Erratum: Global pressures, specific responses: effects of nutrient enrichment in streams from different biomes
Joan ArtigasEmili García‐BerthouDelia Elena BauerM. I. CastroJoaquín CocheroDarío César ColauttiAgustina CortelezziJohn DonatoArturo ElosegiClaudia FeijoóAdonis GiorgiNora GómezLeonardo LeggieriIsabel MuñozAlberto Rodrı́gues-Capı́tuloAnna M. RomaníSergi Sabater
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Biomes are large-scale biotic communities (ecosystems) distinguished by specific ecological functionality and evolutionary origins. They can be studied and delimited using functional variables but also using physiognomic and vegetation-textural surrogates. Biomes are spatially explicit units, and as such, they can be seen as complexes of biotic communities at various hierarchical levels, including zonobiomes, global biomes, continental biomes, and regional biomes. Each of these categories has its characteristic own set of ecological drivers. Walter's zonobiome system is possibly the most common biome system coined to explain the diversity of large-scale biotic communities on Earth. It is a bioclimatic approach, recognising the role of climatic factors driving the zonal biome patterns at large scales. It also provides for biomes driven by other factors, such as soils and hydrology, called azonal biomes. This chapter aims to revisit the usefulness of the zonal/azonal conceptual framework in the ocean-dominated Southern Hemisphere. It puts significant emphasis (at the large-scale biome levels) on the climato-genetic drivers, modern tools of bioclimatology, and sources of bioclimatic data. By doing so, this chapter is also a prelude to the formulation of a new zonobiome system, serving as a basis for a Global Hierarchical Biome System.
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Biome conservatism is often regarded as common in diversifying lineages, based on the detection of low biome shift rates or high phylogenetic signal. However, many studies testing biome conservatism utilise a single-biome-per-species approach, which may influence the detection of biome conservatism. Meta-analyses show that biome shift rates are significantly lower (less than a tenth), when single biome occupancy approaches are adopted. Using New Zealand plant lineages, estimated biome shifts were also significantly lower (14–67% fewer biome shifts) when analysed under the assumption of a single biome per species. Although a single biome approach consistently resulted in lower biome shifts, it detected fewer instances of biome conservatism. A third of clades (3 out of 9) changed status in biome conservatism tests between single and multiple biome occupancy approaches, with more instances of significant biome conservatism when using a multiple biome occupancy approach. A single biome approach may change the likelihood of finding biome conservatism because it assumes biome specialisation within species, falsely recognises some biome shift types and fails to include other biome shift types. Our results indicate that the degree of biome fidelity assumed has a strong influence on analyses assessing biome shift rates, and biome conservatism testing. We advocate analyses that allow species to occupy multiple biomes.
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Abstract Aim Recent studies in southern Africa identified past biome stability as an important predictor of biodiversity. We aimed to assess the extent to which past biome stability predicts present global biodiversity patterns, and the extent to which projected climatic changes may lead to eventual biome changes in areas with constant past biome. Location Global. Taxon Spermatophyta; terrestrial vertebrates. Methods Biome constancy was assessed and mapped using results from 89 dynamic global vegetation model simulations, driven by outputs of palaeoclimate experiments spanning the past 140 ka. We tested the hypothesis that terrestrial vertebrate diversity is predicted by biome constancy. We also simulated potential future vegetation, and hence potential future biome patterns, and quantified and mapped the extent of projected eventual future biome change in areas of past constant biome. Results Approximately 11% of global ice‐free land had a constant biome since 140 ka. Apart from areas of constant Desert, many areas with constant biome support high species diversity. All terrestrial vertebrate groups show a strong positive relationship between biome constancy and vertebrate diversity in areas of greater diversity, but no relationship in less diverse areas. Climatic change projected by 2100 commits 46%–66% of global ice‐free land, and 34%–52% of areas of past constant biome (excluding areas of constant Desert) to eventual biome change. Main conclusions Past biome stability strongly predicts vertebrate diversity in areas of higher diversity. Future climatic changes will lead to biome changes in many areas of past constant biome, with profound implications for biodiversity conservation. Some projected biome changes will result in substantial reductions in biospheric carbon sequestration and other ecosystem services.
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The file contains BIOME 6000 reconstructions of vegetation at 0, 6, and 21ka at individual sites, where the original published nomenclature for individual regions has been converted to a globally-applicable standardized classification (BIOME 6000 Consolidated Name). Two other standardized classifications are also given: common biome names between BIOME 6000 and the BIOME 4.2 model (BIOME 4.2 BIOME 6000 common names) and the megabiome scheme used by Harrison and Bartlein (2012) (MegaBiome Scheme 2). Additional information to translate BIOME 4.2 outputs into either BIOME 6000 Consolidated Names or BIOME 4.2 BIOME 6000 common names is also given.
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Biomes are important constructs for organizing understanding of how the worlds' major terrestrial ecosystems differ from one another and for monitoring change in these ecosystems. Yet existing biome classification schemes have been criticized for being overly subjective and for explicitly or implicitly invoking climate. We propose a new biome map and classification scheme that uses information on (i) an index of vegetation productivity, (ii) whether the minimum of vegetation activity is in the driest or coldest part of the year, and (iii) vegetation height. Although biomes produced on the basis of this classification show a strong spatial coherence, they show little congruence with existing biome classification schemes. Our biome map provides an alternative classification scheme for comparing the biogeochemical rates of terrestrial ecosystems. We use this new biome classification scheme to analyse the patterns of biome change observed over recent decades. Overall, 13% to 14% of analysed pixels shifted in biome state over the 30-year study period. A wide range of biome transitions were observed. For example, biomes with tall vegetation and minimum vegetation activity in the cold season shifted to higher productivity biome states. Biomes with short vegetation and low seasonality shifted to seasonally moisture-limited biome states. Our findings and method provide a new source of data for rigorously monitoring global vegetation change, analysing drivers of vegetation change and for benchmarking models of terrestrial ecosystem function.
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Temporal variation of nutrient uptake in streams may be large because nutrient uptake is driven by many factors that vary substantially over time. Although many studies have compared nutrient uptake among streams, the range and variation of nutrient uptake within streams is known only for a few streams and a few nutrients. We investigated the monthly variation of NH4+, NO3−, and PO43− uptake in 2 New Zealand streams over 1 y. To measure uptake, each nutrient was added individually along with a conservative tracer (Cl−) into each stream on 3 successive days in each month. Ambient nutrient concentrations were low and nutrients were efficiently removed from the water column, with maximum uptake velocities (vf) of 71, 12, and 11 mm/min for NH4+, NO3−, and PO43−, respectively. Nutrient uptake varied considerably during the year (CV = 37–109%), with shortest nutrient uptake lengths (Sw) and highest vf generally in spring and summer months. The range of vf occurring within the streams spanned 25 to 89% of the range of vf among other streams. The range of uptake rates (U) within the streams was lower, accounting for 2 to 40% of the range among other streams. Variation in Sw was largely explained by changes in velocity and effective depth. Physical factors (temperature, transient storage) and chlorophyll a were generally poor predictors of vf and U. There was little correlation in uptake among nutrients, suggesting different factors were responsible for uptake of each nutrient. Our results show that the range and variation of nutrient uptake within some streams can be large. Within-stream variation should be considered when comparing among streams and may be useful for understanding what factors drive nutrient uptake in streams.
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