scholarly journals Repeatability of adaptive radiation depends on spatial scale: regional versus global replicates of stickleback in lake versus stream habitats

2019 ◽  
Author(s):  
Antoine Paccard ◽  
Dieta Hanson ◽  
Yoel E. Stuart ◽  
Frank A. von Hippel ◽  
Martin Kalbe ◽  
...  
Keyword(s):  
Adaptive Radiation ◽  
Genetic Divergence ◽  
Gasterosteus Aculeatus ◽  
Spatial Scales ◽  
Parallel Evolution ◽  
Spatial Separation ◽  
Global Scale ◽  
Freshwater Ecosystems ◽  
Geographic Scale ◽  
Genetic Constraints

ABSTRACTThe repeatability of adaptive radiation is expected to be scale dependent, with determinism decreasing as greater spatial separation among “replicates” leads to their increased genetic and ecological independence. Threespine stickleback (Gasterosteus aculeatus) provide an opportunity to test whether this expectation holds for the early stages of adaptive radiation - their diversification in freshwater ecosystems has been replicated many times. To better understand the repeatability of that adaptive radiation, we examined the influence of geographic scale on levels of parallel evolution by quantifying phenotypic and genetic divergence between lake and stream stickleback pairs sampled at regional (Vancouver Island) and global (North America and Europe) scales. We measured phenotypes known to show lake-stream divergence and used reduced representation genome-wide sequencing to estimate genetic divergence. We assessed the scale-dependence of parallel evolution by comparing effect sizes from multivariate models and also the direction and magnitude of lake-stream divergence vectors. At the phenotypic level, parallelism was greater at the regional than the global scale. At the genetic level, putative selected loci showed greater lake-stream parallelism at the regional than the global scale. Generally, the level of parallel evolution was low at both scales, except for some key univariate traits. Divergence vectors were often orthogonal, highlighting possible ecological and genetic constraints on parallel evolution at both scales. Overall, our results confirm that the repeatability of adaptive radiation decreases at increasing spatial scales. We suggest that greater environmental heterogeneity at larger scales imposes different selection regimes, thus generating lower repeatability of adaptive radiation at larger spatial scales.

scholarly journals Repeatability of Adaptive Radiation Depends on Spatial Scale: Regional Versus Global Replicates of Stickleback in Lake Versus Stream Habitats

2019 ◽  
Author(s):  
Antoine Paccard ◽  
Dieta Hanson ◽  
Yoel E Stuart ◽  
Frank A von Hippel ◽  
Martin Kalbe ◽  
...  
Keyword(s):  
Adaptive Radiation ◽  
Genetic Divergence ◽  
Gasterosteus Aculeatus ◽  
Spatial Scales ◽  
Parallel Evolution ◽  
Spatial Separation ◽  
Global Scale ◽  
Freshwater Ecosystems ◽  
Geographic Scale ◽  
Genetic Constraints

Abstract The repeatability of adaptive radiation is expected to be scale-dependent, with determinism decreasing as greater spatial separation among “replicates” leads to their increased genetic and ecological independence. Threespine stickleback (Gasterosteus aculeatus) provide an opportunity to test whether this expectation holds for the early stages of adaptive radiation—their diversification in freshwater ecosystems has been replicated many times. To better understand the repeatability of that adaptive radiation, we examined the influence of geographic scale on levels of parallel evolution by quantifying phenotypic and genetic divergence between lake and stream stickleback pairs sampled at regional (Vancouver Island) and global (North America and Europe) scales. We measured phenotypes known to show lake-stream divergence and used reduced representation genome-wide sequencing to estimate genetic divergence. We assessed the scale dependence of parallel evolution by comparing effect sizes from multivariate models and also the direction and magnitude of lake-stream divergence vectors. At the phenotypic level, parallelism was greater at the regional than the global scale. At the genetic level, putative selected loci showed greater lake-stream parallelism at the regional than the global scale. Generally, the level of parallel evolution was low at both scales, except for some key univariate traits. Divergence vectors were often orthogonal, highlighting possible ecological and genetic constraints on parallel evolution at both scales. Overall, our results confirm that the repeatability of adaptive radiation decreases at increasing spatial scales. We suggest that greater environmental heterogeneity at larger scales imposes different selection regimes, thus generating lower repeatability of adaptive radiation at larger spatial scales.

scholarly journals Adaptive Divergence in Experimental Populations of Pseudomonas fluorescens. IV. Genetic Constraints Guide Evolutionary Trajectories in a Parallel Adaptive Radiation

Genetics ◽  
2009 ◽  
Vol 183 (3) ◽  
pp. 1041-1053 ◽  
Author(s):  
Michael J. McDonald ◽  
Stefanie M. Gehrig ◽  
Peter L. Meintjes ◽  
Xue-Xian Zhang ◽  
Paul B. Rainey
Keyword(s):  
Adaptive Radiation ◽  
Parallel Evolution ◽  
Adaptive Divergence ◽  
Genetic Constraints ◽  
Regulatory Modules ◽  
Fitness Effects ◽  
Evolutionary Trajectories ◽  
Adaptive Radiations ◽  
Encoding Gene ◽  
Do So

The capacity for phenotypic evolution is dependent upon complex webs of functional interactions that connect genotype and phenotype. Wrinkly spreader (WS) genotypes arise repeatedly during the course of a model Pseudomonas adaptive radiation. Previous work showed that the evolution of WS variation was explained in part by spontaneous mutations in wspF, a component of the Wsp-signaling module, but also drew attention to the existence of unknown mutational causes. Here, we identify two new mutational pathways (Aws and Mws) that allow realization of the WS phenotype: in common with the Wsp module these pathways contain a di-guanylate cyclase-encoding gene subject to negative regulation. Together, mutations in the Wsp, Aws, and Mws regulatory modules account for the spectrum of WS phenotype-generating mutations found among a collection of 26 spontaneously arising WS genotypes obtained from independent adaptive radiations. Despite a large number of potential mutational pathways, the repeated discovery of mutations in a small number of loci (parallel evolution) prompted the construction of an ancestral genotype devoid of known (Wsp, Aws, and Mws) regulatory modules to see whether the types derived from this genotype could converge upon the WS phenotype via a novel route. Such types—with equivalent fitness effects—did emerge, although they took significantly longer to do so. Together our data provide an explanation for why WS evolution follows a limited number of mutational pathways and show how genetic architecture can bias the molecular variation presented to selection.

scholarly journals The Patterns and Puzzles of Genetic Diversity of Endangered Freshwater Mussel Unio crassus Philipsson, 1788 Populations from Vistula and Neman Drainages (Eastern Central Europe)

Life ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 119
Author(s):  
Adrianna Kilikowska ◽  
Monika Mioduchowska ◽  
Anna Wysocka ◽  
Agnieszka Kaczmarczyk-Ziemba ◽  
Joanna Rychlińska ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Genetic Structure ◽  
Spatial Scales ◽  
Freshwater Mussel ◽  
Its Region ◽  
Strong Relationship ◽  
Mantel Test ◽  
Freshwater Ecosystems ◽  
Hierarchical Organization ◽  
Anthropogenic Factors

Mussels of the family Unionidae are important components of freshwater ecosystems. Alarmingly, the International Union for Conservation of Nature and Natural Resources Red List of Threatened Species identifies almost 200 unionid species as extinct, endangered, or threatened. Their decline is the result of human impact on freshwater habitats, and the decrease of host fish populations. The Thick Shelled River Mussel Unio crassus Philipsson, 1788 is one of the examples that has been reported to show a dramatic decline of populations. Hierarchical organization of riverine systems is supposed to reflect the genetic structure of populations inhabiting them. The main goal of this study was an assessment of the U. crassus genetic diversity in river ecosystems using hierarchical analysis. Different molecular markers, the nuclear ribosomal internal transcribed spacer ITS region, and mitochondrial DNA genes (cox1 and ndh1), were used to examine the distribution of U. crassus among-population genetic variation at multiple spatial scales (within rivers, among rivers within drainages, and between drainages of the Neman and Vistula rivers). We found high genetic structure between both drainages suggesting that in the case of the analyzed U. crassus populations we were dealing with at least two different genetic units. Only about 4% of the mtDNA variation was due to differences among populations within drainages. However, comparison of population differentiation within drainages for mtDNA also showed some genetic structure among populations within the Vistula drainage. Only one haplotype was shared among all Polish populations whereas the remainder were unique for each population despite the hydrological connection. Interestingly, some haplotypes were present in both drainages. In the case of U. crassus populations under study, the Mantel test revealed a relatively strong relationship between genetic and geographical distances. However, in detail, the pattern of genetic diversity seems to be much more complicated. Therefore, we suggest that the observed pattern of U. crassus genetic diversity distribution is shaped by both historical and current factors i.e. different routes of post glacial colonization and history of drainage systems, historical gene flow, and more recent habitat fragmentation due to anthropogenic factors.

scholarly journals 8-Day and Daily Maximum and Minimum Air Temperature Estimation via Machine Learning Method on a Climate Zone to Global Scale

2021 ◽  
Vol 13 (12) ◽  
pp. 2355
Author(s):  
Linglin Zeng ◽  
Yuchao Hu ◽  
Rui Wang ◽  
Xiang Zhang ◽  
Guozhang Peng ◽  
...  
Keyword(s):  
Spatial Scale ◽  
Air Temperature ◽  
Spatial Scales ◽  
Model Performance ◽  
Global Scale ◽  
Scale Model ◽  
Validation Dataset ◽  
Daily Maximum ◽  
Climate Zone ◽  
Temporal And Spatial

Air temperature (Ta) is a required input in a wide range of applications, e.g., agriculture. Land Surface Temperature (LST) products from Moderate Resolution Imaging Spectroradiometer (MODIS) are widely used to estimate Ta. Previous studies of these products in Ta estimation, however, were generally applied in small areas and with a small number of meteorological stations. This study designed both temporal and spatial experiments to estimate 8-day and daily maximum and minimum Ta (Tmax and Tmin) on three spatial scales: climate zone, continental and global scales from 2009 to 2018, using the Random Forest (RF) method based on MODIS LST products and other auxiliary data. Factors contributing to the relation between LST and Ta were determined based on physical models and equations. Temporal and spatial experiments were defined by the rules of dividing the training and validation datasets for the RF method, in which the stations selected in the training dataset were all included or not in the validation dataset. The RF model was first trained and validated on each spatial scale, respectively. On a global scale, model accuracy with a determination coefficient (R2) > 0.96 and root mean square error (RMSE) < 1.96 °C and R2 > 0.95 and RMSE < 2.55 °C was achieved for 8-day and daily Ta estimations, respectively, in both temporal and spatial experiments. Then the model was trained and cross-validated on each spatial scale. The results showed that the data size and station distribution of the study area were the main factors influencing the model performance at different spatial scales. Finally, the spatial patterns of the model performance and variable importance were analyzed. Both daytime and nighttime LST had a significant contribution in the 8-day Tmax estimation on all the three spatial scales; while their contribution in daily Tmax estimation varied over different continents or climate zones. This study was expected to improve our understanding of Ta estimation in terms of accuracy variations and influencing variables on different spatial and temporal scales. The future work mainly includes identifying underlying mechanisms of estimation errors and the uncertainty sources of Ta estimation from a local to a global scale.

scholarly journals Recent changes of relative humidity: regional connection with land and ocean processes

2017 ◽  
Author(s):  
Sergio M. Vicente-Serrano ◽  
Raquel Nieto ◽  
Luis Gimeno ◽  
Cesar Azorin-Molina ◽  
Anita Drumond ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Interannual Variability ◽  
Air Temperature ◽  
Spatial Scales ◽  
Global Scale ◽  
Sea Surface ◽  
Positive Trend ◽  
Source Regions ◽  
Strong Agreement

Abstract. We analyzed changes in surface relative humidity (RH) at the global scale from 1979 to 2014 using both observations and ERA-Interim dataset. We compared the variability and trends of RH with those of land evapotranspiration and ocean evaporation in moisture source areas across a range of selected regions worldwide. The sources of moisture for each particular region were identified by integrating different observational data and model outputs into a lagrangian approach. The aim was to account for the possible role of changes in air temperature over land, in comparison to sea surface temperature (SST), on RH variability. Results demonstrate a strong agreement between the interannual variability of RH and the interannual variability of precipitation and land evapotranspiration in regions with continentally-originated humidity. In contrast, albeit with the dominant positive trend of air temperature/SST ratio in the majority of the analyzed regions, the interannual variability of RH in the target regions did not show any significant correlation with this ratio over the source regions. Also, we did not find any significant association between the interannual variability of oceanic evaporation in the oceanic humidity source regions and RH in the target regions. Our findings stress the need for further investigation of the role of both dynamic and radiative factors in the evolution of RH over continental regions at different spatial scales.

The CIMR mission and its unique capabilities for soil moisture sensing

2021 ◽  
Author(s):  
Maria Piles ◽  
Roberto Fernandez-Moran ◽  
Luis Gómez-Chova ◽  
Gustau Camps-Valls ◽  
Dara Entekhabi ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Spatial Scales ◽  
Microwave Radiometer ◽  
Critical Time ◽  
Global Scale ◽  
The Arctic ◽  
Temporal Perspective ◽  
Microwave Radiometers ◽  
Moisture Sensing

&lt;p&gt;The Copernicus Imaging Microwave Radiometer (CIMR) mission is currently being developed as a High Priority Copernicus Mission to support the Integrated European Policy for the Arctic. Due to its measurement characteristics, CIMR has exciting capabilities to enable a unique set of land surface products and science applications at a global scale. These characteristics go beyond what previous microwave radiometers (e.g. AMSR series, SMAP and SMOS) provide, and therefore allow for entirely new approaches to the estimation of bio-geophysical products from brightness temperature observations. Most notably, CIMR channels (L-,C-,X-,Ka-,Ku-bands) are very well fit for the simultaneous retrieval of soil moisture and vegetation properties, like biomass and moisture of different plant components such as leaves, stems or trunks. Also, the distinct spatial resolution of each frequency band allows for the development of approaches to cascade information and obtain these properties at multiple spatial scales. From a temporal perspective, CIMR has a higher revisit time than previous L-band missions dedicated to soil moisture monitoring (about 1 day global, sub-daily at the poles). This improved temporal resolution could allow resolving critical time scales of water processes, which is relevant to better model and understand land-atmosphere exchanges and feedbacks. In this presentation, new opportunities for soil moisture remote sensing made possible by the CIMR mission, as well as synergies and cross-sensor opportunities will be discussed.&amp;#160;&amp;#160;&lt;/p&gt;

Scale-dependent impacts of natural and anthropogenic drivers on groundwater level dynamics – analysis of shallow coastal aquifers using deep learning

2021 ◽  
Author(s):  
Annika Nolte ◽  
Steffen Bender ◽  
Jens Hartmann ◽  
Stefan Baltruschat
Keyword(s):  
Deep Learning ◽  
Groundwater Level ◽  
Coastal Aquifers ◽  
Short Term Memory ◽  
Spatial Scales ◽  
Global Scale ◽  
Meteorological Forcing ◽  
Inaccurate Information ◽  
Learning Techniques ◽  
Data Elements

&lt;p&gt;Groundwater level dynamics are very sensitive to groundwater withdrawal, but their effects and magnitude &amp;#8211; especially in combination with natural fluctuations &amp;#8211; must be often estimated due to missing or inaccurate information of all local pumping activities in an area. This study examines the potential of deep learning applications at large spatial scales to estimate the parts of local withdrawal activities and natural impacts &amp;#8211; meteorological and environmental &amp;#8211; on groundwater level dynamics. We will use big data elements from a newly constructed global groundwater database in a single long-term short-term memory (LSTM) model to examine scale-dependent impacts. The data used in the model consists of continuous groundwater level observations and catchment attributes &amp;#8211; spatially heterogeneous but temporally static catchment attributes (e.g. topography) and continuous observations of the meteorological forcing (e.g. precipitation) &amp;#8211; from several hundred catchments of shallow coastal aquifers of different continents. Our approach is to use only freely accessible data sources covering the global scale as catchment attributes. We will test how relationships between groundwater level dynamics and catchment attributes, at different scales, can improve interpretability of groundwater level simulations using deep learning techniques.&lt;/p&gt;

scholarly journals Comparison of generalized non-data-driven lake and reservoir routing models for global-scale hydrologic forecasting of reservoir outflow at diurnal time steps

2020 ◽  
Vol 24 (5) ◽  
pp. 2711-2729 ◽  
Author(s):  
Joseph L. Gutenson ◽  
Ahmad A. Tavakoly ◽  
Mark D. Wahl ◽  
Michael L. Follum
Keyword(s):  
Large Scale ◽  
Spatial Scales ◽  
Model Performance ◽  
Global Scale ◽  
Army Corps ◽  
Time Step ◽  
Large Spatial Scale ◽  
Reservoir Routing ◽  
Routing Methods ◽  
Improved Model

Abstract. Large-scale hydrologic forecasts should account for attenuation through lakes and reservoirs when flow regulation is present. Globally generalized methods for approximating outflow are required but must contend with operational complexity and a dearth of information on dam characteristics at global spatial scales. There is currently no consensus on the best approach for approximating reservoir release rates in large spatial scale hydrologic forecasting, particularly at diurnal time steps. This research compares two parsimonious reservoir routing methods at daily steps: Döll et al. (2003) and Hanasaki et al. (2006). These reservoir routing methods have been previously implemented in large-scale hydrologic modeling applications and have been typically evaluated seasonally. These routing methods are compared across 60 reservoirs operated by the U.S. Army Corps of Engineers. The authors vary empirical coefficients for both reservoir routing methods as part of a sensitivity analysis. The method proposed by Döll et al. (2003) outperformed that presented by Hanasaki et al. (2006) at a daily time step and improved model skill over most run-of-the-river conditions. The temporal resolution of the model influences model performances. The optimal model coefficients varied across the reservoirs in this study and model performance fluctuates between wet years and dry years, and for different configurations such as dams in series. Overall, the method proposed by Döll et al. (2003) could enhance large-scale hydrologic forecasting, but can be subject to instability under certain conditions.

scholarly journals Global-scale drought risk assessment for agricultural systems

2019 ◽  
Author(s):  
Isabel Meza ◽  
Stefan Siebert ◽  
Petra Döll ◽  
Jürgen Kusche ◽  
Claudia Herbert ◽  
...  
Keyword(s):  
Spatial Scales ◽  
Global Scale ◽  
Drought Indices ◽  
Drought Risk ◽  
Agricultural Systems ◽  
Coping Capacity ◽  
Climate Conditions ◽  
Hazard Exposure ◽  
Social Ecological ◽  
The Impact

Abstract. Droughts continue to affect ecosystems, communities, and entire economies. Agriculture bears much of the impact, and in many countries it is the most heavily affected sector. Over the past decades, efforts have been made to assess drought risk at different spatial scales. Here, we present for the first time an integrated assessment of drought risk for both irrigated and rain-fed agricultural systems at the global scale. Composite hazard indicators were calculated for irrigated and rain-fed systems separately using different drought indices based on historical climate conditions (1980–2016). Exposure was analyzed for irrigated and non-irrigated crops. Vulnerability was assessed through a social-ecological systems perspective, using social-ecological susceptibility and lack of coping capacity indicators that were weighted by drought experts from around the world. The analysis shows that drought risk of rain-fed and irrigated agricultural systems displays heterogeneous pattern at the global level with higher risk for southeastern Europe, as well as northern and southern Africa. By providing information on the drivers and spatial patterns of drought risk in all dimensions of hazard, exposure, and vulnerability, the presented analysis can support the identification of tailored measures to reduce drought risk and increase the resilience of agricultural systems.

scholarly journals Global-scale drivers of crop visitor diversity and the historical development of agriculture

2019 ◽  
Vol 286 (1915) ◽  
pp. 20192096 ◽  
Author(s):  
Julian Brown ◽  
Saul A. Cunningham
Keyword(s):  
Evolutionary History ◽  
Habitat Management ◽  
Spatial Scales ◽  
Global Scale ◽  
Landscape Scale ◽  
Region Of Origin ◽  
Flower Visitor ◽  
History Of ◽  
Bee Diversity ◽  
Analyse Data

Understanding diversity in flower-visitor assemblages helps us improve pollination of crops and support better biodiversity conservation outcomes. Much recent research has focused on drivers of crop-visitor diversity operating over spatial scales from fields to landscapes, such as pesticide and habitat management, while drivers operating over larger scales of continents and biogeographic realms are virtually unknown. Flower and visitor traits influence attraction of pollinators to flowers, and evolve in the context of associations that can be ancient or recent. Plants that have been adopted into agriculture have been moved widely around the world and thereby exposed to new flower visitors. Remarkably little is known of the consequence of these historical patterns for present-day crop-visiting bee diversity. We analyse data from 317 studies of 27 crops worldwide and find that crops are visited by fewer bee genera outside their region of origin and outside their family's region of origin. Thus, recent human history and the deeper evolutionary history of crops and bees appear to be important determinants of flower-visitor diversity at large scales that constrain the levels of visitor diversity that can be influenced by field- and landscape-scale interventions.

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