Dust storms increase the tolerance of phytoplankton to thermal and pH changes.

Aquatic communities are increasingly subjected to multiple stressors through global change, including warming, pH shifts, and elevated nutrient concentrations. These stressors often surpass species tolerance range, leading to unpredictable consequences for aquatic communities and ecosystem functioning. Phytoplankton, as the foundation of the aquatic food web, play a crucial role in controlling water quality and the transfer of nutrients and energy to higher trophic levels. Despite the significance in understanding the effect of multiple stressors, further research is required to explore the combined impact of multiple stressors on phytoplankton. In this study, we used a combination of crossed experiment and mechanistic model to analyze the ecological and biogeochemical effects of global change on aquatic ecosystems and to forecast phytoplankton dynamics. We examined the effect of dust (0-75 mg L-1 ), temperature (19-27°C), and pH (6.3-7.3) on the growth rate of the algal species Scenedesmus obliquus. Furthermore, we carried out a geospatial analysis to identify regions of the planet where aquatic systems could be most affected by atmospheric dust deposition. Our mechanistic model and our empirical data show that dust exerts a positive effect on phytoplankton growth rate, broadening its thermal and pH tolerance range. Finally, our geospatial analysis identifies several high-risk areas including the highlands of the Tibetan Plateau, western United States, South America, central and southern Africa, central Australia as well as the Mediterranean region where dust-induced changes are expected to have the greatest impacts. Overall, our study shows that increasing dust storms associated with a more arid climate and land degradation can reverse the negative effects of high temperatures and low pH on phytoplankton growth, affecting the biogeochemistry of aquatic ecosystems and their role in the cycles of the elements and tolerance to global change.

Warming increased bark beetle-induced tree mortality by 30% during an extreme drought in California.

Quantifying the responses of forest disturbances to climate warming is critical to our understanding of carbon cycles and energy balances of the Earth system. The impact of warming on bark beetle outbreaks is complex as multiple drivers of these events may respond differently to warming. Using a novel model of bark beetle biology and host tree interactions, we assessed how contemporary warming affected western pine beetle (Dendroctonus brevicomis) populations and mortality of its host, ponderosa pine (Pinus ponderosa), during an extreme drought in the Sierra Nevada, California, United States. When compared with the field data, our model captured the western pine beetle flight timing and rates of ponderosa pine mortality observed during the drought. In assessing the influence of temperature on western pine beetles, we found that contemporary warming increased the development rate of the western pine beetle and decreased the overwinter mortality rate of western pine beetle larvae leading to increased population growth during periods of lowered tree defense. We attribute a 29.9% (95% CI: 29.4%-30.2%) increase in ponderosa pine mortality during drought directly to increases in western pine beetle voltinism (i.e., associated with increased development rates of western pine beetle) and, to a much lesser extent, reductions in overwintering mortality. These findings, along with other studies, suggest each degree (°C) increase in temperature may have increased the number of ponderosa pine killed by upwards of 35%-40% °C-1 if the effects of compromised tree defenses (15%-20%) and increased western pine beetle populations (20%) are additive. Due to the warming ability to considerably increase mortality through the mechanism of bark beetle populations, models need to consider climate's influence on both host tree stress and the bark beetle population dynamics when determining future levels of tree mortality.

The first assessment of the genetic diversity and structure of the endangered West Indian manatee in Cuba.

The coastal waters of Cuba are home to a small, endangered population of West Indian manatee, which would benefit from a comprehensive characterization of the population's genetic variation. We conducted the first genetic assessment of Cuban manatees to determine the extent of the population's genetic structure and characterize the neutral genetic diversity among regions within the archipelago. We genotyped 49 manatees at 18 microsatellite loci, a subset of 27 samples on 1703 single nucleotide polymorphisms (SNPs), and sequenced 59 manatees at the mitochondrial control region. The Cuba manatee population had low nuclear (microsatellites HE = 0.44, and SNP HE = 0.29) and mitochondrial genetic diversity (h = 0.068 and π = 0.00025), and displayed moderate departures from random mating (microsatellite FIS = 0.12, SNP FIS = 0.10). Our results suggest that the western portion of the archipelago undergoes periodic exchange of alleles based on the evidence of shared ancestry and low but significant differentiation. The southeast Guantanamo Bay region and the western portion of the archipelago were more differentiated than southwest and northwest manatees. The genetic distinctiveness observed in the southeast supports its recognition as a demographically independent unit for natural resource management regardless of whether it is due to historical isolation or isolation by distance. Estimates of the regional effective population sizes, with the microsatellite and SNP datasets, were small (all Ne < 60). Subsequent analyses using additional samples could better examine how the observed structure is masking simple isolation by distance patterns or whether ecological or biogeographic forces shape genetic patterns.

Oviposition Model for a Southern Population of Mountain Pine Beetle.

We develop a predictive oviposition model for a southern population of mountain pine beetle (MPB) using a previously developed rate curve, incorporating variation in both oviposition rate and fecundity. We also introduce a method for determining the time delay before oviposition. The model describes the probability of oviposition for a season of MPB attacks using hourly phloem temperature and adult MPB attack data. We also develop an asymptotic approximation of MPB oviposition that is much less computationally taxing. The detailed oviposition model and its asymptotic approximation are compared with other ovipositional models for MPB; the predictive capacity of each model is evaluated using previously published observations.

Progressive ultrastructural changes in the casein matrix during the ripening of inadequately acidified feta cheese.

This study investigated the ultrastructural changes underlying the undesired softening of insufficiently acidified feta cheese during cold storage. Experimental feta cheeses with a range of pH values before brining were manufactured by allowing the cheese blocks to ferment overnight at 3 temperatures (35, 20, and 3°C), which resulted in pH values of 4.80, 4.88, and 5.17, respectively. Cheese blocks were stored in pH-adjusted whey brine solutions for up to 120 d, at which point significant decreases in the cheese firmness were confirmed with compression and shear tests. Samples for transmission electron microscopy were taken during the make procedure, after overnight fermentation, and after 7 and 90 d of cold storage. Increasing the initial pH from 4.80 to 5.17 resulted in a fundamentally different ultrastructure at d 90, with the protein matrix as the continuous phase having markedly decreased density compared with the typically open porous and discontinuous protein matrix of high density in the low-pH control feta cheese. Ultrastructural changes were progressive, and the first signs were evident after only 20 h (the overnight fermentation), when fine, proteinaceous material dissociated from the edges of the casein strands into the serum phase. By d 7, the serum phase was completely filled with the loosely aggregated casein closely surrounding the spheroidal fat globules. A further breakdown of the protein matrix was observed after 90 d, with the complete loss of open porous network structure. Image analysis quantitatively confirmed the progressive and significant decrease in density of the protein matrix. In summary, this is the first study to provide a comprehensive and in-depth view of the progressive and most likely irreversible ultrastructural changes that lead to this textural defect.

Differential dispersal and the Allee effect create power-law behaviour: Distribution of spot infestations during mountain pine beetle outbreaks.

Mountain pine beetles (MPB, Dendroctonus ponderosae Hopkins) are aggressive insects attacking Pinus host trees. Pines use defensive resin to overwhelm attackers, creating an Allee effect requiring beetles to attack en masse to successfully reproduce. MPB kill hosts, leaving observable, dying trees with red needles. Landscape patterns of infestation depend on MPB dispersal, which decreases with host density. Away from contiguously impacted patches (low beetle densities), infestations are characterized by apparently random spots (of 1-10 trees). It remains unclear whether the new spots are spatially random eruptions of a locally endemic population or a mode of MPB spread, with spatial distribution determined by beetle motility and the need to overcome the Allee effect. To discriminate between the hypothesis of population spread versus independent eruption, a model of spot formation by dispersing beetles facing a local Allee effect is derived. The model gives rise to an inverse power distribution of travel times from existing outbreaks. Using landscape-level host density maps in three study areas, an independently calibrated model of landscape resistance depending on host density, and aerial detection surveys, we calculated yearly maps of travel time to previous beetle impact. Isolated beetle spots were sorted by travel time and compared with predictions. Random eruption of locally endemic populations was tested using artificially seeded spots. We also evaluated the relationship between number of new spots and length of the perimeter of previously infested areas. Spot distributions conformed strongly to predicted power-law behaviour. The spatially random eruption hypothesis was found to be highly improbable. Spot numbers grew consistently with perimeter of previously infested area, suggesting that MPB spread long distances from infestation boundaries via spots following an inverse power distribution. The Allee effect in MPB therefore accelerates, rather than limits, invasion rates, contributing to recent widespread landscape-scale mortality in western North America.

When mechanism matters: Bayesian forecasting using models of ecological diffusion.

Ecological diffusion is a theory that can be used to understand and forecast spatio-temporal processes such as dispersal, invasion, and the spread of disease. Hierarchical Bayesian modelling provides a framework to make statistical inference and probabilistic forecasts, using mechanistic ecological models. To illustrate, we show how hierarchical Bayesian models of ecological diffusion can be implemented for large data sets that are distributed densely across space and time. The hierarchical Bayesian approach is used to understand and forecast the growth and geographic spread in the prevalence of chronic wasting disease in white-tailed deer (Odocoileus virginianus). We compare statistical inference and forecasts from our hierarchical Bayesian model to phenomenological regression-based methods that are commonly used to analyse spatial occurrence data. The mechanistic statistical model based on ecological diffusion led to important ecological insights, obviated a commonly ignored type of collinearity, and was the most accurate method for forecasting.

Invasion speeds with active dispersers in highly variable landscapes: Multiple scales, homogenization, and the migration of trees.

The distribution of many tree species is strongly determined by the behavior and range of vertebrate dispersers, particularly birds. Many models for seed dispersal exist, and are built around the assumption that seeds undergo a random walk while they are being carried by vertebrates, either in the digestive tract or during the process of seed storage (caching). We use a PDF of seed handling (caching and digesting) times to model non-constant seed settling during dispersal, and model the random component of seed movement using ecological diffusion, in which animals make movement choices based purely on local habitat type instead of population gradients. Spatial variability in habitat directly affects the movement of dispersers and leads to anisotropic dispersal kernels. For birds, which can easily move many kilometers, habitat changes on the scale of tens of meters can viewed as rapidly varying. We introduce multiple scales and apply the method of homogenization to determine leading order solutions for the seed digestion kernel (SDK). Using an integrodifference equation (IDE) model for adult trees, we investigate the rate of forest migration. The existing theory for predicting spread rates in IDE does not apply when dispersal kernels are anisotropic. However, the homogenized SDK is isotropic on large scales and depends only on harmonically averaged motilities and modal rates of digestion. We show that speeds calculated using the harmonic average motility accurately predict rates of invasion for the spatially variable system.

Integrating models to investigate critical phenological overlaps in complex ecological interactions: the mountain pine beetle-fungus symbiosis.

The fates of individual species are often tied to synchronization of phenology, however, few methods have been developed for integrating phenological models involving linked species. In this paper, we focus on mountain pine beetle (MPB, Dendroctonus ponderosae) and its two obligate mutualistic fungi, Grosmannia clavigera and Ophiostoma montium. Growth rates of all three partners are driven by temperature, and their idiosyncratic responses affect interactions at important life stage junctures. One critical phase for MPB-fungus symbiosis occurs just before dispersal of teneral (new) adult beetles, when fungi are acquired and transported in specialized structures (mycangia). Before dispersal, fungi must capture sufficient spatial resources within the tree to ensure contact with teneral adults and get packed into mycangia. Mycangial packing occurs at an unknown time during teneral feeding. We adapt thermal models predicting fungal growth and beetle development to predict overlap between the competing fungi and MPB teneral adult feeding windows and emergence. We consider a spectrum of mycangial packing strategies and describe them in terms of explicit functions with unknown parameters. Rates of growth are fixed by laboratory data, the unknown parameters describing various packing strategies, as well as the degree to which mycangial growth is slowed in woody tissues as compared to agar, are determined by maximum likelihood and two years of field observations. At the field location used, the most likely fungus acquisition strategy for MPB was packing mycangia just prior to emergence. Estimated model parameters suggested large differences in the relative growth rates of the two fungi in trees at the study site, with the most likely model estimating that G. clavigera grew approximately twenty-five times faster than O. montium under the bark, which is completely unexpected in comparison with observed fungal growth on agar.

A Model for Mountain Pine Beetle Outbreaks in an Age-Structured Forest: Predicting Severity and Outbreak-Recovery Cycle Period.

The mountain pine beetle (MPB, Dendroctonus ponderosae), a tree-killing bark beetle, has historically been part of the normal disturbance regime in lodgepole pine (Pinus contorta) forests. In recent years, warm winters and summers have allowed MPB populations to achieve synchronous emergence and successful attacks, resulting in widespread population outbreaks and resultant tree mortality across western North America. We develop an age-structured forest demographic model that incorporates temperature-dependent MPB infestations. Stability of fixed points is analyzed as a function of (thermally controlled) MPB population growth rates and indicates the existence of periodic outbreaks that intensify as growth rates increase. We devise analytical methods to predict outbreak severity and duration as well as outbreak return time. After incorporating a spatial aspect and controlling initial stand demographic variation, the model predicts cycle periods that fall within observed outbreak return time ranges. To assess future MPB impact on forests, we use climate model projected temperatures with our model-based approximation methods to predict potential severity of future outbreaks that reflect the effects of changing climate.

Mountain pine beetle seasonal timing and constraints to bivoltinism.

Mountain pine beetle tree colonization typically occurs in July and August, with completion of a generation one (univoltinism) or two (semivoltinism) years later. In a 2012 publication, Mitton and Ferrenberg suggested that climate change resulted in an unprecedented generation between June and September (a summer generation), with a concomitant shift to two generations in one year (bivoltinism). Although summer generations are not uncommon in this species, completion of a second generation across winter, between September and June, would be required for bivoltinism, a phenomenon not previously observed. Mitton and Ferrenberg showed that a summer generation can occur, but they failed to adequately track cohorts and provided no compelling evidence for bivoltinism. We demonstrate that a winter generation-and hence bivoltinism-would have been physiologically impossible at the high-elevation site used in Mitton and Ferrenberg due to lower thermal developmental thresholds. The mountain pine beetle is indeed being influenced by climate change. To address the challenges of future population outbreaks of this significant tree mortality agent, however, it is imperative to consider evolved, thermally dependent traits that serve to maintain seasonality.

Homogenization, sex, and differential motility predict spread of chronic wasting disease in mule deer in southern Utah.

Chronic wasting disease (CWD) is an infectious prion disease that affects mule deer, along with other Cervids. It is a slow-developing, fatal disease which is rare in the free-ranging deer population of Utah. We present a sex-structured, spatial model for the spread of CWD over heterogeneous landscapes, incorporating both horizontal and environmental transmission pathways. To connect the local movement of deer to the regional spread of CWD, we use ecological diffusion with motility coefficients estimated from mule deer movement data. Ecological diffusion allows for aggregation of populations in desirable habitats and therefore allows for an interaction between density dependent disease transmission and landscape structure. The major innovation presented is use of homogenization to accelerate simulations of disease spread in southeastern Utah, from the La Sal Mountains near Moab to the Abajo Mountains near Monticello. The homogenized model provides accuracy while maintaining fidelity to small-scale habitat effects on deer distribution, including differential aggregation in land cover types with high residence times, with errors comparable to the order parameter measuring separation of small and large scales ([Formula: see text] in this case). We use the averaged coefficients from the homogenized model to explore asymptotic invasion speed and the impact of current population size on disease spread in southeastern Utah.

Body size mediated coexistence in swans.

Differences in body sizes may create a trade-off between foraging efficiency (foraging gains/costs) and access to resources. Such a trade-off provides a potential mechanism for ecologically similar species to coexist on one resource. We explored this hypothesis for tundra (Cygnus columbianus) and trumpeter swans (Cygnus buccinator), a federally protected species, feeding solely on sago pondweed (Stuckenia pectinata) tubers during fall staging and wintering in northern Utah. Foraging efficiency was higher for tundra swans because this species experienced lower foraging and metabolic costs relative to foraging gains; however, trumpeter swans (a) had longer necks and therefore had access to exclusive resources buried deep in wetland sediments and (b) were more aggressive and could therefore displace tundra swans from lucrative foraging locations. We conclude that body size differentiation is an important feature of coexistence among ecologically similar species feeding on one resource. In situations where resources are limiting and competition for resources is strong, conservation managers will need to consider the trade-off between foraging efficiency and access to resources to ensure ecologically similar species can coexist on a shared resource.

Blood mineral concentrations in manatees (Trichechus manatus latirostris and Trichechus manatus manatus).

Limited information is available regarding the role of minerals and heavy metals in the morbidity and mortality of manatees. Whole-blood and serum mineral concentrations were evaluated in apparently healthy, free-ranging Florida (Trichechus manatus latirostris, n = 31) and Belize (Trichechus manatus manatus, n = 14) manatees. Toxicologic statuses of the animals and of their environment had not been previously determined. Mean mineral whole-blood (WB) and serum values in Florida (FL) and Belize (BZ) manatees were determined, and evaluated for differences with respect to geographic location, relative age, and sex. Mean WB and serum silver, boron, cobalt, magnesium, molybdenum, and WB cadmium concentrations were significantly higher in BZ versus FL manatees (P < 0.05). Mean WB aluminum, calcium, manganese, sodium, phosphorus, vanadium, and serum zinc concentrations were significantly lower in BZ versus FL manatees. Adult manatees had significant and higher mean WB aluminum, manganese, sodium, antimony, vanadium, and serum manganese and zinc concentrations compared to juvenile animals. Significant and lower mean WB and serum silver, boron, cobalt, and serum copper and strontium concentrations were present in adults compared to juveniles (P < or = 0.05). Females had significant and higher mean WB nickel and serum barium compared to males (P < or = 0.05). Mean WB arsenic and zinc, and mean serum iron, magnesium, and zinc concentrations fell within toxic ranges reported for domestic species. Results reveal manatee blood mineral concentrations differ with location, age, and sex. Influence from diet, sediment, water, and anthropogenic sources on manatee mineral concentration warrant further investigation.

Carrying BioMath education in a Leaky Bucket.

In this paper, we describe a project-based mathematical lab implemented in our Applied Mathematics in Biology course. The Leaky Bucket Lab allows students to parameterize and test Torricelli's law and develop and compare their own alternative models to describe the dynamics of water draining from perforated containers. In the context of this lab students build facility in a variety of applied biomathematical tools and gain confidence in applying these tools in data-driven environments. We survey analytic approaches developed by students to illustrate the creativity this encourages as well as prepare other instructors to scaffold the student learning experience. Pedagogical results based on classroom videography support the notion that the Biology-Applied Math Instructional Model, the teaching framework encompassing the lab, is effective in encouraging and maintaining high-level cognition among students. Research-based pedagogical approaches that support the lab are discussed.

Streamlined process for the chemical synthesis of RNA using 2'-O-thionocarbamate-protected nucleoside phosphoramidites in the solid phase.

An improved method for the chemical synthesis of RNA was developed utilizing a streamlined method for the preparation of phosphoramidite monomers and a single-step deprotection of the resulting oligoribonucleotide product using 1,2-diamines under anhydrous conditions. The process is compatible with most standard heterobase protection and employs a 2'-O-(1,1-dioxo-1λ(6)-thiomorpholine-4-carbothioate) as a unique 2'-hydroxyl protective group. Using this approach, it was demonstrated that the chemical synthesis of RNA can be as simple and robust as the chemical synthesis of DNA.

Homogenization of large-scale movement models in ecology.

A difficulty in using diffusion models to predict large scale animal population dispersal is that individuals move differently based on local information (as opposed to gradients) in differing habitat types. This can be accommodated by using ecological diffusion. However, real environments are often spatially complex, limiting application of a direct approach. Homogenization for partial differential equations has long been applied to Fickian diffusion (in which average individual movement is organized along gradients of habitat and population density). We derive a homogenization procedure for ecological diffusion and apply it to a simple model for chronic wasting disease in mule deer. Homogenization allows us to determine the impact of small scale (10-100 m) habitat variability on large scale (10-100 km) movement. The procedure generates asymptotic equations for solutions on the large scale with parameters defined by small-scale variation. The simplicity of this homogenization procedure is striking when compared to the multi-dimensional homogenization procedure for Fickian diffusion,and the method will be equally straightforward for more complex models.

Modeling the effects of developmental variation on insect phenology.

Phenology, the timing of developmental events such as oviposition or pupation, is highly dependent on temperature; since insects are ectotherms, the time it takes them to complete a life stage (development time) depends on the temperatures they experience. This dependence varies within and between populations due to variation among individuals that is fixed within a life stage (giving rise to what we call persistent variation) and variation from random effects within a life stage (giving rise to what we call random variation). It is important to understand how both types of variation affect phenology if we are to predict the effects of climate change on insect populations.We present three nested phenology models incorporating increasing levels of variation. First, we derive an advection equation to describe the temperature-dependent development of a population with no variation in development time. This model is extended to incorporate persistent variation by introducing a developmental phenotype that varies within a population, yielding a phenotype-dependent advection equation. This is further extended by including a diffusion term describing random variation in a phenotype-dependent Fokker-Planck development equation. These models are also novel because they are formulated in terms of development time rather than developmental rate; development time can be measured directly in the laboratory, whereas developmental rate is calculated by transforming laboratory data. We fit the phenology models to development time data for mountain pine beetles (MPB) (Dendroctonus ponderosae Hopkins [Coleoptera: Scolytidae]) held at constant temperatures in laboratory experiments. The nested models are parameterized using a maximum likelihood approach. The results of the parameterization show that the phenotype-dependent advection model provides the best fit to laboratory data, suggesting that MPB phenology may be adequately described in terms of persistent variation alone. MPB phenology is simulated using phloem temperatures and attack time distributions measured in central Idaho. The resulting emergence time distributions compare favorably to field observations.

Leading students to investigate diffusion as a model of brine shrimp movement.

Integrating experimental biology laboratory exercises with mathematical modeling can be an effective tool to enhance mathematical relevance for biologists and to emphasize biological realism for mathematicians. This paper describes a lab project designed for and tested in an undergraduate biomathematics course. In the lab, students follow and track the paths of individual brine shrimp confined in shallow salt water in a Petri dish. Students investigate the question, "Is the movement well characterized as a 2-dimensional random walk?" Through open, but directed discussions, students derive the corresponding partial differential equation, gain an understanding of the solution behavior, and model brine shrimp dispersal under the experimental conditions developed in class. Students use data they collect to estimate a diffusion coefficient, and perform additional experiments of their own design tracking shrimp migration for model validation. We present our teaching philosophy, lecture notes, instructional and lab procedures, and the results of our class-tested experiments so that others can implement this exercise in their classes. Our own experience has led us to appreciate the pedagogical value of allowing students and faculty to grapple with open-ended questions, imperfect data, and the various issues of modeling biological phenomena.

Modeling the evolution of insect phenology.

Climate change is likely to disrupt the timing of developmental events (phenology) in insect populations in which development time is largely determined by temperature. Shifting phenology puts insects at risk of being exposed to seasonal weather extremes during sensitive life stages and losing synchrony with biotic resources. Additionally, warming may result in loss of developmental synchronization within a population making it difficult to find mates or mount mass attacks against well-defended resources at low population densities. It is unknown whether genetic evolution of development time can occur rapidly enough to moderate these effects. We present a novel approach to modeling the evolution of phenology by allowing the parameters of a phenology model to evolve in response to selection on emergence time and density. We use the Laplace method to find asymptotic approximations for the temporal variation in mean phenotype and phenotypic variance arising in the evolution model that are used to characterize invariant distributions of the model under periodic temperatures at leading order. At these steady distributions the mean phenotype allows for parents and offspring to be oviposited at the same time of year in consecutive years. Numerical simulations show that populations evolve to these steady distributions under periodic temperatures. We consider an example of how the evolution model predicts populations will evolve in response to warming temperatures and shifting resource phenology.