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Linking resources with demography to understand resource limitation for bears

1. Identifying the resources that limit growth of animal populations is essential for effective conservation; however, resource limitation is difficult to quantify. Recent advances in geographical information systems (GIS) and resource modelling can be combined with demographic modelling to yield insights into resource limitation. 2. Using long-term data on a population of black bears Ursus americanus, we evaluated competing hypotheses about whether availability of hard mast (acorns and nuts) or soft mast (fleshy fruits) limited bears in the southern Appalachians, USA, during 1981-2002. The effects of clearcutting on habitat quality were also evaluated. Annual survival, recruitment and population growth rate were estimated using capture-recapture data from 101 females. The availability of hard mast, soft mast and clearcuts was estimated with a GIS, as each changed through time as a result of harvest and succession, and then availabilities were incorporated as covariates for each demographic parameter. 3. The model with the additive availability of hard mast and soft mast across the landscape predicted survival and population growth rate. Availability of young clearcuts predicted recruitment, but not population growth or survival. 4. Availability of hard mast stands across the landscape and availability of soft mast across the landscape were more important than hard mast production and availability of soft mast in young clearcuts, respectively. 5. Synthesis and applications. Our results indicate that older stands, which support high levels of hard mast and moderate levels of soft mast, should be maintained to sustain population growth of bears in the southern Appalachians. Simultaneously, the acreage of intermediate aged stands (10-25 years), which support very low levels of both hard mast and soft mast, should be minimized. The approach used in this study has broad application for wildlife management and conservation. State and federal wildlife agencies often possess long-term data on both resource availability and capture-recapture for wild populations. Combined, these two data types can be used to estimate survival, recruitment, population growth, elasticities of vital rates and the effects of resource availability on demographic parameters. Hence data that are traditionally used to understand population trends can be used to evaluate how and why demography changes over time. ?? 2007 The Authors.

Journal of Applied Ecology↗

Biogeography of Iberian freshwater fishes revisited: The roles of historical versus contemporary constraints

Aim The question of how much of the shared geographical distribution of biota is due to environmental vs. historical constraints remains unanswered. The aim of this paper is to disentangle the contribution of historical vs. contemporary factors to the distribution of freshwater fish species. In addition, it illustrates how quantifying the contribution of each type of factor improves the classification of biogeographical provinces. Location Iberian Peninsula, south-western Europe ( c . 581,000 km 2 ). Methods We used the most comprehensive data on native fish distributions for the Iberian Peninsula, compiled from Portuguese and Spanish sources on a 20-km grid-cell resolution. Overall, 58 species were analysed after being categorized into three groups according to their ability to disperse through saltwater: (1) species strictly intolerant of saltwater (primary species); (2) species partially tolerant of saltwater, making limited incursions into saltwaters (secondary species); and (3) saltwater-tolerant species that migrate back and forth from sea to freshwaters or have invaded freshwaters recently (peripheral species). Distance-based multivariate analyses were used to test the role of historical (basin formation) vs. contemporary environmental (climate) conditions in explaining current patterns of native fish assemblage composition. Cluster analyses were performed to explore species co-occurrence patterns and redefine biogeographical provinces based on the distributions of fishes. Results River basin boundaries were better at segregating species composition for all species groups than contemporary climate variables. This historical signal was especially evident for primary and secondary freshwater fishes. Eleven biogeographical provinces were delineated. Basins flowing to the Atlantic Ocean north of the Tagus Basin and those flowing to the Mediterranean Sea north of the Mijares Basin were the most dissimilar group. Primary and secondary freshwater species had higher province fidelity than peripheral species. Main conclusions The results support the hypothesis that historical factors exert greater constraints on native freshwater fish assemblages in the Iberian Peninsula than do current environmental factors. After examining patterns of assemblage variation across space, as evidenced by the biogeographical provinces, we discuss the likely dispersal and speciation events that underlie these patterns.

Iberian Peninsula↗

Potential spread of highly pathogenic avian influenza H5N1 by wildfowl: dispersal ranges and rates determined from large-scale satellite telemetry

1. Migratory birds are major candidates for long-distance dispersal of zoonotic pathogens. In recent years, wildfowl have been suspected of contributing to the rapid geographic spread of the highly pathogenic avian influenza (HPAI) H5N1 virus. Experimental infection studies reveal that some wild ducks, geese and swans shed this virus asymptomatically and hence have the potential to spread it as they move. 2. We evaluate the dispersive potential of HPAI H5N1 viruses by wildfowl through an analysis of the movement range and movement rate of birds monitored by satellite telemetry in relation to the apparent asymptomatic infection duration (AID) measured in experimental studies. We analysed the first large-scale data set of wildfowl movements, including 228 birds from 19 species monitored by satellite telemetry in 2006–2009, over HPAI H5N1 affected regions of Asia, Europe and Africa. 3. Our results indicate that individual migratory wildfowl have the potential to disperse HPAI H5N1 over extensive distances, being able to perform movements of up to 2900 km within timeframes compatible with the duration of asymptomatic infection. 4. However, the likelihood of such virus dispersal over long distances by individual wildfowl is low: we estimate that for an individual migratory bird there are, on average, only 5–15 days per year when infection could result in the dispersal of HPAI H5N1 virus over 500 km. 5. Staging at stopover sites during migration is typically longer than the period of infection and viral shedding, preventing birds from dispersing a virus over several consecutive but interrupted long-distance movements. Intercontinental virus dispersion would therefore probably require relay transmission between a series of successively infected migratory birds. 6. Synthesis and applications . Our results provide a detailed quantitative assessment of the dispersive potential of HPAI H5N1 virus by selected migratory birds. Such dispersive potential rests on the assumption that free-living wildfowl will respond analogously to captive, experimentally-infected birds, and that asymptomatic infection will not alter their movement abilities. Our approach of combining experimental exposure data and telemetry information provides an analytical framework for quantifying the risk of spread of avian-borne diseases.

Journal of Applied Ecology↗

Coproduction and modeling spatial contact networks prevent bias about infectious hematopoietic necrosis virus transmission for Snake River Basin salmonids

Much remains unknown about variation in pathogen transmission across the geographic range of a free-ranging fish or animal species and about the influence of movement (associated with husbandry practices or animal behavior) on pathogen transmission. Salmonid hatcheries are an ideal system in which to study these processes. Salmonid hatcheries are managed for endangered species recovery, supplementation of threatened or at-risk fish stocks, support of fisheries, and ecosystem stability. Infectious hematopoietic necrosis virus (IHNV) is a rhabdovirus of significant concern to salmon aquaculture. Landscape IHNV transmission dynamics previously had been estimated only for salmonid hatcheries in the Lower Columbia River Basin (LCRB). The objectives of this study were to estimate IHNV transmission dynamics in a unique geographic region, the Snake River Basin (SRB), and to quantitatively estimate the effect of model coproduction on inference because previous assessments of coproduction have been qualitative. In contrast to the LCRB, the SRB has hatchery complexes consisting of a main hatchery and ≥1 satellite facility. Knowledge about hatchery complexes was held by a subset of project researchers but would not have been available to project modelers without coproduction. Project modelers generated and tested multiple versions of Bayesian susceptible-exposedinfected models to realistically represent the SRB and estimate the effect of coproduction. Models estimated the frequency of transmission routes, route-specific infection probabilities, and infection probabilities for combinations of salmonid hosts and IHNV lineages. Model results indicated that in the SRB, avoiding exposure to IHNV-positive adult salmonids is the most important action to prevent juvenile infections. Migrating adult salmonids exposed juvenile cohort-sites most frequently, and the infection probability was greatest following exposure to migrating adults. Without coproduction, the frequency of exposure by migrating adults would have been overestimated by 70 cohort-sites, and the infection probability following exposure to migrating adults would have been underestimated by∼0.09. The coproduced model had less uncertainty in the infection probability if no transmission route could be identified (Bayesian credible interval (BCI) width = 0.12) compared to the model without coproduction (BCI width = 0.34). Evidence for virus lineage MD specialization on steelhead and rainbow trout (both Oncorhynchus mykiss) was apparent without model coproduction. In the SRB, we found a greater probability of virus lineage UC infection in Chinook salmon (Oncorhynchus tshawytscha) compared to in O. mykiss, whereas in the LCRB, UC more clearly exhibited a generalist approach. Coproduction influenced estimates that depended on transmission routes, which operated differently at main hatcheries and satellite sites within hatchery complexes. Hatchery complexes are found outside of the SRB and are not specific to salmonid hatcheries alone. There is great potential for coproduction and modeling spatial contact networks to advance understanding about infectious disease transmission in complex production systems and surrounding free-ranging animal populations.

Idaho, Oregon, Washington↗

What common-garden experiments tell us about climate responses in plants

Common garden experiments are indoor or outdoor plantings of species or populations collected from multiple distinct geographic locations, grown together under shared conditions. These experiments examine a range of questions for theory and application using a variety of methods for analysis. The eight papers of this special feature comprise a cross section of contemporary approaches, summarized and synthesized here by what they tell us about the relationships between climate-related trait spectra and fitness optima. Four of the eight papers are based on field experiments in prairie, desert, Mediterranean and boreal biomes. Representative of many common garden experiments, these experiments reveal consistent evidence of traits varying with population climate provenance, but evidence of a tradeoff between growth and tolerance traits or of consistent fitness optimization at home is scant, in contrast to trait theory. Two synthesis papers highlight dominant patterns of trait divergence, including for an exotic invasive species. One theoretical paper warned that unknown kinship relationships between populations can result in the misidentification of adaptive trait divergence. A third synthesis paper formulated novel and ambitious goals for common-garden studies through including measurement of response variables at multiple levels of biological organization. The featured papers discuss multiple avenues for improving common garden studies. Genomic analysis, together with the quantification of kinship relationships, will continue to reveal the influence of environmental drivers on gene selection. Measuring a more complete set of fitness traits, especially for traits related to regeneration, will permit the development of projection models to explicitly link trait spectra, climate patterns and fitness consequences. More standardized data reporting will additionally improve abilities to synthesize findings across experiments. Testing population performance in competition with other species will produce more robust fitness comparisons between genotypes, especially for slower-growing genotypes in higher-resource environments. Adding gardens in and beyond climatic edge locations will furthermore strengthen the understanding of population failure and species exclusion. Finally, there is unrealized potential in adding ecosystem-level observations to common-garden studies that will enhance integrative analysis across scales of biological organization and scientific domains. Synthesis . With novel, creative designs, data integration and synthesis, common garden experiments will continue to advance the understanding of trait ensembles interacting with climate across scales of biological organization, provide pivotal data for global change models and guide ecological applications such as restoration of habitats for rare and climate sensitive species.

Journal of Ecology↗

The major-ion composition of Cenozoic seawater: the past 36 million years from fluid inclusions in marine halite

Fluid inclusions from ten Cenozoic (Eocene-Miocene) marine halites are used to quantify the major-ion composition (Mg 2+ , Ca 2+ , K + , Na + , SO 4 2− , and Cl − ) of seawater over the past 36 My. Criteria used to determine a seawater origin of the halites include: (1) stratigraphic, sedimentologic, and paleontologic observations; (2) Br − in halite; (3) δ 34 S of sulfate minerals; (4) 87 Sr/ 86 Sr of carbonates and sulfates; and (5) fluid inclusion brine compositions and evaporation paths, which must overlap from geographically separated basins of the same age to confirm a “global” seawater chemical signal. Changes in the major-ion chemistry of Cenozoic seawater record the end of a systematic, long term (>150 My) shift from the Ca 2+ -rich, Mg 2+ - and SO 4 2− -poor seawater of the Mesozoic (“CaCl 2 seas”) to the “MgSO 4 seas” (with higher Mg 2+ and SO 4 2− >Ca 2+ ) of the Cenozoic. The major ion composition of Cenozoic seawater is calculated for the Eocene-Oligocene (36-34 Ma), Serravallian-Tortonian (13.5-11.8 Ma) and the Messinian (6-5 Ma), assuming chlorinity (565 mmolal), salinity, and the K + concentration (11 mmolal) are constant and the same as in modern seawater. Fluid inclusions from Cenozoic marine halites show that the concentrations of Mg 2+ and SO 4 2− have increased in seawater over the past 36 My and the concentration of Ca 2+ has decreased. Mg 2+ concentrations increased from 36 mmolal in Eocene-Oligocene seawater (36-34 Ma) to 55 mmolal in modern seawater. The Mg 2+ /Ca 2+ ratio of seawater has risen from ∼2.3 at the end of the Eocene, to 3.4 and 4.0, respectively, at 13.5 to 11.8 Ma and 6 to 5 Ma, and to 5 in modern seawater. Eocene-Oligocene seawater (36-34 Ma) has estimated ranges of SO 4 2− = 14–23 mmolal and Ca 2+ = 11–20 mmolal. If the (Ca 2+ )(SO 4 2− ) product is assumed to be the same as in modern seawater (∼300 mmolal 2 ), Eocene-Oligocene seawater had Ca 2+ ∼16 mmolal and SO 4 2− ∼19 mmolal. The same estimates of Ca 2+ and SO 4 2− for Serravallian-Tortonian seawater (13.5-11.8 Ma) are SO 4 2− = 19–27 mmolal and Ca 2+ = 8–16 mmolal and SO 4 2− ∼24 mmolal and Ca 2+ ∼ 13 mmolal if the (Ca 2+ )(SO 4 2− ) product is equal to that in modern seawater. Messinian seawater has an estimated range of SO 4 2− ∼21–29 mmolal and Ca 2+ ∼7–15 mmolal with SO 4 2− ∼26 mmolal and Ca 2+ ∼12 mmolal assuming the (Ca 2+ )(SO 4 2− ) product is equal to that in modern seawater. Regardless of the estimation procedure, SO 4 2− shows progressively increasing concentrations from 36 Ma to the present values, which are the highest of the Cenozoic.

American Journal of Science↗

A 30-m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on Google Earth Engine cloud computing platform

Mapping high resolution (30-m or better) cropland extent over very large areas such as continents or large countries or regions accurately, precisely, repeatedly, and rapidly is of great importance for addressing the global food and water security challenges. Such cropland extent products capture individual farm fields, small or large, and are crucial for developing accurate higher-level cropland products such as cropping intensities, crop types, crop watering methods (irrigated or rainfed), crop productivity, and crop water productivity. It also brings many challenges that include handling massively large data volumes, computing power, and collecting resource intensive reference training and validation data over complex geographic and political boundaries. Thereby, this study developed a precise and accurate Landsat 30-m derived cropland extent product for two very important, distinct, diverse, and large countries: Australia and China. The study used of eight bands (blue, green, red, NIR, SWIR1, SWIR2, TIR1, and NDVI) of Landsat-8 every 16-day Operational Land Imager (OLI) data for the years 2013–2015. The classification was performed by using a pixel-based supervised random forest (RF) machine learning algorithm (MLA) executed on the Google Earth Engine (GEE) cloud computing platform. Each band was time-composited over 4–6 time-periods over a year using median value for various agro-ecological zones (AEZs) of Australia and China. This resulted in a 32–48-layer mega-file data-cube (MFDC) for each of the AEZs. Reference training and validation data were gathered from: (a) field visits, (b) sub-meter to 5-m very high spatial resolution imagery (VHRI) data, and (c) ancillary sources such as from the National agriculture bureaus. Croplands versus non-croplands knowledge base for training the RF algorithm were derived from MFDC using 958 reference-training samples for Australia and 2130 reference-training samples for China. The resulting 30-m cropland extent product was assessed for accuracies using independent validation samples: 900 for Australia and 1972 for China. The 30-m cropland extent product of Australia showed an overall accuracy of 97.6% with a producer’s accuracy of 98.8% (errors of omissions = 1.2%), and user’s accuracy of 79% (errors of commissions = 21%) for the cropland class. For China, overall accuracies were 94% with a producer’s accuracy of 80% (errors of omissions = 20%), and user’s accuracy of 84.2% (errors of commissions = 15.8%) for cropland class. Total cropland areas of Australia were estimated as 35.1 million hectares and 165.2 million hectares for China. These estimates were higher by 8.6% for Australia and 3.9% for China when compared with the traditionally derived national statistics. The cropland extent product further demonstrated the ability to estimate sub-national cropland areas accurately by providing an R 2 value of 0.85 when compared with province-wise cropland areas of China. The study provides a paradigm-shift on how cropland maps are produced using multi-date remote sensing. These products can be browsed at www.croplands.org and made available for download at NASA’s Land Processes Distributed Active Archive Center (LP DAAC) https://www.lpdaac.usgs.gov/node/1282 .

ISPRS Journal of Photogrammetry and Remote Sensing↗

Thirty years of regional groundwater-quality trend studies in the United States: Major findings and lessons learned

Changes in groundwater quality have been evaluated for more than 2,200 wells in 25 Principal Aquifers in the United States based on repeated decadal sampling (once every 10 years) from 1988 to 2021. The purpose of this study is to identify contaminants with changing concentrations, the locations and magnitude of those changes, the factors driving those changes, the obstacles to interpreting the changes, and approaches to ameliorate those obstacles. Sampling was conducted in 89 networks of 20–30 wells each that represent various geographic regions, aquifer types and land use types. Each network, and the wells that comprise them, are sampled on a rotating basis once every 10 years. Of the 28 constituents evaluated for trends, concentrations of Na, Cl, dissolved solids, SO 4 , and NO 3 exhibited statistically significant increases at the network level more frequently than other constituents. Factors affecting trends in Cl and NO 3 are emphasized in this study. Regional patterns show large increases of Cl in urban areas in the Northeast and Midcontinent, where road-deicing salt application rates are 10 to 100 times greater than in other regions of the country, and in semiarid and arid regions of the western United States, where evaporation concentrates solutes in recharge. The largest increases in NO 3 were in agricultural areas of the semiarid west, arid west and Pacific regions which are characterized by oxic groundwater, long-term increases in nitrogen fertilizer usage, and high rates of irrigation. However, finding a direct relation between increasing contaminant sources and corresponding groundwater quality response, particularly when sampling once every 10 years, can be complicated by factors such as uncertainty in the timing, mass, and location of contaminant sources, groundwater residence time (recharge date), geochemical conditions in the aquifer that affect contaminant transport, and variability in water quality due to climatic factors such as seasonality and hydrologic conditions. Understanding groundwater residence time allows the changes in groundwater quality to be evaluated in the context of recharge date rather than the sample date. Likewise, information on geochemical characteristics of the aquifer can be helpful for understanding relations between contaminant source inputs and groundwater concentrations. For example, oxic geochemical conditions in the aquifer may allow for conservative transport and accumulation of NO 3 in groundwater, whereas reducing environments could favor NO 3 degradation. Differences in hydrologic conditions (wetter or drier than average) on the date of sampling could impact the statistical results of sampling at decadal intervals and obscure long-term patterns. Samples collected under substantially different hydrologic conditions can be identified, and high-frequency sampling can improve interpretation of measured results in these cases. Although decadal sampling and associated water-quality interpretations have limitations, repeated, scheduled sampling of thousands of wells over multiple decades has great value for identifying and understanding long-term, regional groundwater-quality trends. Despite these limitations, the concepts presented herein provide options that could be used to interpret trends or changes when sampling over longer timespans, which is less common than trend networks with higher frequency sampling intervals.

Conterminous United States↗

Imaging the magmatic plumbing of the Clear Lake Volcanic Field using 3-D gravity inversions

The Quaternary Clear Lake Volcanic Field (CLVF) in the Northern California Coast Range is the youngest of a string of northward-younging volcanic centers in the state. The CLVF is located within the broad San Andreas Transform Fault System and has been active intermittently for ∼2 million years. Heat beneath the CLVF supports The Geysers, one of the largest producing geothermal fields in the world. Previous geophysical studies proposed the existence of a magma reservoir beneath Mount Hannah, which is northeast of The Geysers, near the geographic center of the CLVF. The lateral extent, depth, and presence of melt within this reservoir are poorly constrained, as is the relationship between this body and the broader magmatic plumbing of the CLVF. To gain a clearer and more comprehensive picture of the CLVF magma source region, a gravity dataset was compiled and the first 3-D gravity inversions of the CLVF were completed. Field and synthetic model inversions from the current study both indicate that the gravity low roughly centered on Mount Hannah is not accurately explained by a 5–7 km thick lens of Mesozoic Great Valley Sequence ( ρ = 2.58 g/cm 3 "> �=2.58g/cm3 ) as proposed by Stanley et al. (1998) . The observed gravity low is more accurately described by one or more silicic, partial melt bodies between The Geysers and Mount Hannah. Although our inversions cannot constrain the exact depth and geometry of these bodies, the recovered models indicate the existence of a partial melt zone between 6 and 13 km depth. The prolonged eruption history of the CLVF, coupled with the compositional variation of erupted rocks over time and space, is consistent with the existence of several, potentially ephemeral, melt-bearing bodies as opposed to one large melt body. Given the density and location of the recovered anomaly, rhyolite-MELTS thermodynamic modeling suggests the existence of 10–30% rhyodacitic melt within the proposed silicic magma reservoir at about 700 °C and 8 km depth (210 MPa). Independent petrologic, geochemical, and seismic evidence indicates that this silicic partial melt zone is underlain by basaltic melt in the lower to middle crust (13 to 21 km depth), which is fed by a mantle source. Eruptions in the past ∼8.5–13.5 thousand years; high regional heat flow; 3 He enrichment of hydrothermal fluids; and our modeling, which suggests the presence of a mid-crustal, silicic partial melt zone, point to a still-active CLVF. The relatively low estimates of partial melt (10–30%) predicted by thermodynamic modeling indicates that an injection of new magma into the imaged partial melt zone is needed to generate sufficient melt to incite future eruptions. Despite the low percent melt estimates within the proposed silicic partial melt zone the potential for future volcanic eruption remains. Due to the proximity of the CLVF to cities surrounding Clear Lake and the densely populated San Francisco Bay Area, continued research and monitoring of the volcanic field are warranted. The geophysical and petrologic modeling presented here improves our understanding of the CLVF magma plumbing system and allows us to better characterize its associated volcanic hazards.

California↗

Classification tree and minimum-volume ellipsoid analyses of the distribution of ponderosa pine in the western USA

Aim? Ponderosa pine (Pinus ponderosa Douglas ex Lawson & C. Lawson) is an economically and ecologically important conifer that has a wide geographic range in the western USA, but is mostly absent from the geographic centre of its distribution - the Great Basin and adjoining mountain ranges. Much of its modern range was achieved by migration of geographically distinct Sierra Nevada (P. ponderosa var. ponderosa) and Rocky Mountain (P. ponderosa var. scopulorum) varieties in the last 10,000 years. Previous research has confirmed genetic differences between the two varieties, and measurable genetic exchange occurs where their ranges now overlap in western Montana. A variety of approaches in bioclimatic modelling is required to explore the ecological differences between these varieties and their implications for historical biogeography and impending changes in western landscapes. Location? Western USA. Methods? We used a classification tree analysis and a minimum-volume ellipsoid as models to explain the broad patterns of distribution of ponderosa pine in modern environments using climatic and edaphic variables. Most biogeographical modelling assumes that the target group represents a single, ecologically uniform taxonomic population. Classification tree analysis does not require this assumption because it allows the creation of pathways that predict multiple positive and negative outcomes. Thus, classification tree analysis can be used to test the ecological uniformity of the species. In addition, a multidimensional ellipsoid was constructed to describe the niche of each variety of ponderosa pine, and distances from the niche were calculated and mapped on a 4-km grid for each ecological variable. Results? The resulting classification tree identified three dominant pathways predicting ponderosa pine presence. Two of these three pathways correspond roughly to the distribution of var. ponderosa, and the third pathway generally corresponds to the distribution of var. scopulorum. The classification tree and minimum-volume ellipsoid model show that both varieties have very similar temperature limitations, although var. ponderosa is more limited by the temperature extremes of the continental interior. The precipitation limitations of the two varieties are seasonally different, with var. ponderosa requiring significant winter moisture and var. scopulorum requiring significant summer moisture. Great Basin mountain ranges are too cold at higher elevations to support either variety of ponderosa pine, and at lower elevations are too dry in summer for var. scopulorum and too dry in winter for var. ponderosa. Main conclusions? The classification tree analysis indicates that var. ponderosa is ecologically as well as genetically distinct from var. scopulorum. Ecological differences may maintain genetic separation in spite of a limited zone of introgression between the two varieties in western Montana. Two hypotheses about past and future movements of ponderosa pine emerge from our analyses. The first hypothesis is that, during the last glacial period, colder and/or drier summers truncated most of the range of var. scopulorum in the central Rockies, but had less dramatic effects on the more maritime and winter-wet distribution of var. ponderosa. The second hypothesis is that, all other factors held constant, increasing summer temperatures in the future should produce changes in the distribution of var. scopulorum that are likely to involve range expansions in the central Rockies with the warming of mountain ranges currently too cold but sufficiently wet in summer for var. scopulorum. Finally, our results underscore the growing need to focus on genotypes in biogeographical modelling and ecological forecasting.

Journal of Biogeography↗

Climate change and the global redistribution of biodiversity: Substantial variation in empirical support for expected range shifts

Background Among the most widely predicted climate change-related impacts to biodiversity are geographic range shifts, whereby species shift their spatial distribution to track their climate niches. A series of commonly articulated hypotheses have emerged in the scientific literature suggesting species are expected to shift their distributions to higher latitudes, greater elevations, and deeper depths in response to rising temperatures associated with climate change. Yet, many species are not demonstrating range shifts consistent with these expectations. Here, we evaluate the impact of anthropogenic climate change (specifically, changes in temperature and precipitation) on species’ ranges, and assess whether expected range shifts are supported by the body of empirical evidence. Methods We conducted a Systematic Review, searching online databases and search engines in English. Studies were screened in a two-stage process (title/abstract review, followed by full-text review) to evaluate whether they met a list of eligibility criteria. Data coding, extraction, and study validity assessment was completed by a team of trained reviewers and each entry was validated by at least one secondary reviewer. We used logistic regression models to assess whether the direction of shift supported common range-shift expectations (i.e., shifts to higher latitudes and elevations, and deeper depths). We also estimated the magnitude of shifts for the subset of available range-shift data expressed in distance per time (i.e., km/decade). We accounted for methodological attributes at the study level as potential sources of variation. This allowed us to answer two questions: (1) are most species shifting in the direction we expect (i.e., each observation is assessed as support/fail to support our expectation); and (2) what is the average speed of range shifts? Review findings We found that less than half of all range-shift observations (46.60%) documented shifts towards higher latitudes, higher elevations, and greater marine depths, demonstrating significant variation in the empirical evidence for general range shift expectations. For the subset of studies looking at range shift rates, we found that species demonstrated significant average shifts towards higher latitudes (average = 11.8 km/dec) and higher elevations (average = 9 m/dec), although we failed to find significant evidence for shifts to greater marine depths. We found that methodological factors in individual range-shift studies had a significant impact on the reported direction and magnitude of shifts. Finally, we identified important variation across dimensions of range shifts (e.g., greater support for latitude and elevation shifts than depth), parameters (e.g., leading edge shifts faster than trailing edge for latitude), and taxonomic groups (e.g., faster latitudinal shifts for insects than plants). Conclusions Despite growing evidence that species are shifting their ranges in response to climate change, substantial variation exists in the extent to which definitively empirical observations confirm these expectations. Even though on average, rates of shift show significant movement to higher elevations and latitudes for many taxa, most species are not shifting in expected directions. Variation across dimensions and parameters of range shifts, as well as differences across taxonomic groups and variation driven by methodological factors, should be considered when assessing overall confidence in range-shift hypotheses. In order for managers to effectively plan for species redistribution, we need to better account for and predict which species will shift and by how much. The dataset produced for this analysis can be used for future research to explore additional hypotheses to better understand species range shifts.

Journal of Environmental Evidence↗