Biology subjects

Maitner, B. S.

Publications and source records attributed to Maitner, B. S..

8 recordsLinked to original sources

bioRxiv2025

Challenges and opportunities in detecting leaf water and carotenoid content across biomes from satellite multispectral indices

Climate change is causing vegetation stress across the globe, increasing the need for reliable indicators to monitor plant health. Leaf water and carotenoid content, and the chlorophyll/carotenoid ratio, are established proxies for environmental stress that can be detected by remote sensing. Here, we evaluated the sensitivity of 11 multispectral vegetation indices (VIs) designed to monitor these three stress-related leaf traits across a broad range of environmental and vegetation conditions. For this, we combined radiative transfer modeling with cross-biome field and satellite observations from Sentinel-2, Landsat 8, and MODIS from the National Ecological Observatory Network (NEON), spanning in most major terrestrial ecosystems. Our model-based analysis showed that VIs have a low to moderate sensitivity to their target traits, ranging from water indices with 66% of their variability explained by leaf water content, to carotenoid indices with 27% variability explained by leaf carotenoid content. Surprisingly, our field-based analyses revealed minimal to no sensitivity to leaf water and carotenoid content and chlorophyll/carotenoid ratio across all VIs. In contrast, we showed that leaf area index was the dominant driver of all studied VIs, accounting for 54-74 % of their variability in the field-based analysis. Lastly, we detected that VI[s] sensitivity to atmospheric conditions and field sampling issues contribute to their low performance in validating ground truth observations. These findings show that improvements in the VIs formulation and field sampling strategies are needed to increase the reliability of vegetation stress monitoring from multispectral satellites and support a generalized use of VIs across ecosystems. Highlights: 3-5 bullet points, 85 characters[bullet] Sensitivity of water and carotenoid multispectral indices was evaluated [bullet]Analysis based on cross-biome field data and radiative transfer models [bullet]Field data showed indices had minimal sensitivity to leaf water and carotenoid [bullet]Leaf area index explained most cross-biome variation in water and carotenoid indices [bullet]We propose strategies to improve stress-related index formulation and validation

ecology↗

bioRxiv2025

Flexible Methods for Species Distribution Modeling with Small Samples

O_LISpecies distribution models (SDMs) are used for understanding where species live or could potentially live and are a key resource for ecological research and conservation decision-making. However, current SDM methods often perform poorly for rare or inadequately sampled species, which includes most species on earth as well as most of those of the greatest conservation concern. C_LIO_LIHere, we evaluate the performance of three recently developed modeling approaches specifically designed for data-deficient situations: 1) plug-and-play modeling, 2) density-ratio modeling, and 3) environmental-range modeling. We compare the performance of these methods with Maxent, a widely used method. We compare model performance across sample sizes as well as comparisons limited to only data-poor species. We also ask to what extent model cross-validation performance on training data was correlated with model performance on independent, presence-absence data. C_LIO_LIWe show that, across all species, one or more of the plug-and-play, density-ratio, or environmental-range algorithms outperformed Maxent in 72% of cases, with three of the algorithms having AUC distributions not significantly different from Maxents. For data-poor species (those with 20 or fewer occurrences), 24 of the algorithms considered had AUC distributions that were not significantly different from Maxent. However, despite these comparable AUC scores, we found that the algorithm outputs (when thresholded to predict presence vs absence) spanned a wide gradient of sensitivity vs. specificity. Specificity and prediction accuracy assessed on training data were strongly correlated with specificity and prediction accuracy assessed on independent presence-absence data, however AUC and sensitivity had weak correlations. We found that only for 16% of species was the model that performed best on the training data the best performing model when evaluated on independent, presence-absence data. Finally, we show how ensembles of models that span the sensitivity-specificity gradient can represent model disagreement in poorly sampled species and improve model predictions. C_LIO_LIThis work supports plug-and-play, density-ratio, and environmental-range modeling as useful alternatives to Maxent, particularly for data-deficient species. While our work suggests that identifying the best model for a given species is challenging, we argue that incorporating the predictions of multiple models provides a useful way forward. C_LI Data/Code for peer reviewAnonymized data and code underlying this work are publicly available at: https://anonymous.4open.science/r/Flexible_Methods_for_Small_Sample_Size_Distribution_Modeling

ecology↗

bioRxiv2022

Socioeconomics and biogeography jointly drive geographic biases in our knowledge of plant traits: a global assessment of the Raunkiaerian shortfall in plants

The traits of plants determine how they interact with each other and their environment, constituting key knowledge for diverse fields. The lack of comprehensive knowledge of plant traits (the "Raunkiaerian shortfall") poses a major, cross-disciplinary, barrier to scientific advancement. Spatial biases in trait coverage may also lead to erroneous conclusions affecting ecosystem management and conservation planning. Thus, there is an urgent need to assess the spatial completeness of plant trait data, understand drivers of geographic biases, and to identify solutions for filling regional gaps. Here, we leverage a comprehensive set of regional species checklists for vascular plants and trait data for 2,027 traits and 128,929 plant species from the TRY database to assess trait data completeness across the globe. We show that trait data availability in TRY is associated with socioeconomic and biological factors influencing sampling likelihood: trait completeness was positively associated with mean species range size, research expenditure, and human population density and negatively associated with endemism and vascular plant species richness. Integration of a second, regional trait database (AusTraits) more than doubled trait completeness for the continent covered, indicating that the creation and integration of regional databases can rapidly expand trait completeness. Plain Language SummaryThe traits of plants determine how they interact with each other and their environment. Our knowledge of plant traits is incomplete, limiting scientific advancement as well as our ability to manage ecosystems and plan conservation actions. We show that there are large biases in trait data availability which are associated with both biological factors (range size, endemism, species richness) and socioeconomic factors (research expenditure, human population density). We also show how regionally-focused efforts can help rapidly expand trait data availability.

ecology↗

bioRxiv2022

Geographic Name Resolution Service: A tool for the standardization and indexing of world political division names, with applications to species distribution modeling

Massive biological databases of species occurrences, or georeferenced locations where a species has been observed, are essential inputs for modeling present and future species distributions. Location accuracy is often assessed by determining whether the observation geocoordinates fall within the boundaries of the declared political divisions. This otherwise simple validation is complicated by the difficulty of matching political division names to the correct geospatial object. Spelling errors, abbreviations, alternative codes, and synonyms in multiple languages present daunting name disambiguation challenges. The inability to resolve political division names reduces usable data and analysis of erroneous observations can lead to flawed results. Here, we present the Geographic Name Resolution Service (GNRS), an application for the correction, standardization and indexing of world political division names. The GNRS resolves political division names against a reference database that combines names and codes from GeoNames with geospatial object identifiers from the Global Administrative Areas Database (GADM). In a trial resolution of political division names extracted from >270 million species occurrences, only 1.9%, representing just 6% of occurrences, matched exactly to GADM political divisions in their original form. The GNRS was able to resolve, completely or in part, 92% of the remaining 378,568 political division names, or 86% of the full biodiversity occurrence dataset. In an assessment of geocoordinate accuracy for >239 million species occurrences, resolution of political divisions by the GNRS enabled detection of an order of magnitude more errors and an order of magnitude more error-free occurrences. By providing a novel solution to a major data quality impediment, the GNRS liberates a tremendous amount of biodiversity data for quantitative biodiversity research. The GNRS runs as a web service and can be accessed via an API, an R package, and a web-based graphical user interface. Its modular architecture is easily integrated into existing data validation workflows.

bioinformatics↗

bioRxiv2021

Source range phylogenetic community structure can predict the outcome of avian introductions

Competing phylogenetic models have been proposed to explain the success of species introduced to other communities. Here, we present a study predicting the establishment success of birds introduced to Florida, Hawaii, and New Zealand using several alternative models, considering species phylogenetic relatedness to source and recipient range taxa, propagule pressure, and traits. We find consistent support for the predictive ability of source region phylogenetic structure. However, we find that the effects of recipient region phylogenetic structure vary in sign and magnitude depending on inclusion of source region phylogenetic structure, delineation of the recipient species pool, and the use of phylogenetic correction in the models. We argue that tests of alternative phylogenetic hypotheses including the both source and recipient community phylogenetic structure, as well as important covariates such as propagule pressure, are likely to be critical for identifying general phylogenetic patterns in introduction success, predicting future invasions, and for stimulating further exploration of the underlying mechanisms of invasibility.

ecology↗

bioRxiv2020

Quaternary climate change explains global patterns of tree beta-diversity

Both historical and contemporary environmental conditions determine present biodiversity patterns, but their relative importance is not well understood. One way to disentangle their relative effects is to assess how different dimensions of beta-diversity relate to past climatic changes, i.e., taxonomic, phylogenetic and functional compositional dissimilarity, and their components generated by replacement of species, lineages and traits (turnover) and richness changes (nestedness). Here, we quantify global patterns of each of these aspects of beta-diversity among neighboring sites for angiosperm trees using the most extensive global database of tree species-distributions (43,635 species). We found that temperature change since the Last Glacial Maximum (LGM) was the major influence on both turnover and nestedness components of beta-diversity, with a negative correlation to turnover and a positive correlation to nestedness. Moreover, phylogenetic and functional nestedness was higher than expected from taxonomic beta-diversity in regions that experienced large temperature changes since the LGM. This pattern reflects relatively greater losses of phylogenetic and functional diversity in species-poor assemblages, possibly caused by phylogenetically and functionally selective species extinction and recolonization during glacial-interglacial oscillations. Our results send a strong warning that rapid anthropogenic climate change is likely to result in a long-lasting phylogenetic and functional compositional simplification, potentially impairing forest ecosystem functioning.

ecology↗

bioRxiv2020

Paleoclimate and current climate collectively shape the phylogenetic and functional diversity of trees worldwide

Trees are of vital importance for ecosystem functioning and services at local to global scales, yet we still lack a detailed overview of the global patterns of tree diversity and the underlying drivers, particularly the imprint of paleoclimate. Here, we present the high-resolution (110 km) worldwide mapping of tree species richness, functional and phylogenetic diversities based on [~]7 million quality-assessed occurrences for 46,752 tree species (80.5% of the estimated total number of tree species), and subsequent assessments of the influence of paleo-climate legacies on these patterns. All three tree diversity dimensions exhibited the expected latitudinal decline. Contemporary climate emerged as the strongest driver of all diversity patterns, with Pleistocene and deeper-time (>107 years) paleoclimate as important co-determinants, and, notably, with past cold and drought stress being linked to reduced current diversity. These findings demonstrate that tree diversity is affected by paleoclimate millions of years back in time and highlight the potential for tree diversity losses from future climate change.

ecology↗

bioRxiv2020

Half of the world's tree biodiversity is unprotected and is increasingly threatened by human activities

Although trees are key to ecosystem functioning, many forests and tree species across the globe face strong threats. Preserving areas of high biodiversity is a core priority for conservation; however, different dimensions of biodiversity and varied conservation targets make it difficult to respond effectively to this challenge. Here, we (i) identify priority areas for global tree conservation using comprehensive coverage of tree diversity based on taxonomy, phylogeny, and functional traits; and (ii) compare these findings to existing protected areas and global biodiversity conservation frameworks. We find that ca. 51% of the top-priority areas for tree biodiversity are located in current protected areas. The remaining half top-priority areas are subject to moderate to high human pressures, indicating conservation actions are needed to mitigate these human impacts. Our findings emphasize the effectiveness of using tree conservation priority areas for future global conservation planning.

ecology↗