Differential responses of production and respiration to temperature and moisture drive the carbon balance across a climatic gradient in New Mexico

Southwestern North America faces an imminent transition to a warmer, more arid climate, and it is critical to understand how these changes will affect the carbon balance of southwest ecosystems. In order to test our hypothesis that differential responses of production and respiration to temperature and moisture shape the carbon balance across a range of spatio‐temporal scales, we quantified net ecosystem exchange (NEE) of CO₂ and carbon storage across the New Mexico Elevational Gradient, which consists of six eddy‐covariance sites representing biomes ranging from desert to subalpine conifer forest. Within sites, hotter and drier conditions were associated with an increasing advantage of respiration relative to production such that daily carbon uptake peaked at intermediate temperatures – with carbon release often occurring on the hottest days – and increased with soil moisture. Across sites, biotic adaptations modified but did not override the dominant effects of climate. Carbon uptake increased with decreasing temperature and increasing precipitation across the elevational gradient; NEE ranged from a source of ～30 g C m^?2 yr^?1 in the desert grassland to a sink of ～350 g C m^?2 yr^?1 in the subalpine conifer forest. Total aboveground carbon storage increased dramatically with elevation, ranging from 186 g C m^?2 in the desert grassland to 26 600 g C m^?2 in the subalpine conifer forest. These results make sense in the context of global patterns in NEE and biomass storage, and support that increasing temperature and decreasing moisture shift the carbon balance of ecosystems in favor of respiration, such that the potential for ecosystems to sequester and store carbon is reduced under hot and/or dry conditions. This implies that projected climate change will trigger a substantial net release of carbon in these New Mexico ecosystems (～3 Gt CO₂ statewide by the end of the century), thereby acting as a positive feedback to climate change.     

Canopy duration has little influence on annual carbon storage in the deciduous broad leaf forest

Vegetation phenology, the study of the timing and length of the terrestrial growing season and its connection to climate, is increasingly important in integrated Earth system science. Phenological variability is an excellent barometer of short‐ and long‐term climatic variability, strongly influences surface meteorology, and may influence the carbon cycle. Here, using the 1895–1993 Vegetation/Ecosystem Modelling and Analysis dataset and the Biome‐BGC terrestrial ecosystem model, we investigated the relationship between phenological metrics and annual net ecosystem exchange (NEE) of carbon. For the 1167 deciduous broad leaf forest pixels, we found that NEE was extremely weakly related to canopy duration (days from leaf appearance to complete leaf fall). Longer canopy duration, did, however, sequester more carbon if warm season precipitation was above average. Carbon uptake period (number of days with net CO₂ uptake from the atmosphere), which integrates the influence of all ecosystem states and processes, was strongly related to NEE. Results from the Harvard Forest eddy‐covariance site supported our findings. Such dramatically different results from two definitions of ‘growing season length’ highlight the potential for confusion among the many disciplines engaged in phenological research.     

Deriving land surface phenology indicators from CO2 eddy covariance measurements

Recent progress of CO₂ eddy covariance (EC) technique and accumulation of measurements offer an unprecedented perspective to study the land surface phenology (LSP) in a more objective way than previously possible by allowing the actual photosynthesis measurement – gross primary productivity (GPP). Because of the spatial, temporal, and ecological complexity of processes controlling GPP time series, the extraction of important LSP dates from GPP has been elusive. Here, we present objective measures of several LSP metrics from GPP time series data. A case study based on long term GPP measurements over a mature boreal deciduous forest is provided together with LSP estimates from remote sensing data. Results show that most LSP metrics are interrelated within each season (spring and autumn) both from GPP and remote sensing based estimates. We provide simple mathematical derivatives of GPP time series to objectively estimate key LSP metrics such as: the start, end and length of growing season; end of greenup; start of browndown; length of canopy closure; start, end and length of peak; and peak of season. These key LSP metrics indicate the collective ecological responses to environmental changes over space and time.     

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.     

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.     

Forest biomass is strongly shaped by forest height across boreal to tropical forests in China

Aims Forest height is a major factor shaping geographic biomass patterns, and there is a growing dependence on forest height derived from satellite light detecting and ranging (LiDAR) to monitor large-scale biomass patterns. However, how the relationship between forest biomass and height is modulated by climate and biotic factors has seldom been quantified at broad scales and across various forest biomes, which may be crucial for improving broad-scale biomass estimations based on satellite LiDAR.Methods We used 1263 plots, from boreal to tropical forest biomes across China, to examine the effects of climatic (energy and water availability) and biotic factors (forest biome, leaf form and leaf phenology) on biomass–height relationship, and to develop the models to estimate biomass from forest height in China.Important findings (i) Forest height alone explained 62% of variation in forest biomass across China and was far more powerful than climate and other biotic factors. (ii) However, the relationship between biomass and forest height were significantly affected by climate, forest biome, leaf phenology (evergreen vs. deciduous) and leaf form (needleleaf vs. broadleaf). Among which, the effect of climate was stronger than other factors. The intercept of biomass–height relationship was more affected by precipitation while the slope more affected by energy availability. (iii) When the effects of climate and biotic factors were considered in the models, geographic biomass patterns could be well predicted from forest height with an r 2 between 0.63 and 0.78 (for each forest biome and for all biomes together). For most biomes, forest biomass could be well predicted with simple models including only forest height and climate. (iv) We provided the first broad-scale models to estimate biomass from forest height across China, which can be utilized by future LiDAR studies. (v) Our results suggest that the effect of climate and biotic factors should be carefully considered in models estimating broad-scale forest biomass patterns with satellite LiDAR.     

Asymmetric response of forest and grassy biomes to climate variability across the African Humid Period: influenced by anthropogenic disturbance?

A comprehensive understanding of the relationship between land cover, climate change and disturbance dynamics is needed to inform scenarios of vegetation change on the African continent. Although significant advances have been made, large uncertainties exist in projections of future biodiversity and ecosystem change for the world's largest tropical landmass. To better illustrate the effects of climate–disturbance–ecosystem interactions on continental-scale vegetation change, we apply a novel statistical multivariate envelope approach to subfossil pollen data and climate model outputs (TraCE-21ka). We target paleoenvironmental records across continental Africa, from the African Humid Period (AHP: ca 14 700–5500 yr BP) – an interval of spatially and temporally variable hydroclimatic conditions – until recent times, to improve our understanding of overarching vegetation trends and to compare changes between forest and grassy biomes (savanna and grassland). Our results suggest that although climate variability was the dominant driver of change, forest and grassy biomes responded asymmetrically: 1) the climatic envelope of grassy biomes expanded, or persisted in increasingly diverse climatic conditions, during the second half of the AHP whilst that of forest did not; 2) forest retreat occurred much more slowly during the mid to late Holocene compared to the early AHP forest expansion; and 3) as forest and grassy biomes diverged during the second half of the AHP, their ecological relationship (envelope overlap) fundamentally changed. Based on these asymmetries and associated changes in human land use, we propose and discuss three hypotheses about the influence of anthropogenic disturbance on continental-scale vegetation change.     

Mid-Holocene and glacial-maximum vegetation geography of the northern continents and Africa

BIOME 6000 is an international project to map vegetation globally at mid‐Holocene (6000 ¹⁴C yr bp ) and last glacial maximum (LGM, 18,000 ¹⁴C yr bp ), with a view to evaluating coupled climate‐biosphere model results. Primary palaeoecological data are assigned to biomes using an explicit algorithm based on plant functional types. This paper introduces the second Special Feature on BIOME 6000. Site‐based global biome maps are shown with data from North America, Eurasia (except South and Southeast Asia) and Africa at both time periods. A map based on surface samples shows the method’s skill in reconstructing present‐day biomes. Cold and dry conditions at LGM favoured extensive tundra and steppe. These biomes intergraded in northern Eurasia. Northern hemisphere forest biomes were displaced southward. Boreal evergreen forests (taiga) and temperate deciduous forests were fragmented, while European and East Asian steppes were greatly extended. Tropical moist forests (i.e. tropical rain forest and tropical seasonal forest) in Africa were reduced. In south‐western North America, desert and steppe were replaced by open conifer woodland, opposite to the general arid trend but consistent with modelled southward displacement of the jet stream. The Arctic forest limit was shifted slighly north at 6000 ¹⁴C yr bp in some sectors, but not in all. Northern temperate forest zones were generally shifted greater distances north. Warmer winters as well as summers in several regions are required to explain these shifts. Temperate deciduous forests in Europe were greatly extended, into the Mediterranean region as well as to the north. Steppe encroached on forest biomes in interior North America, but not in central Asia. Enhanced monsoons extended forest biomes in China inland and Sahelian vegetation into the Sahara while the African tropical rain forest was also reduced, consistent with a modelled northward shift of the ITCZ and a more seasonal climate in the equatorial zone. Palaeobiome maps show the outcome of separate, independent migrations of plant taxa in response to climate change. The average composition of biomes at LGM was often markedly different from today. Refugia for the temperate deciduous and tropical rain forest biomes may have existed offshore at LGM, but their characteristic taxa also persisted as components of other biomes. Examples include temperate deciduous trees that survived in cool mixed forest in eastern Europe, and tropical evergreen trees that survived in tropical seasonal forest in Africa. The sequence of biome shifts during a glacial‐interglacial cycle may help account for some disjunct distributions of plant taxa. For example, the now‐arid Saharan mountains may have linked Mediterranean and African tropical montane floras during enhanced monsoon regimes. Major changes in physical land‐surface conditions, shown by the palaeobiome data, have implications for the global climate. The data can be used directly to evaluate the output of coupled atmosphere‐biosphere models. The data could also be objectively generalized to yield realistic gridded land‐surface maps, for use in sensitivity experiments with atmospheric models. Recent analyses of vegetation‐climate feedbacks have focused on the hypothesized positive feedback effects of climate‐induced vegetation changes in the Sahara/Sahel region and the Arctic during the mid‐Holocene. However, a far wider spectrum of interactions potentially exists and could be investigated, using these data, both for 6000 ¹⁴C yr bp and for the LGM.     

Data gaps in anthropogenically driven local‐scale species richness change studies across the Earth's terrestrial biomes

There have been numerous attempts to synthesize the results of local‐scale biodiversity change studies, yet several geographic data gaps exist. These data gaps have hindered ecologist's ability to make strong conclusions about how local‐scale species richness is changing around the globe. Research on four of the major drivers of global change is unevenly distributed across the Earth's biomes. Here, we use a dataset of 638 anthropogenically driven species richness change studies to identify where data gaps exist across the Earth's terrestrial biomes based on land area, future change in drivers, and the impact of drivers on biodiversity, and make recommendations for where future studies should focus their efforts. Across all drivers of change, the temperate broadleaf and mixed forests and the tropical moist broadleaf forests are the best studied. The biome–driver combinations we have identified as most critical in terms of where local‐scale species richness change studies are lacking include the following: land‐use change studies in tropical and temperate coniferous forests, species invasion and nutrient addition studies in the boreal forest, and warming studies in the boreal forest and tropics. Gaining more information on the local‐scale effects of the specific human drivers of change in these biomes will allow for better predictions of how human activity impacts species richness around the globe.     

Phenology, seasonal timing and circannual rhythms: towards a unified framework

Phenology refers to the periodic appearance of life-cycle events and currently receives abundant attention as the effects of global change on phenology are so apparent. Phenology as a discipline observes these events and relates their annual variation to variation in climate. But phenology is also studied in other disciplines, each with their own perspective. Evolutionary ecologists study variation in seasonal timing and its fitness consequences, whereas chronobiologists emphasize the periodic nature of life-cycle stages and their underlying timing programmes (e.g. circannual rhythms). The (neuro-) endocrine processes underlying these life-cycle events are studied by physiologists and need to be linked to genes that are explored by molecular geneticists. In order to fully understand variation in phenology, we need to integrate these different perspectives, in particular by combining evolutionary and mechanistic approaches. We use avian research to characterize different perspectives and to highlight integration that has already been achieved. Building on this work, we outline a route towards uniting the different disciplines in a single framework, which may be used to better understand and, more importantly, to forecast climate change impacts on phenology.     

Climate Change Could Negate Positive Tree Diversity Effects on Forest Productivity: A Study Across Five Climate Types in Spain and Canada

A positive relationship between tree diversity and forest productivity is reported for many forested biomes of the world. However, whether tree diversity is able to increase the stability of forest growth to changes in climate is still an open question. We addressed this question using 36,378 permanent forest plots from National Forest Inventories of Spain and Québec (Eastern Canada), covering five of the most important climate types where forests grow on Earth and a large temperature and precipitation gradient. The plots were used to compute forest productivity (aboveground woody biomass increment) and functional diversity (based on the functional traits of species). Divergence from normal levels of precipitation (dryer or wetter than 30-year means) and temperature (warmer or colder) were computed for each plot from monthly temperature and precipitation means. Other expected drivers of forest growth were also included. Our results show a significant impact of climate divergences on forest productivity, but not always in the expected direction. Furthermore, although functional trait diversity had a general positive impact on forest productivity under normal conditions, this effect was not maintained in stands having suffered from temperature divergence (i.e., warmer conditions). Contrary to our expectations, we found that tree diversity did not result in more stable forest’s growth conditions during changes in climate. These results could have important implications for the future dynamics and management of mixed forests worldwide under climate change.     

Facing complexity in tropical conservation: how reduced impact logging and climatic extremes affect beta diversity in tropical amphibian assemblages

Biodiversity in pristine forest biomes is increasingly disturbed by human activity. Drivers such as logging and climate extremes are thought to collectively erode diversity, but their interactions are not well understood. However, ignoring such complexities may result in poor conservation management decisions. Here, we present the first study dealing with the complexity arising from the effects of interactions of two increasingly important disturbance factors (selective logging and climatic extreme events) on beta diversity patterns at different scales. Specifically, we examined extensive amphibian assemblage datasets obtained within a quasi‐experimental pre‐/post‐harvesting scheme in the lowland rainforests of Central Guyana. Changes in small‐scale patterns of beta diversity were not detectable at the higher landscape level, indicating that local‐scale dynamics are more informative for evaluating disturbance impacts. The results also underscore the importance of including abundance data when investigating homogenization or heterogenization effects, which should be considered when designing post‐logging impact assessments and selecting impact indicators. Moreover, logging should be regarded as a multifaceted driver that contributes to changes in biodiversity patterns in different ways, depending on interactions with other drivers. The effects of extreme climate events were significantly more pronounced in unlogged forest, while logged forest assemblages appeared buffered due to the presence of novel habitats. Imprudent post‐logging renaturation measures may thus counteract conservation targets. These findings highlight the fact that indicator bias and unaccounted interactions between multiple drivers can lead to misguided management strategies.     

Variability and evolution of global land surface phenology over the past three decades (1982–2012)

Monitoring land surface phenology (LSP) is important for understanding both the responses and feedbacks of ecosystems to the climate system, and for representing these accurately in terrestrial biosphere models. Moreover, by shedding light on phenological trends at a variety of scales, LSP provides the potential to fill the gap between traditional phenological (field) observations and the large‐scale view of global models. In this study, we review and evaluate the variability and evolution of satellite‐derived growing season length (GSL) globally and over the past three decades. We used the longest continuous record of Normalized Difference Vegetation Index data available to date at global scale to derive LSP metrics consistently over all vegetated land areas and for the period 1982–2012. We tested GSL, start‐ and end‐of‐season metrics (SOS and EOS, respectively) for linear trends as well as for significant trend shifts over the study period. We evaluated trends using global environmental stratification information in place of commonly used land cover maps to avoid circular findings. Our results confirmed an average lengthening of the growing season globally during 1982–2012 – averaging 0.22–0.34 days yr^?1, but with spatially heterogeneous trends. About 13–19% of global land areas displayed significant GSL change, and over 30% of trends occurred in the boreal/alpine biome of the Northern Hemisphere, which showed diverging GSL evolution over the past three decades. Within this biome, the ‘Cold and Mesic’ environmental zone appeared as an LSP change hotspot. We also examined the relative contribution of SOS and EOS to the overall changes, finding that EOS trends were generally stronger and more prevalent than SOS trends. These findings constitute a step towards the identification of large‐scale phenological drivers of vegetated land surfaces, necessary for improving phenological representation in terrestrial biosphere models.     

Genomic data reveal ancient microendemism in forest scorpions across the California Floristic Province

The California Floristic Province (CFP) in western North America is a globally significant biodiversity hotspot. Elucidating patterns of endemism and the historical drivers of this diversity has been an important challenge of comparative phylogeography for over two decades. We generated phylogenomic data using ddRADseq to examine genetic structure in Uroctonus forest scorpions, an ecologically restricted and dispersal‐limited organism widely distributed across the CFP north to the Columbia River. We coupled our genetic data with species distribution models (SDMs) to determine climatically suitable areas for Uroctonus both now and during the Last Glacial Maximum. Based on our analyses, Uroctonus is composed of two major genetic groups that likely diverged over 2 million years ago. Each of these groups itself contains numerous genetic groups that reveal a pattern of vicariance and microendemism across the CFP. Migration rates among these populations are low. SDMs suggest forest scorpion habitat has remained relatively stable over the last 21 000 years, consistent with the genetic data. Our results suggest tectonic plate rafting, mountain uplift, river drainage formation and climate‐induced habitat fragmentation have all likely played a role in the diversification of Uroctonus. The intricate pattern of genetic fragmentation revealed across a temporal continuum highlights the potential of low‐dispersing species to shed light on small‐scale patterns of biodiversity and the underlying processes that have generated this diversity in biodiversity hotspots.     

Role of vegetation in determining carbon sequestration along ecological succession in the southeastern United States

Vegetation plays a central role in controlling terrestrial carbon (C) exchange, but quantifying its impacts on C cycling on time scales of ecological succession is hindered by a lack of long‐term observations. The net ecosystem exchange of carbon (NEE) was measured for several years in adjacent ecosystems that represent distinct phases of ecological succession in the southeastern USA. The experiment was designed to isolate the role of vegetation – apart from climate and soils – in controlling biosphere–atmosphere fluxes of CO₂ and water vapor. NEE was near zero over 5 years at an early successional old‐field ecosystem (OF). However, mean annual NEE was nearly equal, approximately ?450 g C m^?2 yr^?1, at an early successional planted pine forest (PP) and a late successional hardwood forest (HW) due to the sensitivity of the former to drought and ice storm damage. We hypothesize that these observations can be explained by the relationships between gross ecosystem productivity (GEP), ecosystem respiration (RE) and canopy conductance, and long‐term shifts in ecosystem physiology in response to climate to maintain near‐constant ecosystem‐level water‐use efficiency (EWUE). Data support our hypotheses, but future research should examine if GEP and RE are causally related or merely controlled by similar drivers. At successional time scales, GEP and RE observations generally followed predictions from E. P. Odum's ‘Strategy of Ecosystem Development’, with the surprising exception that the relationship between GEP and RE resulted in large NEE at the late successional HW. A practical consequence of this research suggests that plantation forestry may confer no net benefit over the conservation of mature forests for C sequestration.     

Strong contribution of autumn phenology to changes in satellite‐derived growing season length estimates across Europe (1982–2011)

Land Surface Phenology (LSP) is the most direct representation of intra‐annual dynamics of vegetated land surfaces as observed from satellite imagery. LSP plays a key role in characterizing land‐surface fluxes, and is central to accurately parameterizing terrestrial biosphere–atmosphere interactions, as well as climate models. In this article, we present an evaluation of Pan‐European LSP and its changes over the past 30 years, using the longest continuous record of Normalized Difference Vegetation Index (NDVI) available to date in combination with a landscape‐based aggregation scheme. We used indicators of Start‐Of‐Season, End‐Of‐Season and Growing Season Length (SOS, EOS and GSL, respectively) for the period 1982–2011 to test for temporal trends in activity of terrestrial vegetation and their spatial distribution. We aggregated pixels into ecologically representative spatial units using the European Landscape Classification (LANMAP) and assessed the relative contribution of spring and autumn phenology. GSL increased significantly by 18–24 days decade^?1 over 18–30% of the land area of Europe, depending on methodology. This trend varied extensively within and between climatic zones and landscape classes. The areas of greatest growing‐season lengthening were the Continental and Boreal zones, with hotspots concentrated in southern Fennoscandia, Western Russia and pockets of continental Europe. For the Atlantic and Steppic zones, we found an average shortening of the growing season with hotspots in Western France, the Po valley, and around the Caspian Sea. In many zones, changes in the NDVI‐derived end‐of‐season contributed more to the GSL trend than changes in spring green‐up, resulting in asymmetric trends. This underlines the importance of investigating senescence and its underlying processes more closely as a driver of LSP and global change.     

Quantifying the biophysical and socioeconomic drivers of changes in forest and agricultural land in South and Southeast Asia

South and Southeast Asia (SSEA) has been a hotspot for land use and land cover change (LULCC) in the past few decades. The identification and quantification of the drivers of LULCC are crucial for improving our understanding of LULCC trends. So far, the biophysical and socioeconomic drivers of forest change have not been quantified at the regional scale, particularly for SSEA. In this study, we quantify the biophysical and socioeconomic drivers of forest change on a country‐by‐country basis in SSEA using an integrated quantitative methodology, which systematically accounts for previously published driver information and regional datasets. We synthesize more than 200 publications to identify the drivers of the forest change at different spatial scales in SSEA. Subsequently, we collect spatially explicit proxy data to represent the identified drivers. We quantify the dynamics of forest and agricultural land from 1992 to 2015 using the Climate Change Initiative (CCI) land cover data developed by the European Space Agency (ESA). A geographically weighted regression method is employed to quantify the spatially heterogeneous drivers of forest change. Our results show that socioeconomic drivers are more important than biophysical drivers for the conversion of forest to agricultural land in South Asia and maritime Southeast Asia. In contrast, biophysical drivers are more important than socioeconomic drivers for the conversion of agricultural land to forest in maritime Southeast Asia and less important in South Asia. Both biophysical and socioeconomic drivers contribute approximately equally to both changes in the mainland Southeast Asia region. By quantifying the dynamics of forest and agricultural land and the spatially explicit drivers of their changes in SSEA, this study provides a solid foundation for LULCC modeling and projection.     

Forest tree species adaptation to climate across biomes: Building on the legacy of ecological genetics to anticipate responses to climate change

Intraspecific variation plays a critical role in extant and future forest responses to climate change. Forest tree species with wide climatic niches rely on the intraspecific variation resulting from genetic adaptation and phenotypic plasticity to accommodate spatial and temporal climate variability. A centuries-old legacy of forest ecological genetics and provenance trials has provided a strong foundation upon which to continue building on this knowledge, which is critical to maintain climate-adapted forests. Our overall objective is to understand forest trees intraspecific responses to climate across species and biomes, while our specific objectives are to describe ecological genetics models used to build our foundational knowledge, summarize modeling approaches that have expanded the traditional toolset, and extensively review the literature from 1994 to 2021 to highlight the main contributions of this legacy and the new analyzes of provenance trials. We reviewed 103 studies comprising at least three common gardens, which covered 58 forest tree species, 28 of them with range-wide studies. Although studies using provenance trial data cover mostly commercially important forest tree species from temperate and boreal biomes, this synthesis provides a global overview of forest tree species adaptation to climate. We found that evidence for genetic adaptation to local climate is commonly present in the species studied (79%), being more common in conifers (87.5%) than in broadleaf species (67%). In 57% of the species, clines in fitness-related traits were associated with temperature variables, in 14% of the species with precipitation, and in 25% of the species with both. Evidence of adaptation lags was found in 50% of the species with range-wide studies. We conclude that ecological genetics models and analysis of provenance trial data provide excellent insights on intraspecific genetic variation, whereas the role and limits of phenotypic plasticity, which will likely determine the fate of extant forests, is vastly understudied.     

Photographic assessment of temperate forest understory phenology in relation to springtime meteorological drivers

Phenology shows sensitive responses to seasonal changes in atmospheric conditions. Forest understory phenology, in particular, is a crucial component of the forest ecosystem that interacts with meteorological factors, and ecosystem functions such as carbon exchange and nutrient cycling. Quantifying understory phenology is challenging due to the multiplicity of species and heterogeneous spatial distribution. The use of digital photography for assessing forest understory phenology was systematically tested in this study within a temperate forest during spring 2007. Five phenology metrics (phenometrics) were extracted from digital photos using three band algebra and two greenness percentage (image binarization) methods. Phenometrics were compared with a comprehensive suite of concurrent meteorological variables. Results show that greenness percentage cover approaches were relatively robust in capturing forest understory green-up. Derived spring phenology of understory plants responded to accumulated air temperature as anticipated, and with day-to-day changes strongly affected by estimated moisture availability. This study suggests that visible-light photographic assessment is useful for efficient forest understory phenology monitoring and allows more comprehensive data collection in support of ecosystem/land surface models.     

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.