Esri (Canada)

Experimental evolution has been a useful tool for investigating long-term temporal evolutionary dynamics and molecular mechanisms underlying adaptation. However, extracting fundamental principles and predictive features of evolutionary outcomes from these datasets remains challenging. Here we sought to circumvent these challenges by comparing distant yeast species that share several evolutionary features but differ in evolutionary history and genome architecture, that is Saccharomyces cerevisiae and Schizosaccharomyces pombe. We evolved ten populations of the fission yeast for 10,000 generations in the same conditions as a pre-existing budding yeast dataset, allowing us to observe repeatable evolutionary outcomes within species but diverse molecular targets of adaptation across species. The most frequent route of adaptation was through changes in carbon flux metabolism, which was previously unseen in S. cerevisiae evolved populations, but similar evolutionary paths have been observed in wild populations. This suggests that parallelism is pervasive and that mechanisms of adaptation can be shared among closely related or distant species. Despite similar gene content and identical environments, recurrent adaptation across S. pombe populations involved different genes than in S. cerevisiae and was detectable mostly at the transcriptomic level. This indicates that trans-regulatory effects and contingency may contribute to differences in evolutionary outcomes between these species.

Various modeling efforts have been conducted to evaluate ecosystem services (ES) of agricultural conservation practices but typically these models are too complex for conservation stakeholders to use. This research developed a cloud-based WebGIS tool for communicating integrated ES modeling to conservation stakeholders. The integrated ES modeling was developed by linking farm economic, watershed hydrologic, and soil carbon modeling within a spatial optimization framework for identifying conservation practices to minimize economic costs subject to multiple ES targets including water quality and soil carbon improvement benefits. The WebGIS tool, named "Ecosystem Services Assessment Tool" (ESAT), has a suite of functions to visualize watershed characteristics, summarize the effectiveness of existing agricultural conservation practices, examine the cost, effectiveness, and cost-effectiveness of future agricultural conservation practices, and further, identify optimal sets of conservation practices for achieving cost-effectiveness. The study area for the integrated ES modeling and WebGIS tool development was the 4,820-km2 Modeste watershed in Alberta, Canada. The ESAT application demonstrated its functionalities to support decision making, particularly in identifying cost-effective conservation practices for achieving sediment, phosphorus or nitrogen reduction, or soil carbon increase target. In the research, conservation stakeholders including municipal and provincial governments, conservation management agencies, and NGOs were actively engaged in data collection, modeling development, WebGIS tool development, and training for the use of the WebGIS tool. Conservation stakeholders assessed that the ESAT is a very useful tool for supporting decision making in agri-environmental programs. However, the WebGIS tool can be further simplified and streamlined to improve the user-friendliness of the ESAT.

Accurately quantifying carbon sinks and sources in coastal regions is essential for global carbon budgeting, but it can be a challenging task. This is especially true for rapidly changing sub-Arctic and Arctic seas where baseline observations of seawater CO2 partial pressure (pCO2) are limited. Hudson Bay, Canada, is a prime example of an area with sparse data geographically and temporally. To bridge this gap, we utilized a novel approach by integrating predictor variables from satellite imagery and reanalysis data with advanced machine learning algorithms to provide more precise regional estimates of pCO2. In addition, we examined the ocean's carbon uptake and spatiotemporal fluctuations over different periods by incorporating wind speed and atmospheric CO2 data. Our study not only reveals insights into the dynamics of Hudson Bay CO2 sources and sinks but also demonstrates the potential of machine learning in extrapolating ship observations over space and time.

This letter summarizes the transformative impacts Geographic Information System (GIS) technology can have on cancer care accessibility and outcomes, emphasizing its utility in precisely defining cancer center catchment areas and improving service delivery. By integrating GIS, cancer centers can better understand equity in access to care and take steps to assess and address a spectrum of community health needs within their catchments. By approaching cancer care geographically, spatial information can inform policy development, engage stakeholders, enhance clinical trial participation, guide resource allocation, and provide more compelling and understandable research and information to the public. This letter also aims to illustrate the comprehensive role GIS plays in bridging the gap between genetics and geography in cancer care. The concept of location is ubiquitous in our lives and in our data, yet we are not fully taking advantage of this key resource. I strongly advocate for the wider adoption of geographic approaches in oncology to ensure that advancements in cancer treatment and care are accessible to all, thereby improving health outcomes and equity across populations.

Mekânsal teknolojilerin eğitim ortamlarında kullanımı gittikçe yaygınlaşmaktadır. Bu çalışmada mekânsal teknoloji aracı olarak gösterilen ve ESRI tarafından geliştirilen “story map” uygulamasının eğitim ortamlarında kullanımını konu edinen çalışmalar sistematik olarak incelenmiştir. Web tabanlı bir uygulama olan story map, verileri görselleştirmeye, mekânsal analiz yapmaya ve araştırılan konuyu hikâyeleştirerek anlatmaya yarayan bir sunu aracıdır. Story map sunduğu zenginleştirilmiş içerik ve uygulama şablonlarıyla öğretmen ve öğrenciler için vazgeçilmez bir teknoloji aracı olarak görülmektedir. Araştırmanın amacına uygun olarak öncelikle Academia, Google Scholar, ERIC, Researchgate, Semantic Scholar, SCI-HUB, ProQuest, Taylor&Francis, Wiley ve YÖK Tez veri tabanlarında “ESRI Story Map” AND “Education”, “ESRI Story Map” AND “Educational technology”, anahtar kelimeleri kullanılarak alanyazın taraması yapılmıştır. Yapılan tarama sonucunda 2014-2023 yılları arasında yayımlanmış 31 çalışmanın tümüne ulaşılmıştır. Ulaşılan çalışmalar araştırma yöntemine, örneklem grubuna, veri toplama araçlarına, çalışma alanına göre betimsel içerik analizine tabi tutulmuştur. Araştırmanın sonucunda mevcut çalışmaların çoğunluğunun nitel (22) ve coğrafya alanında olduğu, bununla birlikte tarih, topoğrafya, sosyal bilgiler alanlarında ve story map aracının eğitim ortamlarında kullanmanın gerekliliğini kuramsal düzeyde ele alan çalışmalara da rastlanmıştır.

Abstract Soil erosion is an important cause of global land degradation, and accurate monitoring of it is essential. The Soil and Water Assessment Tool (SWAT), a distributed hydrological model, is an advanced technique for predicting soil erosion at watershed scale. However, as the erosion framework was established in gently sloping land, SWAT is limited in predicting soil erosion in some highland and mountainous regions. Therefore, this study suggested a method to integrate the sediment transport theoretical formula that can reflect the morphology of gully regions into SWAT to obtain SWAT‐S to enhance the calculation performance of sediment load, and the SWAT‐S was evaluated according to the coefficient of determination (R2), Nash‐Sutcliffe coefficient (NSE), Percent‐Bias (P‐BIAS) and root mean square errors (RMSE)‐observations SD ratio (RSR) in the Yanhe basin on the Chinese Loess Plateau. The results showed that SWAT‐S is more successful in reproducing the monthly sediment load, with R2, NSE, |P‐BIAS| and RSR were changed by 5.08%, 17.65%, −2.92% and −10.00% in the calibration, as well as by 1.18%, 10.39%, 45.45% and −18.75% in the validation of the SWAT‐S compared to SWAT. Meanwhile, SWAT‐S estimates 2.66 × 106 t more sediment than SWAT during the June–September flood season and better matches observed data. In total, the revised SWAT can improve the performance of sediment estimation, which is beneficial for the wider application of the model in more regions of the world.

Advancements in sensor technology have led to significant growth in the volume and variety of geospatial data. Optical, radar, lidar, and sonar sensor technologies have presented us with valuable opportunities to understand our changing world. However, a key challenge still lies in developing data models that can efficiently manage diverse types of spatial and temporal data collected from these sensors to enable information extraction. In this paper, we describe the integrated data cubes within ArcGIS that effectively handle spatial and temporal data. Our approach includes a mosaic dataset for managing satellite time series and gridded climate data, a cloud raster format (CRF) file for storing pixel-aligned analysis-ready data, and a trajectory dataset for managing points from altimetry sensors. We present several use cases to demonstrate the analysis capabilities based on these data models.

Scalable and high-throughput electrophysiological measurement systems are necessary to accelerate the elucidation of cardiac diseases in drug development. Optical mapping is the primary method of simultaneously measuring several key electrophysiological parameters, such as action potentials, intracellular free calcium and conduction velocity, at high spatiotemporal resolution. This tool has been applied to isolated whole-hearts, whole-hearts in-vivo, tissue-slices and cardiac monolayers/tissue-constructs. Although optical mapping of all of these substrates have contributed to our understanding of ion-channels and fibrillation dynamics, cardiac monolayers/tissue-constructs are scalable macroscopic substrates that are particularly amenable to high-throughput interrogation. Here, we describe and validate a scalable and fully-automated monolayer optical mapping robot that requires no human intervention and with reasonable costs. As a proof-of-principle demonstration, we performed parallelized macroscopic optical mapping of calcium dynamics in the well-established neonatal-rat-ventricular-myocyte monolayer plated on standard 35 mm dishes. Given the advancements in regenerative and personalized medicine, we also performed parallelized macroscopic optical mapping of voltage dynamics in human pluripotent stem cell-derived cardiomyocyte monolayers using a genetically encoded voltage indictor and a commonly-used voltage sensitive dye to demonstrate the versatility of our system.