Uncertainties in measuring precipitation hinders precise evaluation of loss of diversity in biomes and ecotones

npj Climate and Atmospheric Science, Год журнала: 2024, Номер 7(1)

Опубликована: Фев. 2, 2024

Abstract Assessing changes in the distribution of biological communities that share a climate (biomes) is essential for estimating their vulnerability to change. We use CMIP6 models calculate biome as featuring classifications such Holdridge’s Life Zones (climate envelopes). found transitional zones between biomes (known ecotones) are expected decline under all change scenarios, but also model consensus remains low. Accurate assessments diversity loss limited certain areas globe, while still poor half planet. identify where there robust estimates and ecotones, lacking. argue caution should be exercised measuring biodiversity latter, greater confidence can placed former. find shortcomings life zone classification related inter-model variability, which ultimately depends on larger problem, namely accurate estimation precipitation compared CRU. Application methodology other confirms findings.

Язык: Английский

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WorldSeasons: a seasonal classification system interpolating biome classifications within the year for better temporal aggregation in climate science

Scientific Data, Год журнала: 2024, Номер 11(1)

Опубликована: Авг. 27, 2024

Abstract We present a seasonal classification system to improve the temporal framing of comparative scientific analysis. Research often uses yearly aggregates understand inherently phenomena like harvests, monsoons, and droughts. This obscures important trends across time differences through space by including redundant data. Our allows for more targeted approach. split global land into four principal climate zones: desert, arctic high montane, tropical, temperate. A cluster analysis with zone-specific variables weighting splits each month year discrete seasons based on monthly climate. expect data will be able answer questions like: are winters less icy than before? Are wildfires frequent now in dry season? How severe monsoon season flooding events? is natural extension historical concept biomes, made possible recent advances availability artificial intelligence.

Язык: Английский

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Patterns and Drivers of Phylogenetic Beta Diversity in the Forests and Savannas of Africa

Journal of Biogeography, Год журнала: 2025, Номер unknown

Опубликована: Апрель 7, 2025

ABSTRACT Aim Studying beta diversity, or the variation in species composition among communities, can give insights into plant community assembly over space and time. If different biomes show contrasting large‐scale beta‐diversity patterns, this indicate divergent evolutionary histories ecological processes that then drive turnover communities. Here, we examine phylogenetic patterns across Africa forest savanna assemblages, two most widespread tropical on continent. We hypothesise savannas will lower diversity due to their younger history. Location Tropical Africa. Taxon Woody angiosperms. Methods gathered 301,159 occurrences of woody angiosperms representing 1883 1302 species. compared levels between analysed spatial using 1° grid cells modelled relationship with climate, disturbance geographical distance. Results found greater relative regional whereas assemblages local diversity. The distribution showed strong East–West for both forests savannas, aligned a major floristic discontinuity associated Albertine rift. Our results also highlighted West as showing high amount compositional change biomes, arranged along an aridity gradient. Variance partitioning predictors linked precipitation were main drivers but importance individual was each biome. Main Conclusions Contrary our expectations, may have deeper richer history than suggested by previous studies regions conservation value. Finally, demonstrate environmental filtering is dominant force influencing these important at continental scale.

Язык: Английский

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Modeling drought mortality and resilience of savannas and forests in tropical Asia

Ecological Modelling, Год журнала: 2024, Номер 494, С. 110783 - 110783

Опубликована: Июнь 21, 2024

The projected increase of drought occurrence in many tropical and sub-tropical regions globally under future climates will affect terrestrial ecosystems, particularly by increasing drought-induced plant mortality. capacity to simulate mortality vegetation models is therefore essential understand ecosystem dynamics. Using the trait-based model aDGVM2, we assessed resilience Asia climate change. We conducted simulations for ten sites Asia, representing a biogeographic gradient. Responses attributes rates were simulated until 2099 hypothetical scenarios recovery times calculated. Model showed biomass dieback during due increased mortality, primarily among tall old trees. Drought responses related hydraulic traits associated ecological strategies. Despite severe impacts, was possible, but differed between attributes. conclude that aDGVM2 enhances our ability impacts ecosystems. can trait- individual-based modeling framework. It indicated forests adaptation changes community trait composition demographic structure. Yet, further improvements are required better represent impact recovery.

Язык: Английский

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Crowd-sourced trait data can be used to delimit global biomes

Biogeosciences, Год журнала: 2024, Номер 21(21), С. 4909 - 4926

Опубликована: Ноя. 11, 2024

Abstract. Terrestrial biomes and their biogeographic patterns have been derived from a large variety of variables including species distributions bioclimate or remote sensing products. However, classifying the biosphere into functional perspective using biophysical traits has rarely tested. Such trait-based biome classification limited by data availability. Here, we aimed to exploit crowd-sourced plant observations trait databases systematically assess which are most suitable for classification. We global 33 covering around 50 % land surface combining distribution Global Biodiversity Information Facility (GBIF) TRY database. Using these maps as predictors supervised cluster analyses, tested what extent can reconstruct 31 published maps. A sensitivity analysis with randomly sampled combinations was performed identify that appropriate Performance quantified comparing modeled respective observation-based Finally, spatial gaps in resulting were filled models obtain continuous showed be used conduit density; rooting depth; height; different leaf traits, specific area nitrogen content. The best performance obtained based on zonation distributions, contrast optical reflectance. availability is heterogeneous, and, despite its exponential growth, prevalent. Nonetheless, it possible derive schemes predict good agreement. Therefore, our valuable approach towards understanding associated ecological strategies.

Язык: Английский

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Comment on egusphere-2024-276

Опубликована: Апрель 2, 2024

Abstract. Biomes and their biogeographic patterns have been derived from a large variety of variables including species distributions, bioclimate or remote sensing products. Yet, whether plant trait data are suitable for biome classification has rarely tested. Here, we aimed to assess systematically which traits most classification. We 33 different by combining crowd-sourced distribution the TRY database. Using supervised cluster analyses, developed schemes using these 31 maps. A sensitivity analysis with randomly sampled combinations was performed identify maps that appropriate achieved highest data-model agreement. Due gaps in data, models were used obtain at global scale. showed can be conduit density, rooting depth, height, leaf traits, specific area nitrogen. Data-model agreement maximized when inform analyses based on zonation contrast optical reflectance. The availability is heterogeneous prevalent. Nonetheless, it possible derive predict good Filling essential further improve trait-based

Язык: Английский

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Comment on egusphere-2024-276

Опубликована: Апрель 17, 2024

Abstract. Biomes and their biogeographic patterns have been derived from a large variety of variables including species distributions, bioclimate or remote sensing products. Yet, whether plant trait data are suitable for biome classification has rarely tested. Here, we aimed to assess systematically which traits most classification. We 33 different by combining crowd-sourced distribution the TRY database. Using supervised cluster analyses, developed schemes using these 31 maps. A sensitivity analysis with randomly sampled combinations was performed identify maps that appropriate achieved highest data-model agreement. Due gaps in data, models were used obtain at global scale. showed can be conduit density, rooting depth, height, leaf traits, specific area nitrogen. Data-model agreement maximized when inform analyses based on zonation contrast optical reflectance. The availability is heterogeneous prevalent. Nonetheless, it possible derive predict good Filling essential further improve trait-based

Язык: Английский

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Comment on egusphere-2024-276

Опубликована: Апрель 18, 2024

Abstract. Biomes and their biogeographic patterns have been derived from a large variety of variables including species distributions, bioclimate or remote sensing products. Yet, whether plant trait data are suitable for biome classification has rarely tested. Here, we aimed to assess systematically which traits most classification. We 33 different by combining crowd-sourced distribution the TRY database. Using supervised cluster analyses, developed schemes using these 31 maps. A sensitivity analysis with randomly sampled combinations was performed identify maps that appropriate achieved highest data-model agreement. Due gaps in data, models were used obtain at global scale. showed can be conduit density, rooting depth, height, leaf traits, specific area nitrogen. Data-model agreement maximized when inform analyses based on zonation contrast optical reflectance. The availability is heterogeneous prevalent. Nonetheless, it possible derive predict good Filling essential further improve trait-based

Язык: Английский

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Reply on CC1

Опубликована: Май 7, 2024

Abstract. Biomes and their biogeographic patterns have been derived from a large variety of variables including species distributions, bioclimate or remote sensing products. Yet, whether plant trait data are suitable for biome classification has rarely tested. Here, we aimed to assess systematically which traits most classification. We 33 different by combining crowd-sourced distribution the TRY database. Using supervised cluster analyses, developed schemes using these 31 maps. A sensitivity analysis with randomly sampled combinations was performed identify maps that appropriate achieved highest data-model agreement. Due gaps in data, models were used obtain at global scale. showed can be conduit density, rooting depth, height, leaf traits, specific area nitrogen. Data-model agreement maximized when inform analyses based on zonation contrast optical reflectance. The availability is heterogeneous prevalent. Nonetheless, it possible derive predict good Filling essential further improve trait-based

Язык: Английский

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Reply on RC1

Опубликована: Май 7, 2024

Abstract. Biomes and their biogeographic patterns have been derived from a large variety of variables including species distributions, bioclimate or remote sensing products. Yet, whether plant trait data are suitable for biome classification has rarely tested. Here, we aimed to assess systematically which traits most classification. We 33 different by combining crowd-sourced distribution the TRY database. Using supervised cluster analyses, developed schemes using these 31 maps. A sensitivity analysis with randomly sampled combinations was performed identify maps that appropriate achieved highest data-model agreement. Due gaps in data, models were used obtain at global scale. showed can be conduit density, rooting depth, height, leaf traits, specific area nitrogen. Data-model agreement maximized when inform analyses based on zonation contrast optical reflectance. The availability is heterogeneous prevalent. Nonetheless, it possible derive predict good Filling essential further improve trait-based

Язык: Английский

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