Local adaptation: Causal agents of selection and adaptive trait divergence

Divergent selection across the landscape can favor the evolution of local adaptation in populations experiencing contrasting conditions. Local adaptation is widely observed in a diversity of taxa, yet we have a surprisingly limited understanding of the mechanisms that give rise to it. For instance, few have experimentally confirmed the biotic and abiotic variables that promote local adaptation, and fewer yet have identified the phenotypic targets of selection that mediate local adaptation. Here, we highlight critical gaps in our understanding of the process of local adaptation and discuss insights emerging from in-depth investigations of the agents of selection that drive local adaptation, the phenotypes they target, and the genetic basis of these phenotypes. We review historical and contemporary methods for assessing local adaptation, explore whether local adaptation manifests differently across life history, and evaluate constraints on local adaptation.

Artificial light at night and anthropogenic noise alter the foraging activity and structure of vertebrate communities

Light and noise pollution from human activity are increasing at a dramatic rate. These sensory stimuli can have a wide range of effects on animal behavior, reproductive success, and physiology. However, less is known about the functional and community-level consequences of these sensory pollutants, especially when they co-occur. Using camera traps in a manipulative field experiment, we studied the effects of anthropogenic light and noise, singularly and in tandem, on richness and community turnover at both the taxa and functional group level as well as foraging activity. We showed that both light and noise pollution did alter taxonomic richness and that these effects can differ depending on the scale of observation. Increases in light levels had a negative effect on richness at the camera-level scale, but light-treated sites had the highest pooled (i.e., cumulative) richness of all treatment types. In contrast, noise was found to have a negative effect on cumulative richness; however, when both stimuli were present, the addition of night-lighting mitigated the effects of noise. Artificial light and moonlight had the strongest influence on community turnover, and results remained consistent at both the taxa and functional group level. Additionally, increases in ambient noise and moonlight, but not artificial light, reduced foraging activity. Our study provides evidence that alterations to the sensory environment can alter the richness and composition of communities and that effects can be scale-dependent and also alter foraging behavior. Unexpectedly, the addition of artificial light may have mitigated the negative effects of noise on cumulative taxonomic richness. This highlights the importance of researching the consequences of co-exposure to these globally common pollutants.

Modeling Ambitions Outpace Observations of Forest Carbon Allocation

There have been vociferous calls for 'tree-centered' vegetation models to refine predictions of forest carbon (C) cycling. Unfortunately, our global survey at flux-tower sites indicates insufficient empirical data support for this much-needed model development. We urge for a new generation of studies across large environmental gradients that strategically pair long-term ecosystem monitoring with manipulative experiments on mature trees. For this, we outline a versatile experimental framework to build cross-scale data archives of C uptake and allocation to structural, non-structural, and respiratory sinks. Community-wide efforts and discussions are needed to implement this framework, especially in hitherto underrepresented tropical forests. Global coordination and realistic priorities for data collection will thereby be key to achieve and maintain adequate empirical support for tree-centered vegetation modeling.

Understanding the Response of Nitrifying Communities to Disturbance in the McMurdo Dry Valleys, Antarctica

Polar ecosystems are generally limited in nitrogen (N) nutrients, and the patchy availability of N is partly determined by biological pathways, such as nitrification, which are carried out by distinctive prokaryotic functional groups. The activity and diversity of microorganisms are generally strongly influenced by environmental conditions. However, we know little of the attributes that control the distribution and activity of specific microbial functional groups, such as nitrifiers, in extreme cold environments and how they may respond to change. To ascertain relationships between soil geochemistry and the ecology of nitrifying microbial communities, we carried out a laboratory-based manipulative experiment to test the selective effect of key geochemical variables on the activity and abundance of ammonia-oxidizing communities in soils from the McMurdo Dry Valleys of Antarctica. We hypothesized that nitrifying communities, adapted to different environmental conditions within the Dry Valleys, will have distinct responses when submitted to similar geochemical disturbances. In order to test this hypothesis, soils from two geographically distant and geochemically divergent locations, Miers and Beacon Valleys, were incubated over 2 months under increased conductivity, ammonia concentration, copper concentration, and organic matter content. Amplicon sequencing of the 16S rRNA gene and transcripts allowed comparison of the response of ammonia-oxidizing Archaea (AOA) and ammonia-oxidizing Bacteria (AOB) to each treatment over time. This approach was combined with measurements of ¹⁵NH₄⁺ oxidation rates using ¹⁵N isotopic additions. Our results showed a higher potential for nitrification in Miers Valley, where environmental conditions are milder relative to Beacon Valley. AOA exhibited better adaptability to geochemical changes compared to AOB, particularly to the increase in copper and conductivity. AOA were also the only nitrifying group found in Beacon Valley soils. This laboratorial manipulative experiment provided new knowledge on how nitrifying groups respond to changes on key geochemical variables of Antarctic desert soils, and we believe these results offer new insights on the dynamics of N cycling in these ecosystems.

The onset of xylogenesis in Smith fir is not related to outer bark thickness

PREMISE

The resumption of stem growth varies across the ontogenetic development of trees. Compared with younger trees, older ones have thicker outer bark with a temperature-insulating effect that could potentially prevent the stem from warming in the spring. However, the question of whether xylogenesis in old trees is influenced by the thick bark still remains unresolved.

METHODS

We investigated the onset of xylogenesis across the ontogenetic development of Smith fir (Abies georgei var. smithii) trees in the Sygera Mountains, southeastern Tibetan Plateau. The outer bark of older trees was also removed. Xylogenesis was monitored in microcores we collected every 3 days during May and June in 2017.

RESULTS

Xylogenesis began in late May in young (<50 yr) and mature (50-100 yr) trees, 1 week earlier than in adult (>100-150 yr) and old (>150-200 yr) trees. Older (>200 yr) trees had the latest onset of xylogenesis, 2 weeks after young trees. The resumption of xylogenesis was similar between the control and bark-removed trees.

CONCLUSIONS

Growth resumption was delayed in older and bigger trees. Outer bark did not affect the onset of xylogenesis, which indicated that the delayed resumption of growth during the lifespan of trees could be more related to endogenous factors than to an insulating effect of the thick bark of older individuals.

Behavioural Phenotypic Plasticity of Submerged Oviposition in Damselflies (Insecta: Odonata)

Emerald damselfly Lestes sponsa is a common species within the temperate zone, with no special need for protection. The tactic of submerged oviposition is well known from other Odonata species, but has rarely been noticed or described in Lestes sponsa. Our study investigated the tactics of oviposition in this species, and shows that submerged oviposition indeed occurs frequently in Lestes sponsa. We experimentally tested the difference in the roles of males and females during the submerged ovipositional behaviour by combining males/females from submerging populations with males/females from non-submerging populations. We discovered that, whereas submerging males coupling with non-submerging females did not lead to submersion, the opposite combination of pairs submerged. Other patterns of submersions are discussed further in this paper. Our research led to the conclusion that damselflies have the ability to learn and react to different situations in keeping with the learning potential of insects in general.

Successional change in species composition alters climate sensitivity of grassland productivity

Succession theory predicts altered sensitivity of ecosystem functions to disturbance (i.e., climate change) due to the temporal shift in plant community composition. However, empirical evidence in global change experiments is lacking to support this prediction. Here, we present findings from an 8-year long-term global change experiment with warming and altered precipitation manipulation (double and halved amount). First, we observed a temporal shift in species composition over 8 years, resulting in a transition from an annual C₃ -dominant plant community to a perennial C₄ -dominant plant community. This successional transition was independent of any experimental treatments. During the successional transition, the response of aboveground net primary productivity (ANPP) to precipitation addition magnified from neutral to +45.3%, while the response to halved precipitation attenuated substantially from -17.6% to neutral. However, warming did not affect ANPP in either state. The findings further reveal that the time-dependent climate sensitivity may be regulated by successional change in species composition, highlighting the importance of vegetation dynamics in regulating the response of ecosystem productivity to precipitation change.

Conserved thermal performance curves across the geographic range of a gametophytic fern

Species-level responses to environmental change depend on the collective responses of their constituent populations and the degree to which populations are specialized to local conditions. Manipulative experiments in common-garden settings make it possible to test for population variation in species' responses to specific climate variables, including those projected to shift as the climate changes in the future. While this approach is being applied to a variety of plant taxa to evaluate their responses to climate change, these studies are heavily biased towards seed-bearing plant species. Given several unique morphological and physiological traits, fern species may exhibit very different responses from angiosperms and gymnosperms. Here, we tested the hypothesis that previously detected population differentiation in a fern species is due to differentiation in thermal performance curves among populations. We collected explants from six populations spanning the species' geographic range and exposed them to 10 temperature treatments. Explant survival, lifespan and the change in photosynthetic area were analysed as a function of temperature, source population and their interaction. Overall results indicated that explants performed better at the lowest temperature examined, and the threshold for explant performance reflects maximum temperatures likely to be experienced in the field. Surprisingly, explant fitness did not differ among source populations, suggesting that temperature is not the driver behind previously detected patterns of population differentiation. These results highlight the importance of other environmental axes in driving population differentiation across a species range, and suggest that the perennial life history strategy, asexual mating system and limited dispersal potential of Vittaria appalachiana may restrict the rise and differentiation of adaptive genetic variation in thermal performance traits among populations.

Differential responses of canopy nutrients to experimental drought along a natural aridity gradient

The allocation and stoichiometry of plant nutrients in leaves reflect fundamental ecosystem processes, biotic interactions, and environmental drivers such as water availability. Climate change will lead to increases in drought severity and frequency, but how canopy nutrients will respond to drought, and how these responses may vary with community composition along aridity gradients is poorly understood. We experimentally addressed this issue by reducing precipitation amounts by 66% during two consecutive growing seasons at three sites located along a natural aridity gradient. This allowed us to assess drought effects on canopy nitrogen (N) and phosphorus (P) concentrations in arid and semiarid grasslands of northern China. Along the aridity gradient, canopy nutrient concentrations were positively related to aridity, with this pattern was driven primarily by species turnover (i.e., an increase in the relative biomass of N- and P-rich species with increasing aridity). In contrast, drought imposed experimentally increased N but decreased P concentrations in plant canopies. These changes were driven by the combined effects of species turnover and intraspecific variation in leaf nutrient concentrations. In addition, the sensitivity of canopy N and P concentrations to drought varied across the three sites. Canopy nutrient concentrations were less affected by drought at drier than wetter sites, because of the opposing effects of species turnover and intraspecific variation, as well as greater drought tolerance for nutrient-rich species. These contrasting effects of long-term aridity vs. short-term drought on canopy nutrient concentrations, as well as differing sensitivities among sites in the same grassland biome, highlight the challenge of predicting ecosystem responses to future climate change.

Using dynamic N-mixture models to test cavity limitation on northern flying squirrel demographic parameters using experimental nest box supplementation

Dynamic N-mixture models have been recently developed to estimate demographic parameters of unmarked individuals while accounting for imperfect detection. We propose an application of the Dail and Madsen (2011: Biometrics, 67, 577-587) dynamic N-mixture model in a manipulative experiment using a before-after control-impact design (BACI). Specifically, we tested the hypothesis of cavity limitation of a cavity specialist species, the northern flying squirrel, using nest box supplementation on half of 56 trapping sites. Our main purpose was to evaluate the impact of an increase in cavity availability on flying squirrel population dynamics in deciduous stands in northwestern Québec with the dynamic N-mixture model. We compared abundance estimates from this recent approach with those from classic capture-mark-recapture models and generalized linear models. We compared apparent survival estimates with those from Cormack-Jolly-Seber (CJS) models. Average recruitment rate was 6 individuals per site after 4 years. Nevertheless, we found no effect of cavity supplementation on apparent survival and recruitment rates of flying squirrels. Contrary to our expectations, initial abundance was not affected by conifer basal area (food availability) and was negatively affected by snag basal area (cavity availability). Northern flying squirrel population dynamics are not influenced by cavity availability at our deciduous sites. Consequently, we suggest that this species should not be considered an indicator of old forest attributes in our study area, especially in view of apparent wide population fluctuations across years. Abundance estimates from N-mixture models were similar to those from capture-mark-recapture models, although the latter had greater precision. Generalized linear mixed models produced lower abundance estimates, but revealed the same relationship between abundance and snag basal area. Apparent survival estimates from N-mixture models were higher and less precise than those from CJS models. However, N-mixture models can be particularly useful to evaluate management effects on animal populations, especially for species that are difficult to detect in situations where individuals cannot be uniquely identified. They also allow investigating the effects of covariates at the site level, when low recapture rates would require restricting classic CMR analyses to a subset of sites with the most captures.