Cold threat and moisture deficit induced individual tree mortality via 25-year monitoring in seminatural mixed forests, northeastern China.

Accurately predicting tree mortality in mixed forests sets a challenge for conventional models because of large uncertainty, especially under changing climate. Machine learning algorithms had potential for predicting individual tree mortality with higher accuracy via filtering the relevant climatic and environmental factors. In this study, the sensitivity of individual tree mortality to regional climate was validated by modeling in seminatural mixed coniferous forests based on 25-year observations in northeast of China. Three advanced machine learning and deep learning algorithms were employed, including support vector machines, multi-layer perceptron, and random forests. Mortality was predicted by the effects of multiple inherent and environmental factors, including tree size and growth, topography, competition, stand structure and regional climate. All three types of models performed satisfactorily with their values of the areas under receiving operating characteristic curve (AUC) > 0.9. With tree growth, competition and regional climate as input variables, a model based on random forests showed the highest values of the explained variance score (0.862) and AUC (0.914). Since the trees were vulnerable despite their species, mortality could occur after growth limit induced by insufficient or excessive sun radiation during growing seasons, cold threat caused thermal insufficiency in winters, and annual moisture constraints in these mixed coniferous forests. Our findings could enrich basic knowledge on individual tree mortality caused by water and heat inadequacy with the negative impacts of global warming. Successful individual tree mortality modeling via advanced algorithms in mixed forests could assist in adaptive forest ecology modeling in large areas.

Tall Bornean forests experience higher canopy disturbance rates than those in the eastern Amazon or Guiana shield.

The future of tropical forests hinges on the balance between disturbance rates, which are expected to increase with climate change, and tree growth. Whereas tree growth is a slow process, disturbance events occur sporadically and tend to be short-lived. This difference challenges forest monitoring to achieve sufficient resolution to capture tree growth, while covering the necessary scale to characterize disturbance rates. Airborne LiDAR time series can address this challenge by measuring landscape scale changes in canopy height at 1 m resolution. In this study, we present a robust framework for analysing disturbance and recovery processes in LiDAR time series data. We apply this framework to 8000 ha of old-growth tropical forests over a 4-5-year time frame, comparing growth and disturbance rates between Borneo, the eastern Amazon and the Guiana shield. Our findings reveal that disturbance was balanced by growth in eastern Amazonia and the Guiana shield, resulting in a relatively stable mean canopy height. In contrast, tall Bornean forests experienced a decrease in canopy height due to numerous small-scale (<0.1 ha) disturbance events outweighing the gains due to growth. Within sites, we found that disturbance rates were weakly related to topography, but significantly increased with maximum canopy height. This could be because taller trees were particularly vulnerable to disturbance agents such as drought, wind and lightning. Consequently, we anticipate that tall forests, which contain substantial carbon stocks, will be disproportionately affected by the increasing severity of extreme weather events driven by climate change.

Local carbon reserves are insufficient for phloem terpene induction during drought in Pinus edulis in response to bark beetle-associated fungi.

Stomatal closure during drought inhibits carbon uptake and may reduce a tree's defensive capacity. Limited carbon availability during drought may increase a tree's mortality risk, particularly if drought constrains trees' capacity to rapidly produce defenses during biotic attack. We parameterized a new model of conifer defense using physiological data on carbon reserves and chemical defenses before and after a simulated bark beetle attack in mature Pinus edulis under experimental drought. Attack was simulated using inoculations with a consistent bluestain fungus (Ophiostoma sp.) of Ips confusus, the main bark beetle colonizing this tree, to induce a defensive response. Trees with more carbon reserves produced more defenses but measured phloem carbon reserves only accounted for c. 23% of the induced defensive response. Our model predicted universal mortality if local reserves alone supported defense production, suggesting substantial remobilization and transport of stored resin or carbon reserves to the inoculation site. Our results show that de novo terpene synthesis represents only a fraction of the total measured phloem terpenes in P. edulis following fungal inoculation. Without direct attribution of phloem terpene concentrations to available carbon, many studies may be overestimating the scale and importance of de novo terpene synthesis in a tree's induced defense response.

Spatial Pattern of Living Woody and Coarse Woody Debris in Warm-Temperate Broad-Leaved Secondary Forest in North China.

The investigation into the spatial distribution of living woody (LWD) and coarse woody debris (CWD) within forests represents a fundamental methodology for probing the inherent mechanisms governing coexistence and mortality within forest ecosystems. Here, a complete spatial randomness (CSR) null model was employed to scrutinize the spatial pattern, while canonical correspondence analysis (CCA) and the Torus-translation test (TTT) were utilized to elucidate the distribution patterns of LWD and CWD within warm-temperate deciduous broadleaf secondary forests in Dongling Mountains plot, northern China. The results reveal that both LWD and CWD exhibit an aggregated distribution as the predominant pattern in the Dongling Mountains plot, with the proportion and intensity of aggregation diminishing as spatial scale increases. Specifically, the aggregation intensity g0-10 demonstrates a significant negative correlation with abundance and maximum diameter at breast height (DBH). Notably, the g0-10 of LWD manifests a stronger correlation with the maximum DBH, whereas the g0-10 of CWD exhibits a greater association with the mortality rate. CCA outcomes suggest that elevation, convexity, and aspect significantly impact LWD distribution, whereas CWD distribution shows substantial negative correlations with elevation, convexity, slope, and aspect. TTT findings indicate that ecosystems characterized by a substantial presence of LWD also display a notable prevalence of CWD. Additionally, the majority of species exhibit no habitat preference, displaying neutral habitat connections and low ecological niche differentiation within the sampled plot.

Using climate envelopes and earth system model simulations for assessing climate change induced forest vulnerability.

Changing climatic conditions threaten forest ecosystems. Drought, disease and infestation, are leading to forest die-offs which cause substantial economic and ecological losses. In central Europe, this is especially relevant for commercially important coniferous tree species. This study uses climate envelope exceedance (CEE) to approximate species risk under different future climate scenarios. To achieve this, we used current species presence-absence and historical climate data, coupled with future climate scenarios from various Earth System Models. Climate scenarios tended towards drier and warmer conditions, causing strong CEEs especially for spruce. However, we show that annual averages of temperature and precipitation obscure climate extremes. Including climate extremes reveals a broader increase in CEEs across all tree species. Our study shows that the consideration of climate extremes, which cannot be adequately reflected in annual averages, leads to a different assessment of the risk of forests and thus the options for adapting to climate change.

Effects of canopy gaps on microclimate, soil biological activity and their relationship in a European mixed floodplain forest.

Forest canopy gaps can influence understorey microclimate and ecosystem functions such as decomposition. Gaps can arise from silviculture or tree mortality, increasingly influenced by climate change. However, to what degree canopy gaps affect the buffered microclimate in the understorey under macroclimatic changes is unclear. We, therefore, investigated the effect of forest gaps differing in structure and size (25 gaps: single tree gaps up to 0.67 ha cuttings) on microclimate and soil biological activity compared to closed forest in a European mixed floodplain forest. During the investigation period in the drought year 2022 between May and October, mean soil moisture and temperature as well as soil and air temperature fluctuations increased with increasing openness. In summer, the highest difference of monthly means between cuttings and closed forest in the topsoil was 3.98 ± 9.43 % volumetric moisture and 2.05 ± 0.89 °C temperature, and in the air at 30 cm height 0.61 ± 0.35 °C temperature. For buffering, both the over- and understorey tree layers appeared as relevant with a particularly strong influence of understorey density on soil temperature. Three experiments, investigating soil biological activity by quantifying decomposition rates of tea and wooden spatulas as well as mesofauna feeding activity with bait-lamina stripes, revealed no significant differences between gaps and closed forest. However, we found a positive significant effect of mean soil temperature on feeding activity throughout the season. Although soil moisture decreased during this period, it showed no counteracting effect on feeding activity. Generally, very few significant relationships were observed between microclimate and soil biological activity in single experiments. Despite the dry growing season, decomposition rates remained high, suggesting temperature had a stronger influence than soil moisture. We conclude that the microclimatic differences within the gap gradient of our experiment were not strong enough to affect soil biological activity considerably.

Meta-analysis of livestock effects on tree regeneration in oak agroforestry systems.

Livestock grazing occupies over a quarter of terrestrial land and is prevalent to agroforestry ecosystems, potentially affecting the survival, growth, and density of trees' early developmental stages, such as seeds, seedlings, and saplings. To address the effects of livestock on tree recruitment in the face of ongoing debates about their impacts, we conducted a 33-year meta-analysis in Quercus-dominated agroforestry systems. Our analysis revealed a consistently negative effect of livestock on oak acorns, seedlings, and saplings. Significantly, livestock body size influenced oak regeneration, with small-sized livestock, notably sheep and goats, having a more pronounced negative impact compared to mixed-size systems, mainly involving cattle and sheep. The effects of small-sized livestock were markedly detrimental on acorn survival and seedling/sapling density, although no studies eligible for meta-analysis examined large livestock impacts on acorns. Overall, mixed-size livestock systems, often involving cattle and sheep, lessen the negative effects. Our findings indicate that the body size and foraging behaviors of livestock should be considered for the ecological sustainability of the tree component in agroforestry systems. While protective measures have long been integral to well-managed agroforestry systems, our results underscore the importance of integrating diverse livestock sizes and applying specific protective strategies, particularly for acorns and saplings, to further refine these practices. Future research should expand to underrepresented regions and livestock types to refine global agroforestry management practices.

Hydraulic properties and drought response of a tropical bamboo (Cephalostachyum pergracile).

Bamboo plants are an essential component of tropical ecosystems, yet their vulnerability to climate extremes, such as drought, is poorly understood due to limited knowledge of their hydraulic properties. Cephalostachyum pergracile, a commonly used tropical bamboo species, exhibited a substantially higher mortality rate than other co-occurring bamboos during a severe drought event in 2019, but the underlying mechanisms remain unclear. This study investigated the leaf and stem hydraulic traits related to drought responses, including leaf-stem embolism resistance (P50leaf; P50stem) estimated using optical and X-ray microtomography methods, leaf pressure-volume and water-releasing curves. Additionally, we investigated the seasonal water potentials, native embolism level (PLC) and xylem water source using stable isotope. We found that C. pergracile exhibited strong resistance to embolism, showing low P50leaf, P50stem, and turgor loss point, despite its rapid leaf water loss. Interestingly, its leaves displayed greater resistance to embolism than its stem, suggesting a lack of effective hydraulic vulnerability segmentation (HVS) to protect the stem from excessive xylem tension. During the dry season, approximately 49% of the water was absorbed from the upper 20-cm-deep soil layer. Consequently, significant diurnal variation in leaf water potentials and an increase in midday PLC from 5.87 ± 2.33% in the wet season to 12.87 ± 4.09% in the dry season were observed. In summary, this study demonstrated that the rapid leaf water loss, high reliance on surface water, and a lack of effective HVS in C. pergracile accelerated water depletion and increased xylem embolism even in the typical dry season, which may explain its high mortality rate during extreme drought events in 2019.

Positive effects of tree species diversity on productivity switch to negative after severe drought mortality in a temperate forest experiment.

The synthesis of a large body of evidence from field experiments suggests more diverse plant communities are more productive as well as more resistant to the effects of climatic extremes like drought. However, this view is strongly based on data from grasslands due to the limited empirical evidence from tree diversity experiments. Here we report on the relationship between tree diversity and productivity over 10 years in a field experiment established in 2005 that was then affected by the 2018 mega-drought in central Europe. Across a number of years, tree species diversity and productivity were significantly positively related; however, the slope switched to negative in the year of the drought. Net diversity effects increased through time, with complementarity effects making greater contributions to the net diversity effect than selection effects. Complementarity effects were clearly positive in three- and five-species mixtures before the drought (2012-2016) but were found to decrease in the year of the drought. Selection effects were clearly positive in 2016 and remained positive in the drought year 2018 in two-, three-, and five-species mixtures. The survival of Norway spruce (Picea abies) plummeted in response to the drought, and a negative relationship between species diversity and spruce survival was found. Taken together, our findings suggest that tree diversity per se may not buffer communities against the impacts of extreme drought and that tree species composition and the drought tolerance of tree species (i.e., species identity) will be important determinants of community productivity as the prevalence of drought increases.

Mechanistic links between physiology and spectral reflectance enable previsual detection of oak wilt and drought stress.

Tree mortality due to global change-including range expansion of invasive pests and pathogens-is a paramount threat to forest ecosystems. Oak forests are among the most prevalent and valuable ecosystems both ecologically and economically in the United States. There is increasing interest in monitoring oak decline and death due to both drought and the oak wilt pathogen (Bretziella fagacearum). We combined anatomical and ecophysiological measurements with spectroscopy at leaf, canopy, and airborne levels to enable differentiation of oak wilt and drought, and detection prior to visible symptom appearance. We performed an outdoor potted experiment with Quercus rubra saplings subjected to drought stress and/or artificially inoculated with the pathogen. Models developed from spectral reflectance accurately predicted ecophysiological indicators of oak wilt and drought decline in both potted and field experiments with naturally grown saplings. Both oak wilt and drought resulted in blocked water transport through xylem conduits. However, oak wilt impaired conduits in localized regions of the xylem due to formation of tyloses instead of emboli. The localized tylose formation resulted in more variable canopy photosynthesis and water content in diseased trees than drought-stressed ones. Reflectance signatures of plant photosynthesis, water content, and cellular damage detected oak wilt and drought 12 d before visual symptoms appeared. Our results show that leaf spectral reflectance models predict ecophysiological processes relevant to detection and differentiation of disease and drought. Coupling spectral models that detect physiological change with spatial information enhances capacity to differentiate plant stress types such as oak wilt and drought.