Globally consistent climate sensitivity of natural disturbances across boreal and temperate forest ecosystems

Disturbance regimes are changing in forests across the world in response to global climate change. Despite the profound impacts of disturbances on ecosystem services and biodiversity, assessments of disturbances at the global scale remain scarce. Here, we analyzed natural disturbances in boreal and temperate forest ecosystems for the period 2001–2014, aiming to 1) quantify their within- and between-biome variation and 2) compare the climate sensitivity of disturbances across biomes. We studied 103 unmanaged forest landscapes with a total land area of 28.2 × 10⁶ ha, distributed across five continents. A consistent and comprehensive quantification of disturbances was derived by combining satellite-based disturbance maps with local expert knowledge of disturbance agents. We used Gaussian finite mixture models to identify clusters of landscapes with similar disturbance activity as indicated by the percent forest area disturbed as well as the size, edge density and perimeter–area-ratio of disturbed patches. The climate sensitivity of disturbances was analyzed using Bayesian generalized linear mixed effect models and a globally consistent climate dataset. Within-biome variation in natural disturbances was high in both boreal and temperate biomes, and disturbance patterns did not vary systematically with latitude or biome. The emergent clusters of disturbance activity in the boreal zone were similar to those in the temperate zone, but boreal landscapes were more likely to experience high disturbance activity than their temperate counterparts. Across both biomes high disturbance activity was particularly associated with wildfire, and was consistently linked to years with warmer and drier than average conditions. Natural disturbances are a key driver of variability in boreal and temperate forest ecosystems, with high similarity in the disturbance patterns between both biomes. The universally high climate sensitivity of disturbances across boreal and temperate ecosystems indicates that future climate change could substantially increase disturbance activity.     

Remotely sensed vegetation phenology for describing and predicting the biomes of South Africa

Questions: What are the patterns of remotely sensed vegetation phenology, including their inter‐annual variability, across South Africa? What are the phenological attributes that contribute most to distinguishing the different biomes? How well can the distribution of the recently redefined biomes be predicted based on remotely sensed, phenology and productivity metrics? Location: South Africa. Method: Ten‐day, 1 km, NDVI AVHRR were analysed for the period 1985 to 2000. Phenological metrics such as start, end and length of the growing season and estimates of productivity, based on small and large integral (SI, LI) of NDVI curve, were extracted and long‐term means calculated. A random forest regression tree was run using the metrics as the input variables and the biomes as the dependent variable. A map of the predicted biomes was reproduced and the differentiating importance of each metric assessed. Results: The phenology metrics (e.g. start of growing season) showed a clear relationship with the seasonality of rainfall, i.e. winter and summer growing seasons. The distribution of the productivity metrics, LI and SI were significantly correlated with mean annual precipitation. The regression tree initially split the biomes based on vegetation production and then by the seasonality of growth. A regression tree was used to produce a predicted biome map with a high level of accuracy (73%). Main conclusion: Regression tree analysis based on remotely sensed metrics performed as good as, or better than, previous climate‐based predictors of biome distribution. The results confirm that the remotely sensed metrics capture sufficient functional diversity to classify and map biome level vegetation patterns and function.     

Climate more important than soils for predicting forest biomass at the continental scale

Above-ground biomass in forests is critical to the global carbon cycle as it stores and sequesters carbon from the atmosphere. Climate change will disrupt the carbon cycle hence understanding how climate and other abiotic variables determine forest biomass at broad spatial scales is important for validating and constraining Earth System models and predicting the impacts of climate change on forest carbon stores. We examined the importance of climate and soil variables to explaining above-ground biomass distribution across the Australian continent using publicly available biomass data from 3130 mature forest sites, in 6 broad ecoregions, encompassing tropical, subtropical and temperate biomes. We used the Random Forest algorithm to test the explanatory power of 14 abiotic variables (8 climate, 6 soil) and to identify the best-performing models based on climate-only, soil-only and climate plus soil. The best performing models explained ~50% of the variation (climate-only: R² = 0.47 ± 0.04, and climate plus soils: R² = 0.49 ± 0.04). Mean temperature of the driest quarter was the most important climate variable, and bulk density was the most important soil variable. Climate variables were consistently more important than soil variables in combined models, and model predictive performance was not substantively improved by the inclusion of soil variables. This result was also achieved when the analysis was repeated at the ecoregion scale. Predicted forest above-ground biomass ranged from 18 to 1066 Mg ha⁻¹, often under-predicting measured above-ground biomass, which ranged from 7 to 1500 Mg ha⁻¹. This suggested that other non-climate, non-edaphic variables impose a substantial influence on forest above-ground biomass, particularly in the high biomass range. We conclude that climate is a strong predictor of above-ground biomass at broad spatial scales and across large environmental gradients, yet to predict forest above-ground biomass distribution under future climates, other non-climatic factors must also be identified.     

Efficiency of protected areas in Amazon and Atlantic Forest conservation: A spatio-temporal view

The Amazon and Atlantic Forest are considered the world's most biodiverse biomes. Human and climate change impacts are the principal drivers of species loss in both biomes, more severely in the Atlantic Forest. In response to species loss, the main conservation action is the creation of protected areas (PAs). Current knowledge and research on the PA network's conservation efficiency is scarce, and existing studies have mainly considered a past temporal view. In this study, we tested the efficiency of the current PA network to maintain climatically stable areas (CSAs) across the Amazon and Atlantic Forest. To this, we used an ecological niche modeling approach to biome and paleoclimatic simulations. We propose three categories of conservation priority areas for both biomes, considering CSAs, PAs and intact forest remnants. The biomes vary in their respective PA networks' protection efficiency. Regarding protect CSAs, the Amazon PA network is four times more efficient than the Atlantic Forest PA network. New conservation efforts in these two forest biomes require different approaches. We discussed the conservation actions that should be taken in each biome to increase the efficiency of the PA network, considering both the creation and expansion of PAs as well as restoration programs.     

Temperature,precipitation, and insolation effects on autumn vegetation phenology in temperate China

Autumn phenology plays a critical role in regulating climate–biosphere interactions. However, the climatic drivers of autumn phenology remain unclear. In this study, we applied four methods to estimate the date of the end of the growing season (EOS) across China's temperate biomes based on a 30‐year normalized difference vegetation index (NDVI) dataset from Global Inventory Modeling and Mapping Studies (GIMMS). We investigated the relationships of EOS with temperature, precipitation sum, and insolation sum over the preseason periods by computing temporal partial correlation coefficients. The results showed that the EOS date was delayed in temperate China by an average rate at 0.12 ± 0.01 days per year over the time period of 1982–2011. EOS of dry grassland in Inner Mongolia was advanced. Temporal trends of EOS determined across the four methods were similar in sign, but different in magnitude. Consistent with previous studies, we observed positive correlations between temperature and EOS. Interestingly, the sum of precipitation and insolation during the preseason was also associated with EOS, but their effects were biome dependent. For the forest biomes, except for evergreen needle‐leaf forests, the EOS dates were positively associated with insolation sum over the preseason, whereas for dry grassland, the precipitation over the preseason was more dominant. Our results confirmed the importance of temperature on phenological processes in autumn, and further suggested that both precipitation and insolation should be considered to improve the performance of autumn phenology models.     

Geographic variation in growth and phenology of two dominant central US grasses: consequences for climate change

Aims The rate of climate change may exceed many plant species' migration rates, particularly for long-lived perennial species that dominate most ecosystems. If bioclimatic envelopes shift more rapidly than dominant species can migrate, individuals located peripheral to biomes or in adjacent biomes may become a significant source of traits for future dominant populations (DPs). Thus, traits of individuals from peripheral populations (PPs) may affect future ecosystem functioning more than those of today's DPs.Methods We assessed key traits of individuals collected from populations that currently dominate two central US grasslands, the shortgrass steppe (Bouteloua gracilis) and the tallgrass prairie (Andropogon gerardii). We compared these to individuals from PPs in a reciprocal-transplant common garden experiment with gardens at the Shortgrass Steppe Long Term Ecological Research site in Colorado and the Konza Prairie Biological Station Long Term Ecological Research site in Kansas. DPs and PPs were subjected to high and reduced water availability in common gardens located in each biome. Traits measured included the following: individual plant biomass, reproductive allocation, specific leaf area (SLA) and plant–water relations. We focused on the climate-change relevant comparisons of traits from PPs versus DPs expressed under the climate of DPs.Important findings PPs of B. gracilis differed from DPs primarily in phenological traits. Under a semiarid shortgrass steppe climate, PPs initiated flowering later in the season, produced fewer reproductive tillers and were more sensitive to water stress. Biomass differences between populations were minimal. For A. gerardii, biomass in PPs was 50% lower than in DPs under the mesic tallgrass prairie climate and reproductive tillers were considerably smaller, despite higher SLA in PPs. Biomass of PPs was less sensitive to water stress, however. From these results, we conclude that key traits of PPs differed from DPs in both grassland types, but potential effects on reproductive phenology were greater for the bioclimatic shift in which a mesic biome becomes arid, whereas aboveground productivity may be affected more when a semiarid biome becomes more mesic.     

Phenological variation within and among populations of Plathymenia reticulata in Brazilian Cerrado, the Atlantic Forest and transitional sites

BACKGROUND AND AIMS: Plathymenia reticulata (Leguminosae) is a Brazilian tree that occurs in two biomes: Cerrado, a woody savanna vegetation, and the Atlantic Forest, a tropical forest. In this study, phenological patterns and their variability within and among populations located in these biomes and in transitional zones between them were assessed. METHODS: During a 15-month period, individuals from two populations in Cerrado, two in the Atlantic Forest, and six in transitional zones (three in a cerrado-like environment and three in forest fragments) were evaluated in Minas Gerais State, Brazil. The individuals were evaluated monthly according to the proportion of the canopy in each vegetative phenophase (leaf fall, leaf flush and mature leaves) and each reproductive phenophase (floral buds, flowers, immature fruits and mature fruit/seed dispersal). In order to assess the phenological variability within and among populations, habitats and biomes, the Shannon-Wiener diversity index, the Morisita-Horn similarity index and genetic population approach of partitioning diversity were used. KEY RESULTS: Populations of P. reticulata, in general, showed similar phenology; the main differences were related to leaf fall, a process that starts months earlier in the Cerrado than in transitional sites, and even later in forest areas. Considerable synchrony was observed for reproductive phenology among populations and between biomes. Most phenological diversity was due to differences among individuals within populations. CONCLUSION: In spite of environmental differences, P. reticulata from the Atlantic Forest and Cerrado showed similar phenological behavior with only about 10% of the total diversity being attributed to differences between biomes.     

A global prognostic scheme of leaf onset using satellite data

Leaf phenology describes the seasonal cycle of leaf functioning. Although it is essential for understanding the interactions between the biosphere, the climate, and biogeochemical cycles, it has received little attention in the modelling community at global scale. This article focuses on the prediction of spatial patterns of the climatological onset date of leaf growth for the decade 1983–93. It examines the possibility of extrapolating existing local models of leaf onset date to the global scale. Climate is the main variable that controls leaf phenology for a given biome at this scale, and satellite observations provide a unique means to study the seasonal cycle of canopies. We combine leaf onset dates retrieved from NOAA/AVHRR satellite NDVI with climate data and the DISCover land‐cover map to identify appropriate models, and determine their new parameters at a 0.5° spatial resolution. We define two main regions: at temperate and high latitudes leaf onset models are mainly dependent on temperature; at low latitudes they are controlled by water availability. Some local leaf onset models are no longer relevant at the global scale making their calibration impossible. Nevertheless, we define our unified model by retaining the model that best reproduced the spatial distribution of leaf onset dates for each biome. The main spatial patterns of leaf onset date are well simulated, such as the Sahelian gradient due to aridity and the high latitude gradient due to frost. At temperate and high latitudes, simulated onset dates are in good agreement with climatological observations; 62% of treated grid‐cells have a simulated leaf onset date within 10 days of the satellite observed onset date (which is also the temporal resolution of the NDVI data). In tropical areas, the subgrid heterogeneity of the phenology is larger and our model's predictive power is diminished. The difficulties encountered in the tropics are due to the ambiguity of the satellite signal interpretation and the low reliability of rainfall and soil moisture fields.     

浙江古田山亚热带常绿阔叶林叶衰老物候影响因子研究

该文选取浙江省古田山亚热带常绿阔叶林72种木本植物,探究气候因素、系统发育关系和功能性状对亚热带常绿阔叶林叶衰老物候的影响。结果表明,叶变色期在9—12月,落叶期在10—12月。每月落叶物种数与月均温、月均降水量和月均日照时数没有显著相关性,每月叶变色物种数与月均温和月均日照时数呈弱相关;落叶性对叶变色期和落叶期具有显著影响;植物间系统发育关系对叶变色期和落叶期没有显著影响。因此,生物和非生物因子都会影响常绿阔叶树种的叶衰老,这对于提高秋季物候预测模型具有重要价值。     

How do seasonality,substrate, and management history influence macrofungal fruiting assemblages in a central Amazonian Forest?

Worldwide, fungal richness peaks in tropical forest biomes where they are the primary drivers of decomposition. Understanding how environmental and anthropogenic factors influence tropical macrofungal fruiting patterns should provide insight as to how, for example, climate change and deforestation may impact their long‐term demographic stability and evolutionary potential. However, in Amazonia no studies have yet to disentangle the effects of substrate, seasonality and forest history on phenology. Here, we quantitate spatial and temporal variation in community structure of fruiting macrofungi in relation to these factors at a long‐term forest management research site in central Amazonia: the Biomass and Nutrients of Tropical Rain Forest (BIONTE's). Basidiome surveys of four substrate classes (leaves, soil, branches and trunks) were conducted along 250 m² transects in primary and secondary (managed) forests, between 2012–13. From the 669 basidiomes collected, 290 taxa were identified of which 44 percent were restricted to primary and 36 percent to secondary forests. Although species‐accumulation curves did not asymptote, rarefaction analyses and Fisher's alpha indicate contrasting differences in richness among forests in relation to substrate type. For example, leaf litter basidiome richness was higher in secondary forests, whereas the contrary was observed for soil communities, suggesting that variation in fruiting patterns in relation to disturbance is substrate‐dependent possibly due to differences in necromass quality and/or understory micro‐climates. Furthermore, secondary forests harbored significantly lower basidiome richness and abundance in dry months, suggesting synergistic impacts of seasonality and management history on fruiting regimes.     

Consistent shifts in spring vegetation green‐up date across temperate biomes in China, 1982–2006

Understanding spring phenology changes in response to the rapid climate change at biome‐level is crucial for projecting regional ecosystem carbon exchange and climate–biosphere interactions. In this study, we assessed the long‐term changes and responses to changing climate of the spring phenology in six temperate biomes of China by analyzing the global inventory monitoring and modeling studies (GIMMS) NOAA/AVHRR Normalized Difference Vegetation Index (NDVI) and concurrent mean temperature and precipitation data for 1982–2006. Results show that the spring phenology trends in the six temperate biomes are not continuous throughout the 25 year period. The spring phenology in most areas of the six biomes showed obvious advancing trends (ranging from ?0.09 to ?0.65 day/yr) during the 1980s and early 1990s, but has subsequently suffered consistently delaying trends (ranging from 0.22 to 1.22 day/yr). Changes in spring (February–April) temperature are the dominating factor governing the pattern of spring vegetation phenology in the temperate biomes of China. The recently delayed spring phenology in these temperate biomes has been mainly triggered by the stalling or reversal of the warming trend in spring temperatures. Results in this study also reveal that precipitation during November–January can explain 16.1% (P < 0.05), 20.9% (P < 0.05) and 14.2% (P < 0.05) of the variations in temperate deciduous forest (TDF), temperate steppe (TS), temperate desert (TD) respectively, highlighting the important role of winter precipitation in regulating changes in the spring vegetation phenology of water–limited biomes.     

中亚热带森林单木地上生物量的机载激光雷达估测

以雪峰山武冈林场为研究对象,利用遥感数据和地面实测样地数据,研究机载激光雷达（LiDAR）估测中亚热带森林乔木层单木地上生物量的能力.利用条件随机场和最优化方法实现LiDAR点云的单木分割,以单木尺度为对象提取的植被点云空间结构、回波特征以及地形特征等作为遥感变量,采用回归模型估测乔木层地上生物量.结果表明: 针叶林、阔叶林和针阔混交林的单木识别率分别为93%、86%和60%;多元逐步回归模型的调整决定系数分别为0.83、0.81和0.74,均方根误差分别为28.22、29.79和32.31 t·hm^-2;以冠层体积、树高百分位值、坡度和回波强度值构成的模型精度明显高于以树高为因子的传统回归模型精度.以单木为对象从LiDAR点云中提取的遥感变量有助于提高森林生物量估测精度.
     

Carbon cycling and storage in world forests: biome patterns related to forest age

Forest age, which is affected by stand‐replacing ecosystem disturbances (such as forest fires, harvesting, or insects), plays a distinguishing role in determining the distribution of carbon (C) pools and fluxes in different forested ecosystems. In this synthesis, net primary productivity (NPP), net ecosystem productivity (NEP), and five pools of C (living biomass, coarse woody debris, organic soil horizons, soil, and total ecosystem) are summarized by age class for tropical, temperate, and boreal forest biomes. Estimates of variability in NPP, NEP, and C pools are provided for each biome‐age class combination and the sources of variability are discussed. Aggregated biome‐level estimates of NPP and NEP were higher in intermediate‐aged forests (e.g., 30–120 years), while older forests (e.g., >120 years) were generally less productive. The mean NEP in the youngest forests (0–10 years) was negative (source to the atmosphere) in both boreal and temperate biomes (?0.1 and –1.9 Mg C ha^?1 yr^?1, respectively). Forest age is a highly significant source of variability in NEP at the biome scale; for example, mean temperate forest NEP was ?1.9, 4.5, 2.4, 1.9 and 1.7 Mg C ha^?1 yr^?1 across five age classes (0–10, 11–30, 31–70, 71–120, 121–200 years, respectively). In general, median NPP and NEP are strongly correlated (R²=0.83) across all biomes and age classes, with the exception of the youngest temperate forests. Using the information gained from calculating the summary statistics for NPP and NEP, we calculated heterotrophic soil respiration (R_h) for each age class in each biome. The mean R_h was high in the youngest temperate age class (9.7 Mg C ha^?1 yr^?1) and declined with age, implying that forest ecosystem respiration peaks when forests are young, not old. With notable exceptions, carbon pool sizes increased with age in all biomes, including soil C. Age trends in C cycling and storage are very apparent in all three biomes and it is clear that a better understanding of how forest age and disturbance history interact will greatly improve our fundamental knowledge of the terrestrial C cycle.     

Functional identity of overstorey tree height and understorey conservative traits drive aboveground biomass in a subtropical forest

The niche complementarity hypothesis has received empirical support but species differ in functional strategies for their contribution to ecosystem function, as predicted by the mass ratio hypothesis. Our understanding of how functional identity of conservative and acquisitive strategies of trees predicts aboveground biomass across forest strata (i.e. overstorey and understorey) remains unclear. Aboveground biomass, community-weighted mean (CWM − functional identity) of trait values (6 leaf and 2 stem traits), and soil physicochemical properties were estimated for 125 plots in a 5-ha subtropical forest in Eastern China. We used multiple linear regressions models to relate aboveground biomass to CWM indices at overstorey and understorey strata separately, and whole-community level. We finally employed the structural equation model to test for the effects of overstorey on understorey strata, in addition to the effects of soil physicochemical properties. Forest strata optimal models showed that overstorey strata had high aboveground biomass when they are dominated by functional identity of tree height, whereas high aboveground biomass in understorey strata was driven by functional identity of dense-wooded conservative strategy. Whole-community optimal model showed that communities dominated by functional identity of leaf dry matter content and mean leaf area had high aboveground biomass. Aboveground biomass was negatively related to soil nutrients across forest strata and whole-community level. The structural equation model showed that CWM of overstorey tree height did not affect understorey functional identity and aboveground biomass, when soil physicochemical properties were accounted. Soil nutrients had positive effect on functional identity of overstorey tree height whereas negative effect on functional identity of understorey dense-wooded strategy. This study highlights the fundamental roles of forest strata where overstorey and understorey strata contribute to their corresponding aboveground biomass with contrasting functional strategies across a range of soil nutrients. High aboveground biomass was potentially driven by functional identity of tree height through making use of plentiful soil nutrients at overstorey strata, whereas by conservative strategy at understorey strata through enduring nutrient-poor soils. To better understand the roles of functional identity of conservative and acquisitive strategies in driving ecosystem functions, it is worth to analyse forest strata separately.     

Linking canopy leaf area and light environments with tree size distributions to explain Amazon forest demography

Forest biophysical structure – the arrangement and frequency of leaves and stems – emerges from growth, mortality and space filling dynamics, and may also influence those dynamics by structuring light environments. To investigate this interaction, we developed models that could use LiDAR remote sensing to link leaf area profiles with tree size distributions, comparing models which did not (metabolic scaling theory) and did allow light to influence this link. We found that a light environment‐to‐structure link was necessary to accurately simulate tree size distributions and canopy structure in two contrasting Amazon forests. Partitioning leaf area profiles into size‐class components, we found that demographic rates were related to variation in light absorption, with mortality increasing relative to growth in higher light, consistent with a light environment feedback to size distributions. Combining LiDAR with models linking forest structure and demography offers a high‐throughput approach to advance theory and investigate climate‐relevant tropical forest change.     

Divergent biomass partitioning to aboveground and belowground across forests in China

Aims Belowground to aboveground biomass (BGB/AGB) ratio is a highly valued parameter of the terrestrial carbon cycle and productivity. However, it remains far from clear whether plant biomass partitioning to aboveground and belowground is isometric (equal partitioning) or allometric (unequal partitioning) at community levels and what factors are necessary in order to regulate the partitioning. This study aimed to comprehensively find out the patterns of biomass partitioning and their regulatory factors across forests in China.Methods The data of AGB and BGB were compiled from 1542 samples for communities across forests in China. Standardized major axis regression was conducted to examine whether AGB and BGB were allocated isometrically or allometrically at a community level. Redundancy analysis was used to analyze the relationships of BGB/AGB ratio with climatic factors and soil properties.Important findings We found that the slopes of the relationship between logAGB and logBGB were not always comparable to 1.0 (isometric allocation) at community levels, including primary forest, secondary forest, and planted forest. Meanwhile, samples in clay, loam, and sand soil types also presented the same phenomenon. Furthermore, the radically different allocations of AGB and BGB were found in northern and southern China. Environmental factors totally explained 3.86% of the variations in the BGB/AGB ratio at the community level, which include the mean annual precipitation, mean annual temperature, potential water deficit index, soil carbon content, soil nitrogen content, soil clay, soil loam, soil sand, soil pH, and soil bulk density. In addition, the environmental factors also have effects on the BGB/AGB ratio in other categories. The patterns revealed in this study are helpful for better understanding biomass partitioning and spreading the carbon circle models.     

Variations in leaf litter decomposition across contrasting forest stands and controlling factors at local scale

Aims Litter decomposition is a critical pathway linking the above- and belowground processes. However, factors underlying the local spatial variations in forest litter decomposition are still not fully addressed. We investigated leaf litter decomposition across contrasting forest stands in central China, with objective to determine the spatial variations and controlling factors in forest floor leaf litter decomposition in relation to changes in forest stands in a temperate forest ecosystem.Methods Leaf litter decomposition was studied by using litterbag method across several typical forest stand types in Baotianman Nature Reserve, central China, including pure stands of Quercus aliena var. acuteserrata, Q. glandulifera var. brevipetiolata and Q. variabilis, respectively, and mixed pine/oak stands dominated by Pinus armandii and Q. aliena var. acuteserrata, as well as stands of pure Q. aliena var. acuteserrata trees ranging in stand age from ~40 to>160 years. Measurements were made on litter mass remaining and changes in litter chemistry during decomposition over a 2-year period, along with data collections on selective biotic and environmental factors. A reciprocal transplant experiment involving Q. aliena var. acuteserrata and Q. variabilis was concurrently carried out to test the occurrence of 'home-field advantage (HFA)' in local forests when only considering contrasting oak tree species. Correlation analyses and path analyses were performed to identify the dominant drivers and their relative contributions to variations in leaf litter decomposition.Important findings Significant variations were found in the rate of leaf litter decomposition among stands of different tree species but not among stand age classes. The values of decay constant, k, varied from 0.62 in Q. aliena var. acuteserrata stands to 0.56 in Q. variabilis stands. The reciprocal litter transplant experiment showed that the rate of leaf litter decomposition was on average 5% slower in home-fields than on reciprocal sites. Path analysis identified litter acid-unhydrolyzable residue (AUR) to N ratio, soil microbial biomass carbon (MBC), soil pH and soil organic carbon (SOC) as most prominent factors controlling the rate of leaf litter decomposition, collectively accounting for 57.8% of the variations; AUR/N had the greatest negative effect on k value, followed by weaker positive effects of SOC and MBC. Our findings suggest that tree species plays a primary role in affecting forest floor leaf litter decomposition by determining the litter quality, with site environment being a secondary factor contributing to the local variations in leaf litter decomposition in this temperate forest ecosystem.     

Climatic sensitivity of species’ vegetative and reproductive phenology in a Hawaiian montane wet forest

Understanding how tropical tree phenology (i.e., the timing and amount of seed and leaf production) responds to climate is vital for predicting how climate change may alter ecological functioning of tropical forests. We examined the effects of temperature, rainfall, and photosynthetically active radiation (PAR) on seed phenology of four dominant species and community-level leaf phenology in a montane wet forest on the island of Hawaiʻi using monthly data collected over ~ 6 years. We expected that species phenologies would be better explained by variation in temperature and PAR than rainfall because rainfall at this site is not limiting. The best-fit model for all four species included temperature, rainfall, and PAR. For three species, including two foundational species of Hawaiian forests (Acacia koa and Metrosideros polymorpha), seed production declined with increasing maximum temperatures and increased with rainfall. Relationships with PAR were the most variable across all four species. Community-level leaf litterfall decreased with minimum temperatures, increased with rainfall, and showed a peak at PAR of ~ 400 μmol/m²s⁻¹. There was considerable variation in monthly seed and leaf production not explained by climatic factors, and there was some evidence for a mediating effect of daylength. Thus, the impact of future climate change on this forest will depend on how climate change interacts with other factors such as daylength, biotic, and/or evolutionary constraints. Our results nonetheless provide insight into how climate change may affect different species in unique ways with potential consequences for shifts in species distributions and community composition.     

Landscape-Scale Controls on Aboveground Forest Carbon Stocks on the Osa Peninsula,Costa Rica

Tropical forests store large amounts of carbon in tree biomass, although the environmental controls on forest carbon stocks remain poorly resolved. Emerging airborne remote sensing techniques offer a powerful approach to understand how aboveground carbon density (ACD) varies across tropical landscapes. In this study, we evaluate the accuracy of the Carnegie Airborne Observatory (CAO) Light Detection and Ranging (LiDAR) system to detect top-of-canopy tree height (TCH) and ACD across the Osa Peninsula, Costa Rica. LiDAR and field-estimated TCH and ACD were highly correlated across a wide range of forest ages and types. Top-of-canopy height (TCH) reached 67 m, and ACD surpassed 225 Mg C ha^-1, indicating both that airborne CAO LiDAR-based estimates of ACD are accurate in tall, high-biomass forests and that the Osa Peninsula harbors some of the most carbon-rich forests in the Neotropics. We also examined the relative influence of lithologic, topoedaphic and climatic factors on regional patterns in ACD, which are known to influence ACD by regulating forest productivity and turnover. Analyses revealed a spatially nested set of factors controlling ACD patterns, with geologic variation explaining up to 16% of the mapped ACD variation at the regional scale, while local variation in topographic slope explained an additional 18%. Lithologic and topoedaphic factors also explained more ACD variation at 30-m than at 100-m spatial resolution, suggesting that environmental filtering depends on the spatial scale of terrain variation. Our result indicate that patterns in ACD are partially controlled by spatial variation in geologic history and geomorphic processes underpinning topographic diversity across landscapes. ACD also exhibited spatial autocorrelation, which may reflect biological processes that influence ACD, such as the assembly of species or phenotypes across the landscape, but additional research is needed to resolve how abiotic and biotic factors contribute to ACD variation across high biomass, high diversity tropical landscapes.     

Driving factors and temporal fluctuation of Collembola communities and reproductive mode across forest types and regions

Despite the major role of Collembola in forest soil animal food webs, ecological and evolutionary determinants of their community composition are not well understood. We investigated abundance, community structure, life forms, and reproductive mode of Collembola in four different forest types (coniferous, young managed beech, old managed beech, and unmanaged beech forests) representing different management intensities. Forest types were replicated within three regions across Germany: the Schorfheide‐Chorin, the Hainich, and the Swabian Alb, differing in geology, altitude, and climate. To account for temporal variation, samples were taken twice with an interval of 3 years. To identify driving factors of Collembola community structure, we applied structural equation modeling, including an index of forest management intensity, abiotic and biotic factors such as pH, C‐to‐N ratio of leaf litter, microbial biomass, and fungal‐to‐bacterial ratio. Collembola abundance, biomass, and community composition differed markedly between years, with most pronounced differences in the Schorfheide, the region with the harshest climatic conditions. There, temporal fluctuations of parthenogenetic Collembola were significantly higher than in the other regions. In the year with the more favorable conditions, parthenogenetic species flourished, with their abundance depending mainly on abiotic, density‐independent factors. This is in line with the “Structured Resource Theory of Sexual Reproduction,” stating that parthenogenetic species are favored if density‐independent factors, such as desiccation, frost or flooding, prevail. In contrast, sexual species in the same year were mainly influenced by resource quality‐related factors such as the fungal‐to‐bacterial ratio and the C‐to‐N ratio of leaf litter. The influence of forest management intensity on abundances was low, indicating that disturbance through forest management plays a minor role. Accordingly, differences in community composition were more pronounced between regions than between different forest types, pointing to the importance of regional factors.