Is my study system good enough? A case study for identifying maternal effects

In this paper, we demonstrate how simulation studies can be used to answer questions about identifiability and consequences of omitting effects from a model. The methodology is presented through a case study where identifiability of genetic and/or individual (environmental) maternal effects is explored. Our study system is a wild house sparrow (Passer domesticus) population with known pedigree. We fit pedigree‐based (generalized) linear mixed models (animal models), with and without additive genetic and individual maternal effects, and use deviance information criterion (DIC) for choosing between these models. Pedigree and R‐code for simulations are available. For this study system, the simulation studies show that only large maternal effects can be identified. The genetic maternal effect (and similar for individual maternal effect) has to be at least half of the total genetic variance to be identified. The consequences of omitting a maternal effect when it is present are explored. Our results indicate that the total (genetic and individual) variance are accounted for. When an individual (environmental) maternal effect is omitted from the model, this only influences the estimated (direct) individual (environmental) variance. When a genetic maternal effect is omitted from the model, both (direct) genetic and (direct) individual variance estimates are overestimated.     

Batesian mimics influence the evolution of conspicuousness in an aposematic salamander

Conspicuousness, or having high contrast relative to the surrounding background, is a common feature of unpalatable species. Several hypotheses have been proposed to explain the occurrence of conspicuousness, and while most involve the role of conspicuousness as a direct signal of unpalatability to potential predators, one hypothesis suggests that exaggerated conspicuousness may evolve in unpalatable species to reduce predator confusion with palatable species (potential Batesian mimics). This hypothesis of antagonistic coevolution between palatable and unpalatable species hinges on the ‘cost of conspicuousness’, in which conspicuousness increases the likelihood of predation more in palatable species than in unpalatable species. Under this mimicry scenario, four patterns are expected: (i) mimics will more closely resemble local models than models from other localities, (ii) there will be a positive relationship between mimic and model conspicuousness, (iii) models will be more conspicuous in the presence of mimics, and (iv) when models and mimics differ in conspicuousness, mimics will be less conspicuous than models. We tested these predictions in the salamander mimicry system involving Notophthalmus viridescens (model) and one colour morph of Plethodon cinereus (mimic). All predictions were supported, indicating that selection for Batesian mimicry not only influences the evolution of mimics, but also the evolution of the models they resemble. These findings indicate that mimicry plays a large role in the evolution of model warning signals, particularly influencing the evolution of conspicuousness.     

Hybridization selects for prime‐numbered life cycles in Magicicada: An individual‐based simulation model of a structured periodical cicada population

We investigate competition between separate periodical cicada populations each possessing different life‐cycle lengths. We build an individual‐based model to simulate the cicada life cycle and allow random migrations to occur between patches inhabited by the different populations. We show that if hybridization between different cycle lengths produces offspring that have an intermediate life‐cycle length, then predation acts disproportionately to select against the hybrid offspring. This happens because they emerge in low densities without the safety‐in‐numbers provided by either parent population. Thus, prime‐numbered life cycles that can better avoid hybridization are favored. However, we find that this advantage of prime‐numbered cycles occurs only if there is some mechanism that can occasionally synchronize emergence between local populations in sufficiently many patches.     

Age‐ and temperature‐dependent oviposition model of Neoseiulus californicus (McGregor) (Acari: Phytoseiidae) with Tetranychus urticae as prey

In this study, we developed an oviposition model of Neoseiulus californicus (McGregor) with Tetranychus urticae Koch as prey. To obtain data for the model, we investigated the longevity, fecundity and survivorship of adult female N. californicus at six constant temperatures (16, 20, 24, 28, 32 and 36°C), 60–70% RH and a photoperiod of 16 : 8 (L : D) h. Longevity (average ± SE) decreased as temperature increased and was longest at 16°C (46.7 ± 5.25 days) and shortest at 36°C (12.8 ± 0.75 days). Adult developmental rate (1/average longevity) was described by the Lactin 1 model (r² = 0.95). The oviposition period (average±SE) was also longest at 16°C (29.8 ± 2.93 days) and shortest at 36°C (6.7 ± 0.54 days). Fecundity (average±SE) was greatest at 24°C (43.8 ± 3.23 eggs) and lowest at 36°C (15.9 ± 1.50 eggs). The oviposition model comprised temperature‐dependent fecundity, age‐specific cumulative oviposition rate and age‐specific survival rate functions. The temperature‐dependent fecundity was best described by an exponential equation (r² = 0.81). The age‐specific cumulative oviposition rate was best described by the three‐parameter Weibull function (r² = 0.96). The age‐specific survival rate was best described by a reverse sigmoid function (r² = 0.85).     

Global change‐type drought‐induced tree mortality: vapor pressure deficit is more important than temperature per se in causing decline in tree health

Drought‐induced tree mortality is occurring across all forested continents and is expected to increase worldwide during the coming century. Regional‐scale forest die‐off influences terrestrial albedo, carbon and water budgets, and land‐surface energy partitioning. Although increased temperatures during drought are widely identified as a critical contributor to exacerbated tree mortality associated with “global‐change‐type drought”, corresponding changes in vapor pressure deficit (D) have rarely been considered explicitly and have not been disaggregated from that of temperature per se. Here, we apply a detailed mechanistic soil–plant–atmosphere model to examine the impacts of drought, increased air temperature (+2°C or +5°C), and increased vapor pressure deficit (D; +1 kPa or +2.5 kPa), singly and in combination, on net primary productivity (NPP) and transpiration and forest responses, especially soil moisture content, leaf water potential, and stomatal conductance. We show that increased D exerts a larger detrimental effect on transpiration and NPP, than increased temperature alone, with or without the imposition of a 3‐month drought. Combined with drought, the effect of increased D on NPP was substantially larger than that of drought plus increased temperature. Thus, the number of days when NPP was zero across the 2‐year simulation was 13 or 14 days in the control and increased temperature scenarios, but increased to approximately 200 days when D was increased. Drought alone increased the number of days of zero NPP to 88, but drought plus increased temperature did not increase the number of days. In contrast, drought and increased D resulted in the number of days when NPP = 0 increasing to 235 (+1 kPa) or 304 days (+2.5 kPa). We conclude that correct identification of the causes of global change‐type mortality events requires explicit consideration of the influence of D as well as its interaction with drought and temperature.     

Probabilistic accounting of uncertainty in forecasts of species distributions under climate change

Forecasts of species distributions under future climates are inherently uncertain, but there have been few attempts to describe this uncertainty comprehensively in a probabilistic manner. We developed a Monte Carlo approach that accounts for uncertainty within generalized linear regression models (parameter uncertainty and residual error), uncertainty among competing models (model uncertainty), and uncertainty in future climate conditions (climate uncertainty) to produce site‐specific frequency distributions of occurrence probabilities across a species' range. We illustrated the method by forecasting suitable habitat for bull trout (Salvelinus confluentus) in the Interior Columbia River Basin, USA, under recent and projected 2040s and 2080s climate conditions. The 95% interval of total suitable habitat under recent conditions was estimated at 30.1–42.5 thousand km; this was predicted to decline to 0.5–7.9 thousand km by the 2080s. Projections for the 2080s showed that the great majority of stream segments would be unsuitable with high certainty, regardless of the climate data set or bull trout model employed. The largest contributor to uncertainty in total suitable habitat was climate uncertainty, followed by parameter uncertainty and model uncertainty. Our approach makes it possible to calculate a full distribution of possible outcomes for a species, and permits ready graphical display of uncertainty for individual locations and of total habitat.     

Improving our understanding of environmental controls on the distribution of C3 and C4 grasses

A number of studies have demonstrated the ecological sorting of C₃ and C₄ grasses along temperature and moisture gradients. However, previous studies of C₃ and C₄ grass biogeography have often inadvertently compared species in different and relatively unrelated lineages, which are associated with different environmental settings and distinct adaptive traits. Such confounded comparisons of C₃ and C₄ grasses may bias our understanding of ecological sorting imposed strictly by photosynthetic pathway. Here, we used MaxEnt species distribution modeling in combination with satellite data to understand the functional diversity of C₃ and C₄ grasses by comparing both large clades and closely related sister taxa. Similar to previous work, we found that C₄ grasses showed a preference for regions with higher temperatures and lower precipitation compared with grasses using the C₃ pathway. However, air temperature differences were smaller (2 °C vs. 4 °C) and precipitation and % tree cover differences were larger (1783 mm vs. 755 mm, 21.3% vs. 7.7%, respectively) when comparing C₃ and C₄ grasses within the same clade vs. comparing all C₄ and all C₃ grasses (i.e., ignoring phylogenetic structure). These results were due to important differences in the environmental preferences of C₃ BEP and PACMAD clades (the two main grass clades). Winter precipitation was found to be more important for understanding the distribution and environmental niche of C₃ PACMADs in comparison with both C₃ BEPs and C₄ taxa, for which temperature was much more important. Results comparing closely related C₃–C₄ sister taxa supported the patterns derived from our modeling of the larger clade groupings. Our findings, which are novel in comparing the distribution and niches of clades, demonstrate that the evolutionary history of taxa is important for understanding the functional diversity of C₃ and C₄ grasses, and should have implications for how grasslands will respond to global change.     

Genetic demography at the leading edge of the distribution of a rabies virus vector

The common vampire bat, Desmodus rotundus, ranges from South America into northern Mexico in North America. This sanguivorous species of bat feeds primarily on medium to large‐sized mammals and is known to rely on livestock as primary prey. Each year, there are hotspot areas of D. rotundus‐specific rabies virus outbreaks that lead to the deaths of livestock and economic losses. Based on incidental captures in our study area, which is an area of high cattle mortality from D. rotundus transmitted rabies, it appears that D. rotundus are being caught regularly in areas and elevations where they previously were thought to be uncommon. Our goal was to investigate demographic processes and genetic diversity at the north eastern edge of the range of D. rotundus in Mexico. We generated control region sequences (441 bp) and 12‐locus microsatellite genotypes for 602 individuals of D. rotundus. These data were analyzed using network analyses, Bayesian clustering approaches, and standard population genetic statistical analyses. Our results demonstrate panmixia across our sampling area with low genetic diversity, low population differentiation, loss of intermediate frequency alleles at microsatellite loci, and very low mtDNA haplotype diversity with all haplotypes being very closely related. Our study also revealed strong signals of population expansion. These results follow predictions from the leading‐edge model of expanding populations and supports conclusions from another study that climate change may allow this species to find suitable habitat within the U.S. border.     

Lizards fail to plastically adjust nesting behavior or thermal tolerance as needed to buffer populations from climate warming

Although observations suggest the potential for phenotypic plasticity to allow adaptive responses to climate change, few experiments have assessed that potential. Modeling suggests that Sceloporus tristichus lizards will need increased nest depth, shade cover, or embryonic thermal tolerance to avoid reproductive failure resulting from climate change. To test for such plasticity, we experimentally examined how maternal temperatures affect nesting behavior and embryonic thermal sensitivity. The temperature regime that females experienced while gravid did not affect nesting behavior, but warmer temperatures at the time of nesting reduced nest depth. Additionally, embryos from heat‐stressed mothers displayed increased sensitivity to high‐temperature exposure. Simulations suggest that critically low temperatures, rather than high temperatures, historically limit development of our study population. Thus, the plasticity needed to buffer this population has not been under selection. Plasticity will likely fail to compensate for ongoing climate change when such change results in novel stressors.     

Glucose metabolism down‐regulates the uptake of 6‐(N‐(7‐nitrobenz‐2‐oxa‐1,3‐diazol‐4‐yl)amino)‐2‐deoxyglucose (6‐NBDG) mediated by glucose transporter 1 isoform (GLUT1): theory and simulations using the symmetric four‐state carrier model

The non‐metabolizable fluorescent glucose analogue 6‐(N‐(7‐nitrobenz‐2‐oxa‐1,3‐diazol‐4‐yl)amino)‐2‐deoxyglucose (6‐NBDG) is increasingly used to study cellular transport of glucose. Intracellular accumulation of exogenously applied 6‐NBDG is assumed to reflect concurrent gradient‐driven glucose uptake by glucose transporters (GLUTs). Here, theoretical considerations are provided that put this assumption into question. In particular, depending on the microscopic parameters of the carrier proteins, theory proves that changes in glucose transport can be accompanied by opposite changes in flow of 6‐NBDG. Simulations were carried out applying the symmetric four‐state carrier model on the GLUT1 isoform, which is the only isoform whose kinetic parameters are presently available. Results show that cellular 6‐NBDG uptake decreases with increasing rate of glucose utilization under core‐model conditions, supported by literature, namely where the transporter is assumed to work in regime of slow reorientation of the free‐carrier compared with the ligand–carrier complex. To observe an increase of 6‐NBDG uptake with increasing rate of glucose utilization, and thus interpret 6‐NBDG increase as surrogate of glucose uptake, the transporter must be assumed to operate in regime of slow ligand–carrier binding, a condition that is currently not supported by literature. Our findings suggest that the interpretation of data obtained with NBDG derivatives is presently ambiguous and should be cautious because the underlying transport kinetics are not adequately established.     

Estimation of vegetation photosynthetic capacity from space‐based measurements of chlorophyll fluorescence for terrestrial biosphere models

Photosynthesis simulations by terrestrial biosphere models are usually based on the Farquhar's model, in which the maximum rate of carboxylation (V_cmax) is a key control parameter of photosynthetic capacity. Even though V_cmax is known to vary substantially in space and time in response to environmental controls, it is typically parameterized in models with tabulated values associated to plant functional types. Remote sensing can be used to produce a spatially continuous and temporally resolved view on photosynthetic efficiency, but traditional vegetation observations based on spectral reflectance lack a direct link to plant photochemical processes. Alternatively, recent space‐borne measurements of sun‐induced chlorophyll fluorescence (SIF) can offer an observational constraint on photosynthesis simulations. Here, we show that top‐of‐canopy SIF measurements from space are sensitive to V_cmax at the ecosystem level, and present an approach to invert V_cmax from SIF data. We use the Soil‐Canopy Observation of Photosynthesis and Energy (SCOPE) balance model to derive empirical relationships between seasonal V_cmax and SIF which are used to solve the inverse problem. We evaluate our V_cmax estimation method at six agricultural flux tower sites in the midwestern US using spaced‐based SIF retrievals. Our V_cmax estimates agree well with literature values for corn and soybean plants (average values of 37 and 101 μmol m^?2 s^?1, respectively) and show plausible seasonal patterns. The effect of the updated seasonally varying V_cmax parameterization on simulated gross primary productivity (GPP) is tested by comparing to simulations with fixed V_cmax values. Validation against flux tower observations demonstrate that simulations of GPP and light use efficiency improve significantly when our time‐resolved V_cmax estimates from SIF are used, with R² for GPP comparisons increasing from 0.85 to 0.93, and for light use efficiency from 0.44 to 0.83. Our results support the use of space‐based SIF data as a proxy for photosynthetic capacity and suggest the potential for global, time‐resolved estimates of V_cmax.     

Did Gause Have a Yeast Infection?

We planned to develop predator–prey models using Paramecium and yeast, but they have not been empirically examined since work by Gause in the 1930s. Therefore, we evaluated if Paramecium aurelia ingests and grows on eight yeasts. Recognising that it ingested yeasts but could not grow, we assessed if it might grow on other yeasts, by empirically parameterising a predator–prey model that relies on ingestion, not growth. Simulations were compared to P. aurelia‐yeast time‐series data, from Gause. We hypothesised that if the model simulated predator–prey dynamics that mimicked the original data, then possibly P. aurelia could grow on yeast; simulations did not mimic the original data. Reviewing works by Gause exposed two issues: experiments were undoubtedly contaminated with bacteria, allowing growth on bacteria, not yeast; and the population cycle data cannot be considered a self‐sustaining time series, as they were manipulated by adding yeast and ciliates. We conclude that past and future work should not rely on this system, for either empirical or theoretical evaluations. Finally, although we show that P. aurelia, P. caudatum, Euplotes patella, and Blepharisma sp. cannot grow on yeast, Tetrahymena pyriformis and Colpidium striatum can; these may provide models to explore predator–prey dynamics.     

Development characteristics of the box‐tree moth Cydalima perspectalis and its potential distribution in Europe

The box‐tree moth Cydalima perspectalis (Walker) is an invasive pest causing severe damage to box trees (Buxus spp.). It is native to Japan, Korea and China, but established populations have been recorded in a number of locations across Europe since 2007 and the spread of the insect continues. The developmental investigations suggest that larvae overwinter mainly in their 3rd instar in Europe and that diapause is induced by a day length of about 13.5 h. One and a half to 2 months in the cold are necessary to terminate diapause. Threshold temperatures for development and number of degree‐days to complete a generation are slightly different from those calculated in previous studies in Japan. A bioclimatic (CLIMEX^®) model for C. perspectalis in Europe was developed, based on climate, ecological and developmental parameters from the literature and new field and laboratory studies on diapause termination, thermal requirements and phenology. The model was then validated with actual distribution records and phenology data. The current distribution and life history of C. perspectalis in Europe were consistent with the predicted distribution. The climate model suggests that C. perspectalis is likely to continue its spread across Europe, except for Northern Fenno‐Scandinavia, Northern Scotland and high mountain regions. The northern distribution of C. perspectalis is expected to be limited by a number of degree‐days above the temperature threshold insufficient to complete a generation, whereas its southern range is limited by the absence of a cold period necessary to resume diapause. The model predicts relatively high Ecoclimatic Indices throughout most of Europe, suggesting that the insect has the potential of becoming a pest in most of its predicted range. However, damage is likely to be higher in Southern and Central Europe where the moth is able to complete at least two generations per year.     

Simulations of chlorophyll fluorescence incorporated into the Community Land Model version 4

Several studies have shown that satellite retrievals of solar‐induced chlorophyll fluorescence (SIF) provide useful information on terrestrial photosynthesis or gross primary production (GPP). Here, we have incorporated equations coupling SIF to photosynthesis in a land surface model, the National Center for Atmospheric Research Community Land Model version 4 (NCAR CLM4), and have demonstrated its use as a diagnostic tool for evaluating the calculation of photosynthesis, a key process in a land surface model that strongly influences the carbon, water, and energy cycles. By comparing forward simulations of SIF, essentially as a byproduct of photosynthesis, in CLM4 with observations of actual SIF, it is possible to check whether the model is accurately representing photosynthesis and the processes coupled to it. We provide some background on how SIF is coupled to photosynthesis, describe how SIF was incorporated into CLM4, and demonstrate that our simulated relationship between SIF and GPP values are reasonable when compared with satellite (Greenhouse gases Observing SATellite; GOSAT) and in situ flux‐tower measurements. CLM4 overestimates SIF in tropical forests, and we show that this error can be corrected by adjusting the maximum carboxylation rate (V_max) specified for tropical forests in CLM4. Our study confirms that SIF has the potential to improve photosynthesis simulation and thereby can play a critical role in improving land surface and carbon cycle models.     

Assessing forest vulnerability to climate warming using a process‐based model of tree growth: bad prospects for rear‐edges

Growth models can be used to assess forest vulnerability to climate warming. If global warming amplifies water deficit in drought‐prone areas, tree populations located at the driest and southernmost distribution limits (rear‐edges) should be particularly threatened. Here, we address these statements by analyzing and projecting growth responses to climate of three major tree species (silver fir, Abies alba; Scots pine, Pinus sylvestris; and mountain pine, Pinus uncinata) in mountainous areas of NE Spain. This region is subjected to Mediterranean continental conditions, it encompasses wide climatic, topographic and environmental gradients, and, more importantly, it includes rear‐edges of the continuous distributions of these tree species. We used tree‐ring width data from a network of 110 forests in combination with the process‐based Vaganov–Shashkin‐Lite growth model and climate–growth analyses to forecast changes in tree growth during the 21st century. Climatic projections were based on four ensembles CO₂ emission scenarios. Warm and dry conditions during the growing season constrain silver fir and Scots pine growth, particularly at the species rear‐edge. By contrast, growth of high‐elevation mountain pine forests is enhanced by climate warming. The emission scenario (RCP 8.5) corresponding to the most pronounced warming (+1.4 to 4.8 °C) forecasted mean growth reductions of ?10.7% and ?16.4% in silver fir and Scots pine, respectively, after 2050. This indicates that rising temperatures could amplify drought stress and thus constrain the growth of silver fir and Scots pine rear‐edge populations growing at xeric sites. Contrastingly, mountain pine growth is expected to increase by +12.5% due to a longer and warmer growing season. The projections of growth reduction in silver fir and Scots pine portend dieback and a contraction of their species distribution areas through potential local extinctions of the most vulnerable driest rear‐edge stands. Our modeling approach provides accessible tools to evaluate forest vulnerability to warmer conditions.