Historical Climate Change Research Articles

Intervention in Portuguese Historic Villages Facing Desertification and Climate Change

The 12 Historical Villages of Portugal, located on the border between Serra da Estrela and Spain, are a remarkable piece of Portuguese history. However, these villages have been deeply impacted by the increasing issue of depopulation, aging, and abandonment. While this phenomenon is not limited to these villages, there are certainly unique factors that contribute to the tension between maintaining the historical significance of the villages and addressing the everyday needs of the local. In the particular context of the buildings that still withstand, mostly in the central areas of the villages, many of those who insist on remaining in this territory end up abandoning the stone houses inside the villages and migrating to new buildings built in their surroundings.Despite its valuable symbolic capital (for its environmental, landscape and heritage potential), the tourism sector is clearly not the sole answer as its revenue to the local economy proves to be insufficient for the essential material, social and economic balance that attracts and fixes the population.The issue of unattractiveness in these villages is multifaceted. A key factor contributing to this problem is poor housing conditions, which fail to provide residents with the comfort they deserve. This lack of comfort also results in misguided interventions that mischaracterize the existing heritage, leading to a further devaluation of the symbolic capital of these communities.Considering this context and in articulation with the SDG11, it is imperative to establish solid bases for interventions in existing buildings that allow reconciling the need for adequate comfort levels with the protection of the landscape and heritage legacy, which incorporate innovation in terms of sustainability of materials and energy expenditure, with an alliance of ancestral knowledge with innovation in efficient water management, but also that pay attention to environmental, social, economic sustainability with beneficial impact on society and territory. These bases must also incorporate an adaptation to climate change that affects both the landscape and the comfort conditions inside the existent buildings.

Reconstruction of Spatial–Temporal Changes in Cropland Cover from 1650 to 1980 in Taiyuan City

As a crucial component of studies on land use and cover change (LUCC), the reconstruction of historical cropland cover is important for assessing human impact on the environment. This study collects cropland records of each county in Taiyuan City based on historical documents, agricultural statistics, and survey data such as the Gazetteers, Agriculture and Commercial Statistics Table and Datasets of Land and Resources of China. The cropland area at the county level from 1650 to 1980 is determined by revising, correcting, and extrapolating the obtained historical records. By assessing the driving physiogeographic factors for the distribution of cropland through GeoDetector, we establish a land suitability-based gridded allocation model. The cropland areas at the county level are allocated into 1 km × 1 km grid cells. Our results indicated the following. (1) The total cropland area increased since the Qing Dynasty, reaching its maximum value in 1937, after which it declined due to the impact of urbanization after 1937. (2) In terms of the spatial distribution patterns of cropland, from 1650 to 1980, the cropland was mainly distributed in the Fenhe River Valley Plain, and the cropland expanded from the center to the south after 1952. (3) Comparing the reconstruction results for 1980 with the 1 km resolution satellite-based cropland cover data, differences of most (95.77%) grids are between −20% and +20%, comparing the HYDE3.2 dataset with our results. The HYDE3.2 dataset is distinctly lower than our datasets, and the grids with large differences are mainly in the central and southern parts of the study area, especially in the Qing Dynasty. Our reconstruction could evaluate the accuracy of the global dataset when applied to regional areas and serve as base data in studying historical climate change.

Agricultural adaptation and resilience through climatic shifts in semi-arid India: 2000 years of archaeobotanical evidence from Vadnagar, Gujarat

The relationship between historical climate change and past agricultural production contributes to a better understanding of the impacts of projected climate change by providing empirical data for resilient human responses. This study explores the periods of dynastic transitions and crop production at the urban site of Vadnagar, in semi-arid northwest India through several climate events, generally characterised by weakening summer monsoon precipitation during the Late Holocene. Artefacts from the site present an unbroken sequence of seven successive cultures from the first century BCE to the nineteenth century CE. Archaeobotanical data indicate the sufficient water availability during the Historic and Medieval periods, allowing crop production dominated large-grained cereals (C3 plants). However, during the Post-Medieval period (ca.1300−1850 CE) a resilient crop economy based on small-grained cereals (C4 plants) dominated, representing a human adaptation to prolonged weakening of monsoonal precipitation. Isotopic and phytolith data at the site present a clear signal of changing local environmental conditions over two millennia, consistent with regional palaeoclimate records, providing and interpretive context for agricultural evidence at Vadnagar. Despite long-term reduction in summer humidity, we argue that an adaptable agricultural package coupled with suitable water management systems allowed for the resilience of the urban settlement at Vadnagar.

Global patterns and ecological drivers of taxonomic and phylogenetic endemism in angiosperm genera

Endemism of lineages lies at the core of understanding variation in community composition among geographic regions because it reflects how speciation, extinction, and dispersal have influenced current distributions. Here, we investigated geographic patterns and ecological drivers of taxonomic and phylogenetic endemism of angiosperm genera across the world. We identify centers of paleo-endemism and neo-endemism of angiosperm genera, and show that they are mostly located in the Southern Hemisphere in tropical and subtropical regions, particularly in Asia and Australia. Different categories of phylogenetic endemism centers can be differentiated using current climate conditions. Current climate, historical climate change, and geographic variables together explained ∼80% of global variation in taxonomic and phylogenetic endemism, while 42−46%, 1%, and 15% were independently explained by these three types of variables, respectively. Thus our findings show that past climate change, current climate, and geography act together in shaping endemism, which are consistent with the findings of previous studies that higher temperature and topographic heterogeneity promote endemism. Our study showed that many centers of phylogenetic endemism of angiosperms, including regions in Amazonia, Venezuela, and west-central tropical Africa that have not previously been identified as biodiversity hotspots, are missed by taxon-based measures of endemism, indicating the importance of including evolutionary history in biodiversity assessment.

Out of the desert: Paleoclimatic changes drove the diversification of arid-adapted Ocymyrmex ants in southern Africa

A highly endemic ant fauna is found in the arid regions of southern Africa, including species in the genus Ocymyrmex. This genus of ants has higher species richness in the western arid regions of southern Africa compared to tropical and subtropical parts of the continent. The processes that have produced these patterns of diversity and distribution of arid adapted ants in southern Africa have never been investigated. The diversification of many other taxa in the region has been associated with past climate fluctuations that occurred during the Miocene epoch. In this study, the nature and timing of historical processes that may have led to the diversification within Ocymyrmex were assessed. We hypothesized that past climate oscillations, characterized by long periods of aridification, have driven the current distribution of Ocymyrmex species that resulted in the highest species richness of the genus in the Deserts & xeric shrublands biome in southern Africa.Ninety-four Ocymyrmex worker specimens from Botswana, Kenya, Namibia, South Africa, Tanzania and Zimbabwe, representing 21 currently described species and six morphospecies, were included in a phylogenomic analysis. Phylogenies for the genus, based on next generation sequencing data from ultraconserved elements, were inferred using Maximum Likelihood, and a dating analysis was performed using secondary age estimates as calibration points. A distribution database of Ocymyrmex records was used to assign species ranges, which were then coded according to major biomes in southern Africa and used as input for biogeographical analysis. We explored the phylogenomic relationships of Ocymyrmex and analysed these within a biogeographical and paleoclimatic framework to disentangle the potential processes responsible for diversification in this group. Dating analyses estimated that the crown age of Ocymyrmex dates to the Oligocene, around 32 Ma. Diversification within this group occurred between the mid-Miocene (∼12.5 Ma) and Pleistocene (∼2 Ma). Our biogeographic analyses suggest that Ocymyrmex species originated in the south-western region of southern Africa, which is now part of the Deserts & xeric shrublands biome and diversified into eastern subtropical areas during the Pliocene. Paleoclimatic changes resulting in increased aridity during the Miocene likely drove the diversification of the genus Ocymyrmex. It is most likely that the diversification of grasslands, because of historical climate change, facilitated the diversification of these ants to the eastern parts of southern Africa when open grasslands replaced forests during the early Miocene.

Paleontology as a didactic tool to learn about environmental change

Introduction and Objective. This paper describes a workshop on historical climate change for teachers at the University of Buenos Aires, Argentina. Methodology. In this workshop, teachers analyzed hypothetical evidence of fossil records to relate them to climate and environmental change. Results. This work describes the subsequent analysis of the proposed activity. Teachers' prior knowledge about these concepts and their cognitive-linguistic abilities are also described. Conclusion. The workshop provided teachers with a didactic tool for teaching fossil records, climate change, and geological time within Earth Science.

Human displacements from Tropical Cyclone Idai attributable to climate change

Abstract. Extreme weather events, such as tropical cyclones, often trigger population displacement. The frequency and intensity of tropical cyclones are affected by anthropogenic climate change. However, the effect of historical climate change on displacement risk has so far not been quantified. Here, we show how displacement can be partially attributed to climate change using the example of the 2019 Tropical Cyclone Idai in Mozambique. We estimate the population exposed to high water levels following Idai's landfall using a combination of a 2D hydrodynamical storm surge model and a flood depth estimation algorithm to determine inland flood depths from remote sensing images, factual (climate change) and counterfactual (no climate change) mean sea level, and maximum wind speed conditions. Our main estimates indicate that climate change has increased displacement risk from this event by approximately 12 600–14 900 additional displaced persons, corresponding to about 2.7 % to 3.2 % of the observed displacements. The isolated effect of wind speed intensification is double that of sea level rise. These results are subject to important uncertainties related to both data and modeling assumptions, and we perform multiple sensitivity experiments to assess the range of uncertainty where possible. Besides highlighting the significant effects on humanitarian conditions already imparted by climate change, our study provides a blueprint for event-based displacement attribution.

MIROC6 Large Ensemble (MIROC6-LE): experimental design and initial analyses

Abstract. Single model initial-condition large ensembles (LEs) are a useful approach to understand the roles of forced responses and internal variability in historical and future climate change. Here, we produce one of the largest ensembles thus far using the MIROC6 coupled atmosphere–ocean global climate model (MIROC6-LE). The total experimental period of MIROC6-LE is longer than 76 000 years. MIROC6-LE consists of a long preindustrial control run, 50-member historical simulations, 8 single forcing historical experiments with 10 or 50 members, 5 future scenario experiments with 50 members and 3 single forcing future experiments with 50 members. Here, we describe the experimental design. The output data of most of the experiments are freely available to the public. This dataset would be useful to a wide range of research communities. We also demonstrate some examples of initial analyses. Specifically, we confirm that the linear additivity of the forcing-response relationship holds for the 1850–2020 trends of the annual mean values and extreme indices of surface air temperature and precipitation by analyzing historical fully forced runs and the sum of single forced historical runs. To isolate historical anthropogenic signals of annual mean and extreme temperature for 2000–2020 relative to 1850–1900, ensemble sizes of 4 and 15, respectively, are sufficient in most of the world. Historical anthropogenic signals of annual mean and extreme precipitation are significant with the 50-member ensembles in 76 % and 69 % of the world, respectively. Fourteen members are sufficient to examine differences in changes in annual mean values and extreme indices of temperature and precipitation between the shared socioeconomic pathways (ssp), ssp585 and ssp126, in most of the world. Ensembles larger than 50 members are desirable for investigations of differences in annual mean and extreme precipitation changes between ssp126 and ssp119. Historical and future changes in internal variability, represented by departures from the ensemble mean, are analyzed with a focus on the El Niño/Southern Oscillation (ENSO) and global annual mean temperature and precipitation. An ensemble size of 31 is large enough to detect ENSO intensification from preindustrial conditions to 1951–2000, from 1951–2000 to 2051–2100 in all future experiments, and from low- to high-emission future scenario experiments. The single forcing historical experiments with 27 members can isolate ENSO intensification due to anthropogenic greenhouse gas and aerosol forcings. Future changes in the global mean temperature variability are discernible with 23 members under all future experiments, while 50 members are not sufficient for detecting changes in the global mean precipitation variability in ssp119 and ssp126. We also confirm that these temperature and precipitation variabilities are not precisely analyzed when detrended anomalies from the long-term averages are used due to interannual climate responses to the historical natural forcing, which highlights the importance of large ensembles for assessing internal variability.

Predicting Habitat Suitability and Adaptation Strategies of an Endangered Endemic Species, Camellia luteoflora Li ex Chang (Ericales: Theaceae) under Future Climate Change

Camellia luteoflora Li ex Chang is an endangered plant endemic to the East Asian flora with high ornamental value as well as phylogenetic and floristic research value. Predicting the impact of climate change on its distribution and suitable habitat is crucial until scientific conservation measures are implemented. Based on seven environmental variables and 17 occurrence records, this study optimized the MaxEnt model using the kuenm data package to obtain the optimal parameter combinations (RM = 1.3, FC = LPT) and predicted the potential distribution pattern of C. luteoflora in various future periods. The results revealed that the mean diurnal range, temperature annual range, and precipitation of the wettest month were the influential factors determining the distribution pattern of C. luteoflora, contributing 60.2%, 14.4%, and 12.3% of the variability in the data, respectively. Under the current conditions, the area of suitable habitats for C. luteoflora was only about 21.9 × 104 km2. Overall, the suitable area around the C. luteoflora distribution points will shrink in a circular pattern in response to future global warming, but some potentially suitable distribution areas will expand and migrate to higher latitudes and the Hengduan Mountains region, representing a survival strategy for coping with climate change. It is hypothesized that the future climate refugia will be the highly suitable area and the Hengduan Mountains region. Furthermore, a retrospective validation method was employed to assess the reliability of the predictions and estimate the model’s predictive performance in the future. This study proposes a survival strategy and adaptation measures for C. luteoflora in response to climate change, and the proposed measures can be generalized for application in conservation planning and restoration processes. We also recommend that future studies incorporate factors such as the anthropogenic disturbances and associated socio-economic activities related to C. luteoflora into the model and to further predict the distribution pattern for C. luteoflora in response to historical climatic changes, tracing the evolutionary history of its population.

Elucidating microbial mechanisms of microcystin-LR degradation in Lake Erie beach sand through metabolomics and metatranscriptomics

As one of five Laurentian Great Lakes, Lake Erie ranks among the top freshwater drinking sources and ecosystems globally. Historical and current agriculture mismanagement and climate change sustains the environmental landscape for late summer cyanobacterial harmful algal blooms, and consequently, cyanotoxins such as microcystin (MC). Microcystin microbial degradation is a promising mitigation strategy, however the mechanisms controlling the breakdown of MCs in Lake Erie are not well understood. Pelee Island, Ontario, Canada is located in the western basin of Lake Erie and the bacterial community in the sand has demonstrated the capacity of metabolizing the toxin. Through a multi-omic approach, the metabolic, functional and taxonomical signatures of the Pelee Island microbial community during MC-LR degradation was investigated over a 48-hour period to comprehensively study the degradation mechanism. Cleavage of bonds surrounding nitrogen atoms and the upregulation of nitrogen deamination (dadA, alanine dehydrogenase, leucine dehydrogenase) and assimilation genes (glnA, gltB) suggests a targeted isolation of nitrogen by the microbial community for energy production. Methylotrophic pathways RuMP and H4MPT control assimilation and dissimilation of carbon, respectively and differential abundance of Methylophilales indicates an interconnected role through electron exchange of denitrification and methylotrophic pathways. The detected metabolites did not resolve a clear breakdown pathway, but rather the diversity of products in combination with taxonomic and functional results supports that a variety of strategies are applied, such as epoxidation, hydroxylation, and aromatic degradation. Annual repeated exposure to the toxin may have allowed the community to adaptatively establish a novel pathway through functional plasticity and horizontal gene transfer. The culmination of these results reveals the complexity of the Pelee Island sand community and supports a dynamic and cooperative metabolism between microbial species to achieve MC degradation.

Attributing historical streamflow changes in the Jhelum River basin to climate change

Amid a heated debate on what are possible and what are plausible climate futures, ascertaining evident changes that are attributable to historical climate change can provide a clear understanding of how warmer climates will shape our future habitability. Hence, we detect changes in the streamflow simulated using three different datasets for the historical period (1901–2019) and analyze whether these changes can be attributed to observed climate change. For this, we first calibrate and validate the Soil and Water Integrated Model and then force it with factual (observed) and counterfactual (baseline) climates presented in the Inter-Sectoral Impact Model Intercomparison Project Phase 3a protocol. We assessed the differences in simulated streamflow driven by the factual and counterfactual climates by comparing their trend changes ascertained using the Modified Mann–Kendall test on monthly, seasonal, and annual timescales. In contrast to no trend for counterfactual climate, our results suggest that mean annual streamflow under factual climate features statistically significant decreasing trends, which are − 5.6, − 3.9, and − 1.9 m3s−1 for the 20CRv3-w5e5, 20CRv3, and GSWP3-w5e5 datasets, respectively. Such trends, which are more pronounced after the 1960s, for summer, and for high flows can be attributed to the weakening of the monsoonal precipitation regime in the factual climate. Further, discharge volumes in the recent factual climate dropped compared to the early twentieth-century climate, especially prominently during summer and mainly for high flows whereas earlier shifts found in the center of volume timings are due to early shifts in the nival regime. These findings clearly suggest a critical role of monsoonal precipitation in disrupting the hydrological regime of the Jhelum River basin in the future.

Lizard richness in mainland China is more strongly correlated with energy and climatic stability than with diversification rates

AbstractAimContemporary environmental, historical and evolutionary factors are increasingly used to decipher the drivers of spatial patterns of species richness. Evidence of such correlations for Chinese reptiles is scarce and poorly understood. We therefore explored the validity of the environmental capacity, historical climatic stability and diversification rates hypotheses on Chinese lizard richness.LocationMainland China.TaxonSquamata: Sauria.MethodsWe mapped the distribution ranges of all 237 lizards in mainland China using a combination of different datasets. We used current environmental conditions (ambient energy, environmental productivity, and habitat heterogeneity), historical climate stability indices (long term: since ~3.3 Ma and short term: since the last glacial maximum) and mean tip diversification rates, to test whether current environmental conditions, historical climate change and diversification rates drive contemporary richness patterns of lizards in China. We applied piecewise structural equation models (pSEM) to jointly evaluate our hypotheses, considering direct and indirect effects.ResultsChinese lizards showed strong latitudinal diversity gradients. We found consistent support for contemporary climatic and environmental factors relationships with richness. Richness was also positively correlated with short‐term climatic stability, but less so with long‐term stability. Diversification rates were seldom found to be positively correlated with lizard richness.Main ConclusionsOur results support the environmental capacity and historical climate hypotheses, which link high richness to highly productive warm and stable regions (and low richness to cold and unstable regions). We conclude that post‐speciation dispersal and short‐term climatic oscillations quickly swamp the long‐term signal of diversification rates and climatic fluctuations, creating strong current climate–richness associations.

A Predictive Model For Quantifying The Combined Effect Of Land Use Change And Climatic Variability On Sedimentation In Malaba Sub Catchment

Over the previous years, sedimentation in Malaba sub catchment has become a major problem, this research aimed at using SWAT as a predictive model to assess the impacts of historical and future climate change and land use changes on sedimentation in Malaba sub catchment. Two variables rainfall and temperature were considered under climate change. Four scenarios were modeled in SWAT during this study, the first scenario focused on historical sedimentation in the catchment, land use data of 2000 and weather data of 1990 to 2005 was used to simulate flow and sediment yield in the catchment. The second scenario focused on the current sediment yield in the catchment where land use data of 2020 and weather data of 2003 to 2020 was used to simulate the sediment yield and flow. Calibration and validation was done using SWAT CUP software. The calibrated and validated model was then used to further simulate two future scenarios. The two future scenarios used projected land use data and projected weather data. Land use data was projected using Clerk Labs Terr set software while weather data was projected using the Statistical Downscaling Model (SDSM). The third scenario considered projected land use data of 2035 and projected weather data of 2020 to 2035 to simulate flow and sediment yield of 2023 to 2035. The forth scenario considered projected land use data of 2050 and projected weather data of 2033 to 2050 to simulate catchment flow and sediment yield of 2036 to 2050. The results obtained from climate change analysis indicated un even changes, rainfall over the catchment is expected to increase, maximum temperature is expected to increase, minimum temperature is expected to reduce. Land use change results after comparison between the historical land use and projected land use indicated that from 2020 to 2050 cropland and built up area will increase while forests and water bodies will reduce. Average annual Sediment yield of 1993 to 2020 is expected to generally increase from 4975.4 tons/km2/year to an average annual sediment yield of 5525.6 tons/km2/year from 2023 to 2050. Therefore, mitigation measures should be adopted to ensure sustainable management of the catchment. Some of the recommendations made in this research are; Government through NEMA should put restrictions on cultivation close to the river banks, encourage planting trees within the catchment, bare lands within the catchment should be converted to other sustainable land uses. The study findings of this research shall be relevant for planning, design and management of reservoirs, dams, irrigation systems and sustainability of eco systems in the catchment.

Homogenization and species compositional shifts in subalpine vegetation during the 60-year period

Subalpine and alpine plant communities are considered highly sensitive and hence endangered by global changes. In central Europe, the highly sensitive habitats are also influenced by human activities: land use, industrial pollution, and tourism. That is especially true for subalpine plant communities formed on mid-latitude mountains during specific postglacial development. Our study aimed to (1) document changes in cover and plant species diversity between the past (1950s and 1970s) and present (2019) and (2) reveal differences in the functional composition of the species among the studied periods. In 2019, quasi-permanent marked plots originally surveyed in the 1950s and 1970s were resurveyed at Králický Sněžník (Śnieżnik Kłodski) Mountains, the High Sudetes Mts.. We assessed temporal changes in plant species composition, species cover, functional groups, growth forms, and degree of specialization. We found homogenization of the vegetation over time and changes in the cover of specific functional groups that were attributed to environmental factors connected with the cessation of historical land use, atmospheric deposition, and climate change. Implementing a suitable combination of mowing and grazing to support diversity, and to prevent homogenization of vegetation is highly recommended.

Quantifying the relative contributions of climate change and ENSO to flood occurrence in Bangladesh

Bangladesh is highly vulnerable to flood hazards, and its flood risk is projected to increase with global warming. In addition to climate change, internal climate variation, such as the El Niño–Southern Oscillation (ENSO), influences flooding in many rivers worldwide. However, the impact of internal climate variability on flooding in Bangladesh remains unclear due to the limited observations. Here, we assess the impacts of ENSO and climate change on flood occurrence in Bangladesh using a large-ensemble climate simulation dataset and a global river model (CaMa-Flood). After separating 6000 years of simulation (100-member ensemble river simulations for 1950–2010) into El Niño, La Niña, and neutral years, we calculated the extent to which each ENSO stage increased flood occurrence probability relative to the neutral state using the fraction of attributable risk method. In addition, we estimated the impact of historical climate change on past flood occurrence through a comparison of simulations with and without historical global warming. Under the no-global-warming climate, La Niña increased the occurrence probability of a 10 year return period flood at Hardinge Bridge on the Ganges River by 38% compared to neutral years. The influence of La Niña or El Niño state on flood occurrence probability in the Brahmaputra River at Bahadurabad station is negligible. Historical global warming increased the occurrence of flooding in the Ganges River, the Brahmaputra River, and their confluence by 59%, 44%, and 55%, respectively. The impact of ENSO on flood occurrence probability decreased in the historical simulation, likely due to the conflation of ENSO and climate change signals, and no significant correlation between ENSO and flood occurrence was detected when only small-ensemble simulations were used. These findings suggest that the use of large-ensemble climate simulation datasets is essential for precise attribution of the impacts of internal climate variability on flooding in Bangladesh.

Effective management of the watershed in response to historical climate change using a GIS-based multi-criteria decision analysis (MCDA)

Abstract Watershed management is necessary to conserve water resources because the watershed hydrological processes are more affected by climate and land use change, resulting in the problems of droughts, floods, soil erosion, etc. This study determined suitable alternatives that can ensure viable strategies for tackling the climate change impacts at the Soan River Basin (SRB). A framework was applied to assess the impacts of climate change and land use/cover change (LUCC) using the Soil and Water Assessment Tool (SWAT). A multi-criteria decision analysis (MCDA) was used to prioritize watershed management alternatives by comparing watershed management criteria and alternatives using the analytic hierarchy process (AHP). Framework findings showed a 69 and 31% decline in runoff, and a 58 and 42% increment in evapotranspiration (ET) due to climate change and LUCC, respectively. The top prioritized suitable alternatives were water harvesting structure (WHS) and vegetative cover (VC). Suitability analysis showed that 63.61 and 16.56% area of the SRB were moderately to highly suitable for WHS, respectively. For soil and water management, VC has been found suitable to moderately suitable for 72.68 and 26.75% of the basin area, respectively. So, there should be adoption of such measures which will assist in configuring the climate adaptive strategies.

Historical Climate Change Dynamics Facilitated Speciation and Hybridization Between Highland and Lowland Species of Baripus Ground Beetles From Patagonia

One of the largest beetles of Patagonia, Baripus (Cardiophthalmus), includes 20 currently described species. Its distribution ranges from the tip of Patagonia, on Tierra del Fuego Island, to isolated patches along the Andes and extra-Andes mountains in northern Patagonia on the Payunia at >3000 m elevation. Here, using RADseq data, evidence is found of mixed ancestry in different lineages. Phylogenetic network reconstruction shows two hybridizing edges between lowland and highland species. Using environmental niche modeling, we show changes in geographic distribution of potential niches of species during the last glacial maximum compared to their present distribution. Increasing potential niche overlap among different species pairs possibly explains how lineages came into secondary contact, supporting the hypothesis of hybridization. In addition, morphological evolution is studied using geometric morphometrics on the network, and evidence of transgressive evolution has been found involving the pronotum shape, as well as highland/lowland habitat preferences. Finally, based on genomics and morphological data and using an integrative coalescent-based species delimitation approach, the separate evolution of two lineages in early stages of speciation is found. Taken together, dynamics of diversification of Baripus beetles in both space and time are discussed.

Trends in the risk of heat stress to Canadian dairy cattle in a changing climate

Canada's climate is warming faster than the global average, but the warming is unevenly distributed. This study analyzes historical and future climate change in dairy-producing regions across Canada to better understand how Canada's dairy cows are affected. Historical changes (i.e., 1960–2019) were assessed using temperature and humidity data from 29 weather stations across the country. The temperature–humidity index (THI) was used as an indicator of dairy cattle at risk of heat stress, and three THI metrics evaluated the frequency, severity, and duration of potential heat stress. Future scenarios were investigated using five global climate models to project daily THI under three Shared Socioeconomic Pathways (SSPs). Projections were grouped into three time periods (2020–2049, 2040–2069, and 2060–2089). Historical climate trends show an increase in temperature, humidity, and THI exceedance in most west coast and eastern Canada locations, affecting 84% of the national dairy herd. Future scenarios project that 90% of the national herd will experience a large increase in the frequency, severity, and duration of THI exceedance under all but the most optimistic SSP. These findings highlight the need for Canadian dairy farmers to consider heat-stress adaptation strategies.

A novel statistical model for flood prediction in the Eel River watershed, New Brunswick, Canada

ABSTRACT A strong correlation between the effect of climate change and the increase in flooding frequency and magnitude has been reported in Canada. Consequently, there is a crucial need to examine the effects of future climate change scenarios on flooding conditions. The main objective of this research is to better understand the destructive effects of flood events under historical and future climate change conditions for a small watershed (Eel River watershed) in New Brunswick (NB), Eastern Canada. A practical model had been developed using the modified Artificial Neural Network (ANN) in MATLAB by the authors of this study. The architecture and data structure of ANN is characterized by a back propagation with the Levenberg–Marquardt method. The observed daily total precipitation, daily maximum and minimum air temperatures, daily discharge for the period 1967 to 1983, the simulated monthly maximum and minimum air temperatures, and monthly total precipitation for the period of 1996–2099 from the CanESM2, the second-generation Canadian Earth System Model (CGCM), were used as input of the model. The Representative Concentration Pathways (RCP 4.5 and 8.5), as suitable climate change scenarios, were selected based on the Intergovernmental Panel on Climate Change (IPCC) recommendations for flood studies. Daily values of temperatures, precipitations, and discharges were converted to monthly mean values for better prediction of the output results. In addition, two series of observed discharges were prepared using mean monthly (Qavg) and daily maximum discharges (Qd) as the Target of the model. For more accurate analysis, the time frames of 1996–2012 (for the historical) and 2022–2038, 2039–2055, 2056–2072, 2073–2089, and 2083–2099 (for the future) were considered with a duration of 16 years for each time frame. The output results of ANN were predicted daily maximum (Qd) and mean (Qavg) discharges under the impact of climate change scenarios. As a part of the developed model, Flood Frequency Analysis (FFA) was undertaken using the generalized extreme value (GEV) and the three-parameter lognormal (LN3) distributions based on the predicted and observed discharges. The performance of FFA and ANN were demonstrated using the Anderson–Darling (AD), the Chi-square (CS) tests and coefficient of correlation (R) and mean squared error (MSE), respectively. In conclusion, the three most critical time frames with the highest values of predicted discharges were 2022–2038, 2056–2072, and 2073–2089 for RCP4.5 and 2039–2055, 2073–2089, and 2083–2099 for RCP8.5. Also, based on the FFA, the magnitudes of flood recurrence for the future time period of 100 years will dramatically increase according to the most critical time frames of 2056–2072 and 2039–2055 for RCP 4.5 and 8.5, respectively. Findings indicated that the Eel River watershed will encounter severe floods, and about a 50% increase in mean discharge, especially for the critical time frames. Finally, flood occurrences show increasing trends due to climate change effects in the most critical time frames.

Fennoscandian tree-ring anatomy shows a warmer modern than medieval climate.

Earth system models and various climate proxy sources indicate global warming is unprecedented during at least the Common Era1. However, tree-ring proxies often estimate temperatures during the Medieval Climate Anomaly (950-1250CE) that are similar to, or exceed, those recorded for the past century2,3, in contrast tosimulation experiments at regional scales4. This not only calls into question the reliability of models and proxies but also contributes to uncertainty in future climate projections5. Here we show that the current climate of the Fennoscandian Peninsula is substantially warmer than that of the medieval period. This highlights the dominant role of anthropogenic forcing in climate warming even at the regional scale, thereby reconciling inconsistencies between reconstructions and model simulations. We used an annually resolved 1,170-year-long tree-ring record that relies exclusively on tracheid anatomical measurements from Pinus sylvestris trees, providing high-fidelity measurements of instrumental temperature variability during the warm season. We therefore call for the construction of more such millennia-long records to further improve our understanding and reduce uncertainties around historical and future climate change at inter-regional and eventually global scales.