109 research outputs found
Postglacial migration supplements climate in determining plant species ranges in Europe
The influence of dispersal limitation on species ranges remains controversial. Considering the dramatic impacts of the last glaciation in Europe, species might not have tracked climate changes through time and, as a consequence, their present-day ranges might be in disequilibrium with current climate. For 1016 European plant species, we assessed the relative importance of current climate and limited postglacial migration in determining species ranges using regression modelling and explanatory variables representing climate, and a novel species-specific hind-casting-based measure of accessibility to postglacial colonization. Climate was important for all species, while postglacial colonization also constrained the ranges of more than 50 per cent of the species. On average, climate explained five times more variation in species ranges than accessibility, but accessibility was the strongest determinant for one-sixth of the species. Accessibility was particularly important for species with limited long-distance dispersal ability, with southern glacial ranges, seed plants compared with ferns, and small-range species in southern Europe. In addition, accessibility explained one-third of the variation in species' disequilibrium with climate as measured by the realized/potential range size ratio computed with niche modelling. In conclusion, we show that although climate is the dominant broad-scale determinant of European plant species ranges, constrained dispersal plays an important supplementary role
‘LandsatTS': an R package to facilitate retrieval, cleaning, cross‐calibration, and phenological modeling of Landsat time series data
The Landsat satellites provide decades of near‐global surface reflectance measurements that are increasingly used to assess interannual changes in terrestrial ecosystem function. These assessments often rely on spectral indices related to vegetation greenness and productivity (e.g. Normalized Difference Vegetation Index, NDVI). Nevertheless, multiple factors impede multi‐decadal assessments of spectral indices using Landsat satellite data, including ease of data access and cleaning, as well as lingering issues with cross‐sensor calibration and challenges with irregular timing of cloud‐free acquisitions. To help address these problems, we developed the ‘LandsatTS' package for R. This software package facilitates sample‐based time series analysis of surface reflectance and spectral indices derived from Landsat sensors. The package includes functions that enable the extraction of the full Landsat 5, 7, and 8 records from Collection 2 for point sample locations or small study regions using Google Earth Engine accessed directly from R. Moreover, the package includes functions for 1) rigorous data cleaning, 2) cross‐sensor calibration, 3) phenological modeling, and 4) time series analysis. For an example application, we show how ‘LandsatTS' can be used to assess changes in annual maximum vegetation greenness from 2000 to 2022 across the Noatak National Preserve in northern Alaska, USA. Overall, this software provides a suite of functions to enable broader use of Landsat satellite data for assessing and monitoring terrestrial ecosystem function during recent decades across local to global geographic extents
Vegetation structure from LiDAR explains the local richness of birds across Denmark
Classic ecological research into the determinants of biodiversity patterns emphasised the important role of three‐dimensional (3D) vegetation heterogeneity. Yet, measuring vegetation structure across large areas has historically been difficult. A growing focus on large‐scale research questions has caused local vegetation heterogeneity to be overlooked compared with more readily accessible habitat metrics from, for example, land cover maps.
Using newly available 3D vegetation data, we investigated the relative importance of habitat and vegetation heterogeneity for explaining patterns of bird species richness and composition across Denmark (42,394 km).
We used standardised, repeated point counts of birds conducted by volunteers across Denmark alongside metrics of habitat availability from land‐cover maps and vegetation structure from rasterised LiDAR data (10 m resolution). We used random forest models to relate species richness to environmental features and considered trait‐specific responses by grouping species by nesting behaviour, habitat preference and primary lifestyle. Finally, we evaluated the role of habitat and vegetation heterogeneity metrics in explaining local bird assemblage composition.
Overall, vegetation structure was equally as important as habitat availability for explaining bird richness patterns. However, we did not find a consistent positive relationship between species richness and habitat or vegetation heterogeneity; instead, functional groups displayed individual responses to habitat features. Meanwhile, habitat availability had the strongest correlation with the patterns of bird assemblage composition.
Our results show how LiDAR and land cover data complement one another to provide insights into different facets of biodiversity patterns and demonstrate the potential of combining remote sensing and structured citizen science programmes for biodiversity research. With the growing coverage of LiDAR surveys, we are witnessing a revolution of highly detailed 3D data that will allow us to integrate vegetation heterogeneity into studies at large spatial extents and advance our understanding of species' physical niches
Transferability and the effect of colour calibration during multi-image classification of Arctic vegetation change
What evidence exists for temporal variability in Arctic terrestrial and freshwater biodiversity throughout the Holocene? A systematic map protocol
Background: The Arctic tundra is subject to the greatest climate change-induced temperature rises of any biome. Both terrestrial and freshwater biota are responding to recent climate warming through variability in their distribution, abundance, and richness. However, uncertainty arises within models of future change when considering processes that operate over centennial timescales. A systematic evidence synthesis of centennial-scale variability in biodiversity does not currently exist for the Arctic biome. Here, we sought to address the primary research question: what evidence exists for temporal variability in Arctic terrestrial and freshwater biodiversity throughout the Holocene (11,650 years before present (yBP)-OyBP)? Methods: Consultation with stakeholders informed key definitions, scoping and the appropriateness of the research question. The research question was structured using a PECO framework-Arctic biota (P), a timestamped year in the Holocene (E), another year in the Holocene (C), and the dimensions of biodiversity that have been measured (O)-to inform the search strategy. Search strings were benchmarked against a test list of 100 known sources to ensure a specific and comprehensive return of literature. Searches will occur across 13 bibliographic databases. The eligibility criteria specify that sources must: (a) use 'proxy' methods to measure biodiversity; (b) fall within the spatial extent of the contemporary Arctic tundra biome; and (c) consist of a time-series that overlaps with 11,650yBP to OyBP (1950AD). Information coded from studies will include proxy-specific information to account for both temporal uncertainty (i.e., the characteristics of age-depth models and dating methods) and taxonomic uncertainty (i.e., the samples and processes used for taxonomic identification). We will assess temporal uncertainty within each source by determining the quality of dating methods and measures; this information will be used to harmonise dates onto the IntCa120 calibration curve and determine the available temporal resolution and extent of evidence through space. Key outputs of this systematic map will be: (1) a graph database containing the spatial-temporal properties of each study dataset with taxonomic harmonisation; and (2) a geographical map of the evidence base.Peer reviewe
Orações adverbiais reduzidas de gerúndio: o ensino do português e a perspectiva da gramática discursivofuncional
Esta pesquisa tem como objetivo central discutir o modo como são tratadas as orações adverbiais reduzidas de gerúndio pelas gramáticas prescritivas e pelos livros didáticos, orientados pelos Parâmetros Curriculares Nacionais (PCNs), com a finalidade de verificar em que grau essa abordagem se aproxima ou se distancia da descrição deste tipo de adverbial no uso cotidiano. Para tanto, foram utilizados os fundamentos metodológicos da Gramática Discursivo-Funcional (HENGEVELD e MACKENZIE, 2008), verificando-se como tais embasamentos podem contribuir para que se faça uma abordagem mais ampla das orações adverbiais reduzidas de gerúndio, levando os alunos à reflexão sobre o uso e o funcionamento da língua. Para a análise dos dados, foram utilizadas ocorrências de uso real extraídas da mídia virtual que compõe a esfera jornalística. Os dados revelam que, dependendo da situação comunicativa em que estão inseridas, elas podem autorizar mais de uma interpretação, possíveis de serem recuperadas pela intuição do interlocutor por meio do próprio contexto; também revelam que as orações adverbiais reduzidas de gerúndio possuem sujeito correferencial ao da oração principal, são orações factuais e, geralmente, apresentam-se como estadode-coisas
Status and trends in Arctic vegetation: Evidence from experimental warming and long-term monitoring
Changes in Arctic vegetation can have important implications for trophic interactions and ecosystem
functioning leading to climate feedbacks. Plot-based vegetation surveys provide detailed insight into
vegetation changes at sites around the Arctic and improve our ability to predict the impacts of
environmental change on tundra ecosystems. Here, we review studies of changes in plant community composition and phenology from both long-term monitoring and warming experiments in Arctic environments. We find that Arctic plant communities and species are generally sensitive to warming, but trends over a period of time are heterogeneous and complex and do not always mirror
expectations based on responses to experimental manipulations. Our findings highlight the need for more
geographically widespread, integrated, and comprehensive monitoring efforts that can better resolve the interacting
effects of warming and other local and regional ecological
factors
Plant functional trait change across a warming tundra biome
Accepted versionThe tundra is warming more rapidly than any other biome on Earth, and the potential ramifications are far-reaching because of global feedback effects between vegetation and climate. A better understanding of how environmental factors shape plant structure and function is crucial for predicting the consequences of environmental change for ecosystem functioning. Here we explore the biome-wide relationships between temperature, moisture and seven key plant functional traits both across space and over three decades of warming at 117 tundra locations. Spatial temperature–trait relationships were generally strong but soil moisture had a marked influence on the strength and direction of these relationships, highlighting the potentially important influence of changes in water availability on future trait shifts in tundra plant communities. Community height increased with warming across all sites over the past three decades, but other traits lagged far behind predicted rates of change. Our findings highlight the challenge of using space-for-time substitution to predict the functional consequences of future warming and suggest that functions that are tied closely to plant height will experience the most rapid change. They also reveal the strength with which environmental factors shape biotic communities at the coldest extremes of the planet and will help to improve projections of functional changes in tundra ecosystems with climate warming
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