Global Change Biology最新文献

Changes in phenology are occurring from global climate change, yet the impacts of other types of global change on the phenology of animals remain less appreciated. Understanding the potential for synergistic effects of different types of global change on phenology is needed, because changing climate regimes can have cascading effects, particularly on invasive species that vary in their thermal tolerances. Using 25 years of data from 5963 nests and 4675 marked individuals across the entire US breeding range of an endangered predator, the snail kite (Rostrhamus sociabilis plumbeus), we isolated the effects of an invasion of novel prey and warming temperatures on breeding phenology and its demographic consequences. Over this time period, breeding season length doubled, increasing by approximately 14 weeks. Both temperature and the establishment of invasive prey interacted to explain the timing of nest initiation. Temperature and invasive prey played distinct roles: earlier nest initiation occurred with increasing temperatures, whereas late nesting increased with invasion. Ultimately, both nest survival and juvenile survival declined later in the year, such that effects from invasive prey, but not warming temperatures, have the apparent potential for mistiming in breeding phenology by some individuals. Nonetheless, relatively few nesting events occurred during late fall when nest survival was very low, and seasonal declines in nest survival were weaker and renesting was more frequent in invaded wetlands, such that total reproductive output increased with invasion. Variation in demographic effects illustrate that considering only particular components of demography (e.g., nest survival rates) may be inadequate to infer the overall consequences of changes in phenology, particularly the potential for mistiming of phenological events. These results emphasize that species invasions may profoundly alter phenology of native species, such effects are distinct from climate effects, and both interact to drive population change.

Measurements of net primary productivity (NPP) and litter decomposition from tropical peatlands are severely lacking, limiting our ability to parameterise and validate models of tropical peatland development and thereby make robust predictions of how these systems will respond to future environmental and climatic change. Here, we present total NPP (i.e., above- and below-ground) and decomposition data from two floristically and structurally distinct forested peatland sites within the Pastaza Marañón Foreland Basin, northern Peru, the largest tropical peatland area in Amazonia: (1) a palm (largely Mauritia flexuosa) dominated swamp forest and (2) a hardwood dominated swamp forest (known as ‘pole forest’, due to the abundance of thin-stemmed trees). Total NPP in the palm forest and hardwood-dominated forest (9.83 ± 1.43 and 7.34 ± 0.84 Mg C ha⁻¹ year⁻¹, respectively) was low compared with values reported for terra firme forest in the region (14.21–15.01 Mg C ha⁻¹ year⁻¹) and for tropical peatlands elsewhere (11.06 and 13.20 Mg C ha⁻¹ year⁻¹). Despite the similar total NPP of the two forest types, there were considerable differences in the distribution of NPP. Fine root NPP was seven times higher in the palm forest (4.56 ± 1.05 Mg C ha⁻¹ year⁻¹) than in the hardwood forest (0.61 ± 0.22 Mg C ha⁻¹ year⁻¹). Above-ground palm NPP, a frequently overlooked component, made large contributions to total NPP in the palm-dominated forest, accounting for 41% (14% in the hardwood-dominated forest). Conversely, Mauritia flexuosa litter decomposition rates were the same in both plots: highest for leaf material, followed by root and then stem material (21%, 77% and 86% of mass remaining after 1 year respectively for both plots). Our results suggest potential differences in these two peatland types' responses to climate and other environmental changes and will assist in future modelling studies of these systems.

Marine heatwaves (MHWs), increasing in duration and intensity because of climate change, are now a major threat to marine life and can have lasting effects on the structure and function of ecosystems. However, the responses of marine taxa and ecosystems to MHWs can be highly variable, making predicting and interpreting biological outcomes a challenge. Here, we review how biological responses to MHWs, from individuals to ecosystems, are mediated by fine-scale spatial variability in the coastal marine environment (hereafter, local gradients). Viewing observed responses through a lens of ecological theory, we present a simple framework of three ‘resilience processes’ (RPs) by which local gradients can influence the responses of marine taxa to MHWs. Local gradients (1) influence the amount of stress directly experienced by individuals, (2) facilitate local adaptation and acclimatization of individuals and populations, and (3) shape community composition which then influences responses to MHWs. We then synthesize known examples of fine-scale gradients that have affected responses of benthic foundation species to MHWs, including kelp forests, coral reefs, and seagrass meadows and link these varying responses to the RPs. We present a series of case studies from various marine ecosystems to illustrate the differential impacts of MHWs mediated by gradients in both temperature and other co-occurring drivers. In many cases, these gradients had large effect sizes with several examples of local gradients causing a 10-fold difference in impacts or more (e.g., survival, coverage). This review highlights the need for high-resolution environmental data to accurately predict and manage the consequences of MHWs in the context of ongoing climate change. While current tools may capture some of these gradients already, we advocate for enhanced monitoring and finer scale integration of local environmental heterogeneity into climate models. This will be essential for developing effective conservation strategies and mitigating future marine biodiversity loss.

Given the context of significant global warming and the intensification of extreme climate events in the last century, large-scale reforestation and afforestation have been recognized as effective strategies to mitigate the climate crisis. Since the 1970s, China has launched several afforestation programs aimed at regional ecological protection, playing an important role in reaching carbon neutrality by 2060. This study provided a detailed analysis of the growth suitability of the main planted conifers (Pinus sylvestris var. mongolica and Pinus tabulaeformis) and broadleaves (Populus spp., Robinia pseudoacacia) in the semi-arid northern China. We compared the radial growth trends of plantations and their responses to extreme droughts from 1980 to 2018. Growth of most plantations has significantly increased over time, but broadleaves showed recent growth reductions in the past decade, which may be related to tree age and reduced soil moisture. Nevertheless, under warmer climate scenarios, the growth of plantations is forecasted to continue increasing. Broadleaves showed a better post-drought recovery, probably linked to their anisohydric behavior, than conifers, which presented a better resistance to drought. Growth of conifers depended more on warmer temperature and better precipitation conditions during the growing season, whereas broadleaves mainly reacted to warm temperature. Additionally, pre-drought growth levels weakened resilience components, while post-drought precipitation compensated for drought-induced growth deficit. Growth and resilience were negatively related to tree age, while higher stand density reduced growth. This assessment and projections of growth and drought resilience indicate the sustainability of most plantations in semi-arid regions, but future warmer and drier conditions may lead to an uncertain future regarding forest health and reduce their carbon sink potential.

Tree allometric models, essential for monitoring and predicting terrestrial carbon stocks, are traditionally built on global databases with forest inventory measurements of stem diameter (D) and tree height (H). However, these databases often combine H measurements obtained through various measurement methods, each with distinct error patterns, affecting the resulting H:D allometries. In recent decades, terrestrial laser scanning (TLS) has emerged as a widely accepted method for accurate, non-destructive tree structural measurements. This study used TLS data to evaluate the prediction accuracy of forest inventory-based H:D allometries and to develop more accurate pantropical allometries. We considered 19 tropical rainforest plots across four continents. Eleven plots had forest inventory and RIEGL VZ-400(i) TLS-based D and H data, allowing accuracy assessment of local forest inventory-based H:D allometries. Additionally, TLS-based data from 1951 trees from all 19 plots were used to create new pantropical H:D allometries for tropical rainforests. Our findings reveal that in most plots, forest inventory-based H:D allometries underestimated H compared with TLS-based allometries. For 30-metre-tall trees, these underestimations varied from −1.6 m (−5.3%) to −7.5 m (−25.4%). In the Malaysian plot with trees reaching up to 77 m in height, the underestimation was as much as −31.7 m (−41.3%). We propose a TLS-based pantropical H:D allometry, incorporating maximum climatological water deficit for site effects, with a mean uncertainty of 19.1% and a mean bias of −4.8%. While the mean uncertainty is roughly 2.3% greater than that of the Chave2014 model, this model demonstrates more consistent uncertainties across tree size and delivers less biased estimates of H (with a reduction of 8.23%). In summary, recognizing the errors in H measurements from forest inventory methods is vital, as they can propagate into the allometries they inform. This study underscores the potential of TLS for accurate H and D measurements in tropical rainforests, essential for refining tree allometries.

Effective nitrogen fertilizer management is crucial for reducing nitrous oxide (N₂O) emissions while ensuring food security within planetary boundaries. However, climate change might also interact with management practices to alter N₂O emission and emission factors (EFs), adding further uncertainties to estimating mitigation potentials. Here, we developed a new hybrid modeling framework that integrates a machine learning model with an ensemble of eight process-based models to project EFs under different climate and nitrogen policy scenarios. Our findings reveal that EFs are dynamically modulated by environmental changes, including climate, soil properties, and nitrogen management practices. Under low-ambition nitrogen regulation policies, EF would increase from 1.18%–1.22% in 2010 to 1.27%–1.34% by 2050, representing a relative increase of 4.4%–11.4% and exceeding the IPCC tier-1 EF of 1%. This trend is particularly pronounced in tropical and subtropical regions with high nitrogen inputs, where EFs could increase by 0.14%–0.35% (relative increase of 11.9%–17%). In contrast, high-ambition policies have the potential to mitigate the increases in EF caused by climate change, possibly leading to slight decreases in EFs. Furthermore, our results demonstrate that global EFs are expected to continue rising due to warming and regional drying–wetting cycles, even in the absence of changes in nitrogen management practices. This asymmetrical influence of nitrogen fertilizers on EFs, driven by climate change, underscores the urgent need for immediate N₂O emission reductions and further assessments of mitigation potentials. This hybrid modeling framework offers a computationally efficient approach to projecting future N₂O emissions across various climate, soil, and nitrogen management scenarios, facilitating socio-economic assessments and policy-making efforts.

Global patterns in soil microbiomes are driven by non-linear environmental thresholds. Fertilization is known to shape the soil microbiome of terrestrial ecosystems worldwide. Yet, whether fertilization influences global thresholds in soil microbiomes remains virtually unknown. Here, utilizing optimized machine learning models with Shapley additive explanations on a dataset of 10,907 soil samples from 24 countries, we discovered that the microbial community response to fertilization is highly dependent on environmental contexts. Furthermore, the interactions among nitrogen (N) addition, pH, and mean annual temperature contribute to non-linear patterns in soil bacterial diversity. Specifically, we observed positive responses within a soil pH range of 5.2–6.6, with the influence of higher temperature (>15°C) on bacterial diversity being positive within this pH range but reversed in more acidic or alkaline soils. Additionally, we revealed the threshold effect of soil organic carbon and total nitrogen, demonstrating how temperature and N addition amount interacted with microbial communities within specific edaphic concentration ranges. Our findings underscore how complex environmental interactions control soil bacterial diversity under fertilization.

Micro/nanoplastic (MNP) pollution in soil ecosystems has become a growing environmental concern globally. However, the comprehensive impacts of MNPs on soil health have not yet been explored. We conducted a hierarchical meta-analysis of over 5000 observations from 228 articles to assess the broad impacts of MNPs on soil health parameters (represented by 20 indicators relevant to crop growth, animal health, greenhouse gas emissions, microbial diversity, and pollutant transfer) and whether the impacts depended on MNP properties. We found that MNP exposure significantly inhibited crop biomass and germination, and reduced earthworm growth and survival rate. Under MNP exposure, the emissions of soil greenhouse gases (CO₂, N₂O, and CH₄) were significantly increased. MNP exposure caused a decrease in soil bacteria diversity. Importantly, the magnitude of impact of the soil-based parameters was dependent on MNP dose and size; however, there is no significant difference in MNP type (biodegradable and conventional MNPs). Moreover, MNPs significantly reduced As uptake by plants, but promoted plant Cd accumulation. Using an analytical hierarchy process, we quantified the negative impacts of MNP exposure on soil health as a mean value of −10.2% (−17.5% to −2.57%). Overall, this analysis provides new insights for assessing potential risks of MNP pollution to soil ecosystem functions.

Plant functional groups (FGs) differ in their response to global changes, although species within those groups also vary in such responses. Both species and FG responses to global change are likely influenced by species interactions such as inter-specific competition and facilitation, which are prevalent in species mixtures but not monocultures. As most studies focus on responses of plants growing in either monocultures or mixtures, but rarely both, it remains unclear how interspecific interactions in diverse ecological communities, especially among species in different FGs, modify FG responses to global changes. To address these issues, we leveraged data from a 16-species, 24-year perennial grassland experiment to examine plant FG biomass responses to atmospheric CO₂, and N inputs at different planted diversity. FGs differed in their responses to N and CO₂ treatments in monocultures. Such differences were amplified in mixtures, where N enrichment strongly increased C3 grass success at ambient CO₂ and C4 grass success at elevated CO₂. Legumes declined with N enrichment in mixtures at both CO₂ levels and increased with elevated CO₂ in the initial years of the experiment. Our results suggest that previous studies that considered responses to global changes in monocultures may underestimate biomass changes in diverse communities where interspecific interactions can amplify responses. Such effects of interspecific interactions on responses of FGs to global change may impact community composition over time and consequently influence ecosystem functions.

Atmospheric nitrogen (N) deposition has been substantially reduced due to declines in the reactive N emission in major regions of the world. Nevertheless, the impact of reduced N deposition on soil microbial communities and the mechanisms by which they are regulated remain largely unknown. Here, we examined the effects of N addition and cessation of N addition on plant and soil microbial communities through a 17-year field experiment in a temperate grassland. We found that extreme N input did not irreversibly disrupt the ecosystem, but ceasing high levels of N addition led to greater resilience in bacterial and fungal communities. Fungi exhibited diminished resilience compared to bacteria due to their heightened reliance on changes in plant communities. Neither bacterial nor fungal diversity fully recovered to their original states. Their sensitivity and resilience were mainly steered by toxic metal ions and soil pH differentially regulating on functional taxa. Specifically, beneficial symbiotic microbes such as N-fixing bacteria and arbuscular mycorrhizal fungi experienced detrimental effects from toxic metal ions and lower pH, hindering their recovery. The bacterial functional groups involved in carbon decomposition, and ericoid mycorrhizal and saprotrophic fungi were positively influenced by soil metals, and demonstrated gradual recovery. These findings could advance our mechanistic understanding of microbial community dynamics under ongoing global changes, thereby informing management strategies to mitigate the adverse effects of N enrichment on soil function.