Late-spring frosts (LSFs) affect the performance of plants and animals across the world’s temperate and boreal zones, but despite their ecological and economic impact on agriculture and forestry, the geographic distribution and evolutionary impact of these frost events are poorly understood. Here, we analyze LSFs between 1959 and 2017 and the resistance strategies of Northern Hemisphere woody species to infer trees’ adaptations for minimizing frost damage to their leaves and to forecast forest vulnerability under the ongoing changes in frost frequencies. Trait values on leaf-out and leaf-freezing resistance come from up to 1,500 temperate and boreal woody species cultivated in common gardens. We find that areas in which LSFs are common, such as eastern North America, harbor tree species with cautious (late-leafing) leaf-out strategies. Areas in which LSFs used to be unlikely, such as broad-leaved forests and shrublands in Europe and Asia, instead harbor opportunistic tree species (quickly reacting to warming air temperatures). LSFs in the latter regions are currently increasing, and given species’ innate resistance strategies, we estimate that ∼35% of the European and ∼26% of the Asian temperate forest area, but only ∼10% of the North American, will experience increasing late-frost damage in the future. Our findings reveal region-specific changes in the spring-frost risk that can inform decision-making in land management, forestry, agriculture, and insurance policy.

Abstract. The condition of forest ecosystems depends on the temporal and spatial pattern of management interventions and natural disturbances. Remnants of previous conditions persisting after disturbances, or ecosystem legacies, collectively comprise ecosystem memory. Ecosystem memory in turn contributes to resilience and possibilities of ecosystem reorganization following further disturbance. Understanding the role of disturbance and legacies is a prerequisite for maintaining resilience in the face of global change. Several legacy concepts discussed in the peer-reviewed literature, including disturbance, biological, soil, land-use, and silvicultural legacies, overlap in complex ways. Here, we review these established legacy concepts and propose that the new terms "material legacy" (individuals or matter, e.g., survivors, coarse woody debris, nutrients left after disturbance) and "information legacy" (adaptations to historical disturbance regimes) cut across these previous concepts and lead to a new classification of legacies. This includes six categories: material legacies with above-and belowground, and biotic and abiotic categories, and information legacies with above-and belowground categories. These six legacies are influenced by differential patterns of editing and conditioning by "legacy syndromes" that result from natural or human-manipulated disturbance regimes that can be arranged along a gradient of naturalness. This scheme is applied to a case study of hemiboreal forests in the Baltic States of Estonia, Latvia, and Lithuania, where natural disturbance, traditional clearcut silviculture, and afforestation of abandoned agricultural lands constitute the three main legacy syndromes. These legacy syndromes in turn influence forest response to management actions and constrain resilience, leading to a mosaic of natural, manipulated, and artificial (novel) ecosystems across the landscape, depending on how the legacies in each syndrome affect ecological memory.

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This paper describes a new SAS/STAT ® procedure for fitting models to non-normal or normal data with correlations or nonconstant variability. The GLIMMIX procedure is an add-on for the SAS/STAT product in SAS ® 9.1 on the Windows platform. PROC GLIMMIX extends the SAS mixed model tools in a number of ways. For example, it• models data from non-Gaussian distributions• implements low-rank smoothing based on mixed models • provides new features for LS-means comparisons and display• enables you to use SAS programming statements to compute model effects, or to define link and variance functions• fits models to multivariate data in which observations do not all have the same distribution or linkApplications of the GLIMMIX procedure include estimating trends in disease rates, modeling counts or proportions over time in a clinical trial, predicting probability of occurrence in time series and spatial data, and joint modeling of correlated binary and continuous data.This paper describes generalized linear mixed models and how to use the GLIMMIX procedure for estimation, inference, and prediction.

One of the most fundamental questions in ecology is how many species inhabit the Earth. However, due to massive logistical and financial challenges and taxonomic difficulties connected to the species concept definition, the global numbers of species, including those of important and well-studied life forms such as trees, still remain largely unknown. Here, based on global ground-sourced data, we estimate the total tree species richness at global, continental, and biome levels. Our results indicate that there are ∼73,000 tree species globally, among which ∼9,000 tree species are yet to be discovered. Roughly 40% of undiscovered tree species are in South America. Moreover, almost one-third of all tree species to be discovered may be rare, with very low populations and limited spatial distribution (likely in remote tropical lowlands and mountains). These findings highlight the vulnerability of global forest biodiversity to anthropogenic changes in land use and climate, which disproportionately threaten rare species and thus, global tree richness.

Post‐mining restoration sites often develop novel ecosystems as soil conditions are completely new and ecosystem assemblage can be spontaneous even on afforested sites. This study presents results from long‐term monitoring and evaluation of an afforested oil‐shale quarry in Estonia. The study is based on chronosequence data of soil and vegetation and comparisons are made to similar forest site‐types used in forest management in Estonia. After site reclamation, soil development lowered pH and increased N, K, and organic C content in soil to levels similar to the common Hepatica forest site‐type but P, total C, and pH were more similar to the Calamagrostis forest site‐type. Vegetation of the restoration area differed from that on common forest sites; forest stand development was similar to the Hepatica forest‐type. A variety of species were present that are representive of dry and wet sites, as well as infertile and fertile sites. It appears that novel ecosystems may be developing on post‐mining reclaimed land in Northeast Estonia and may require adaptations to typical forest management regimes that have been based on site‐types. Monitoring and evaluation gives an opportunity to plan further management activities on these areas.

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In the Baltic States region, anthropogenic disturbances at different temporal and spatial scales mostly determine dynamics and development phases of forest ecosystems. We reviewed the state and condition of hemiboreal forests of the Baltic States region and analyzed species composition of recently established and permanent forest (PF). Agricultural deforestation and spontaneous or artificial conversion back to forest is a scenario leading to ecosystems designated as recent forest (RF, age up to two hundred years). Permanent forest (PF) was defined as areas with no records of agricultural activity during the last 200 yr, including mostly forests managed by traditional even‐aged (clear‐cut) silviculture and salvage after natural disturbances. We hypothesized that RF would have distinctive composition, with higher dominance by hardwoods (e.g., aspen and birch), compared to PF. Ordination revealed divergence in the RF stands; about half had the hypothesized composition distinct from PF, with a tight cluster of stands in the part of the ordination space with high hardwood dominance, while the remaining RF stands were scattered throughout the ordination space occupied by PF with highly variable species composition. Planting of conifers, variability in site quality, and variability in spatial proximity to PF with relatively natural ecosystem legacies likely explained the variable compositions of this latter group of RF. We positioned the observations of RF in a classic quantification of site type conditions (based on Estonian forest vegetation survey previously carried out by Lõhmus), which indicated that RF was more likely to occur on areas of higher soil fertility (in ordination space). Climatic and anthropogenic changes to RF create complex dynamic trends that are difficult to project into the future. Further research in tracing land use changes (using pollen analysis and documented evidence) should be utilized to refine the conceptual framework of ecosystem legacy and memory. Occurrence and frequency of deforestation and its characteristics as a novel disturbance regime are of particular interest.