Potential Effects Of Climate Change Research Articles

The effects of climate change on cytotype distributions of endemic genera in the North American Coastal Plain

ABSTRACT Background Approximately 33% of plant species face extinction due to climate change. Polyploidisation, a process resulting in more than two complete sets of chromosomes, may be promoted by periods of climate fluctuations. Ecological niche modelling (ENM) using occurrences of endemic plants in the North American Coastal Plain (NACP) biodiversity hotspot could be used to evaluate the potential effects of climate change on cytotype distributions. Aims We used known diploid and polyploid taxa endemic to the NACP to test hypotheses that diploids and polyploids differed in habitat preferences, considerable overlap existed between cytotypes, and polyploid distributions would increase under climate change projections. Methods We examined niche identity and overlap of 28 congeneric ploidy level pairs and performed ENM to evaluate how climate change could affect these groups. Results Congeneric ploidy level pairs differed significantly in niche identity, and overlap varied across genera. Eleven genera showed greater than 100% increases in habitat suitability and six genera showed almost no remaining suitable habitat in at least one future climate scenario. Conclusions With 70% of the species that showed substantial declines in projected suitable habitat being of conservation concern, we propose that future studies of these genera should be a primary focus in the NACP.

Assessing Potential Effects of Climate Change on Highway-Runoff Flows and Loads in Southern New England by Using Planning-Level Space-for-Time Analyses

Transportation agencies need information about the potential effects of climate change on the volume, quality, and treatment of stormwater to mitigate potential effects of runoff on receiving waters. To address these concerns, the U.S. Geological Survey and the Federal Highway Administration used the Coupled Model Intercomparison Project tool and the Stochastic Empirical Loading and Dilution Model to perform space-for-time stormwater quality analyses. This study indicated that spatial variations in precipitation statistics within and adjacent to southern New England are greater than projected climate-related changes for the centroid of this region. A dilution-factor analysis indicated that highway runoff would become a greater proportion of downstream flows if average event volumes or time between event midpoints increase and would become a smaller proportion of downstream flows if event durations increase. Highway-runoff yield analyses for total phosphorus (TP) indicate that uncertainty in water quality statistics results in variations in long-term average yields from about 1.69 to 7.96 times higher than the lowest TP values simulated. In comparison, variations in precipitation statistics cause yield variations that ranged from 1.41 to 1.76 for the different simulated concentrations. An analysis of stormwater treatment indicated that uncertainties in runoff treatment variables are also larger than the magnitude of climate variations. This study does not question the potentially large climate-related changes in hydrologic and hydraulic variables expected to occur in the foreseeable future. It does indicate that uncertainties in the current data and potential effects of land use change on stormwater quality and treatment variables are larger than the projected effects of climate change.

Quantifying the Potential Vegetation Distribution under Climate Change: The Case of Cryptomeria fortunei in Dongting Lake Watershed, China

Potential vegetation distribution is an important study in environmental sciences. We utilized the Mixed Least Squares–Total Least Squares (MLS-TLS) method and the Signal Mode Decomposition method and the Ecological Niche model to identify the inter-correlations of internal climate change factors and constructed an environmental factor response regression model. We identified the resonance periods and trend relationships among climate factors (temperature, precipitation, and evapotranspiration) and found that the evapotranspiration of the watershed interferes with the correlation between temperature and precipitation on a five-year scale. The specific change degree of extreme climate indicators in the region was quantified by the Range of Variability Approach, among which the precipitation indicators were all below 33% (low change). There were significant differences between the key bioclimatic variables and Aspect of the development of suitable vegetation habitats. The difference between the Aspect and average daily air temperature is the main contributor to the spatial distribution of vegetation, and the mutual contribution is 76.19%. Our regression model can effectively simulate the potential distribution of vegetation (r = 0.854). Compared to the MaxEnt model, our regression model can quantitatively and intuitively provide suitable habitat values for Cryptomeria fortunei at any given location in the basin. Under future scenarios (2021–2040), suitable habitat for Cryptomeria fortunei in the eastern and western regions of the basin is projected to deteriorate further. The research results can provide some help for policymakers to eliminate the potential adverse effects of future climate change on regional ecology.

Extreme drought disrupts plant phenology: Insights from 35 years of cloud forest data in Venezuela.

The potential effects of climate change on plant reproductive phenology include asynchronies with pollinators and reductions in plant fitness, leading to extinction and loss of ecosystem function. In particular, plant phenology is sensitive to extreme weather events, which are occurring with increasing severity and frequency in recent decades and are linked to anthropogenic climate change and shifts in atmospheric circulation. For 15 plant species in a Venezuelan cloud forest, we documented dramatic changes in monthly flower and fruit community composition over a 35-year time series, from 1983 to 2017, and these changes were linked directly to higher temperatures, lower precipitation, and decreased soil water availability. The patterns documented here do not mirror trends in temperate zones but corroborate results from the Asian tropics. More intense droughts are predicted to occur in the region, which will cause dramatic changes in flower and fruit availability.

Multiscale ecological niche modeling exhibits varying climate change impacts on habitat suitability of Madrean Pine-Oak trees

Anthropogenic climate change and increasing greenhouse gas emissions are expected to globally impact the biological function, community structure, and spatial distribution of biodiversity. Many existing studies explore the effect of climate change on biodiversity, generally at a single spatial scale. This study explores the potential effects of climate change on the habitat suitability of seven tree species at two distinct spatial scales: the Coronado National Forest (CNF), a local management area, and the Sierra Madre Occidental (SMO), an ecoregional extent. Habitat suitability was determined by extrapolating Ecological Niche Models (ENMs) based on citizen-science tree occurrence records into future climatic conditions using projected 30-year normals for two anthropogenic emissions scenarios through the end of the century. These ENMs, examined at a spatial resolution of 1 km2, are constructed using a mean average ensemble of three commonly used machine learning algorithms. The results show that habitat suitability is expected to decrease for all seven tree species at varying degrees. Results also show that climate-forcing scenario choice appears to be far less important for understanding changes in species habitat suitability than the spatial scale of modeling extent. Additionally, we observed non-linear changes in tree species habitat suitability within the SMO and CNF dependent on forest community type, latitude, and elevational gradient. The paper concludes with a discussion of the necessary steps to verify the estimated alters of these tree species under climate change. Most importantly, provides a framework for characterizing habitat suitability across spatial scales.

Review of policies and actions on tackling global climate change - COP26 - is this the last chance?

The world is facing the visible and potential consequences of climate change. No place on the Earth is immune to these changes. Current policy applied worldwide anticipates global warming of about 2.7oC compared to pre-industrial level by the end of the century. By implementation of Nationally Determined Contributions (NDCs), warming will be kept to 2.4oC. If long-term commitment targets or net-zero targets are included, then warming would be kept to about 2.1oC above the pre-industrial levels. The warming projections dropped by 0.3oC after the made pledges and established targets by the USA and Peoples’ Republic of China. According to the “optimistic” scenario, if the 140 analysed countries reach the zero emission targets, then the average warming will be 1.8oC, or below 2oC. There is a significant gap between the pledges made by the governments and the total level of actions they have undertaken so far.With the new economic challenges, it is clear that we are at a crossroads. The impact of COVID-19 crisis will be crucial for the future of the climate policy. Climate changes will not wait. Their threat is over our heads and each and every day we face them. Every individual has a role to play in dealing with global climate change and we all can contribute to this threat if we all work together in a synchronous way. A greater political involvement is needed along with collective actions taken by all social actors. Over the last two years, the World Health Organization has advocated for greater inclusion of health authorities and services in Nationally determined contributions through activities to reduce the implications on health by climate change.

Assessing the impact of wildfires on water quality using satellite remote sensing: the Lake Baikal case study

Lakes have been observed as sentinels of climate change. In the last decades, global warming and increasing aridity has led to an increase in both the number and severity of wildfires. This has a negative impact on lake catchments by reducing forest cover and triggering cascading effects in freshwater ecosystems. In this work we used satellite remote sensing to analyse potential fire effects on lake water quality of Lake Baikal (Russia), considering the role of runoff and sediment transport, a less studied pathway compared to fire emissions transport. The main objectives of this study were to analyse time series and investigate relationships among fires (i.e., burned area), meteo-climatic parameters and water quality variables (chlorophyll-a, turbidity) for the period 2003–2020. Because Lake Baikal is oligotrophic, we expected detectable changes in water quality variables at selected areas near the three mains tributaries (Upper Angara, Barguzin, Selenga) due to river transport of fire-derived burned material and nutrients. Time series analysis showed seasonal (from April to June) and inter-annual fire occurrence, precipitation patterns (high intensity in summer) and no significant temporal changes for water quality variables during the studied periods. The most severe wildfires occurred in 2003 with the highest burned area detected (36,767 km2). The three lake sub-basins investigated have shown to respond differently according to their morphology, land cover types and meteo-climatic conditions, indicating their importance in determining the response of water variables to the impact of fires. Overall, our finding suggests that Lake Baikal shows resilience in the medium-long term to potential effects of fires and climate change in the region.

Predicting the Impact of Climate Change on the Distribution of Rhipicephalus sanguineus in the Americas

Climate change may influence the incidence of infectious diseases including those transmitted by ticks. Rhipicephalus sanguineus complex has a worldwide distribution and transmits Rickettsial infections that could cause high mortality rates if untreated. We assessed the potential effects of climate change on the distribution of R. sanguineus in the Americas in 2050 and 2070 using the general circulation model CanESM5 and two shared socioeconomic pathways (SSPs), SSP2-4.5 (moderate emissions) and SSP2-8.5 (high emissions). A total of 355 occurrence points of R. sanguineus and eight uncorrelated bioclimatic variables were entered into a maximum entropy algorithm (MaxEnt) to produce 50 replicates per scenario. The area under the curve (AUC) value for the consensus model (>0.90) and the partial ROC value (>1.28) indicated a high predictive capacity. The models showed that the geographic regions currently suitable for R. sanguineus will remain stable in the future, but also predicted increases in habitat suitability in the Western U.S., Venezuela, Brazil and Bolivia. Scenario 4.5 showed an increase in habitat suitability for R. sanguineus in tropical and subtropical regions in both 2050 and 2070. Habitat suitability is predicted to remain constant in moist broadleaf forests and deserts but is predicted to decrease in flooded grasslands and savannas. Using the high emissions SSP5-8.5 scenario, habitat suitability in tropical and subtropical coniferous forests and temperate grasslands, savannas, and shrublands was predicted to be constant in 2050. In 2070, however, habitat suitability was predicted to decrease in tropical and subtropical moist broadleaf forests and increase in tropical and subtropical dry broadleaf forests. Our findings suggest that the current and potential future geographic distributions can be used in evidence-based strategies in the design of control plans aimed at reducing the risk of exposure to zoonotic diseases transmitted by R. sanguineus.

기후변화에 따른 멸종위기 야생생물 2급 백부자의 잠재서식처 변화와 파편화 예측

Climate change influences various aspects of life on earth including distribution shifts, phenology, and interaction with other organisms. Endangered species respond more sensitively to changes within their limited distribution range. In this study, we analyzed and modeled the current distribution habitat of Aconitum coreanum, which is classified as an endangered species level 2, and further projected potential distribution changes and habitat fragmentation under climate change scenarios (Shared Socio-economic Pathway, SSP). For species distribution modeling (SDM), current habitat coordinates were collected from the national ecosystem survey and the national survey on the distribution of endangered species, and environmental data were obtained from Worldclim. An ensemble model was used as a SDM for potential habitat analysis, and landscape metrics were used for fragmentation analysis. The potential habitat area was about 15,216 km2 and the distribution included the Yeongseo region of Gangwon-do and some areas of Chungcheongbuk-do in the current climate. Modeling revealed potential habitat decreases of at least 80% and complete disappearance in SSP3-7.0. The number of patches, mean patch area, total core area, and patch cohesion index showed a decreasing trend compared to the current climate. Our results provide fundamental information for understanding the potential effects of climate change on the distribution of Aconitum coreanum. Adding ecological processes such as dispersal and population dynamics to such an analysis will make it possible to accurately predict the future impacts of climate change on the distribution of endangered species.

Potential effects of future climate change on global reptile distributions and diversity

AbstractAimUntil recently, complete information on global reptile distributions has not been widely available. Here, we provide the first comprehensive climate impact assessment for reptiles on a global scale.LocationGlobal, excluding Antarctica.Time period1995, 2050 and 2080.Major taxa studiedReptiles.MethodsWe modelled the distribution of 6296 reptile species and assessed potential global and realm‐specific changes in species richness, the change in global species richness across climate space, and species‐specific changes in range extent, overlap and position under future climate change. To assess the future climatic impact on 3768 range‐restricted species, which could not be modelled, we compared the future change in climatic conditions between both modelled and non‐modelled species.ResultsReptile richness was projected to decline significantly over time, globally but also for most zoogeographical realms, with the greatest decreases in Brazil, Australia and South Africa. Species richness was highest in warm and moist regions, with these regions being projected to shift further towards climate extremes in the future. Range extents were projected to decline considerably in the future, with a low overlap between current and future ranges. Shifts in range centroids differed among realms and taxa, with a dominant global poleward shift. Non‐modelled species were significantly stronger affected by projected climatic changes than modelled species.Main conclusionsWith ongoing future climate change, reptile richness is likely to decrease significantly across most parts of the world. This effect, in addition to considerable impacts on species range extent, overlap and position, was visible across lizards, snakes and turtles alike. Together with other anthropogenic impacts, such as habitat loss and harvesting of species, this is a cause for concern. Given the historical lack of global reptile distributions, this calls for a re‐assessment of global reptile conservation efforts, with a specific focus on anticipated future climate change.

Climate change effect on soil erosion using different erosion models: A case study in the Naip Dam basin, Türkiye

Soil erosion, expected to increase with the potential effects of climate change, is the main problem that reduces the useful storage capacity of river dam reservoirs. This problem threatens the safety and sustainability of water and food resources. Over the last few years, a large number of numerical models have been developed and used to predict the current, and future state of soil erosion with Geographic Information Systems (GIS) based erosion models. This study aims to estimate the annual average amount of soil loss in the Naip dam basin in Türkiye Thrace by using GIS-based Revised Universal Soil Loss Equation (RUSLE) and Modified Universal Soil Loss Equation (MUSLE) erosion models and analyze the forecast outputs verified by the reservoir sedimentation results within the framework of the effects of climate change. Thus, the effects of future climate change on the spatiotemporal change of erosion rate and reservoir sedimentation were tried to be explored. Study data were organized using the ArcGIS Soil Erosion Tool, and annual average soil loss was calculated based on the dam basin's RUSLE and MUSLE erosion models. Accordingly, it was understood that the average annual soil loss in the basin area was between 0.31 t ha−1 yr−1 (RUSLE) and 0.36 t ha−1 yr−1 (MUSLE). These results were checked by the results of reservoir sedimentation determined by the volume changes of the Naip dam. RUSLE and reservoir sedimentation results were found to be compatible with each other. Therefore, the RUSLE erosion model was rerun with climate change data for 9-year periods between 2021 and 2050. Because of the predicted effects of climate change, it is understood that erosion will increase more in this area in the future. Thus, helpful and guiding information was provided to the decision makers for the dam reservoir sedimentation management, the dam's sustainability, and the extension of the reservoir life. In terms of adaptation to climate change, it is recommended to take measures to reduce or prevent erosion in the basin area.

Mediterranean songbirds show pronounced seasonal variation in thermoregulatory traits

Addressing the patterns of variation in thermal traits is crucial to better predict the potential effects of climate change on organisms. Here, we assessed seasonal (winter vs summer) adjustments in key thermoregulatory traits in eight Mediterranean-resident songbirds. Overall, songbirds increased whole-animal (by 8%) and mass-adjusted (by 9%) basal metabolic rate and decreased (by 56%) thermal conductance below the thermoneutral zone during winter. The magnitude of these changes was within the lower values found in songbirds from northern temperate areas. Moreover, songbirds increased (by 11%) evaporative water loss within the thermoneutral zone during summer, while its rate of increase above the inflection point of evaporative water loss (i.e., the slope of evaporative water loss versus temperature) decreased by 35% during summer — a value well above that reported for other temperate and tropical songbirds. Finally, body mass increased by 5% during winter, a pattern similar to that found in many northern temperate species. Our findings support the idea that physiological adjustments might enhance the resilience of Mediterranean songbirds to environmental changes, with short-term benefits by saving energy and water under thermally stressful conditions. Nevertheless, not all species showed the same patterns, suggesting different strategies in their thermoregulatory adaptations to seasonal environments.

Intraspecific variations in leaf functional traits of Cunninghamia lanceolata provenances

BackgroundStudies on intra-specific variability in leaf functional traits is important to evaluate adaptation of the species to predicted climate change, and to develop long-term conservation strategy. The main objectives were to investigate the relationship between the functional traits leaves and C, N, P stoichiometry of Chinese fir from different geographical provenances and their relationship with the main environmental factors of provenance.ResultsIn this study, we measured 12 leaf functional traits on 36-year-old Cunninghamia lanceolata trees from 13 provenances. Analysis of variance (ANOVA) was performed to examine the variability. Redundancy analysis (RA) was computed to examine the relationship between geo-climatic factors of provenance origin and leaf functional traits while Pearson’s correlation coefficient was computed to assess inter-trait correlations. The results showed statistically significant differences (P < 0.01) in intraspecific leaf traits among provenances, except leaf P content. The relationships among leaf traits are consistent with the general trend observed in the leaf economic spectrum. Mean annual temperature appeared to be a key factor that influences intraspecific leaf traits variability compared to mean annual precipitation.ConclusionThese results provide useful insights about adaptation of leaf trait of Chinese fir in a changing climatic condition. Thus, our findings shed light on the importance of interspecific trait variability in Chinese fir and the potential effect of climate change.

Effects of Climate Change on the Spatial Distribution of the Threatened Species Rhododendron purdomii in Qinling-Daba Mountains of Central China: Implications for Conservation

The plant species in the mountainous regions might be relatively more vulnerable to climate change. Understanding the potential effects of climate change on keystone species, such as Rhododendron species in the subalpine and alpine ecosystems, is critically important for montane ecosystems management and conservation. In this study, we used the maximum entropy (MaxEnt) model, 53 distribution records, and 22 environmental variables to predict the potential impacts of climate change on the distribution of the endemic and vulnerable species Rhododendron purdomii in China. The main environmental variables affecting the habitat suitability of R. purdomii were altitude, temperature seasonality, annual precipitation, slope, and isothermality. Our results found suitable distribution areas of R. purdomii concentrated continuously in the Qinling-Daba Mountains of Central China under different climate scenarios, indicating that these areas could potentially be long-term climate refugia for this species. The suitable distribution areas of R. purdomii will expand under the SSP126 (2070s), SSP585 (2050s), and SSP585 (2070s) scenarios, but may be negatively influenced under the SSP126 (2050s) scenario. Moreover, the potential distribution changes of R. purdomii showed the pattern of northward shift and west–east migration in response to climate change, and were mainly limited to the marginal areas of species distribution. Finally, conservation strategies, such as habitat protection and assisted migration, are recommended. Our findings will shed light on biotic responses to climate change in the Qinling-Daba Mountains region and provide guidance for the effective conservation of other endangered tree species.

REINFORCING OUR INFRASTRUCTURE FOR THE FUTURE: ACHIEVING RESILIENCE IN THE WAKE OF THE COVID-19 PANDEMIC

The COVID-19 pandemic has highlighted the need for increased resilience and exposed flaws in the infrastructure systems of many nations. Diversifying supply chains, investing in digital infrastructure, enhancing the resilience of the infrastructure itself, strengthening public health systems and improving emergency response systems are all ways that Governments and other organisations can increase the resilience of infrastructure. It’s crucial to take into account community involvement, the private sector, and potential climate change effects. Building infrastructure systems that are better able to withstand upcoming shocks and meet the needs of populations all over the world is possible by using a thorough and co-ordinated approach.

The identification and conservation of climate refugia for two Colombian endemic titi (Plecturocebus) monkeys

Natural resource managers face the challenge of developing conservation plans for key species and given that anthropogenic climate change (CC) effects on biodiversity are becoming increasingly evident, the new challenge is to properly incorporate CC adaptation strategies into such plans. Thus, the objective of this study is to evaluate the potential CC effects on the climatically suitable areas for two Colombian endemic titi monkeys Plecturocebus ornatus and P. caquetensis and to identify the prospective climate refugia as macro-ecological adaptation strategies for each species. A detailed ecological niche modeling (ENM) approach was applied with the maximum entropy algorithm, using presence records and different sets of bioclimatic variables describing baseline (1960–1990) and future climates (∼2070). Models of future climatic suitability were generated using projections of variables under a stabilization (RCP4.5) and business as usual (RCP8.5) scenarios with data from two general circulation models (GCMs) describing storylines of increasing (CESM1_CAM5) and decreasing (CSIRO_ACCESS1_3) rainfall patterns. The results for both species indicate that in a warmer future, opposite rainfall patterns and choice of the bioclimatic variables may lead to divergent responses on the extent and geographic distribution of their climatic niche, which varied from regions gaining, losing, and retaining suitability in potential climate refugia. Moreover, CC represents a serious threat for P. caquetensis and P. ornatus since their ranges may be largely exposed to novel climates. Their baseline climatic suitability area is projected to shrink and shift to higher elevations in the Andes mountains, and the climate refugia identified for both species are poorly covered by protected areas. Therefore, the climate refugia identified in this work and the management recommendations offered should be considered by species conservation plans to contribute to the selection of priority regions for conservation actions. The modeling approach reveals the uncertainties arising from the selection of bioclimatic variables and GCMs in ENM, which can be replicated to identify climate refugia targeting different species of conservation concern.

Modeling days suitable for fieldwork using machine learning, process-based, and rule-based models

ContextPrediction of days suitable for fieldwork is important for understanding the potential effects of climate change and for selecting machinery systems to improve efficiency in field operations and avoid soil damage. Yet, we lack predictive models to inform decision-making at scale. ObjectiveWe filled this knowledge gap by developing and testing five new workability models. MethodsOne model follows soil moisture-based methods (APSIM), one uses simple rain and temperature thresholds, and three follow machine learning techniques (Random Forest, Decision Table, Neural Network). We parameterized the models using USDA survey data from Iowa, USA and evaluated their temporal and spatial prediction over twelve US Corn Belt States and different time periods using multiple statistical indexes and sensitivity analysis. The models operate at a 5-arcminute resolution. Results and conclusionsResults indicated that the simple rule model, the Decision Table model, and the process-based model predicted field workable days with an agreement index of 0.88, 0.86, and 0.84, respectively for the testing datasets (n = 22,671), and hence were deemed sufficient for future use. The selected models are better suited for large timespan evaluations of workability (monthly to annual, normalized root mean square error, nRMSE = 8 to 15%)) than weekly predictions (nRMSE = 21%). The machine learning models tended to cluster their predictions around a mean value and were about 50% less responsive to precipitation than the process-based or rule-based models. We concluded that simple approaches are more robust to be applied at scale than complex approaches with many data input requirements. SignificanceThe developed models enhance our capacity to predict climate change impacts on workability, a valuable indicator for decision-making and overall sustainability.

Plant and Meadow Structure Characterisation of Posidonia oceanica in Its Westernmost Distribution Range

Posidonia oceanica is an endemic seagrass species from the Mediterranean Sea that provides critical ecological services to coastal environments. This species is distributed from the Turkish to the Spanish coast, where its westernmost record was documented in Punta Chullera, Malaga (36°18′36.45′′ N, 5°14′54.31′′ W). Nevertheless, previous studies suggested that its distribution was even further west, although these populations were never described. In this study, we documented and characterised the only known P. oceanica population on the coast of Cadiz, in Cala Sardina (36°18′38.80′′ N, 5°15′15.13′′ W). The newly documented population of P. oceanica presented a fragmented structure, consisting of nine patches found in a rocky shallow area surrounded by the invasive algae Rugulopteryx okamurae, with a total size of 61.14 m2. Shoots had a relatively small size (21.0 ± 2.9 cm) in comparison with centrally-distributed populations. The relatively small size of the plants, alongside the observed low shoot density (437 ± 42 shoots m−2) and leaf area index (4.8 ± 0.7 m2 m−2), may indicate that this meadow could be exposed to sub-optimal environmental conditions for plant development. By contrast, the meadow showed relatively high production rates (0.03 ± 0.01 leaf day−1 shoot−1) in comparison with other Mediterranean populations. The percentage of carbon in plant leaves was 38.73 ± 1.38%, while the nitrogen and C/N were 1.38 ± 0.37% and 29.93 ± 6.57, respectively. The documentation of this meadow extends the distribution of this species to the Mediterranean coast of Cadiz, making this region the place with the highest seagrass biodiversity (four species) in the Iberian Peninsula, and potentially in Europe. This exploratory study provides a baseline to examine the potential effects of climate change, anthropogenic disturbances or the presence of invasive species.

Potential effects of climate change on the growth response of the toxic dinoflagellate Karenia selliformis from Patagonian waters of Chile

Northern Patagonia (41–44°S) is affected by climatic, hydrological and oceanographic anomalies, which in synergy with processes such as global warming and acidification of the coastal oceans may affect the frequency and intensity of harmful algal blooms (HABs). Greater frequency of HABs has been reported in the southeastern Pacific Ocean, including blooms of the toxic dinoflagellate Karenia selliformis, causing massive mortality of marine fauna in the oceanic and coastal areas of Patagonia. The objective of this study was to determine the effects of temperature and pH interaction on the growth of K. selliformis (strain CREAN_KS02), since these factors have wide seasonal fluctuations in the Patagonian fjord ecosystem. The CREAN_KS02 strain isolated from the Aysén Region (43°S) was used in a factorial experiment with five pH levels (7.0, 7.4, 7.7, 8.1 and 9.0) and two temperatures (12 and 17 °C) during a period of 18–21 days. Results indicated a significant effect of temperature and pH interaction on growth rate (range 0.22 ± 0.00 to 0.08 ± 0.01 d−1) and maximum density (range 13,710 ± 2,616 to 2,385 ± 809 cells mL−1) of K. selliformis. The highest density and growth of K. selliformis was found at 12 °C with a reduced pH (7.0–7.7). The results suggest that the current environmental conditions of coastal Patagonia, waters of low temperature and relatively low pH, may be favorable for the development of blooms of this species during autumn. We suggest that there is natural plasticity of K. selliformis in a wide pH range (7.0–8.1) but in a narrow low temperature range (10.6–12.9 °C), values that are typically recorded in the oceanic region of northern Patagonia. In contrast, in an extreme climate change scenario (ocean warming and coastal acidification) in northern Patagonia, a negative effect on the growth of K. selliformis may be expected due to amplification of the acidification effects caused by the thermal stress of high temperature water.

Hydrological sustainability of in-pit reclaimed oil sands landforms under climate change

Development of robust reclamation designs would require understanding the relative effects of climate change on the water budget of reclaimed Athabasca oil sands landforms (Alberta, Canada). A surplus water budget is critical to sustain pit lakes and periodically freshen localized surface water ponds within the closure landscape. In this study, four hypothetical future climate scenarios were developed from statistically downscaled RCP2.6 and RCP8.5 climate projections and used in a hydrological model to investigate the potential effects of climate change on the water budget of an in-pit reclaimed oil sands mine landform. The four scenarios allowed the assessment of climate change effects for endpoints that bracket a range of future climate conditions on the water balance of the landform. Surface water and groundwater flow and chloride transport were simulated for the 2024–2100 period using daily climate forcing and the results were compared with equivalent responses under historical climate (1944–2020). The results suggest that the hydrological behavior under historical and RCP2.6 scenarios is similar. The climatic water deficit (potential evapotranspiration exceeding precipitation) will rise significantly under the RCP8.5 scenario. However, the modeling suggests that the water budget of the landform will not be too different from the early 21st century prolonged dry climate period. The chloride released from the landform under the different projected and historical climate scenarios also remained similar. Although evapotranspiration increases and leads to relatively drier conditions, a modest increase in precipitation helps maintain a surplus water budget in most years. The results demonstrate that incorporating future climate projections into water balance analyses is crucial to understand the potential reductions in runoff depths.