scholarly journals Flock Size Predicts Niche Breadth and Focal Wintering Regions for a Rapidly Declining Boreal-Breeding Passerine, the Rusty Blackbird

Diversity ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 62
Author(s):  
Brian S. Evans ◽  
Luke L. Powell ◽  
Dean W. Demarest ◽  
Sinéad M. Borchert ◽  
Russell S. Greenberg
Keyword(s):  
Niche Breadth ◽  
Primary Objective ◽  
Atlantic Coastal Plain ◽  
Flock Size ◽  
Environmental Niche ◽  
Environmental Predictors ◽  
Environmental Space ◽  
Euphagus Carolinus ◽  
Rusty Blackbird ◽  
Average Minimum Temperature

Once exceptionally abundant, the Rusty Blackbird (Euphagus carolinus) has declined precipitously over at least the last century. The species breeds across the Boreal forest, where it is so thinly distributed across such remote areas that it is extremely challenging to monitor or research, hindering informed conservation. As such, we employed a targeted citizen science effort on the species’ wintering grounds in the more (human) populated southeast United States: the Rusty Blackbird Winter Blitz. Using a MaxEnt machine learning framework, we modeled patterns of occurrence of small, medium, and large flocks (<20, 20–99, and >99 individuals, respectively) in environmental space using both Blitz and eBird data. Our primary objective was to determine environmental variables that best predict Rusty Blackbird occurrence, with emphasis on (1) examining differences in key environmental predictors across flock sizes, (2) testing whether environmental niche breadth decreased with flock size, and (3) identifying regions with higher predicted occurrence (hotspots). The distribution of flocks varied across environmental predictors, with average minimum temperature (~2 °C for medium and large flocks) and proportional coverage of floodplain forest having the largest influence on occurrence. Environmental niche breadth decreased with increasing flock size, suggesting an increasingly restrictive range of environmental conditions capable of supporting larger flocks. We identified large hotspots in floodplain forests in the Lower Mississippi Alluvial Valley, the South Atlantic Coastal Plain, and the Black Belt Prairie.

scholarly journals CLIMATIC NICHE DETERMINES THE GEOGRAPHIC DISTRIBUTION OF MYRTACEAE SPECIES IN BRAZILIAN SUBTROPICAL ATLANTIC FOREST

2021 ◽  
Vol 45 ◽  
Author(s):  
Jéssica Thalheimer de Aguiar ◽  
Pedro Higuchi ◽  
Ana Carolina da Silva
Keyword(s):  
Atlantic Forest ◽  
Geographic Distribution ◽  
Rain Forest ◽  
Deciduous Forest ◽  
Statistical Tests ◽  
Environmental Niche ◽  
Climatic Niche ◽  
Araucaria Forest ◽  
Explanatory Variables ◽  
Environmental Space

ABSTRACT The understanding of factors determining species geographic distribution is a fundamental aim of ecology. We investigated the environmental niche for three Myrtaceae species in the Brazilian Subtropical Atlantic Forest (BSAF), part of a global conservation hotspot. Based on a literature review, we selected one representative Myrtaceae species in three important forest types in this region: Evergreen Rain Forest (coastal plains and associated mountains ranges); Araucaria Forest, and Seasonal Deciduous Forest (continental upland areas). Geographical coordinates of their distribution were obtained from the BIEN database. As explanatory variables, we considered altitude, climate, cloud cover, and soil classes. We summarized the environmental space occupied by each pair of species using Principal Components Analysis, determined niche overlaps, and applied statistical tests to verify niche equivalences and similarities. The selected species in Evergreen Rain Forest, Araucaria Forest, and Seasonal Deciduous Forest were Myrcia splendens (Sw.) DC., Myrcia guianensis (Aubl.) DC., and Campomanesia xanthocarpa O.Berg., respectively. C. xanthocarpa showed a more restricted geographic distribution than the two Myrcia species that occur from central America to southern Brazil. Species’ geographic distribution were fundamentally determined by temperature and rainfall regimes. Only C. xanthocarpa and M. guianensis, from uplands forest formations, showed environmental niche equivalence. In conclusion, we found that both species of Myrcia showed high climatic niche amplitudes occurring throughout the climatic gradient, while C. xanthocarpa was more subtropical, distributed mostly in the south and southeast of Brazil.

The environmental niche of soil bacterial, archaeal, fungal and protist communities differ along edaphic and topoclimatic gradients in the Alps

2021 ◽  
Author(s):  
Lucie A Malard ◽  
Heidi K Mod ◽  
Nicolas Guex ◽  
Olivier Broennimann ◽  
Erika Yashiro ◽  
...  
Keyword(s):  
Niche Breadth ◽  
Environmental Changes ◽  
Environmental Gradients ◽  
Community Diversity ◽  
Environmental Niche ◽  
Alpha And Beta Diversity ◽  
Niche Concept ◽  
The Alps ◽  
Microbial Groups ◽  
Taxonomic Groups

Abstract BackgroundThe niche concept describes the range of conditions supporting the establishment and persistence of species in the environment. Although widely used in ecology, it has not been often applied to microbes, for which comparative niche analyses are still lacking. Yet, quantifying the niche of microbial taxa is necessary to forecast how taxa and the communities they compose might respond to environmental changes. In this study, we identified important topoclimatic, edaphic, spatial and biotic drivers of the alpha and beta diversity of bacterial, archaeal, fungal and protist communities. Then, we established a method to calculate the niche breadth and position of each taxon along environmental gradients to determine whether microorganisms have distinct environmental niches. ResultsFor all microbial groups, edaphic properties were identified as the most important drivers of both community diversity and composition. Protists presented the largest niche breadths, followed by bacteria and archaea, with fungi displaying the smallest. Niche breadth generally decreased towards environmental extremes, especially along edaphic gradients, suggesting increased specialisation of all microbial taxa in highly selective environments. ConclusionIn this study, we showed that microorganisms have well defined niches, as do macro-organisms, and that these likely drive part of the observed spatial patterns of community variations, but with notable differences among taxonomic groups. Applying the niche concept more widely to microbial ecology should open many novel perspectives, especially to tackle global change challenges.

scholarly journals The Rusty Blackbird (Euphagus carolinus) in Connecticut in Winter

The Auk ◽  
1914 ◽  
Vol 31 (2) ◽  
pp. 250-250
Author(s):  
Aretas A. Saunders
Keyword(s):  
Euphagus Carolinus ◽  
Rusty Blackbird

scholarly journals Trophic specialization influences the rate of environmental niche evolution in damselfishes (Pomacentridae)

2012 ◽  
Vol 279 (1743) ◽  
pp. 3662-3669 ◽  
Author(s):  
Glenn Litsios ◽  
Loïc Pellissier ◽  
Félix Forest ◽  
Christian Lexer ◽  
Peter B. Pearman ◽  
...  
Keyword(s):  
Phylogenetic Signal ◽  
Reef Fishes ◽  
Standard Test ◽  
Environmental Niche ◽  
Niche Evolution ◽  
Trophic Specialization ◽  
Mean Values ◽  
Environmental Space ◽  
Behavioural Characteristics ◽  
Adaptive Radiations

The rate of environmental niche evolution describes the capability of species to explore the available environmental space and is known to vary among species owing to lineage-specific factors. Trophic specialization is a main force driving species evolution and is responsible for classical examples of adaptive radiations in fishes. We investigate the effect of trophic specialization on the rate of environmental niche evolution in the damselfish, Pomacentridae, which is an important family of tropical reef fishes. First, phylogenetic niche conservatism is not detected in the family using a standard test of phylogenetic signal, and we demonstrate that the environmental niches of damselfishes that differ in trophic specialization are not equivalent while they still overlap at their mean values. Second, we estimate the relative rates of niche evolution on the phylogenetic tree and show the heterogeneity among rates of environmental niche evolution of the three trophic groups. We suggest that behavioural characteristics related to trophic specialization can constrain the evolution of the environmental niche and lead to conserved niches in specialist lineages. Our results show the extent of influence of several traits on the evolution of the environmental niche and shed new light on the evolution of damselfishes, which is a key lineage in current efforts to conserve biodiversity in coral reefs.

scholarly journals Distribution modelling of an introduced species: do adaptive genetic markers affect potential range?

2020 ◽  
Vol 287 (1935) ◽  
pp. 20201791
Author(s):  
Neftalí Sillero ◽  
Raymond B. Huey ◽  
George Gilchrist ◽  
Leslie Rissler ◽  
Marta Pascual
Keyword(s):  
Introduced Species ◽  
Genetic Markers ◽  
Genetic Bottleneck ◽  
Economic Losses ◽  
Potential Range ◽  
Environmental Niche ◽  
Niche Modelling ◽  
Environmental Space ◽  
Key Factor ◽  
Suitable Habitats

Biological invasions have increased in the last few decades mostly due to anthropogenic causes such as globalization of trade. Because invaders sometimes cause large economic losses and ecological disturbances, estimating their origin and potential geographical ranges is useful. Drosophila subobscura is native to the Old World but was introduced in the New World in the late 1970s and spread widely. We incorporate information on adaptive genetic markers into ecological niche modelling and then estimate the most probable geographical source of colonizers; evaluate whether the genetic bottleneck experienced by founders affects their potential distribution; and finally test whether this species has spread to all its potential suitable habitats worldwide. We find the environmental space occupied by this species in its native and introduced distributions are notably the same, although the introduced niche has shifted slightly towards higher temperature and lower precipitation. The genetic bottleneck of founding individuals was a key factor limiting the spread of this introduced species. We also find that regions in the Mediterranean and north-central Portugal show the highest probability of being the origin of the colonizers. Using genetically informed environmental niche modelling can enhance our understanding of the initial colonization and spread of invasive species, and also elucidate potential areas of future expansions worldwide.

scholarly journals Finite Mixture Model-based classification of a complex vegetation system

2020 ◽  
Vol 1 ◽  
pp. 77-86
Author(s):  
Fabio Attorre ◽  
Vito E. Cambria ◽  
Emiliano Agrillo ◽  
Nicola Alessi ◽  
Marco Alfò ◽  
...  
Keyword(s):  
Species Composition ◽  
Multidimensional Scaling ◽  
Mixture Model ◽  
Finite Mixture Model ◽  
Forest Vegetation ◽  
Finite Mixture ◽  
Environmental Niche ◽  
Environmental Predictors ◽  
Metric Multidimensional Scaling

Aim: To propose a Finite Mixture Model (FMM) as an additional approach for classifying large datasets of georeferenced vegetation plots from complex vegetation systems. Study area: The Italian peninsula including the two main islands (Sicily and Sardinia), but excluding the Alps and the Po plain. Methods: We used a database of 5,593 georeferenced plots and 1,586 vascular species of forest vegetation, created in TURBOVEG by storing published and unpublished phytosociological plots collected over the last 30 years. The plots were classified according to species composition and environmental variables using a FMM. Classification results were compared with those obtained by TWINSPAN algorithm. Groups were characterized in terms of ecological parameters, dominant and diagnostic species using the fidelity coefficient. Interpretation of resulting forest vegetation types was supported by a predictive map, produced using discriminant functions on environmental predictors, and by a non‐metric multidimensional scaling ordination. Results: FMM clustering obtained 24 groups that were compared with those from TWINSPAN, and similarities were found only at a higher classification level corresponding to the main orders of the Italian broadleaf forest vegetation: Fagetalia sylvaticae, Carpinetalia betuli, Quercetalia pubescenti-petraeae and Quercetalia ilicis. At lower syntaxonomic level, these 24 groups were referred to alliances and sub-alliances. Conclusions: Despite a greater computational complexity, FMM appears to be an effective alternative to the traditional classification methods through the incorporation of modelling in the classificatory process. This allows classification of both the co-occurrence of species and environmental factors so that groups are identified not only on their species composition, as in the case of TWINSPAN, but also on their specific environmental niche. Taxonomic reference: Conti et al. (2005). Abbreviations: CLM = Community-level models; FMM = Finite Mixture Model; NMDS = non‐metric multidimensional scaling.

scholarly journals Toward a Monte Carlo approach to selecting climate variables in MaxEnt: A case study using Cassin’s Sparrow (Peucaea cassinii)

2020 ◽  
Author(s):  
John L. Schnase ◽  
Mark L. Carroll ◽  
Roger L. Gill ◽  
Glenn S. Tamkin ◽  
Jian Li ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Main Memory ◽  
Climate Variables ◽  
Environmental Niche ◽  
Environmental Predictors ◽  
Monte Carlo Approach ◽  
Global Estimate

AbstractMaxEnt is an important aid in understanding the influence of climate change on species distributions and abundance. There is growing interest in using IPCC-class global climate model outputs as environmental predictors in this work. These models provide realistic, global representations of the climate system, projections for hundreds of variables (including Essential Climate Variables), and combine observations from an array of satellite, airborne, and in-situ sensors. Unfortunately, direct use of this important class of data in MaxEnt modeling has been limited by the large size of climate model output collections and the fact that MaxEnt can only operate on a relatively small set of predictors stored in a computer’s main memory. In this study, we demonstrate the feasibility of a Monte Carlo method that overcomes this limitation by finding a useful subset of predictors in a larger, externally-stored collection of environmental variables in a reasonable amount of time. Our proposed solution takes an ensemble approach wherein many MaxEnt runs, each drawing on a small random subset of variables, converges on a global estimate of the top contributing subset of variables in the larger collection. In preliminary tests, the Monte Carlo approach selected a consistent set of top six variables within 540 runs, with the four most contributory variables of the top six accounting for approximately 93% of overall permutation importance in the final model. These results suggest that a Monte Carlo approach could offer a viable means of selecting environmental predictors for MaxEnt models that is amenable to parallelization and scalable to very large data sets. This point to the possibility of near-real-time multiprocessor implementations that could enable broader and more exploratory use of global climate model outputs in environmental niche modeling and aid in the discovery of viable predictors.

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