Correlation of Ambient Temperature With Feedlot Cattle Morbidity and Mortality in the Texas Panhandle.

Anecdotal data would suggest that weather patterns influence beef cattle health in feedyards, and cattle producers often associate the seasonality of some illnesses with changes in environmental temperatures. However, to our knowledge, there is little information from large-scale feeding operations and precision weather stations that establishes a link or lack thereof between weather patterns and cattle health. Additionally, we are unaware of any studies correlating other weather parameters with animal health data. Therefore, the objective of this study was to test for associations between monthly temperature variation and animal morbidity/mortality in feedlots in the Texas Panhandle. Weather data was collected from a Texas Tech University Mesonet weather station in close proximity to 19 beef cattle feedyards in the Texas Panhandle. Additionally, near real-time morbidity and mortality data was collected from those yards from 2015 to 2018. These data document a seasonal pattern relative to cattle morbidity and mortality with most health events occurring from November to January. This pattern is differentiated when comparing morbidity and mortality by listed causation (e.g., respiratory, digestive, other), and the majority of deaths over the entire time course were attributed to respiratory disease. Most cattle morbidity was documented in the winter months, most of which were classified as respiratory disorders. Additionally, an increase in health events was observed as the population of the feedyard increased. However, the overall effects of ambient temperature on cattle health were minimal and the two may not be causally linked. The initial overview of the relationships documented in this manuscript may warrant further stratification and exploration.

Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise.

The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much public and scientific attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible unforced states of the climate system (the Envelope of Unforced Noise; EUN). Typically, the EUN is derived from climate models themselves, but climate models might not accurately simulate the correct characteristics of unforced GMT variability. Here, we simulate a new, empirical, EUN that is based on instrumental and reconstructed surface temperature records. We compare the forced GMT signal produced by climate models to observations while noting the range of GMT values provided by the empirical EUN. We find that the empirical EUN is wide enough so that the interdecadal variability in the rate of global warming over the 20(th) century does not necessarily require corresponding variability in the rate-of-increase of the forced signal. The empirical EUN also indicates that the reduced GMT warming over the past decade or so is still consistent with a middle emission scenario's forced signal, but is likely inconsistent with the steepest emission scenario's forced signal.

The rehydration transcriptome of the desiccation-tolerant bryophyte Tortula ruralis: transcript classification and analysis.

BACKGROUND: The cellular response of plants to water-deficits has both economic and evolutionary importance directly affecting plant productivity in agriculture and plant survival in the natural environment. Genes induced by water-deficit stress have been successfully enumerated in plants that are relatively sensitive to cellular dehydration, however we have little knowledge as to the adaptive role of these genes in establishing tolerance to water loss at the cellular level. Our approach to address this problem has been to investigate the genetic responses of plants that are capable of tolerating extremes of dehydration, in particular the desiccation-tolerant bryophyte, Tortula ruralis. To establish a sound basis for characterizing the Tortula genome in regards to desiccation tolerance, we analyzed 10,368 expressed sequence tags (ESTs) from rehydrated rapid-dried Tortula gametophytes, a stage previously determined to exhibit the maximum stress induced change in gene expression. RESULTS: The 10, 368 ESTs formed 5,563 EST clusters (contig groups representing individual genes) of which 3,321 (59.7%) exhibited similarity to genes present in the public databases and 2,242 were categorized as unknowns based on protein homology scores. The 3,321 clusters were classified by function using the Gene Ontology (GO) hierarchy and the KEGG database. The results indicate that the transcriptome contains a diverse population of transcripts that reflects, as expected, a period of metabolic upheaval in the gametophyte cells. Much of the emphasis within the transcriptome is centered on the protein synthetic machinery, ion and metabolite transport, and membrane biosynthesis and repair. Rehydrating gametophytes also have an abundance of transcripts that code for enzymes involved in oxidative stress metabolism and phosphorylating activities. The functional classifications reflect a remarkable consistency with what we have previously established with regards to the metabolic activities that are important in the recovery of the gametophytes from desiccation. A comparison of the GO distribution of Tortula clusters with an identical analysis of 9,981 clusters from the desiccation sensitive bryophyte species Physcomitrella patens, revealed, and accentuated, the differences between stressed and unstressed transcriptomes. Cross species sequence comparisons indicated that on the whole the Tortula clusters were more closely related to those from Physcomitrella than Arabidopsis (complete genome BLASTx comparison) although because of the differences in the databases there were more high scoring matches to the Arabidopsis sequences. The most abundant transcripts contained within the Tortula ESTs encode Late Embryogenesis Abundant (LEA) proteins that are normally associated with drying plant tissues. This suggests that LEAs may also play a role in recovery from desiccation when water is reintroduced into a dried tissue. CONCLUSION: The establishment of a rehydration EST collection for Tortula ruralis, an important plant model for plant stress responses and vegetative desiccation tolerance, is an important step in understanding the genome level response to cellular dehydration. The type of transcript analysis performed here has laid the foundation for more detailed functional and genome level analyses of the genes involved in desiccation tolerance in plants.