Shading and Watering as a Tool to Mitigate the Impacts of Climate Change in Sea Turtle Nests

Increasing sand temperatures resulting from climate change may negatively impact sea turtle nests by altering sex ratios and decreasing reproductive output. We analyzed the effect of nest shading and watering on sand temperatures as climate mitigation strategies in a beach hatchery at Playa Grande, Costa Rica. We set up plots and placed thermocouples at depths of 45cm and 75cm. Half of the plots were shaded and half were exposed to the sun. Within these exposure treatments, we applied three watering treatments over one month, replicating local climatic conditions experienced in this area. We also examined gravimetric water content of sand by collecting sand samples the day before watering began, the day after watering was complete, and one month after completion. Shading had the largest impact on sand temperature, followed by watering and depth. All watering treatments lowered sand temperature, but the effect varied with depth. Temperatures in plots that received water returned to control levels within 10 days after watering stopped. Water content increased at both depths in the two highest water treatments, and 30 days after the end of water application remained higher than plots with low water. While the impacts of watering on sand temperature dissipate rapidly after the end of application, the impacts on water content are much more lasting. Although less effective at lowering sand temperatures than shading, watering may benefit sea turtle clutches by offsetting negative impacts of low levels of rain in particularly dry areas. Prior to implementing such strategies, the natural conditions at the location of interest (e.g. clutch depth, environmental conditions, and beach characteristics) and natural hatchling sex ratios should be taken into consideration. These results provide insight into the effectiveness of nest shading and watering as climate mitigation techniques and illustrate important points of consideration in the crafting of such strategies.     

Occupancy Modeling for Improved Accuracy and Understanding of Pathogen Prevalence and Dynamics

Most pathogen detection tests are imperfect, with a sensitivity < 100%, thereby resulting in the potential for a false negative, where a pathogen is present but not detected. False negatives in a sample inflate the number of non-detections, negatively biasing estimates of pathogen prevalence. Histological examination of tissues as a diagnostic test can be advantageous as multiple pathogens can be examined and providing important information on associated pathological changes to the host. However, it is usually less sensitive than molecular or microbiological tests for specific pathogens. Our study objectives were to 1) develop a hierarchical occupancy model to examine pathogen prevalence in spring Chinook salmon Oncorhynchus tshawytscha and their distribution among host tissues 2) use the model to estimate pathogen-specific test sensitivities and infection rates, and 3) illustrate the effect of using replicate within host sampling on sample sizes required to detect a pathogen. We examined histological sections of replicate tissue samples from spring Chinook salmon O. tshawytscha collected after spawning for common pathogens seen in this population: Apophallus/echinostome metacercariae, Parvicapsula minibicornis, Nanophyetus salmincola/ metacercariae, and Renibacterium salmoninarum. A hierarchical occupancy model was developed to estimate pathogen and tissue-specific test sensitivities and unbiased estimation of host- and organ-level infection rates. Model estimated sensitivities and host- and organ-level infections rates varied among pathogens and model estimated infection rate was higher than prevalence unadjusted for test sensitivity, confirming that prevalence unadjusted for test sensitivity was negatively biased. The modeling approach provided an analytical approach for using hierarchically structured pathogen detection data from lower sensitivity diagnostic tests, such as histology, to obtain unbiased pathogen prevalence estimates with associated uncertainties. Accounting for test sensitivity using within host replicate samples also required fewer individual fish to be sampled. This approach is useful for evaluating pathogen or microbe community dynamics when test sensitivity is <100%.     

Exploring the Gastrointestinal “Nemabiome”: Deep Amplicon Sequencing to Quantify the Species Composition of Parasitic Nematode Communities

Parasitic helminth infections have a considerable impact on global human health as well as animal welfare and production. Although co-infection with multiple parasite species within a host is common, there is a dearth of tools with which to study the composition of these complex parasite communities. Helminth species vary in their pathogenicity, epidemiology and drug sensitivity and the interactions that occur between co-infecting species and their hosts are poorly understood. We describe the first application of deep amplicon sequencing to study parasitic nematode communities as well as introduce the concept of the gastro-intestinal “nemabiome”. The approach is analogous to 16S rDNA deep sequencing used to explore microbial communities, but utilizes the nematode ITS-2 rDNA locus instead. Gastro-intestinal parasites of cattle were used to develop the concept, as this host has many well-defined gastro-intestinal nematode species that commonly occur as complex co-infections. Further, the availability of pure mono-parasite populations from experimentally infected cattle allowed us to prepare mock parasite communities to determine, and correct for, species representation biases in the sequence data. We demonstrate that, once these biases have been corrected, accurate relative quantitation of gastro-intestinal parasitic nematode communities in cattle fecal samples can be achieved. We have validated the accuracy of the method applied to field-samples by comparing the results of detailed morphological examination of L3 larvae populations with those of the sequencing assay. The results illustrate the insights that can be gained into the species composition of parasite communities, using grazing cattle in the mid-west USA as an example. However, both the technical approach and the concept of the ‘nemabiome’ have a wide range of potential applications in human and veterinary medicine. These include investigations of host-parasite and parasite-parasite interactions during co-infection, parasite epidemiology, parasite ecology and the response of parasite populations to both drug treatments and control programs.     

Temporal fluctuations and experimental effects in desert plant communities

In the Chihuahuan Desert of the southwestern United States we monitored responses of both winter and summer annual plant communities to natural environmental variation and to experimental removal of seed-eating rodents and ants for 13 years. Analyses of data on population densities of the species by principal component analysis (PCA) followed by repeated measures analysis of variance (rmANOVA) on PCA scores showed that: (1) composition of both winter and summer annual communities varied substantially from year to year, presumably in response to interannual climatic variation, and (2) community composition of winter annuals was also significantly affected by the experimental manipulations of seed-eating animals, but the composition of the summer annual community showed no significant response to these experimental treatments. Canonical discriminant analysis (CDA) was then applied to the data for winter annuals to more clearly identify the responses to the different classes of experimental manipulations. This analysis showed that removing rodents or ants or both taxa caused distinctive changes in species composition. There was a tendency for large-seeded species to increase on rodent removal plots and to decrease on ant removal plots, and for small-seeded species to change in the opposite direction. In the winter annual community there was a significant time x treatment interaction: certain combinations of species that responded differently to removal of granivores also showed opposite fluctuations in response to long-term climatic variation. The large year-to-year variation in the summer annual community was closely and positively correlated across all experimental treatments. The use of multivariate analysis in conjunction with long-term monitoring and experimental manipulation shows how biotic interactions interact with variation in abiotic conditions to affect community dynamics.     

Annual Records of Airborne Pollen of Poaceae in Five Areas in Lagos,Nigeria

Poaceae pollen grains are known to be highly allergenic and they are potential causes of allergic respiratory diseases. In order to investigate the incidence of airborne Poaceae, and contribute to current trends in the development of aeropalynology/allergy studies in Nigeria, five highly populated locations in Central Lagos State, Surulere, Ebute-Metta, University of Lagos, Bariga and Gbagada, were sampled. Gravimetric aerosamples were collected monthly from January 2013 to December 2014. The lowest count in 2013 was recorded in the Ebute-Metta area (179), while the highest in 2013 was recorded in Gbagada (564). In 2014, the Surulere area (282) had the lowest count while Bariga (671) had the highest. The locations have similar monthly pollen distribution pattern but different peak months. Generally, Poaceae pollen counts were lowest in the months of June and July. These are therefore the safest months for Poaceae pollen hypersensitive individuals in the study areas. Relative humidity was the most important meteorological parameter with significant correlations in Ebute-Metta and Bariga locations. Results from this work will form the basis for a forecast service required to inform and educate the general public and allergy sufferers about Poaceae pollen distribution in Lagos State.