Grassland responses to increased rainfall depend on the timescale of forcing

Factors affecting the nesting success of Swainson's Thrush (Catharus ustulatus) along an elevational gradient

Montane birds experience a range of challenges that may limit their breeding success, including nest predation and severe climactic conditions. The continuing effects of climate change are causing shifts in biotic and abiotic factors that may compound these threats to montane bird species. In northeastern montane forests, many bird species are shifting downslope, potentially as the result of increased precipitation and temperature at higher elevations. Although lower elevations might be more favorable in terms of climactic conditions, nest predation is higher at lower elevations. Thus, montane birds might be faced with the opposing pressures of adverse climactic conditions at higher elevations and increased predation at lower elevations. We monitored nests of Swainson's Thrush (Catharus ustulatus) along an elevation gradient in the White Mountain National Forest in New Hampshire in 2016, 2018, 2019, and 2021 to examine the effect of biotic and abiotic factors on daily nest survival rate (DSR). Linear time explained the most variation of DSR in AICc model comparison, indicating that DSR decreases across the breeding season. Rain intensity (mm/h) had a weak negative effect on DSR, indicating that heavier rain per hour decreases Swainson's Thrush DSR. Moreover, we found some support for a negative interaction effect of elevation in conjunction with minimum daily temperature: DSR of Swainson's Thrush nests at low elevations (281 m) increased with increasing minimum daily temperatures and decreased at high elevations with increasing minimum daily temperatures. Our results suggest nesting survival of montane breeding birds may be at risk as heavier precipitation events become more frequent and intense due to the changing climate and raises the possibility that other passerine species could be at risk in this system.

Long-term elevated precipitation induces grassland soil carbon loss via microbe-plant-soil interplay

Global climate models predict that the frequency and intensity of precipitation events will increase in many regions across the world. However, the biosphere-climate feedback to elevated precipitation (eP) remains elusive. Here, we report a study on one of the longest field experiments assessing the effects of eP, alone or in combination with other climate change drivers such as elevated CO2 (eCO2 ), warming and nitrogen deposition. Soil total carbon (C) decreased after a decade of eP treatment, while plant root production decreased after 2 years. To explain this asynchrony, we found that the relative abundances of fungal genes associated with chitin and protein degradation increased and were positively correlated with bacteriophage genes, suggesting a potential viral shunt in C degradation. In addition, eP increased the relative abundances of microbial stress tolerance genes, which are essential for coping with environmental stressors. Microbial responses to eP were phylogenetically conserved. The effects of eP on soil total C, root production, and microbes were interactively affected by eCO2 . Collectively, we demonstrate that long-term eP induces soil C loss, owing to changes in microbial community composition, functional traits, root production, and soil moisture. Our study unveils an important, previously unknown biosphere-climate feedback in Mediterranean-type water-limited ecosystems, namely how eP induces soil C loss via microbe-plant-soil interplay.

Increasing climatic sensitivity of global grassland vegetation biomass and species diversity correlates with water availability

Grasslands are key repositories of biodiversity and carbon storage and are heavily impacted by effects of global warming and changes in precipitation regimes. Patterns of grassland dynamics associated with variability in future climate conditions across spatiotemporal scales are yet to be adequately quantified. Here, we performed a global meta-analysis of year and growing season sensitivities of vegetation aboveground biomass (AGB), aboveground net primary productivity (ANPP), and species richness (SR) and diversity (Shannon index, H) to experimental climate warming and precipitation shifts. All four variables were sensitive to climate change. Their sensitivities to shifts in precipitation were correlated with local background water availability, such as mean annual precipitation (MAP) and aridity, and AGB and ANPP sensitivities were greater in dry habitats than in nonwater-limited habitats. There was no effect of duration of experiment (short vs long term) on sensitivities. Temporal trends in ANPP and SR sensitivity depended on local water availability; ANPP sensitivity to warming increased over time and SR sensitivity to irrigation decreased over time. Our results provide a global overview of the sensitivities of grassland function and diversity to climate change that will improve the understanding of ecological responses across spatiotemporal scales and inform policies for conservation in dry climates.

Soil bacterial populations are shaped by recombination and gene-specific selection across a grassland meadow

Soil microbial diversity is often studied from the perspective of community composition, but less is known about genetic heterogeneity within species. The relative impacts of clonal interference, gene-specific selection, and recombination in many abundant but rarely cultivated soil microbes remain unknown. Here we track genome-wide population genetic variation for 19 highly abundant bacterial species sampled from across a grassland meadow. Genomic inferences about population structure are made using the millions of sequencing reads that are assembled de novo into consensus genomes from metagenomes, as each read pair describes a short genomic sequence from a cell in each population. Genomic nucleotide identity of assembled genomes was significantly associated with local geography for over half of the populations studied, and for a majority of populations within-sample nucleotide diversity could often be as high as meadow-wide nucleotide diversity. Genes involved in metabolite biosynthesis and extracellular transport were characterized by elevated nucleotide diversity in multiple species. Microbial populations displayed varying degrees of homologous recombination and recombinant variants were often detected at 7-36% of loci genome-wide. Within multiple populations we identified genes with unusually high spatial differentiation of alleles, fewer recombinant events, elevated ratios of nonsynonymous to synonymous variants, and lower nucleotide diversity, suggesting recent selective sweeps for gene variants. Taken together, these results indicate that recombination and gene-specific selection commonly shape genetic variation in several understudied soil bacterial lineages.

Species interactions modulate the response of saltmarsh plants to flooding

BACKGROUND AND AIMS

The vegetation that grows on coastal wetlands is important for ecosystem functioning, a role mediated by plant traits. These traits can be affected by environmental stressors and by the competitive environment the plant experiences. The relative importance of these influences on different traits is poorly understood and, despite theoretical expectations for how factors may interact, empirical data are conflicting. Our aims are to determine the effect of flooding, species composition and their interaction on plant functional traits, and assess the role of biodiversity and species composition in driving community-level responses to flooding.

METHODS

We conducted a factorial glasshouse experiment assessing the effects of species composition (all combinations of three saltmarsh species, Aster tripolium, Plantago maritima and Triglochin maritima) and flooding (immersion of roots) on a suite of functional traits. We also related biomass in mixed species pots to that expected from monocultures to assess how species interactions affect community-level biomass.

KEY RESULTS

Species composition frequently interacted with flooding to influence functional traits and community-level properties. However, there was also considerable intraspecific variability in traits within each treatment. Generally, effects of flooding were more pronounced for below-ground than above-ground biomass, while composition affected above-ground biomass more than below-ground biomass. We found both negative and positive interactions between species (indicated by differences in above- and below-ground biomass from expectations under monoculture), meaning that composition was an important determinate of community function.

CONCLUSIONS

While the effect of flooding alone on traits was relatively weak, it interacted with species composition to modify the response of both individual plants and communities. Our results suggest that responses to increased flooding will be complex and depend on neighbourhood species interactions. Furthermore, intraspecific trait variability is a potential resource that may dampen the effects of changes in flooding regime.

Responses of community structure and diversity to nitrogen deposition and rainfall addition in contrasting steppes are ecosystem-dependent and dwarfed by year-to-year community dynamics

BACKGROUND AND AIMS

Long-term studies to disentangle the multiple, simultaneous effects of global change on community dynamics are a high research priority to forecast future distribution of diversity. Seldom are such multiple effects of global change studied across different ecosystems.

METHODS

Here we manipulated nitrogen deposition and rainfall at levels realistic for future environmental scenarios in three contrasting steppe types in Mongolia and followed community dynamics for 7 years.

KEY RESULTS

Redundancy analyses showed that community composition varied significantly among years. Rainfall and nitrogen manipulations did have some significant effects, but these effects were dependent on the type of response and varied between ecosystems. Community compositions of desert and meadow steppes, but not that of typical steppe, responded significantly to rainfall addition. Only community composition of meadow steppe responded significantly to nitrogen deposition. Species richness in desert steppe responded significantly to rainfall addition, but the other two steppes did not. Typical steppe showed significant negative response of species richness to nitrogen deposition, but the other two steppes did not. There were significant interactions between year and nitrogen deposition in desert steppe and between year and rainfall addition in typical steppe, suggesting that the effect of the treatments depends on the particular year considered.

CONCLUSIONS

Our multi-year experiment thus suggests that responses of community structure and diversity to global change drivers are ecosystem-dependent and that their responses to experimental treatments are dwarfed by the year-to-year community dynamics. Therefore, our results point to the importance of taking annual environmental variability into account for understanding and predicting the specific responses of different ecosystems to multiple global change drivers.

Negative biotic interactions drive predictions of distributions for species from a grassland community

Understanding the factors that determine species' geographical distributions is important for addressing a wide range of biological questions, including where species will be able to maintain populations following environmental change. New methods for modelling species distributions include the effects of biotic interactions alongside more commonly used abiotic variables such as temperature and precipitation; however, it is not clear which types of interspecific relationship contribute to shaping species distributions and should therefore be prioritized in models. Even if some interactions are known to be influential at local spatial scales, there is no guarantee they will have similar impacts at macroecological scales. Here we apply a novel method based on information theory to determine which types of interspecific relationship drive species distributions. Our results show that negative biotic interactions such as competition have the greatest effect on model predictions for species from a California grassland community. This knowledge will help focus data collection and improve model predictions for identifying at-risk species. Furthermore, our methodological approach is applicable to any kind of species distribution model that can be specified with and without interspecific relationships.

Relative importance of climate changes at different time scales on net primary productivity-a case study of the Karst area of northwest Guangxi, China

Climate changes are considered to significantly impact net primary productivity (NPP). However, there are few studies on how climate changes at multiple time scales impact NPP. With MODIS NPP product and station-based observations of sunshine duration, annual average temperature and annual precipitation, impacts of climate changes at different time scales on annual NPP, have been studied with EEMD (ensemble empirical mode decomposition) method in the Karst area of northwest Guangxi, China, during 2000-2013. Moreover, with partial least squares regression (PLSR) model, the relative importance of climatic variables for annual NPP has been explored. The results show that (1) only at quasi 3-year time scale do sunshine duration and temperature have significantly positive relations with NPP. (2) Annual precipitation has no significant relation to NPP by direct comparison, but significantly positive relation at 5-year time scale, which is because 5-year time scale is not the dominant scale of precipitation; (3) the changes of NPP may be dominated by inter-annual variabilities. (4) Multiple time scales analysis will greatly improve the performance of PLSR model for estimating NPP. The variable importance in projection (VIP) scores of sunshine duration and temperature at quasi 3-year time scale, and precipitation at quasi 5-year time scale are greater than 0.8, indicating important for NPP during 2000-2013. However, sunshine duration and temperature at quasi 3-year time scale are much more important. Our results underscore the importance of multiple time scales analysis for revealing the relations of NPP to changing climate.

Long-term enhanced winter soil frost alters growing season CO2 fluxes through its impact on vegetation development in a boreal peatland

At high latitudes, winter climate change alters snow cover and, consequently, may cause a sustained change in soil frost dynamics. Altered winter soil conditions could influence the ecosystem exchange of carbon dioxide (CO₂ ) and, in turn, provide feedbacks to ongoing climate change. To investigate the mechanisms that modify the peatland CO₂ exchange in response to altered winter soil frost, we conducted a snow exclusion experiment to enhance winter soil frost and to evaluate its short-term (1-3 years) and long-term (11 years) effects on CO₂ fluxes during subsequent growing seasons in a boreal peatland. In the first 3 years after initiating the treatment, no significant effects were observed on either gross primary production (GPP) or ecosystem respiration (ER). However, after 11 years, the temperature sensitivity of ER was reduced in the treatment plots relative to the control, resulting in an overall lower ER in the former. Furthermore, early growing season GPP was also lower in the treatment plots than in the controls during periods with photosynthetic photon flux density (PPFD) ≥800 μmol m^-2  s^-1 , corresponding to lower sedge leaf biomass in the treatment plots during the same period. During the peak growing season, a higher GPP was observed in the treatment plots under the low light condition (i.e. PPFD 400 μmol m^-2  s^-1 ) compared to the control. As Sphagnum moss maximizes photosynthesis at low light levels, this GPP difference between the plots may have been due to greater moss photosynthesis, as indicated by greater moss biomass production, in the treatment plots relative to the controls. Our study highlights the different responses to enhanced winter soil frost among plant functional types which regulate CO₂ fluxes, suggesting that winter climate change could considerably alter the growing season CO₂ exchange in boreal peatlands through its effect on vegetation development.

Linking macroecology and community ecology: refining predictions of species distributions using biotic interaction networks

Macroecological models for predicting species distributions usually only include abiotic environmental conditions as explanatory variables, despite knowledge from community ecology that all species are linked to other species through biotic interactions. This disconnect is largely due to the different spatial scales considered by the two sub-disciplines: macroecologists study patterns at large extents and coarse resolutions, while community ecologists focus on small extents and fine resolutions. A general framework for including biotic interactions in macroecological models would help bridge this divide, as it would allow for rigorous testing of the role that biotic interactions play in determining species ranges. Here, we present an approach that combines species distribution models with Bayesian networks, which enables the direct and indirect effects of biotic interactions to be modelled as propagating conditional dependencies among species' presences. We show that including biotic interactions in distribution models for species from a California grassland community results in better range predictions across the western USA. This new approach will be important for improving estimates of species distributions and their dynamics under environmental change.