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Inferring infection hazard in wildlife populations by linking data across individual and population scales

Our ability to infer unobservable disease-dynamic processes such as force of infection (infection hazard for susceptible hosts) has transformed our understanding of disease transmission mechanisms and capacity to predict disease dynamics. Conventional methods for inferring FOI estimate a time-averaged value and are based on population-level processes. Because many pathogens exhibit epidemic cycling and FOI is the result of processes acting across the scales of individuals and populations, a flexible framework that extends to epidemic dynamics and links within-host processes to FOI is needed. Specifically, within-host antibody kinetics in wildlife hosts can be short-lived and produce patterns that are repeatable across individuals, suggesting individual-level antibody concentrations could be used to infer time since infection and hence FOI. Using simulations and case studies (influenza A in lesser snow geese and Yersinia pestis in coyotes), we argue that with careful experimental and surveillance design, the population-level FOI signal can be recovered from individual-level antibody kinetics, despite substantial individual-level variation. In addition to improving inference, the cross-scale quantitative antibody approach we describe can reveal insights into drivers of individual-based variation in disease response, and the role of poorly understood processes such as secondary infections, in population-level dynamics of disease.

Ecology Letters↗

Using genetic data to advance stream fish reintroduction science: A case study in brook trout

Widespread extirpation of native fish populations has led to a rise in species reintroduction efforts worldwide. Most efforts have relied on demographic data alone to guide project design and evaluate success. However, the genetic characteristics of many imperiled fish populations including low diversity, local adaptation, and hatchery introgression emphasize the importance of genetic data in the design and monitoring of reintroduction efforts. Focusing on a case study of brook trout ( Salvelinus fontinalis ) in North Carolina, USA, we show how the combined use of genetic and demographic data can support reintroduction efforts by improving source population selection and providing opportunities to evaluate genetic viability and adaptive potential in restored populations. Using this combined approach, we reintroduced brook trout into a restored stream from two source populations and monitored changes in genetic diversity and population size in source and recipient populations. Three years after the initial translocation, the reintroduced population had comparable density, but higher genetic diversity, than either source population. This study demonstrates the utility of genetic and demographic data for reintroduction efforts, particularly when extant populations are genetically depauperate and maintaining adaptive potential is a primary restoration goal. However, we emphasize the value of continued monitoring at longer temporal and spatial scales to determine the effects of stochastic process on the long-term adaptive capacity and persistence of reintroduced populations. Overall, inclusion of genetic data in reintroduction efforts offers increased ability to meet project goals while simultaneously conserving critical sources of adaptive variation that exist across the landscape.

North Carolina↗

Wildlife ecological risk assessment in the 21st century: Promising technologies to assess toxicological effects

Despite advances in toxicity testing and development of new approach methodologies (NAMs) for hazard assessment, the ecological risk assessment (ERA) framework for terrestrial wildlife (i.e., air-breathing amphibians, reptiles, birds, and mammals) has remained unchanged for decades. While survival, growth, and reproductive endpoints derived from whole animal toxicity tests are central to hazard assessment, non-standard measures of biological effects at multiple levels of biological organization (e.g., molecular, cellular, tissue, organ, organism, population, community, ecosystem) have potential to enhance the relevance of prospective and retrospective wildlife ERAs. Other factors (e.g., indirect effects of contaminants on food supplies and infectious disease processes) are influenced by toxicants at individual, population, and community levels, and need to be factored into chemically-based risk assessments to enhance the “eco” component of ERAs. Regulatory and logistical challenges often relegate such non-standard endpoints and indirect effects to post-registration evaluations of pesticides and industrial chemicals, and contaminated site evaluations. While NAMs are being developed, to date their applications in ERAs focused on wildlife have been limited. No single magic tool or model will address all uncertainties in hazard assessment. Modernizing wildlife ERAs will likely entail combinations of laboratory and field-derived data at multiple levels of biological organization, knowledge collection solutions (e.g., systematic review, adverse outcome pathway frameworks), and inferential methods that facilitate integrations and risk estimations focused on species, populations, interspecific extrapolations, and ecosystem services modeling, with less dependence on whole animal data and simple hazard ratios.

Integrated Environmental Assessment and Management↗

Bringing traits back in the equation: A roadmap to understand species redistribution

Ecological and evolutionary theories have proposed that species traits should be important in mediating species responses to contemporary climate change; yet, empirical evidence has so far provided mixed evidence for the role of behavioral, life history, or ecological characteristics in facilitating or hindering species range shifts. As such, the utility of trait-based approaches to predict species redistribution under climate change has been called into question. We develop the perspective, supported by evidence, that trait variation, if used carefully can have high potential utility, but that past analyses have in many cases failed to identify an explanatory value for traits by not fully embracing the complexity of species range shifts. First, we discuss the relevant theory linking species traits to range shift processes at the leading (expansion) and trailing (contraction) edges of species distributions and highlight the need to clarify the mechanistic basis of trait-based approaches. Second, we provide a brief overview of range shift–trait studies and identify new opportunities for trait integration that consider range-specific processes and intraspecific variability. Third, we explore the circumstances under which environmental and biotic context dependencies are likely to affect our ability to identify the contribution of species traits to range shift processes. Finally, we propose that revealing the role of traits in shaping species redistribution may likely require accounting for methodological variation arising from the range shift estimation process as well as addressing existing functional, geographical, and phylogenetic biases. We provide a series of considerations for more effectively integrating traits as well as extrinsic and methodological factors into species redistribution research. Together, these analytical approaches promise stronger mechanistic and predictive understanding that can help society mitigate and adapt to the effects of climate change on biodiversity.

Global Change Biology↗

Metabarcoding of fecal samples to determine herbivore diets: A case study of the endangered Pacific pocket mouse

Understanding the diet of an endangered species illuminates the animal’s ecology, habitat requirements, and conservation needs. However, direct observation of diet can be difficult, particularly for small, nocturnal animals such as the Pacific pocket mouse (Heteromyidae: Perognathus longimembris pacificus ). Very little is known of the dietary habits of this federally endangered rodent, hindering management and restoration efforts. We used a metabarcoding approach to identify source plants in fecal samples (N = 52) from the three remaining populations known. The internal transcribed spacers (ITS) of the nuclear ribosomal loci were sequenced following the Illumina MiSeq amplicon strategy and processed reads were mapped to reference databases. We evaluated a range of threshold mapping criteria and found the best-performing setting generally recovered two distinct mock communities in proportions similar to expectation. We tested our method on captive animals fed a known diet and recovered almost all plant sources, but found substantial heterogeneity among fecal pellets collected from the same individual at the same time. Observed richness did not increase with pooling of pellets from the same individual. In field-collected samples, we identified 4–14 plant genera in individual samples and 74 genera overall, but over 50 percent of reads mapped to just six species in five genera. We simulated the effects of sequencing error, variable read length, and chimera formation to infer taxon-specific rates of misassignment for the local flora, which were generally low with some exceptions. Richness at the species and genus levels did not reach a clear asymptote, suggesting that diet breadth remained underestimated in the current pool of samples. Large numbers of scat samples are therefore needed to make inferences about diet and resource selection in future studies of the Pacific pocket mouse. We conclude that our minimally invasive method is promising for determining herbivore diets given a library of sequences from local plants.

California↗

Integrating adaptive management and ecosystem services concepts to improve natural resource management: Challenges and opportunities

Executive Summary—Overview Natural resource managers must make decisions that affect broad-scale ecosystem processes involving large spatial areas, complex biophysical interactions, numerous competing stakeholder interests, and highly uncertain outcomes. Natural and social science information and analyses are widely recognized as important for informing effective management. Chief among the systematic approaches for improving the integration of science into natural resource management are two emergent science concepts, adaptive management and ecosystem services. Adaptive management (also referred to as “adaptive decision making”) is a deliberate process of learning by doing that focuses on reducing uncertainties about management outcomes and system responses to improve management over time. Ecosystem services is a conceptual framework that refers to the attributes and outputs of ecosystems (and their components and functions) that have value for humans. This report explores how ecosystem services can be moved from concept into practice through connection to a decision framework—adaptive management—that accounts for inherent uncertainties. Simultaneously, the report examines the value of incorporating ecosystem services framing and concepts into adaptive management efforts. Adaptive management and ecosystem services analyses have not typically been used jointly in decision making. However, as frameworks, they have a natural—but to date underexplored—affinity. Both are policy and decision oriented in that they attempt to represent the consequences of resource management choices on outcomes of interest to stakeholders. Both adaptive management and ecosystem services analysis take an empirical approach to the analysis of ecological systems. This systems orientation is a byproduct of the fact that natural resource actions affect ecosystems—and corresponding societal outcomes—often across large geographic scales. Moreover, because both frameworks focus on resource systems, both must confront the analytical challenges of systems modeling—in terms of complexity, dynamics, and uncertainty. Given this affinity, the integration of ecosystem services analysis and adaptive management poses few conceptual hurdles. In this report, we synthesize discussions from two workshops that considered ways in which adaptive management approaches and ecosystem service concepts may be complementary, such that integrating them into a common framework may lead to improved natural resource management outcomes. Although the literature on adaptive management and ecosystem services is vast and growing, the report focuses specifically on the integration of these two concepts rather than aiming to provide new definitions or an indepth review or primer of the concepts individually. Key issues considered include the bidirectional links between adaptive decision making and ecosystem services, as well as the potential benefits and inevitable challenges arising in the development and use of an integrated framework. Specifically, the workshops addressed the following questions: How can application of ecosystem service analysis within an adaptive decision process improve the outcomes of management and advance understanding of ecosystem service identification, production, and valuation? How can these concepts be integrated in concept and practice? What are the constraints and challenges to integrating adaptive management and ecosystem services? And, should the integration of these concepts be moved forward to wider application—and if so, how?

Circular↗

Flow variations and macroinvertebrate community responses in a small groundwater-dominated stream in south east England

Changes in the macroinvertebrate community in response to flow variations in the Little Stour River, Kent, UK, were examined over a 6 year period (1992-1997). This period included the final year of the 1988-1992 drought, followed by some of the wettest conditions recorded this century and a second period of drought between 1996 and 1997. Each year, samples were collected from 15 sites during late-summer base-flow conditions. Correspondence analysis identified clear differences between samples from upstream and downstream sites, and between drought and non-drought years. Step-wise multiple regression was used to identify hydrological indicators of community variation. Several different indices were used to describe the macroinvertebrate community, including macroinvertebrate community abundance, number of families and species, and individual species. Site characteristics were fundamental in accounting for variation in the unstandardized macroinvertebrate community. However, when differences between sites were controlled, hydrological conditions were found to play a dominant role in explaining ecological variation. Indices of high discharge (or their absence), 4-7 months prior to sampling (i.e. winter-spring), were found to be the most important variables for describing the late-summer community The results are discussed in relation to the role of flow variability in shaping instream communities and management implications. Copyright ?? 2000 John Wiley & Sons, Ltd.Changes in the macroinvertebrate community in response to flow variations in the Little Stour River, Kent, UK, were examined over a 6 year period (1992-1997). This period included the final year of the 1988-1992 drought, followed by some of the wettest conditions recorded this century and a second period of drought between 1996 and 1997. Each year, samples were collected from 15 sites during late-summer base-flow conditions. Correspondence analysis identified clear differences between samples from upstream and downstream sites, and between drought and non-drought years. Step-wise multiple regression was used to identify hydrological indicators of community variation. Several different indices were used to describe the macroinvertebrate community, including macroinvertebrate community abundance, number of families and species, and individual species. Site characteristics were fundamental in accounting for variation in the unstandardized macroinvertebrate community. However, when differences between sites were controlled, hydrological conditions were found to play a dominant role in explaining ecological variation. Indices of high discharge (or their absence), 4-7 months prior to sampling (i.e. winter-spring), were found to be the most important variables for describing the late-summer community. The results are discussed in relation to the role of flow variability in shaping instream communities and management implications.

Hydrological Processes↗

Scale-up of ecological experiments: Density variation in the mobile bivalve Macomona liliana

At present the problem of scaling up from controlled experiments (necessarily at a small spatial scale) to questions of regional or global importance is perhaps the most pressing issue in ecology. Most of the proposed techniques recommend iterative cycling between theory and experiment. We present a graphical technique that facilitates this cycling by allowing the scope of experiments, surveys, and natural history observations to be compared to the scope of models and theory. We apply the scope analysis to the problem of understanding the population dynamics of a bivalve exposed to environmental stress at the scale of a harbour. Previous lab and field experiments were found not to be 1:1 scale models of harbour-wide processes. Scope analysis allowed small scale experiments to be linked to larger scale surveys and to a spatially explicit model of population dynamics.

Conference Paper↗

Long-term assessment of relationships between changing environmental conditions and the physiology of southern Beaufort Sea polar bears (Ursus maritimus)

Climate change is influencing polar bear ( Ursus maritimus ) habitat, diet, and behavior but the effects of these changes on their physiology is not well understood. Blood-based biomarkers are used to assess the physiologic health of individuals but their usefulness for evaluating population health, especially as it relates to changing environmental conditions, has rarely been explored. We describe links between environmental conditions and physiologic functions of southern Beaufort Sea polar bears using data from blood samples collected from 1984 to 2018, a period marked by extensive environmental change. We evaluated associations between 13 physiologic biomarkers and circumpolar (Arctic oscillation index) and regional (wind patterns and ice-free days) environmental metrics and seasonal and demographic co-variates (age, sex, season, and year) known to affect polar bear ecology. We observed signs of dysregulation of water balance in polar bears following years with a lower annual Arctic oscillation index. In addition, liver enzyme values increased over time, which is suggestive of potential hepatocyte damage as the Arctic has warmed. Biomarkers of immune function increased with regional-scale wind patterns and the number of ice-free days over the Beaufort Sea continental shelf and were lower in years with a lower winter Arctic oscillation index, suggesting an increased allocation of energetic resources for immune processes under these conditions. We propose that the variation in polar bear immune and metabolic function is likely indicative of physiologic plasticity, a response that allows polar bears to remain in homeostasis even as they experience changes in nutrition and habitat in response to changing environments.

Alaska↗

Some considerations on the use of ecological models to predict species' geographic distributions

Peterson (2001) used Genetic Algorithm for Rule-set Prediction (GARP) models to predict distribution patterns from Breeding Bird Survey (BBS) data. Evaluations of these models should consider inherent limitations of BBS data: (1) BBS methods may not sample species and habitats equally; (2) using BBS data for both model development and testing may overlook poor fit of some models; and (3) BBS data may not provide the desired spatial resolution or capture temporal changes in species distributions. The predictive value of GARP models requires additional study, especially comparisons with distribution patterns from independent data sets. When employed at appropriate temporal and geographic scales, GARP models show considerable promise for conservation biology applications but provide limited inferences concerning processes responsible for the observed patterns.

Condor↗

Conceptual ecological models to support detection of ecological change on Alaska National Wildlife Refuges

More than 31 million hectares of land are protected and managed in 16 refuges by the U.S. Fish and Wildlife Service (USFWS) in Alaska. The vastness and isolation of Alaskan refuges give rise to relatively intact and complete ecosystems. The potential for these lands to provide habitat for trust species is likely to be altered, however, due to global climate change, which is having dramatic effects at high latitudes. The ability of USFWS to effectively manage these lands in the future will be enhanced by a regional inventory and monitoring program that integrates and supplements monitoring currently being implemented by individual refuges. Conceptual models inform monitoring programs in a number of ways, including summarizing important ecosystem components and processes as well as facilitating communication, discussion and debate about the nature of the system and important management issues. This process can lead to hypotheses regarding future changes, likely results of alternative management actions, identification of monitoring indicators, and ultimately, interpretation of monitoring results. As a first step towards developing a monitoring program, the 16 refuges in Alaska each created a conceptual model of their refuge and the landscape context. Models include prominent ecosystem components, drivers, and processes by which components are linked or altered. The Alaska refuge system also recognizes that designing and implementing monitoring at regional and ecoregional extents has numerous scientific, fiscal, logistical, and political advantages over monitoring conducted exclusively at refuge-specific scales. Broad-scale monitoring is particularly advantageous for examining phenomena such as climate change because effects are best interpreted at broader spatial extents. To enable an ecoregional perspective, a rationale was developed for deriving ecoregional boundaries for four ecoregions (Polar, Interior Alaska, Bering Coast, and North Pacific Coast) from the Unified Ecoregions of Alaska. Ecoregional models were then developed to illustrate resources and processes that operate at spatial scales larger than individual refuges within each ecoregion. Conceptual models also were developed for adjacent marine areas, designated as the North Pacific, Bering Sea, and Beaufort-Chukchi Sea Marine Ecoregions. Although many more conceptual models will be required to support development of a regional monitoring program, these definitions of ecoregions and associated conceptual models are an important foundation.

Alaska↗

Exploring the potential of ground-penetrating radar (GPR) to measure the extent of chronic disturbance in peatlands: Examples from acid mine drainage and peat fire

Peatlands are accumulations of partially decayed organic soil that cover approximately 3% of Earth’s surface and have been shown to serve essential environmental and ecological functions such as sequestering carbon, purifying water, and providing habitat for organisms. However, peatlands are threatened by pressures from agriculture, urban development, mining, and climate change. Geophysical methods have been used in peatlands to determine peat volume and carbon stocks (e.g., Comas et al., 2017), observe differences in humification and water content (e.g., Ulriksen, 1982), guide engineering projects (e.g., Jol and Smith, 1995), learn about subsurface greenhouse gas dynamics (Wright and Comas, 2016), observe seasonal variations in pore water salinity (Walter et al., 2018), and assess hydrological processes (Hare et al., 2017). Among various geophysical methods, ground penetrating radar (GPR) is arguably the most popular for studying peat properties given the method’s sensitivity to variations in water content and ability to resolve major structural properties within the peat at high spatial resolution. Though less widely applied, frequency-domain analysis of GPR may also yield useful information.

Conference Paper↗

Unmarked: An R package for fitting hierarchical models of wildlife occurrence and abundance

Ecological research uses data collection techniques that are prone to substantial and unique types of measurement error to address scientific questions about species abundance and distribution. These data collection schemes include a number of survey methods in which unmarked individuals are counted, or determined to be present, at spatially- referenced sites. Examples include site occupancy sampling, repeated counts, distance sampling, removal sampling, and double observer sampling. To appropriately analyze these data, hierarchical models have been developed to separately model explanatory variables of both a latent abundance or occurrence process and a conditional detection process. Because these models have a straightforward interpretation paralleling mechanisms under which the data arose, they have recently gained immense popularity. The common hierarchical structure of these models is well-suited for a unified modeling interface. The R package unmarked provides such a unified modeling framework, including tools for data exploration, model fitting, model criticism, post-hoc analysis, and model comparison.

Journal of Statistical Software↗

Detection biases yield misleading patterns of species persistence and colonization in fragmented landscapes

Species occurrence patterns, and related processes of persistence, colonization and turnover, are increasingly being used to infer habitat suitability, predict species distributions, and measure biodiversity potential. The majority of these studies do not account for observational error in their analyses despite growing evidence suggesting that the sampling process can significantly influence species detection and subsequently, estimates of occurrence. We examined the potential biases of species occurrence patterns that can result from differences in detectability across species and habitat types using hierarchical multispecies occupancy models applied to a tropical bird community in an agricultural fragmented landscape. Our results suggest that detection varies widely among species and habitat types. Not incorporating detectability severely biased occupancy dynamics for many species by overestimating turnover rates, producing misleading patterns of persistence and colonization of agricultural habitats, and misclassifying species into ecological categories (i.e., forest specialists and generalists). This is of serious concern, given that most research on the ability of agricultural lands to maintain current levels of biodiversity by and large does not correct for differences in detectability. We strongly urge researchers to apply an inferential framework which explicitly account for differences in detectability to fully characterize species-habitat relationships, correctly guide biodiversity conservation in human-modified landscapes, and generate more accurate predictions of species responses to future changes in environmental conditions.

Las Cruces Biological Station↗

A note on scrap in the 1992 U.S. input-output tables

Introduction A key concern of industrial ecology and life cycle analysis is the disposal and recycling of scrap. One might conclude that the U.S. input-output tables are appropriate tools for analyzing scrap flows. Duchin, for instance, has suggested using input-output analysis for industrial ecology, indicating that input-output economics can trace the stocks and flows of energy and other materials from extraction through production and consumption to recycling or disposal. Lave and others use input-output tables to design life cycle assessment models for studying product design, materials use, and recycling strategies, even with the knowledge that these tables suffer from a lack of comprehensive and detailed data that may never be resolved. Although input-output tables can offer general guidance about the interdependence of economic and environmental processes, data reporting by industry and the economic concepts underlying these tables pose problems for rigorous material flow examinations. This is especially true for analyzing the output of scrap and scrap flows in the United States and estimating the amount of scrap that can be recycled. To show how data reporting has affected the values of scrap in recent input-output tables, this paper focuses on metal scrap generated in manufacturing. The paper also briefly discusses scrap that is not included in the input-output tables and some economic concepts that limit the analysis of scrap flows.

Open-File Report↗

Ecological observations on the colonial ascidian Didemnum sp. in a New England tide pool habitat

The colonial ascidian Didemnum sp. has colonized northwestern Atlantic coastal habitats from southern Long Island, New York, to Eastport, Maine. It is also present in offshore habitats of the Georges Bank fishing grounds. It threatens to alter fisheries habitats and shellfish aquacultures. Observations in a tide pool at Sandwich, MA from December 2003 to February 2006 show that Didemnum sp. tolerates water temperatures ranging from ≤ 1 to > 24 °C, with daily changes of up to 11 °C. It attaches to pebbles, cobbles, and boulders, and it overgrows other tunicates, seaweeds, sponges, and bivalves. From May to mid July, colonies appear as small patches on the bottoms of rocks. Colonies grow rapidly from July to September, with some growth into December, and they range in color from pink to pale yellow to pale orange. Colony health declines from October through April, presumably in response to changes in water temperatures, and this degenerative process is manifested by color changes, by the appearance of small dark brown spots that represent clumps of fecal pellets in the colony, by scavenging by periwinkles, and by a peeling-away of colonies from the sides of cobbles and boulders. At Sandwich, colonies died that were exposed to air at low tide. The species does not exhibit this seasonal cycle of growth and decline in subtidal habitats (40–65 m) on the Georges Bank fishing grounds where the daily climate is relatively stable and annual water temperatures range from 4 to 15 °C. Experiments in the tide pool with small colony fragments (5 to 9 cm 2 ) show they re-attach and grow rapidly by asexual budding, increasing in size 6- to 11-fold in the first 15 days. Didemnum sp. at Sandwich has no known predators except for common periwinkles ( Littorina littorea ) that graze on degenerating colonies in the October to April time period and whenever colonies are stressed by desiccation. The tendencies of the ascidian (1) to attach to firm substrates, (2) to rapidly overgrow other species, (3) to tolerate a wide temperature range, (4) to be free from predation, and (5) to spread by colony fragmentation combine to make it a potential threat to benthic marine habitats and aquacultures. Didemnum sp. is known to overgrow mussels, oysters, and sea scallops, and it likely envelops other bivalves too.

Massachusetts↗

U.S. Fish and Wildlife Service 1979 wetland classification: A review

In 1979 the US Fish and Wildlife Service published and adopted a classification of wetlands and deepwater habitats of the United States. The system was designed for use in a national inventory of wetlands. It was intended to be ecologically based, to furnish the mapping units needed for the inventory, and to provide national consistency in terminology and definition. We review the performance of the classification after 13 years of use. The definition of wetland is based on national lists of hydric soils and plants that occur in wetlands. Our experience suggests that wetland classifications must facilitate mapping and inventory because these data gathering functions are essential to management and preservation of the wetland resource, but the definitions and taxa must have ecological basis. The most serious problem faced in construction of the classification was lack of data for many of the diverse wetland types. Review of the performance of the classification suggests that, for the most part, it was successful in accomplishing its objectives, but that problem areas should be corrected and modification could strengthen its utility. The classification, at least in concept, could be applied outside the United States. Experience gained in use of the classification can furnish guidance as to pitfalls to be avoided in the wetland classification process.

Vegetatio↗

Shift of potential natural vegetation against global climate change under historical, current and future scenarios

Potential natural vegetation (PNV), the final successional stage of vegetation, plays a key role in ecological restoration, the design of nature reserves, and development of agriculture and livestock production. Meteorological data from historical and current periods including the last inter-glacial (LIG), last glacial maximum (LGM), mid Holocene (MH) periods and the present day (PD), plus derived data from 2050 and 2070, in conjunction with the Comprehensive and Sequential Classification System (CSCS) model, were used to classify global PNV. The 42 classes of global PNV were regrouped into 10 groups to facilitate analysis of spatial changes. Finally, spatio-temporal patterns and successional processes of global PNV as well as the response to climate changes were analysed. Our study made the following five conclusions. (1) Only one missing class (IA1 frigid-extrarid frigid desert, alpine desert) arose in periods of LIG, MH, 2050, and 2070 for global PNV. (2) The frigid-arid groups were mainly distributed in higher latitudes and elevations, but temperate-humid groups and tropical-perhumid groups occurred in middle and low latitudes, respectively. Temperate zonal forest steppe, warm desert, savanna and tropical zonal forest steppe increased, while six other groups decreased. (3) The conversion from temperate zonal forest steppe to tundra and alpine steppe from LIG to LGM occupied the largest area, indicating a drastic shift in climate and the associated response of terrestrial vegetation sensitive to climate change. (4) The CSCS could be used to simulate the long-term succession of global PNV. (5) As a consequence of global warming, forests shifted to the northern hemisphere and Tibet, areas with much higher latitude and elevation. The PNV groups with greater shift distance revealed the more serious effects of global climate change on vegetation.

Rangeland Journal↗