Biology subjects

Riemer, K.

Publications and source records attributed to Riemer, K..

6 recordsLinked to original sources

bioRxiv2024

Enhanced Ultrasound Image Formation with Computationally Efficient Cross-Angular Delay Multiply and Sum Beamforming

Ultrasound imaging is a valuable clinical tool. It is commonly achieved using the delay and sum beamformer algorithm, which takes the signals received by an array of sensors and generates an image estimating the spatial distribution of the signal sources. This algorithm, while computationally efficient, has limited resolution and suffers from high side lobes. Nonlinear processing has proven to be an effective way to enhance the image quality produced by beamforming in a computationally efficient manner. In this work, we describe a new beamforming algorithm called Cross-Angular Delay Multiply and Sum, which takes advantage of nonlinear compounding to enhance contrast and resolution. This is then implemented with a mathematical reformulation to produce images with tighter point spread functions and enhanced contrast at a low computational cost. We tested this new algorithm over a range of in vitro and in vivo scenarios for both conventional B-Mode and amplitude modulation imaging, and for two types of ultrasound contrast agents, demonstrating its potential for clinical settings.

bioengineering↗

bioRxiv2020

The influence of data type and functional traits on native bee phenology metrics: Opportunistic versus inventory records

Efforts to understand activity patterns of bees, our most important pollinators, often rely on opportunistically collected museum records to model temporal shifts or declines. This type of data, however, may not be suitable for this purpose given high spatiotemporal variability of native bee activity. By comparing phenological metrics calculated from intensive systematic inventory data with those from opportunistic museum records for bee species spanning a range of functional traits, we explored biases and limitations of data types to determine best practices for bee monitoring and assessment. We compiled half a million records of wild bee occurrence from opportunistic museum collections and six systematic inventory efforts, focusing analyses on 45 well-represented species that spanned five functional traits: sociality, nesting habits, floral specialization, voltinism, and body size. We then used permutation tests to evaluate differences between data types in estimating three phenology metrics: flight duration, number of annual abundance peaks, and date of the highest peak. We used GLMs to test for patterns of data type significance across traits. All 45 species differed significantly in the value of at least one phenology metric depending on the data type used. The date of the highest abundance peak differed for 40 species, flight duration for 34 species, and the number of peaks for 15 species. The number of peaks was more likely to differ between data types for larger bees, and flight duration was more likely to differ for larger bees and specialist bees. Our results reveal a strong influence of data type on phenology metrics that necessitates consideration of data source when evaluating changes in phenological activity, possibly applicable to many taxa. Accurately assessing phenological change may require expanding wild bee monitoring and data sharing.

ecology↗

bioRxiv2018

Comparison of large-scale citizen science data and long-term study data for phenology modeling

Large-scale observational data from citizen science efforts are becoming increasingly common in ecology, and researchers often choose between these and data from intensive local-scale studies for their analyses. This choice has potential trade-offs related to spatial scale, observer variance, and inter-annual variability. Here we explored this issue with phenology by comparing models built using data from the large-scale, citizen science National Phenology Network (NPN) effort with models built using data from more intensive studies at Long Term Ecological Research (LTER) sites. We built process based phenology models for species common to each dataset. From these models we compared parameter estimates, estimates of phenological events, and out-of-sample errors between models derived from both NPN and LTER data. We found that model parameter estimates for the same species were most similar between the two datasets when using simple models, but parameter estimates varied widely as model complexity increased. Despite this, estimates for the date of phenological events and out-of-sample errors were similar, regardless of the model chosen. Predictions for NPN data had the lowest error when using models built from the NPN data, while LTER predictions were best made using LTER-derived models, confirming that models perform best when applied at the same scale they were built. Accordingly, the choice of dataset depends on the research question. Inferences about species-specific phenological requirements are best made with LTER data, and if NPN or similar data are all that is available, then analyses should be limited to simple models. Large-scale predictive modeling is best done with the larger-scale NPN data, which has high spatial representation and a large regional species pool. LTER datasets, on the other hand, have high site fidelity and thus characterize inter-annual variability extremely well. Future research aimed at forecasting phenology events for particular species over larger scales should develop models which integrate the strengths of both datasets.

ecology↗

bioRxiv2017

Body Size Shifts Influence Effects Of Increasing Temperatures On Ectotherm Metabolism

INTRODUCTION INTRODUCTION METHODS RESULTS DATA ACCESSIBILITY BIOSKETCH REFERENCES Environmental temperature influences organisms in many ways; temperature increases or decreases rates of physiological processes (Brown et al., 2012), determines timing of reproduction (Olive, 1995), and even directly affects mortality (Pauly, 1980). Because of the far-reaching influence of temperature, projected increases in global temperatures due to climate change are expected to substantially alter diverse species characteristics. Increased temperatures have already been implicated in shifts in species geographic distributions (e.g., Buckley et al., 2010), and in the phenology of species life history and development (e.g., Wolkovich ...

ecology↗

bioRxiv2017

A persistent lack of International representation on editorial boards in biology

The scholars comprising journal editorial boards play a critical role in defining the trajectory of knowledge in their field. Nevertheless, studies of editorial board composition remain rare, especially those focusing on journals publishing research in the increasingly globalized fields of science, technology, engineering, and math (STEM). Using metrics for quantifying the diversity of ecological communities, we quantified international representation on the 1985-2014 editorial boards of twenty-four environmental biology journals. Over the course of three decades there were 3831 unique scientists based in 70 countries that served as editors. The size of the editorial community increased over time - there were 420% more editors serving in 2014 than in 1985 - as did the number of countries in which editors were based. Nevertheless, editors based outside the Global North (the group of economically developed countries with high per capita Gross Domestic Product (GDP) that collectively concentrate most global wealth) were extremely rare. Furthermore, 67.06% of all editors were based in either the USA or UK. Consequently, Geographic Diversity - already low in 1985 - remained unchanged through 2014. We argue that this limited geographic diversity can detrimentally affect the creativity of scholarship published in journals, the progress and direction of research, the composition of the STEM workforce, and the development of science in Latin America, Africa, the Middle East, and much of Asia (i.e., the Global South).

scientific communication and education↗

bioRxiv2017

No general relationship between mass and temperature in endotherm species

Bergmanns rule is a widely-accepted biogeographic rule stating that individuals within a species are smaller in warmer environments. While there are many single-species studies and integrative reviews documenting this pattern, a data-intensive approach has not been used yet to determine the generality of this pattern. We assessed the strength and direction of the intraspecific relationship between temperature and individual mass for 952 bird and mammal species. For eighty-seven percent of species, temperature explained less than 10% of variation in mass, and for 79% of species the correlation was not statistically significant. These results suggest that Bergmanns rule is not general and temperature is not a dominant driver of biogeographic variation in mass. Further understanding of size variation will require integrating multiple processes that influence size. The lack of dominant temperature forcing weakens the justification for the hypothesis that global warming could result in widespread decreases in body size.

ecology↗