a greater proportion of negative correlations than positive correlations. The correlation between LOS and NEP exhibited a positive relationship in most areas. The sensitivity of NEP to vegetation phenological parameters (SOS, POS, and EOS) was negative, while the sensitivity of NEP to LOS was positive (0.75 gC·m−2/d for EVI vs. 0.63 gC·m−2/d for LAI vs. 0.30 gC·m−2/d for SIF). This study provides new insights and a theoretical basis for exploring the relationship between vegetation phenology and NEP under global climate change.

Vegetation restoration strategies in arid or semi-arid regions-From the perspective of optimal control.

Inappropriate human activities contribute to the degradation of ecosystems in arid or semi-arid regions. Therefore, emphasizing the importance of strategies for restoring vegetation in these areas cannot be overstated. However, there has been insufficient research on how to develop effective restoration strategies at minimal cost. This paper addresses this gap by studying how optimizing the spatiotemporal distribution of human activities through local and boundary controls can reduce the level of desertification in vegetation pattern structures, thereby facilitating the recovery of arid land vegetation. The results indicate that vegetation restoration depends on the proportion and number of human activity areas, with a trade-off between them. Furthermore, consistent conclusions were obtained on circular regions, demonstrating the robustness of the approach to boundary shapes. This paper aims to offer new insights into the restoration of arid land vegetation and the prevention of catastrophic ecosystem changes from the perspective of optimal control.

Impact of Three Gorges Dam construction on spatiotemporal variations in the hydrodynamic regime of Poyang Lake (China)

As an important large-scale river-connected lake in the middle–lower reaches of the Yangtze River, Poyang Lake has complex interactions with the main stream of the river. The full operation of the Three Gorges Dam (TGD) on the main stream of the Yangtze River has caused substantial changes in the relationship between the river and the lake, and the hydrological and hydrodynamic regime of Poyang Lake have also shown obvious variations in response. This study constructed a 2D hydrodynamic model of Poyang Lake based on GPU acceleration to realize a long-term simulation of the water flow evolution of Poyang Lake. By comparing the differences in water level at Hukou station between 20-year periods before and after TGD construction, the impact of TGD construction on Poyang Lake was characterized. Results showed that in comparison with the values for the pre-dam period, the water level of Poyang Lake decreased by 0.4–2.0 m and the flow velocity increased by 0.01–0.04 m/s in the post-dam period, and both showed a trend of reduction spatially from the north toward the south. Additionally, the inundation area of the lake decreased by 9 %, the 10-m characteristic water level at Xingzi station advanced by 27 days, the duration of low water extended by 37 days, and in typical dry, normal, and wet years, the time of occurrence of low water advanced. Moreover, TGD construction has aggravated the conditions of Poyang Lake in the dry season. The findings of this study are of great importance in relation to refining the spatiotemporal distribution characteristics of habitats, and supporting further investigation of the changes in the aquatic ecosystem of Poyang Lake under TGD regulation.

Variation of carbon and nitrogen stable isotope composition in leaves and roots of Littorella uniflora (L.) Asch. in relation to water pH and nutrient availability

In a phytotron experiment, the effects of pH variation and eutrophication on isoetids plants from soft-water lakes specifically the submerged form of Littorella uniflora (L.) Asch. was investigated by analyzing stable carbon and nitrogen isotopes (δ13C and δ15N). Conducted in late October 2020, 200 specimens from Lake Zawiad, near Gdansk, Poland, were examined over 75 days. The study tested three pH levels (∼4.5, ∼7.0, and ∼8.5) and a detailed 12-step nutrient gradient (nitrogen: 0–10 mg/l; phosphorus: 0–0.3 mg/l). The analysis focused on isotopic composition in leaves and roots, revealing that acidic conditions favored higher δ13C values (leaves: −22.67 ‰; roots: −23.23 ‰), suggesting a preference for lighter carbon forms in photosynthesis and intensive use of limited sources of CO2. The neutral pH variant showed the lowest δ13C values (leaves: −25.53 ‰; roots: −25.47 ‰), indicating less optimal conditions. δ15N values exhibited minimal fluctuation across pH levels, with slight variations in acidic and alkaline environments compared to neutral conditions. An observed decrease in δ13C across all pH levels with increased nutrients, alongside a rise in δ15N values, indicates a complex interaction between isotopic composition and environmental factors. Our findings suggest that L. uniflora shows a distinct isotopic response to varying pH levels, with higher δ13C values under acidic conditions potentially indicating enhanced CO2 uptake through a specialized carbon assimilation strategy. This highlights the species' adaptive mechanisms to environmental stressors, suggesting that the isotopic composition of aquatic vegetation can serve as a sensitive indicator of changes in lake ecosystems.

Impact of extreme rainfall and flood events on harmful cyanobacterial communities and ecological safety in the Baiyangdian Lake Basin, China

Globally, climate change has intensified extreme rainfall events, leading to substantial hydrological changes in aquatic ecosystems. These changes, in turn, have increased the frequency of harmful algal blooms, particularly those of cyanobacteria. This study examines cyanobacterial community dynamics in the Baiyangdian Lake Basin, China, after heavy rainfall and flooding events. The aim was to clarify how such extreme hydrological events affect cyanobacterial populations in floodplain ecosystems and assess related ecological risks. The results demonstrated a significant increase in cyanobacterial diversity, exemplified by an increase of the Shannon diversity index from an average of 1.7 to 2.1 (p < 0.05). Following heavy rainfall and subsequent flooding, the average relative abundance of cyanobacteria in the microbial community increased from 7.59 % to 9.62 %, along a notable rise in the abundance of harmful cyanobacteria. The community structure exhibited notable differences after flooding, showing an increase in species richness, but a decrease in community tightness and clustering, as well as a reduction in niche overlap among harmful cyanobacteria. Environmental factors such as dissolved oxygen, water temperature, and pH were identified as crucial predictors of harmful cyanobacterial community differences and abundance variations resulting from flooding. These findings provide a critical framework for predicting ecological risks associated with the expansion of bloom-forming cyanobacteria in large shallow lake basins, particularly under intensified rainfall and flooding events. This insight is essential to anticipate potential ecological disruptions in sensitive aquatic ecosystems.

Temporal Study of Environmental DNA and Acoustic Data Reveals Coexistence of Sympatric Bat Species in a North American Ecosystem

ABSTRACTBats are a species‐rich mammalian order that provide a host of ecosystem services, but presently face threats from habitat loss, disease, climate change, and insect declines. Bat species often co‐occur with other ecologically similar bats, making them a suitable group in which to study niche overlap and partitioning. This study aimed to compare different non‐invasive sources of data on wildlife populations, while examining dietary, temporal, and spatial partitioning patterns among sympatric bat species. We used two different methods to assess niche partitioning among insectivorous bats at a site in the San Francisco Bay Area, California: (1) eDNA sequencing of bat feces that were collected weekly from a bat roost, and (2) nightly acoustic recordings of ultrasonic bat calls from recorders at multiple sites. Both the eDNA and acoustic data were collected over the course of an entire roosting season in 2020. We hypothesized that the insectivorous bats at this site would rely on one or more niche partitioning mechanisms to promote interspecific coexistence and limit competition. We found evidence of fine‐scale spatial partitioning of the broad community of bat species in our study area based on acoustic data, as well as temporal differences in activity of different species. The two species using the roosting site, Tadarida brasiliensis and Eptesicus fuscus, displayed some differences in the identities and relative abundances of prey species consumed, but both ultimately exhibited a strong reliance on dipterans and aquatic‐dependent insects. We demonstrate differences between the acoustic data and eDNA data, which has implications for how such datasets may be interpreted in future research. The study finds evidence of some types of niche partitioning in this community and characterizes baseline interactions between species, providing a foundation for future efforts to non‐invasively monitor for unexpected biological change in local ecosystems.

Future directions for deep ocean climate science and evidence-based decision making

IntroductionA defining aspect of the Intergovernmental Panel on Climate Change (IPCC) assessment reports (AR) is a formal uncertainty language framework that emphasizes higher certainty issues across the reports, especially in the executive summaries and short summaries for policymakers. As a result, potentially significant risks involving understudied components of the climate system are shielded from view.MethodsHere we seek to address this in the latest, sixth assessment report (AR6) for one such component—the deep ocean—by summarizing major uncertainties (based on discussions of low confidence issues or gaps) regarding its role in our changing climate system. The goal is to identify key research priorities to improve IPCC confidence levels in deep ocean systems and facilitate the dissemination of IPCC results regarding potentially high impact deep ocean processes to decision-makers. This will accelerate improvement of global climate projections and aid in informing efforts to mitigate climate change impacts. An analysis of 3,000 pages across the six selected AR6 reports revealed 219 major science gaps related to the deep ocean. These were categorized by climate stressor and nature of impacts.ResultsHalf of these are biological science gaps, primarily surrounding our understanding of changes in ocean ecosystems, fisheries, and primary productivity. The remaining science gaps are related to uncertainties in the physical (32%) and biogeochemical (15%) ocean states and processes. Model deficiencies are the leading cited cause of low certainty in the physical ocean and ice states, whereas causes of biological uncertainties are most often attributed to limited studies and observations or conflicting results.DiscussionKey areas for coordinated effort within the deep ocean observing and modeling community have emerged, which will improve confidence in the deep ocean state and its ongoing changes for the next assessment report. This list of key “known unknowns” includes meridional overturning circulation, ocean deoxygenation and acidification, primary production, food supply and the ocean carbon cycle, climate change impacts on ocean ecosystems and fisheries, and ocean-based climate interventions. From these findings, we offer recommendations for AR7 to avoid omitting low confidence-high risk changes in the climate system.

Mathematical models for sustainable fisheries management in U.S. waters: Balancing economic growth and conservation

Sustainable fisheries management is critical for balancing the dual objectives of economic growth and environmental conservation, particularly in U.S. waters where overfishing, habitat degradation, and fluctuating marine ecosystems pose significant challenges. This review explores the role of mathematical models in addressing these challenges and guiding fisheries management decisions. Various models, including population dynamics, bioeconomic, and ecosystem-based approaches, are examined for their utility in setting sustainable catch limits, assessing stock health, and predicting ecosystem changes. Through case studies of U.S. fisheries, the paper highlights how these models have been implemented within the framework of federal regulations, such as the Magnuson-Stevens Act, to achieve sustainable yields while supporting economic growth. The review also identifies trade-offs between short-term economic gains and long-term conservation goals, emphasizing the need for adaptive management strategies. Finally, it explores emerging innovations in mathematical modeling techniques, such as artificial intelligence, and provides policy recommendations to enhance the integration of these models into sustainable fisheries management. This paper underscores the importance of mathematical models as essential tools in ensuring the future viability of U.S. fisheries, balancing economic prosperity with the preservation of marine ecosystems.

Effects and Consequences of Climate Change on the Natural Conditions of Mirzachol District

This article examines the effects and consequences of climate change on the natural conditions of Mirzachol district. Through an in-depth analysis of climate data, ecological studies and socio-economic impacts, the study highlights significant changes in temperature, precipitation and extreme weather events in recent decades. These changes have led to changes in local ecosystems, agricultural productivity, and water resources, challenging the county’s predominantly agricultural economy. The paper also discusses existing adaptation strategies and mitigation efforts and recommends additional measures to increase resilience to future climate change.