Understanding Of Climate Change Research Articles

Modeling Environmental Vulnerability for 2050 Considering Different Scenarios in the Doce River Basin, Brazil

Understanding climate change and land use impacts is crucial for mitigating environmental degradation. This study assesses the environmental vulnerability of the Doce River Basin for 2050, considering future climate change and land use and land cover (LULC) scenarios. Factors including slope, elevation, relief dissection, precipitation, temperature, pedology, geology, urban distance, road distance, and LULC were evaluated using multicriteria analysis. Regional climate models Eta-HadGEM2-ES and Eta-MIROC5 under RCP 4.5 and RCP 8.5 emission scenarios were employed. The Land Change Modeler tool simulated 2050 LULC changes and hypothetical reforestation of legal reserve (RL) areas. Combining two climate and two LULC scenarios resulted in four future vulnerability scenarios. Projections indicate an over 300 mm reduction in average annual precipitation and an up to 2 °C temperature increase from 2020 to 2050. Scenario 4 (RCP 8.5 and LULC for 2050 with reforested RLs) showed the greatest basin area in the lowest vulnerability classes, while scenario 3 (RCP 4.5 and LULC for 2050) exhibited more high-vulnerability areas. Despite the projected relative improvement in environmental vulnerability by 2050 due to reduced rainfall, the complexity of associated relationships must be considered. These results contribute to mitigating environmental damage and adapting to future climatic conditions in the Doce River Basin.

Exploring the Seasonal Comparison of Land Surface Temperature Dominant Factors in the Tibetan Plateau

Abstract. LST (Land Surface Temperature) is a significant parameter that represents the ground energy balance and plays a crucial role in understanding climate change. The LST of the Tibetan Plateau (TP) has a direct influence on the climate and environmental changes of the TP, and it also has a significant impact on global climate and atmospheric circulation. Although there are various factors that drive the spatial and temporal distribution of LST on the TP, the primary driving forces and its seasonal variations of LST are not yet well understood. The research focuses specifically on the TP region, selecting three types of LST data, using geodetector model, to analyze the driving factors affecting the spatial pattern of LST in different seasons. The results indicate that the three factors, Air Temperature (AT), Elevation (Ele), and Permafrost Thermal Stability (PTS), have a significant influence on LST throughout all seasons, whereas other variables demonstrate varying contributions to LST depending on the season. This study contributes to the understanding of the spatial variability of surface thermal conditions and the intricate relationships between their driving factors. It also emphasizes the potential changes in these relationships throughout the year.

Predicting suitable habitat for the endangered tree Ormosia microphylla in China

Climate change has significantly influenced the growth and distribution of plant species, particularly those with a narrow ecological niche. Understanding climate change impacts on the distribution and spatial pattern of endangered species can improve conservation strategies. The MaxEnt model is widely applied to predict species distribution and environmental tolerance based on occurrence data. This study investigated the suitable habitats of the endangered Ormosia microphylla in China and evaluated the importance of bioclimatic factors in shaping its distribution. Occurrence data and environmental variables were gleaned to construct the MaxEnt model, and the resulting suitable habitat maps were evaluated for accuracy. The results showed that the MaxEnt model had an excellent simulation quality (AUC = 0.962). The major environmental factors predicting the current distribution of O. microphylla were the mean diurnal range (bio2) and precipitation of the driest month (bio14). The current core potential distribution areas were concentrated in Guangxi, Fujian, Guizhou, Guangdong, and Hunan provinces in south China, demonstrating significant differences in their distribution areas. Our findings contribute to developing effective conservation and management measures for O. microphylla, addressing the critical need for reliable prediction of unfavorable impacts on the potential suitable habitats of the endangered species.

Climate change education: exploring knowledge, attitudes, and practices of medical students in a Turkish medical school

ABSTRACT Climate change presents a significant health challenge, emphasizing the need for resilient healthcare systems. This study aimed to explore medical students’ knowledge, attitudes, and practices regarding the climate-health link and their curriculum preferences. Conducted from March to June 2023 at the Medical School of Bahçeşehir University, Turkiye, the cross-sectional study utilized an online questionnaire covering demographic data and climate change-related inquiries. Participation was open to all medical students without class-based distinctions. The response rate was 53.6%, with 439 medical students included (average age: 21.8 years). The majority (74.5%) acknowledged human-induced climate change, with over 87% expressing concerns about its impact on health. Nearly 70% emphasized the importance of physicians understanding climate change’s health effects, while 45.8% perceived a lack of information in their medical education. Most students (70.0%) supported integrating climate change’s health effects into medical education, rating its importance at 7.1 on a scale of 0 to 10. Preferences included electives, team-based learning, case-based learning, problem-based learning, clinical practice in climate-sensitive diseases, and theoretical courses on climate change in basic medical sciences. This study underscores the growing awareness among medical students regarding climate change’s health impact and the need for climate-integrated medical education, emphasizing its importance in preparing future physicians for climate-related health challenges and resilient healthcare systems.

Unifying the Nepal height system and China height system based on gravity frequency shift approach

Highly accurate international height reference frames with long-term stability, global consistency, and homogeneity are crucial for monitoring sea level variations, understanding climate change, managing disasters, and supporting other applications that benefit scientific research and societal well-being. Currently, there are over 100 local height reference systems worldwide. Unifying these systems is a pivotal step toward constructing international height reference frames. The method introduced in this study—the gravity frequency shift via Satellite Frequency Signal Transfer (SFST)—represents a groundbreaking relativistic geodetic approach, demonstrating its potential to surpass the constraints of conventional techniques. The advent of high-precision optical atomic clocks (OAC) with an accuracy level of has facilitated this method's implementation. The International Association of Geodesy (IAG) has established the International Height Reference System (IHRS) and its practical realization, the International Height Reference Frame (IHRF). Our study focuses on two neighbouring height systems: the China Height System (CHS) and the Nepal Height System (NHS), separated by the Himalayas and the Tibetan plateau. We aim to unify these two systems by determining the geopotential and orthometric height differences between their respective height datum stations: the Qingdao Height Datum Station (QHDS) and the Madar Height Datum Station (MHDS) using a simulation experiment with the method mentioned above. Using an OAC with an accuracy of , we identified a geopotential difference of and an orthometric height difference of m between QHDS and MHDS. These results suggest that the introduced method could unify any two height systems with few-centimeter-level precision, emphasizing its significance in contributing to the construction of the IHRS/IHRF with today's required precision. In summary, the SFST technique is a novel geodetic method that offers an alternative for height system unification, delivering centimeter-level precision, surpassing traditional methods, and supporting the development of the IHRF.

Becoming octopus: Indigenous ways of knowing and green leadership

On 30 June 2014 we (a small group of academic women) opened our first Green Leadership School, an experiment in decolonising the classroom, exploring indigenous environmental knowledge, and creating a space of healing and love. This paper documents the process of healing and rejuvenating the lives of activists, government officials, trade unionists, and university students. Similar to the concept of Deleuze and Guattari’s (2004) “becoming animal” and “becoming wolf”, we represented the school as “becoming octopus” – a creature with green blood (becoming green), the highest brain-to-body ratio of any invertebrate, many slithering arms to twist and escape oppression and slide away from toxic spaces, and three hearts for the three-hearted practices of love, bodily integration, and mind-spirit awareness. Therefore, the pedagogical experiment focused on transmutation – connecting with the environment through merging human with animal, ritual and magic, gardening, yoga, storytelling, music, and art alongside more conventional lectures such as understanding climate change through South African vernaculars, ‘land grabs’ in Africa, pollution in South Durban, and environmental communication. Damaged by apartheid and post-apartheid wounds and worldwide ruptures in the socius – the participants experienced psychic healing. This paper discusses the role of joyful pedagogies in decolonising education.

Championing a move from sustainability to Planetary Health in nursing curriculum

In this paper, we review the progress on developing sustainability-related content in the Bachelor of Nursing curriculum in Aotearoa New Zealand and engage with Planetary Health. Sustainability in nurse education is explored and the concept of sustainability-practising graduates is promoted. The issueWe have seen ambivalence towards sustainability persisting amongst nurse educators and students, and sustainability-related content discarded. Despite this, we continue to recognise that sustainability is closely related to climate change which is the greatest threat to planetary, human, and animal health and as such is an essential component of nurse education and practice. Never has there been a timelier reminder of nurses' responsibility to recognise we are ideally placed to contribute to, and help lead, the health response to climate change and champion sustainability. A systems-thinking approachThis response includes a systems-thinking approach to understanding climate change and the impact on health, nursing's responsibility to address climate change, promote health, and respond to health needs. As we revise our current Bachelor of Nursing curriculum, it is timely to review how our sustainability content and thinking has progressed since our previous review in 2017. We are mindful of the need to continue championing this topic, ensuring it is situated at the forefront of nurse education. We propose that a gradual and purposeful shift towards a Planetary Health focus will help to counter the sustainability fatigue and ambivalence we have noted amongst our colleagues and students, ensuring our revised Bachelor of Nursing curriculum is future proofed.

Effects of Climate Change-Induced Flooding on Onsite Sanitation Services: A Case Study of Kanyama, Compound in Lusaka, Zambia

The study underscores the absence of a comprehensive assessment of flooding effects on onsite sanitation systems in Kanyama, exacerbating existing issues like inadequate facilities, poor maintenance, and improper waste management. Conducting both qualitative and quantitative methods, the research engaged 210 respondents from six wards in Kanyama, using systematic random sampling for households and purposive sampling for key informants. Employing predictive models (Root Mean Square Error and R-squared values) in SPSS Version 22, the findings revealed negative effects on onsite sanitation systems, including contamination of water, infrastructure damage, and overflowing of pit latrines/septic tanks. Key statistics include 68% of respondents witnessing temperature changes, 63% understanding climate change, and 73% acknowledging changes in rainfall patterns. For flooding, 72% observed increased floods, with a statistical analysis yielding R-squared values of 0.431, 0.427, and 0.373 for water contamination, infrastructure damage, and overflowing of pit latrines/septic tanks, respectively. These values represent the percentage of variation explained by flood-related variables. Chi-squared statistics values of 234.16, 214.564, and 152.132 highlight a significant effect of flood-related variables on observed outcomes. Qualitative data identified themes such as awareness of climate change effects, diverse beliefs, varying community awareness, and the need for tailored education. The study proposed a Sustainability model, emphasizing drainage systems, awareness campaigns, infrastructure development, waste management, and partnerships to enhance community resilience against climate change-induced flooding

Arctic as the ‘radiator fins’ of Earth in a warming climate

Earth radiates thermal radiation to balance the solar radiation it receives. Central to understanding climate change is how the radiation energy budget adjusts both globally and locally to external and internal forcing. In the past 18 years, satellite observations reveal a distinct positive trend of the Earth thermal radiation in the Arctic, which acts to radiate excess heating accumulating in the climate system to the space during global warming, i.e. a radiator fin region in a warming climate. Compared with other regions such as the tropics, the prominent trend in the Arctic results from a stronger surface and atmospheric warming and a less offsetting greenhouse effect of water vapor. Spectral decompositions further show the increase of thermal emission in the Arctic mainly originates from the far-infrared and mid-infrared window region and affirms the unbalanced radiative responses to temperature and humidity changes in these two spectral regions account for the unique thermal radiation trend in the Arctic.

Characteristics of Soil Temperature Change in Lhasa in the Face of Climate Change

Soil temperature is an important index of climate change, and the analysis of soil temperature change is of great significance for understanding climate change and ecohydrological processes. This study was based on the measured meteorological data of a meteorological station, combined with the soil temperature data of 0–10, 10–40, 40–100 and 100–200 cm from the Global Land Data Assimilation System (GLDAS-NOAH). The Mann–Kendall test, wavelet analysis, linear tendency estimation and other methods were used to analyze the variability, periodicity and trend of soil temperature in Lhasa from 2006 to 2022. The results showed that the soil temperature of different soil layers had abrupt changes in annual and seasonal time series, and all showed a warming phenomenon after abrupt changes. In terms of periodicity, the average annual soil temperature of different soil layers has similar periodic changes, and the periodic oscillation is strong around 10a, which is the main cycle of soil temperature change. The soil temperature in Lhasa showed a significant rising trend in the interannual and seasonal time series, and the average annual rising trend of soil temperature was greater than that of air temperature. The correlation between soil temperature and mean air temperature (MAT), maximum air temperature (Tmax), minimum air temperature (Tmin) and snow depth (SD) was investigated by Pearson correlation analysis. Soil temperature in spring, autumn and winter had a strong correlation with MAT, Tmax and Tmin, showing a significant positive correlation. The negative correlation between soil temperature and SD in 0–40 cm soil in spring and winter was more severe. The research results show that Lhasa has experienced a rise in air temperature and soil temperature in the past 17 years, and reveal the specific changes in soil temperature in Lhasa against the background of climate change. These findings have reference significance for understanding the impact of climate change on the natural environment.

Analysis of Probability Distributions for Modelling Extreme Rainfall Events and Detecting Climate Change: Insights from Mathematical and Statistical Methods

Exploring the realm of extreme weather events is indispensable for various engineering disciplines and plays a pivotal role in understanding climate change phenomena. In this study, we examine the ability of 10 probability distribution functions—including exponential, normal, two- and three-parameter log-normal, gamma, Gumbel, log-Gumbel, Pearson type III, log-Pearson type III, and SQRT-ET max distributions—to assess annual maximum 24 h rainfall series obtained over a long period (1972–2022) from three nearby meteorological stations. Goodness-of-fit analyses including Kolmogorov–Smirnov and chi-square tests reveal the inadequacy of exponential and normal distributions in capturing the complexity of the data sets. Subsequent frequency analysis and multi-criteria assessment enable us to discern optimal functions for various scenarios, including hydraulic engineering and sediment yield estimation. Notably, the log-Gumbel and three-parameter log-normal distributions exhibit superior performance for high return periods, while the Gumbel and three-parameter log-normal distributions excel for lower return periods. However, caution is advised regarding the overuse of log-Gumbel, due to its high sensitivity. Moreover, as our study considers the application of mathematical and statistical methods for the detection of extreme events, it also provides insights into climate change indicators, highlighting trends in the probability distribution of annual maximum 24 h rainfall. As a novelty in the field of functional analysis, the log-Gumbel distribution with a finite sample size is utilised for the assessment of extreme events, for which no previous work seems to have been conducted. These findings offer critical perspectives on extreme rainfall modelling and the impacts of climate change, enabling informed decision making for sustainable development and resilience.

Navigating the complexities of student understanding: Exploring the coherency of students' conceptions about the greenhouse effect

AbstractThe greenhouse effect is a complex scientific phenomenon that plays a crucial role in understanding climate change. Grasping students' understanding of this phenomenon on the content‐specific level but also how students' conceptions are organized is vital for effective climate change education. This study addresses both levels and delves into the relationship between students' frameworks and knowledge pieces of the greenhouse effect through the analysis of multiple‐choice questions, employing Bayesian correlations and multiple logistic regression. We thereby focus on specific types of conceptualizations of the greenhouse effect that have been identified in previous research and furthermore investigate the coherency of them. To do so, we analyzed answers of N = 604 grade 11 students in Austria and Germany and interpreted them from different theoretical perspectives. The findings showed that students hold various ideas about the greenhouse effect that are only seldom coherent, in particular when it comes to adequate ideas about the greenhouse effect. However, especially for a reflection‐based framework of the greenhouse effect, our results demonstrate that students' conceptions show some form of coherency. We argue that our results can inform the development of effective teaching strategies that address students' existing knowledge and alternative conceptions. In terms of practical implications, the findings suggest that teaching strategies should provide opportunities for students to integrate their knowledge pieces into a more coherent understanding of the greenhouse effect. The study highlights the need for further investigation into the relationship between knowledge pieces and frameworks not only for the greenhouse effect, but for science education in general.

Seasonal vertical distributions of diurnal variation of ice cloud frequency by CATS measurements over a global region (51°S-51°N)

Ice clouds can strongly affect the radiation budget through the reflection (absorption) of solar shortwave (longwave) radiation in the Earth-atmosphere system. Unlike water clouds, ice clouds present a longer lifetime in the upper troposphere. Therefore, the vertical patterns of diurnal variation of ice clouds are of very importance to understand climate change in the globe. The present paper investigates the diurnal variation of ice cloud frequency (ICF) from March 2015 to October 2017 over the global scale (51 ° S and 51 ° N) by CATS (Cloud-Aerosol Transport System) LiDAR onboard the International Space Station (ISS) and CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) LiDAR measurements. Our results suggest that: (1) ICF derived from the CATS and CALIPSO LiDAR presents the similar geographical variations. (2) The vertical distribution of ICF in land area over the North Hemisphere (NH) is found larger than in the South Hemisphere (SH) likely due to the more dust aerosols as ice nuclei to influence ice cloud formation over the NH. (3) ICF at nighttime (00:00–06:00 and 18:00–23:00) exhibits higher value than daytime (06:00–18:00), especially in high altitude (more than 12 km) ice clouds in the tropics. (4) The number of ice cloud samples is higher in spring and winter compared to summer and autumn, and the highest amount of ice cloud samples in spring(winter) occurs during nighttime(daytime) for most hours. These findings provide significant insights that may help improving the ice cloud's representation in climate models.

Characterization of pelagic communities in the Pacific sector of the Arctic Ocean using a broadband acoustic system, net samplers, and optical instruments

Rising Arctic temperatures are causing substantial declines in sea ice, altering ice retreat and formation in the Pacific Arctic and impacting marine communities. Despite the significant challenges facing the Pacific Arctic, there are still gaps in our understanding of the environmental impacts on pelagic communities, particularly sound scattering layers (SSLs), and their distributions in the southern Chukchi Sea (SCS), northern Chukchi Sea (NCS), and East Siberian Sea (ESS). This study utilized a wideband autonomous transceiver, net samplers, and optical instruments to explore SSLs in the Pacific Arctic, detailing their relationships with hydrographic properties. The findings indicated a greater vertical distribution of pelagic communities in the SCS than in the NCS and ESS. Significant differences in frequency spectra patterns were observed between the SCS and both the NCS and the ESS, though not between the NCS and the ESS. The correlations between the broadband acoustic and hydrographic values were generally weak to moderate. Elevated acoustic values in the SCS were linked to higher water temperature, dissolved oxygen, and chlorophyll and lower salinity. This study also revealed the behavioral properties of individual pelagic animals and identified Ctenophores and Copepods as the most abundant classes based on camera images and net samples. This research offers crucial insights into the distribution and interactions of pelagic communities with environmental factors, laying the groundwork for understanding climate change impacts. Additionally, this paper presents the first findings of frequency spectra from a broadband system in the Arctic Ocean.

Understanding climate changes in East Asia and Europe based on spatial climate analogs

Spatial climate analogs effectively illustrate how a location’s climate may become more similar to that of other locations from the historical period to future projections. Also, novel climates (emerging climate conditions significantly different from the past) have been analyzed as they may result in significant and unprecedented ecological and socioeconomic impacts. This study analyzes historical to future spatial climate analogs across East Asia and Europe, in the context of climatic impacts on ecology and human health, respectively. Firstly, the results of climate analogs analysis for ecological impacts indicate that major cities in East Asia and Europe have generally experienced novel climates and climate shifts originating from southern/warmer regions from the early 20th century to the current period, primarily attributed to extensive warming. In future projections, individual cities are not expected to experience additional significant climate change under a 1.5 °C global warming (warming relative to pre-industrial period), compared to the contemporary climate. In contrast, robust local climate change and climate shifts from southern/warmer regions are expected at 2.0 °C and 3.0 °C global warming levels. Specially, under the 3.0 °C global warming, unprecedented (newly emerging) climate analogs are expected to appear in a few major cities. The climate analog of future projections partially align with growing season length projections, demonstrating important implications on ecosystems. Human health-relevant climate analogs exhibit qualitatively similar results from the historical period to future projections, suggesting an increasing risk of climate-driven impacts on human health. However, distinctions emerge in the specifics of the climate analogs analysis results concerning ecology and human health, emphasizing the importance of considering appropriate climate variables corresponding to the impacts of climate change. Our results of climate analogs present extensive information of climate change signals and spatiotemporal trajectories, which provide important indicators for developing appropriate adaptaion plans as the planet warms.

Clouds and plant ecophysiology: missing links for understanding climate change impacts

Observations and models indicate that human activity is altering cloud patterns on a global scale. Clouds impact incident visible and infrared radiation during both day and night, driving daily and seasonal variability in plant temperatures—a fundamental driver of all physiological processes. To understand the impacts of changing cloud patterns on essential plant-based processes such as carbon sequestration and food production, changes in local cloud regimes must be linked, via ecophysiology, with affected plant systems. This review provides a comprehensive treatment of cloud effects (apart from precipitation) on fundamental ecophysiological processes that serve as the basis of plant growth and reproduction. The radiative effects of major cloud types (cumulus, stratus, cirrus) are differentiated, as well as their relative impacts on plant microclimate and physiology. Cloud regimes of major climate zones (tropical, subtropical, temperate, polar) are superimposed over recent changes in cloud cover and primary productivity. The most robust trends in changing global cloud patterns include: (i) the tropical rain belt (comprised mostly of deep convective clouds) is narrowing, shifting latitudinally, and strengthening, corresponding with shorter but more intense rainy seasons, increased clouds and precipitation in some parts of the tropics, and decreases in others; (ii) tropical cyclones are increasing in intensity and migrating poleward; (iii) subtropical dry zones are expanding, resulting in fewer clouds and drier conditions at these latitudes; (iv) summer mid-latitude storm tracks are weakening and migrating poleward, and clouds in temperate regions are decreasing; and (v) clouds over the Arctic are increasing. A reduction in coastal fog and low clouds (including those associated with montane cloud forests) have also been observed, although these trends can be partially attributed to local patterns of deforestation, urbanization, and/or reductions in aerosols associated with clean air initiatives. We conclude by highlighting gaps in the cloud-ecophysiology literature in order to encourage future research in this under-studied area.

Inferring Global Ocean Mass Increase From Tide Gauges Network With Climate Models

AbstractOcean mass increase contributes to global sea level rise, and plays an important role in understanding climate change. Here, we develop a data assimilation approach that enables the inference of ocean mass increase from global tide gauge network. This approach incorporates outputs from climate models and sea level fingerprints caused by water mass changes over land areas. The results suggest a trend of 2.15 ± 0.72 mm/yr for ocean mass increase over the period 1993–2022, which closes the global sea level budget with estimates of thermosteric sea level rise. Furthermore, the inferred ocean mass increase offers an insight into the causes of sea level rise since 1950. These findings emphasize the significance of climate models, in addition to simulating sea level changes, they contribute to understanding causes of sea level rise over the past decades.

THE ROLE OF GEOMATICS ENGINEERING IN CLIMATE CHANGE STUDIES

Abstract. Geomatics Engineers acquire, manage, analyse, model and present the geo-spatially referenced data quickly, accurately and reliably. They can classify the derived data with geographic information systems and produce many models according to needs. This study focuses on the role of the geomatics discipline in combatting climate change, the capability of measuring climate change parameters and the determination of the causes of the parameters change. Basic information about the latest developments in the Geomatics discipline for climate change studies is given. Geomatics Engineer's studies for understanding Earth’s system and its response to climate change and models created for the solution are explained. Geomatics Engineering provides a wide range of geospatial data and produces applications for understanding climate change. They take place in climate change analyses by measuring various climate parameters, and by processing the atmosphere, land, glaciers and waters in various spatiotemporal analyses. The obtained results have shown the significantly important role of the geomatics discipline in obtaining, monitoring and analysing the data used for climate change effects’ mitigation. In conclusion, Geomatics Engineering contributes to the decision-makers who have a duty in struggling with climate change and all stakeholders of the subject together with practitioners at all levels to create a road map for the studies to be carried out.

Fluctuations in abundance of the striped venus clam Chamelea gallina in the southern Adriatic Sea (Central Mediterranean Sea): knowledge, gaps and insights for ecosystem-based fishery management

An assessment on the fluctuations in abundance of the striped venus clam (Chamelea gallina) in the southern Adriatic Sea (Central Mediterranean Sea), and the northern Gargano area, has been conducted through both historical information and recent data from monitoring surveys during the period 1997–2019. Production trends, conditions of the commercial stock biomass, and depth distribution pattern of juveniles and commercial sizes were analysed testing temporal differences. Moreover, the exploitation of the clam beds and recruitment events were investigated in 2018–2019. Changes in abundance were analysed using non-parametric tests for both juvenile (length class, LC < 22 mm) and commercial (LC ≥ 22 mm) fractions. Hydrodynamic changes, temperature and salinity variations were explored using a 3D hydrodynamic numerical model (MIKE 3 FM-HD) and statistical analysis, as well as changes in benthic assemblages impacted by hydraulic dredges were investigated through PERMANOVA and other multivariate analysis.The results showed a temporal decline of production and biomass of C. gallina during the 1997–2019 period, and a regression of the depth limit in the clams’ distribution towards shallower waters. A significant reduction in juveniles was observed during 2018–2019 with a very limited recruitment. The fishing exploitation showed high impacts on the commercial stock and benthic assemblages in the summer of 2018. Overall, water currents were predominantly directed offshore in 2018, during the C. gallina spawning period. This could affect the larval dispersal and settlement on unsuitable bottoms. Anomalies in temperature (high peaks in August 2018, > 28 °C) and salinity (low values in spring 2018, < 37 PSU) could have induced stress and mortality events on the entire clam bed in the study area. This first study highlights the need to integrate environmental information in the assessment of commercial stocks of clams in the Adriatic Sea, to better understand climate change effects on the fluctuations and to support effective ecosystem-based fishery management.

Strategies for monitoring and evaluation of climate change adaptation: localizing global approaches into Andean realities

While there is increasing progress made at the global scale on understanding climate change (CC) impacts and implementing adaptation solutions, there is still a major gap in documenting and assessing the effectiveness of monitoring and evaluation (M&E) systems for CC adaptation. This is particularly challenging if we consider the diversity of local perceptions and interpretations of what CC adaptation concretely means and how to measure it. We evaluate how global approaches on M&E to CC adaptation are being localized in the design and implementation of public policies and territorial strategies for CC adaptation in the Andes in four national and local case studies in Colombia, Ecuador, Peru and Bolivia. The analysis is based on a review of the status of national programs for M&E of CC adaptation and the implementation in those countries of the project “Adaptation to Climate Change Impacts in Water Resources in the Andes” (AICCA). The M&E systems in the four case studies differed widely in the way in which global M&E approaches are localized, reflecting the diversity of conceptions, goals, strategies and contexts in which adaptation is being implemented as well as power relations among actors and scales. Despite the diversity of implementation contexts and the complexity of monitoring the responses of socio-ecological systems, the M&E proposals share a focus on biophysical indicators over sociopolitical and institutional indicators. In addition, this study emphasizes the need to further implement participatory M&E systems from the community, to improve the territorial articulation of M&E proposals in the Andean region.