Natural Temporal Variability Research Articles

Limits on groundwater-surface water transitions got from temperature time series: characterizing goal-based edges

ABSTRACT This study addresses the challenge of accurately estimating groundwater-surface water fluxes, essential for sustainable water resource management, by improving traditional temperature time series methods. Existing approaches often struggle with distinguishing natural temperature variations from significant water exchanges, especially across different spatial and temporal scales under varying conditions like recharge and discharge. To overcome these issues, advanced statistical tools were applied to temperature data, and COMSOL Multiphysics was used to simulate interactions by coupling fluid flow and heat transport. Multisite and multivariate calibration techniques refined parameters like hydraulic conductivity and porosity, while models accounted for external factors such as climate variability and land-use changes. The findings reveal that the combined method was effective in estimating groundwater-surface water fluxes under recharge conditions. The COMSOL model achieved an MAE of 0.71, MAP has 0.92, RMSE of 0.80, and RMSLE has 0.30, indicating consistent performance across evaluation metrics. This advancement improves groundwater-surface water model precision, especially in distinguishing natural temperature variations from significant water exchanges. It offers more accurate flux estimation, aiding better water resource management.

Warming, stochastic diel thermal fluctuations affect physiological performance and gill plasticity in an amphibious mangrove fish.

Natural temperature variation in many marine ecosystems is stochastic and unpredictable, and climate change models indicate that this thermal irregularity is likely to increase. Temperature acclimation may be more challenging when conditions are highly variable and stochastic, and there is a need for empirical physiological data in these thermal environments. Using the hermaphroditic, amphibious mangrove rivulus (Kryptolebias marmoratus), we hypothesized that compared with regular, warming diel thermal fluctuations, stochastic warm fluctuations would negatively affect physiological performance. To test this, we acclimated fish to: (1) non-stochastic and (2) stochastic thermal fluctuations with a similar thermal load (27-35°C), and (3) a stable/consistent control temperature at the low end of the cycle (27°C). We determined that fecundity was reduced in both cycles, with reproduction ceasing in stochastic thermal environments. Fish acclimated to non-stochastic thermal cycles had growth rates lower than those of control fish. Exposure to warm, fluctuating cycles did not affect emersion temperature, and only regular diel cycles modestly increased critical thermal tolerance. We predicted that warm diel cycling temperatures would increase gill surface area. Notably, fish acclimated to either thermal cycle had a reduced gill surface area and increased intralamellar cell mass when compared with control fish. This decreased gill surface area with warming contrasts with what is observed for exclusively aquatic fish and suggests a preparatory gill response for emersion in these amphibious fish. Collectively, our data reveal the importance of considering stochastic thermal variability when studying the effects of temperature on fishes.

Emergence of lake conditions that exceed natural temperature variability

Lake surface temperatures are projected to increase under climate change, which could trigger shifts in the future distribution of thermally sensitive aquatic species. Of particular concern for lake ecosystems are when temperatures increase outside the range of natural variability, without analogue either today or in the past. However, our knowledge of when such no-analogue conditions will appear remains uncertain. Here, using daily outputs from a large ensemble of SSP3-7.0 Earth system model projections, we show that these conditions will emerge at the surface of many northern lakes under a global warming of 4.0 °C above pre-industrial conditions. No-analogue conditions will occur sooner, under 2.4 °C of warming, at lower latitudes, primarily due to a weaker range of natural variability, which increases the likelihood of the upper natural limit of lake temperature being exceeded. Similar patterns are also projected in subsurface water, with no-analogue conditions occurring first at low latitudes and occurring last, if at all, at higher latitudes. Our study suggests that global warming will induce changes across the water column, particularly at low latitudes, leading to the emergence of unparalleled climates with no modern counterparts, probably affecting their habitability and leading to rearrangements of freshwater habitats this century.

Comparison of KNN and LSTM on the Prediction of the Operational Conditions of Natural Gas Pipeline Transmission Networks

During the gas distribution process, a sequence of compressors creates a pressure difference, causing gas to move from regions of high pressure to areas with comparatively lower pressure. The Natural Gas transmission process experiences variations in pressure and temperature, primarily caused by frictional losses, differences in altitude, gas velocity, and the Joule-Thompson effect. Additionally, effective heat transfer to or from the environment contributes to temperature changes throughout the pipeline. The presence of liquid and density changes (hydrate) within the channel also has an impact on the pressure, influencing both pressure and temperature conditions.. This study implements the KNN and LSTM models to predict pressure conditions in natural gas transmission pipelines to analyze the performance comparison of the best model performance using several appropriate parameters to support maximum method performance results. The results show that the LSTM model is better at predicting pressure conditions in natural gas pipeline transmission networks, with an R2 score of 99.45, compared to the KNN model, with an R2 score of 92.82. This study also obtained prediction results from the KNN and LSTM models; the KNN model tends to produce the same pressure value for eight months, while the LSTM model produces pressure values that tend to vary.

Sustainable Infrastructure Maintenance: Crack Depth Detection in Tunnel Linings via Natural Temperature Variations and Infrared Imaging

In this research, we propose the use of infrared detection methods for identifying cracks in the tunnel lining of concrete structures. Through thermal simulation experiments on pre-existing cracks, we investigate the heat conduction patterns in cracked linings under natural temperature variations. The influence of temperature differences inside and outside the lining, crack depth, and crack width on the temperature distribution on the inner surface of the lining is analyzed by using a controlled variable approach. This exploration aims to assess the feasibility and applicable conditions of using infrared thermal imaging technology for detecting lining crack defects, contributing to sustainable maintenance of infrastructure. We further validate the experimental approach through numerical simulations. Considering the temperature distribution on the inner surface of the lining, it becomes feasible to comprehensively determine the location and depth of cracks. This offers a novel and rapid inspection method for tunnel lining cracks, thereby enhancing the sustainability of tunnel infrastructure.

Effective Spatial Degrees of Freedom of Natural Temperature Variability as a Function of Frequency

Abstract A fundamental statistic of climate variability is its spatiotemporal correlation function. Its complex structure can be concisely summarized by a frequency-dependent measure of the effective spatial degrees of freedom (ESDOF). Here we present, for the first time, frequency-dependent ESDOF estimates of global natural surface temperature variability from purely instrumental measurements, using the HadCRUT4 dataset (1850–2014). The approach is based on a newly developed method for estimating the frequency-dependent spatial correlation function from gappy data fields. Results reveal a multicomponent structure of the spatial correlation function, including a large-amplitude short-distance component (with weak time scale dependence) and a small-amplitude long-distance component (with increasing relative amplitude toward the longer time scales). Two frequency-dependent ESDOF measures are applied, each responding mainly to either of the two components. Both measures exhibit a significant ESDOF reduction from monthly to multidecadal time scales, implying an increase of the effective spatial scale of natural surface temperature fluctuations. Moreover, it is found that a good approximation to the global number of equally spaced samples needed to estimate the variance of global mean temperature is given, at any frequency, by the greater one of the two ESDOF measures, decreasing from ∼130 at monthly to ∼30 at multidecadal time scales. Finally, the multicomponent structure of the correlation function together with the detected ESDOF scaling properties indicate that the ESDOF reduction toward the longer time scales cannot be explained simply by diffusion acting on stochastically driven anomalies, as it might be suggested from simple stochastic-diffusive energy balance models.

Influence of temperature variability on the feeding behavior and blood consumption of Triatoma infestans (Hemiptera: Reduviidae).

The transmission and incidence of vector-borne diseases rely on vector distribution and life history traits such as survival, fecundity, and feeding. Since arthropod disease vectors are ectotherms, these vital rates are strongly influenced by temperature. Chagas disease is a neglected tropical disease caused by the protozoan parasite, Trypanosoma cruzi. This parasite is transmitted when the feces of the infected triatomine enter the bloodstream of the host. One of the most important vector-species of this disease in the Southern Cone region of South America is Triatoma infestans. In this study, we evaluated the role of constant and variable environmental temperature on the feeding behavior of T. infestans. Fifth-instar nymphs were acclimatized to 4 thermal treatments comprising 2 temperatures (27 °C and 18 °C) with and without diurnal thermal variability (27 ± 5 °C and 18 ± 5 °C). Individuals were fed weekly for 7 wk to quantify their feeding. Our results showed lower feeding frequency in nymphs acclimatized to cold temperature compared to those from warmer temperature treatments. However, treatments with thermal variability presented a nonlinear effect on feeding, with an increased feeding rate in the cold, variable treatment and a decreased feeding rate in the warm, variable treatment. Individuals maintained under cold treatments, the variable temperature exhibited a higher feeding rate and the lowest amount of ingested blood among all treatments. Thus, natural diurnal temperature variation cannot be ignored if we are to make more accurate T. cruzi transmission risk predictions now and in the future.

Best of both worlds: Acclimation to fluctuating environments confers advantages and minimizes costs of constant environments

Abstract Thermal acclimation is often considered critical in organismal responses to novel thermal conditions. Our understanding of the physiological implications of acclimation is largely derived from lab studies that either manipulate daytime basking availability or use of constant thermal regimes. In contrast, the importance of the nocturnal thermal environment (e.g. the extent of thermal respite) is often overlooked yet could play a vital role in thermal acclimation in the wild. To fill this gap, we acclimated lizards (Amphibolurus muricatus) under three thermal regimes (Hot Constant, Cold Constant and Alternating) and compared their physiological responses (Metabolic Rate, Sprint Speed, Thermal Preferences and Thermal Limits). We found that animals maintained constantly at hot temperatures (preferred temperature, 35°C) gained sprint performance increases and exhibited shifts in thermal optima not seen in those maintained constantly at cold temperatures (20°C), yet suffered costs to growth (in smaller animals) and maintenance (mass loss in larger animals). Animals maintained at alternating temperatures (12 h 20°C; 12 h 35°C) had performance benefits similar to animals in the hot treatment, without experiencing reductions in juvenile growth and adult mass. Animals acclimated under hot temperatures showed a significant lower preferred and voluntary maximum temperatures compared to animals acclimated under a cold temperature regime. We found no impact of acclimation treatment on behavioural thermal limits or standard metabolic rate. Overall, we show that alternating between access to preferred temperatures and having periods of energetic rest confer the greatest benefits for our animals. These results highlight the importance of natural body temperature variation for enhancing overall ectotherm performance and physiology, and the costs of novel thermal environments that fail to provide this variation. Read the free Plain Language Summary for this article on the Journal blog.

Intergenerational effects of ocean temperature variation: Early life benefits are short-lived in threespine stickleback.

Current climate change models predict an increase in temperature variability and extreme events such as heatwaves, and organisms need to cope with consequent changes to environmental variation. Non-genetic inheritance mechanisms can enable parental generations to prime their offspring's abilities to acclimate to environmental change-but they may also be deleterious. When parents are exposed to predictable environments, intergenerational plasticity can lead to better offspring trait performance in matching environments. Alternatively, parents exposed to variable or unpredictable environments may use plastic bet-hedging strategies to adjust the phenotypic variance among offspring. Here, we used a model species, the threespine stickleback (Gasterosteus aculeatus), to test whether putatively adaptive intergenerational effects can occur in response to shifts in environmental variation as well as to shifts in environmental mean, and whether parents employ plastic bet-hedging strategies in response to increasing environmental variation. We used a full-factorial, split-clutch experiment with parents and offspring exposed to three temperature regimes: constant, natural variation, and increased variation. We show that within-generation exposure to increased temperature variation reduces growth of offspring, but having parents that were exposed to natural temperature variation during gametogenesis may offset some early-life negative growth effects. However, these mitigating intergenerational effects do not appear to persist later in life. We found no indication that stickleback mothers plastically altered offspring phenotypic variance (egg size or clutch size) in response to temperature variation. However, lower inter-individual variance of juvenile fish morphology in offspring of increased variation parents may imply the presence of conservative bet-hedging strategies in natural populations. Overall, in our experiment, parental exposure to temperature variation had limited effects on offspring fitness-related traits. Natural levels of environmental variation promoted a potentially adaptive intergenerational response in early life development, but under more challenging conditions associated with increased environmental variation, the effect was lost.

Recent summer warming over the western Mediterranean region is unprecedented since medieval times

Contextualising anthropogenic warming and investigating linkages between past climate variability and human history require high-resolution temperature reconstructions that extend before the period of instrumental measurements. Here, we present maximum latewood density (MXD) measurements of 534 living and relict Pinus uncinata trees from undisturbed upper treeline ecotones in the Spanish central Pyrenees. Spanning the period 1119–2020 CE continuously, our new MXD composite chronology correlates significantly with gridded May–September mean temperatures over the western Mediterranean region (r = 0.76; p ≤ 0.001; 1950–2020 CE). Based on an integrative ensemble approach, our reconstruction reveals unprecedented summer warming since 2003 CE. The coldest and warmest reconstructed temperature anomalies are −3.4 (±1.4) °C in 1258 and 2.6 (±2.2) °C in 2017 (relative to 1961–90). Abrupt summer cooling of −1.5 (±1.0) °C was found after 20 large volcanic eruptions since medieval times. Comparison of our summer temperature reconstruction with newly compiled historical evidence from the Iberian Peninsula suggests a lack of military conflict during or following exceptionally hot or cold summers, as well as a general tendency towards less warfare and more stable wheat prices during warmer periods. Our study demonstrates the importance of updating and refining annually resolved and absolutely dated climate reconstructions to place recent trends and extremes of anthropogenic warming in a long-term context of natural temperature variability, and to better understand how past climate and environmental changes affected ecological and societal systems.

Forecast of Natural Variations in Air Temperature and Sea Ice on the East Siberian Sea Shelf for the Coming Centuries

Forecast of Natural Variations in Air Temperature and Sea Ice on the East Siberian Sea Shelf for the Coming Centuries

In Situ Drift Monitoring and Calibration of Field-Deployed Potentiometric Sensors Using Temperature Supervision.

Potentiometric ion-selective electrodes (ISEs) have broad applications in personalized healthcare, smart agriculture, oil/gas exploration, and environmental monitoring. However, high-precision potentiometric sensing is difficult with field-deployed sensors due to time-dependent voltage drift and the need for frequent calibration. In the laboratory setting, these issues are resolved by repeated calibration by measuring the voltage response at multiple standard solutions at a constant temperature. For field-deployed sensors, it is difficult to frequently interrupt operation and recalibrate with standard solutions. Moreover, the constant surrounding temperature constraint imposed by the traditional calibration process makes it unsuitable for temperature-varying field use. To address the challenges of traditional calibration for field-deployed sensors, in this study, we propose a novel in situ calibration approach in which we use natural/external temperature variation in the field to obtain the time-varying calibration parameters, without having to relocate the sensors or use any complex system. We also develop a temperature-supervised monitoring method to detect the drift of the sensor during operation. Collectively, the temperature-based drift monitoring and in situ calibration methods allow us to monitor the drift of sensors and correct them periodically to achieve high-precision sensing. We demonstrate our approach in three testbeds: (1) under controlled temperature variation in the lab, (2) under natural temperature variation in a greenhouse, and (3) in the field to monitor nitrate activity of an agricultural site. In the laboratory study, we validate that the calibration parameters of printed nitrate ISEs can be reproduced by our proposed calibration process; therefore, it can serve as an alternative to traditional calibration processes. In the greenhouse, we show the use of natural temperature variation to calibrate the sensors and detect the drift in a fixed concentration nitrate solution. Finally, we demonstrate the use of the method to monitor the nitrate activity of an agricultural field within 10% of laboratory-based measurements (i.e., a sensitivity of 0.03 mM) for a period of 22 days. The findings highlight the prospect of temperature-based calibration and drift monitoring for high-precision sensing with field-deployed ISEs.

Late spring cold reduces grain number at various spike positions by regulating spike growth and assimilate distribution in winter wheat

Late spring cold (LSC) occurred in the reproductive period of wheat impairs spike and floret differentiation during the reproductive period, when young spikelets are very cold-sensitive. However, under LSC, the responses of wheat spikelets at various positions, leaves, and stems and the interactions between them at physiological levels remain unclear. In the present study, two-year treatments at terminal spikelet stage under two temperatures (2 °C, −2 °C) and durations (1, 2, and 3 days) were imposed in an artificial climate chamber to compare the effects of LSC on grain number and yield in the wheat cultivars Yannong 19 (YN19, cold-tolerant) and Xinmai 26 (XM26, cold-sensitive). The night temperature regimes were designed to reproduce natural temperature variation. LSC delayed plant growth and inhibited spike and floret differentiation, leading to high yield losses in both cultivars. LSC reduced dry matter accumulation (DMA, g) in spikes, stems, and leaves, reducing the DMA ratios of the spike to leaf and spike to stem. Plant cell wall invertase (CWINV) activity increased in upper and basal spikelets in YN19, whereas CWINV increased in middle spikelets in XM26. Under LSC, soluble sugar and glucose were transported and distributed mainly in upper and basal spikelets for glume and rachis development, so that spike development was relatively complete in YN19, whereas the upper and basal spikelets were severely damaged and most of the glumes in middle spikelets were relatively completely developed in XM26, resulting in pollen abortion mainly in upper and basal spikelets. The development of glumes and rachides was influenced and grain number per spike was decreased after LSC, with kernels present mainly in middle spikelets. Overall, reduced total DMA and dry matter partitioning to spikes under LSC results in poor spikelet development, leading to high losses of grain yield.

Abiotic conditions affect nectar properties and flower visitation in four herbaceous plant species

Both plant nectar production and insect activity are highly dependent on abiotic environmental conditions. Furthermore, the foraging behaviour of insect pollinators can be affected by nectar properties. In the context of climate change, it is important to understand how plant-pollinator interactions respond to temperature and other abiotic factors. We investigated the effect of natural variation in temperature and solar radiation on nectar quantity (nectar volume) and quality (sucrose concentration and sucrose mass) and on flower visitation rates in four herbaceous plant species (Dictamnus albus, Lamium album, Salvia officinalis, Vincetoxicum hirundinaria) in the Botanical Garden Halle (Germany). Temperature affected nectar properties in all four species. Solar radiation affected nectar quantity and quality in two species, most likely by affecting flower temperature. The number of flower visits was unimodally related to temperature for two species and positively related to solar radiation in another. The variable responses across plant species in the effects of abiotic factors on nectar properties and flower visitation patterns may be due to differences in flower shape and colour, to differences in the composition of flower visitors, or due to other unmeasured extrinsic factors that vary across patches where these species occur. Our study highlights the importance of considering direct and indirect effects of climate factors on pollinator visitation in multiple plant species.

Low-Cost Greywater Treatment Using Polyculture Microalgae-Microalgal Growth, Organics, and Nutrient Removal Subject to pH and Temperature Variations During the Treatment.

Organics and nutrient removal studies are rarely done using polyculture microalgae, and that too in outdoor conditions, as they are often not deemed effective for wastewater treatment purposes. This study examined the organics and nutrient removal efficiency of polyculture microalgae cultivated in greywater. The reactor was operated in outdoor conditions. Hence, it was subjected to natural pH and temperature variations. A growth rate of 0.05gL-1day-1 was observed for temperatures up to 37°C, beyond which the growth rate declined by 0.07g L-1day-1. During the treatment, the pH of the system was observed to be between 7.4 and 8.4. However, the growth rate would again pick up (0.05gL-1day-1) when the pH and temperature moved towards the optimum range, indicating that the polycultures adapt very quickly to their environment. The maximum biomass concentration reached 0.82 gL-1. The highest removal efficiency of organic carbon, ammonia, and phosphate was 80.7, 61.9, and 58.4%, respectively. Nitrate and nitrite concentrations remained ≤ 1.3 mgL-1 and ≤ 2mgL-1, respectively, indicating the absence of nitrification/denitrification and ammonia volatilization. The mass balance of microalgae indicated that the primary removal mechanism of nitrogen and phosphorus removal was assimilation by the microalgae. The study proved polyculture microalgae to be as effective as some monoculture species in wastewater treatment, which require costlier controlled growth conditions. The high organics and nutrient removal by polycultures in outdoor conditions could pave the way to reducing wastewater treatment costs.

Global positioning with animal‐borne pressure sensors

AbstractOver the past decades, tracking technologies have become more ubiquitous and helped uncover crucial spatiotemporal relationships in nature. In order to apply these technologies to small animals and reduce any potential adverse impact of devices, geopositioning methodologies compatible with lightweight devices are highly sought after. Measured by lightweight geolocators, atmospheric pressure provides an untapped opportunity for global geopositioning, as its natural temporal variation is unique to each location.In this study, we estimate the position of birds by comparing pressure data recorded by the geolocator with reference data from a global weather reanalysis database. The method produces a likelihood map of the position based on (1) a mask of the locations for which the ground‐level elevation matches the pressure measured by the geolocator and (2) a mismatch between the temporal time series measured by the geolocator and the reanalysis dataset. This new method is introduced step by step and applied to 16 tracks of nine long‐ and short‐distance migrant species.Using known positions of double‐tagged individuals (light and pressure data), we demonstrate that our method is almost three times more accurate than light‐based positioning with an average error of 44 km in our trials. In contrast to the traditional light‐based approach, pressure geolocation can provide useful information for short stationary periods (less than a day) and is not affected by the equinox problem nor by any shading effects due to weather or animal behaviour. To facilitate the application of the method, we developed an R packageGeoPressureR, together with a user guideGeopressureManualand starting codeGeoPressureTemplate.The use of pressure sensors to position animals has the potential to become widespread thanks to the combination of both affordable lightweight devices (<0.4 g) and this method to estimate position of the device precisely and accurately. In particular, such devices can now be applied to short‐distant migrants (>100 km), forest‐dwelling species, nocturnal animals and altitudinal migrants.

Time-Variation in Online Nonconvex Optimization Enables Escaping From Spurious Local Minima

A major limitation of online algorithms that track the optimizers of time-varying nonconvex optimization problems is that they focus on a specific local minimum trajectory, which may lead to poor spurious local solutions. In this article, we show that the natural temporal variation may help simple online tracking methods find and track time-varying global minima. To this end, we investigate the properties of a time-varying projected gradient flow system with inertia, which can be regarded as the continuous-time limit of (1) the optimality conditions for a discretized sequential optimization problem with a proximal regularization and (2) the online tracking scheme. We introduce the notion of the dominant trajectory and show that the inherent temporal variation could reshape the landscape of the Lagrange functional and help a proximal algorithm escape the spurious local minimum trajectories if the global minimum trajectory is dominant. For a problem with twice continuously differentiable objective function and constraints, sufficient conditions are derived to guarantee that no matter how a local search method is initialized, it will track a time-varying global solution after some time. The results are illustrated on a benchmark example with many local minima.

Interactions between light and temperature during the in vitro as well as in situ modulation of phosphoenolpyruvate carboxylase in leaves of a C3 plant Pisum sativum L.

The C4 phosphoenolpyruvate carboxylase (PEPC) is well known for its modulation by light and temperature. We have attempted to address such coordinated effects of light and temperature on C3 PEPC in leaves of Pisum sativum. Experiments were done with dark-adapted leaf discs as well as with leaves collected at different times during the day and in each month during the year. The modulation of C3 PEPC by temperature was much stronger than that by light. The optimum temperature for in vitro activity of C3 PEPC was 25°C while 20°C was sub-optimal and 30°C to 45°C were supra-optimal. The photo-activation of PEPC was more at 25°C than at 45°C. The activation of C3 PEPC by temperature was more in the dark than in the light. In in situ conditions, a diurnal rhythm in the activity and regulatory properties of C3 PEPC was more prominent at colder than at warm temperatures. However, no consistent trends in the seasonal changes in PEPC activity/ regulatory properties were observed. Scatter plots suggested that light had a greater influence on PEPC activity while temperature exerted a much greater effect on its regulatory properties. Thus, C3 PEPC was also modulated by a natural variation in light and temperature under in situ conditions. These observations correlated well with the light and temperature requirements of C3 plants.

Climate change has limited effect on the growth of Afzelia africana Sm. and Anogeissus leiocarpus (DC.) Guill. and Perr. in riparian forests in the savannas of Ghana

Abstract The growth of trees in riparian forests in semi-arid savannas is resilient to the natural variations in temperature and precipitation due to the availability of riverine water. Climate change can nevertheless, intensify the evapotranspiration of tree species, altering biodiversity, plant productivity and ecosystem services. Understanding the growth response of riparian tree species to climate change is, therefore, critical for their management and conservation. Here, we used 23 cross-dated stem discs of Anogeissus leiocarpus (DC.) Guill. and Perr. and Afzelia africana Sm. randomly sampled from riparian forests in the humid and dry savanna regions of Ghana to assess their growth response to climate change. A generalized additive mixed model (GAMM) was used to integrate species-specific basal area increments to an array of explanatory variables that may affect growth, including tree size and seasonal temperature and precipitation between 1982 and 2013. We observed significant association between tree size, rainy and dry season temperatures and precipitation variables, and changes in tree growth. Despite the strong fluctuations in tree growth over time, the estimated growth rates of the species from the residuals of the GAMMs showed no significant change in growth. Our findings suggest that these riparian forests are highly resistant to weather extremes and therefore, might persist (up to a certain point) even if climate change continues to intensify.

A Comparative Approach to Detect Macrobenthic Response to the Conversion of an Inshore Mariculture Plant into an IMTA System in the Mar Grande of Taranto (Mediterranean Sea, Italy)

The expected bioremediation effect, driven by the conversion of an inshore mariculture plant into an Integrated Multi-Trophic Aquaculture (IMTA) system, which could mitigate the fish farm impact, related to the accumulation of organic matter on the seabed, has been studied. The ecological quality status was studied following a Before-After-Control-Impact (BACI) design and variation measured through M-AMBI and compared with the results of univariate and multivariate analyses of variance, to evaluate the sensitivity of the two methodologies. Results from M-AMBI indicated a sharp change in the ecological quality status, just after one year of the conversion of the plant. By contrast, although changes were detected also utilizing univariate and multivariate statistical analysis, the natural temporal variability characterizing the area partially masked evidence of environmental amelioration.