scholarly journals Using large spatial scale camera trap data and hierarchical occupancy models to evaluate species richness and occupancy of rare and elusive wildlife communities in southwest China

2018 ◽  
Vol 24 (11) ◽  
pp. 1560-1572 ◽  
Author(s):  
Xueyou Li ◽  
William V. Bleisch ◽  
Xuelong Jiang
Keyword(s):  
Species Richness ◽  
Spatial Scale ◽  
Southwest China ◽  
Camera Trap ◽  
Occupancy Models ◽  
Large Spatial Scale

Functional evenness of bird communities varies along the elevational gradient in Europe: Conservation implications

2019 ◽  
Author(s):  
Federico Morelli ◽  
Yanina
Keyword(s):  
Species Richness ◽  
Elevation Gradient ◽  
Bird Species ◽  
Elevational Gradient ◽  
Negative Association ◽  
Bird Communities ◽  
Breeding Bird ◽  
Bird Species Richness ◽  
Large Spatial Scale ◽  
Functional Evenness

ContextThe negative association between elevation and species richness is a well-recognized pattern in macro-ecology. ObjectivesThe aim of this study was to investigate changes in functional evenness of breeding bird communities along an elevation gradient in Europe. MethodsUsing the bird data from the EBCC Atlas of European Breeding Birds we estimated an index of functional evenness which can be assumed as a measure of the potential resilience of communities.ResultsOur findings confirm the existence of a negative association between elevation and bird species richness in all European eco regions. However, we also explored a novel aspect of this relationship, important for conservation: Our findings provide evidence at large spatial scale of a negative association between the functional evenness (potential community resilience) and elevation, independent of the eco region. We also found that the Natura2000 protected areas covers the territory most in need of protection, those characterized by bird communities with low potential resilience, in hilly and mountainous areas.ConclusionsThese results draw attention to European areas occupied by bird communities characterized by a potential lower capacity to respond to strong ecological changes, and, therefore, potentially more exposed to risks for conservation.

Large-scale patterns in species richness and composition of temperate riverine fish communities, south-eastern Australia

2000 ◽  
Vol 51 (2) ◽  
pp. 165 ◽  
Author(s):  
Peter C. Gehrke ◽  
John H. Harris
Keyword(s):  
Species Richness ◽  
Large Scale ◽  
Fish Communities ◽  
Fish Fauna ◽  
South Coast ◽  
North Coast ◽  
Large Spatial Scale ◽  
River Types ◽  
Eastern Australia ◽  
Riverine Fish

Riverine fish in New South Wales were studied to examine longitudinal trends in species richness and to identify fish communities on a large spatial scale. Five replicate rivers of four types (montane, slopes, regulated lowland and unregulated lowland) were selected from North Coast, South Coast, Murray and Darling regions. Fishwere sampled during summer and winter in two consecutive years with standardized gear that maximized the range of species caught. The composition of fish communities varied among regions and river types, with little temporal variation. Distinct regional communities converged in montane reaches and diverged downstream. The fish fauna can be classified into North Coast, South Coast, Murray and Darling communities, with a distinct montane community at high elevations irrespective of the drainage division. Species richness increased downstream in both North Coast and South Coast regions by both replacement and the addition of new species. In contrast, species richness in the Darling and Murray regions reached a maximum in the slopes reaches and then declined, reflecting a loss of species in lowland reaches. The small number of species is typical of the freshwater fish faunas of similar climatic regions world-wide. Fish communities identified in this study form logical entities for fisheries management consistent with the ecosystem-focused, catchment-based approach to river management and water reform being adopted in Australia.

scholarly journals Roles of Spatial Scale and Rarity on the Relationship between Butterfly Species Richness and Human Density in South Africa

PLoS ONE ◽  
2015 ◽  
Vol 10 (4) ◽  
pp. e0124327 ◽  
Author(s):  
Silvia Mecenero ◽  
Res Altwegg ◽  
Jonathan F. Colville ◽  
Colin M. Beale
Keyword(s):  
South Africa ◽  
Species Richness ◽  
Spatial Scale ◽  
Butterfly Species ◽  
The Relationship ◽  
Human Density

scholarly journals A sparse observation model to quantify species interactions in time and space

2019 ◽  
Author(s):  
Sadoune Ait Kaci Azzou ◽  
Liam Singer ◽  
Thierry Aebischer ◽  
Madleina Caduff ◽  
Beat Wolf ◽  
...  
Keyword(s):  
Species Interactions ◽  
Activity Patterns ◽  
Niche Partitioning ◽  
Camera Trap ◽  
Camera Traps ◽  
Observation Model ◽  
Occupancy Models ◽  
Time And Space ◽  
Imperfect Detection ◽  
Mobile Species

SummaryCamera traps and acoustic recording devices are essential tools to quantify the distribution, abundance and behavior of mobile species. Varying detection probabilities among device locations must be accounted for when analyzing such data, which is generally done using occupancy models. We introduce a Bayesian Time-dependent Observation Model for Camera Trap data (Tomcat), suited to estimate relative event densities in space and time. Tomcat allows to learn about the environmental requirements and daily activity patterns of species while accounting for imperfect detection. It further implements a sparse model that deals well will a large number of potentially highly correlated environmental variables. By integrating both spatial and temporal information, we extend the notation of overlap coefficient between species to time and space to study niche partitioning. We illustrate the power of Tomcat through an application to camera trap data of eight sympatrically occurring duiker Cephalophinae species in the savanna - rainforest ecotone in the Central African Republic and show that most species pairs show little overlap. Exceptions are those for which one species is very rare, likely as a result of direct competition.

Relation between species richness and stream slope in riffle fish assemblages is dependent on spatial scale

2016 ◽  
Vol 99 (8-9) ◽  
pp. 603-612 ◽  
Author(s):  
Mateus Camana ◽  
Renato Bolson Dala-Corte ◽  
Fernando Gertum Becker
Keyword(s):  
Species Richness ◽  
Spatial Scale ◽  
Fish Assemblages

scholarly journals Space Is More Important than Season when Shaping Soil Microbial Communities at a Large Spatial Scale

mSystems ◽  
2020 ◽  
Vol 5 (3) ◽  
Author(s):  
Kaoping Zhang ◽  
Manuel Delgado-Baquerizo ◽  
Yong-Guan Zhu ◽  
Haiyan Chu
Keyword(s):  
Seasonal Variation ◽  
Microbial Community ◽  
Spatial Scale ◽  
Environmental Variables ◽  
Soil Microbial Communities ◽  
Spatiotemporal Variation ◽  
Relative Importance ◽  
Large Spatial Scale ◽  
Environmental Covariates ◽  
Soil Microbial

ABSTRACT The relative importance of spatial and temporal variability in shaping the distribution of soil microbial communities at a large spatial scale remains poorly understood. Here, we explored the relative importance of space versus time when predicting the distribution of soil bacterial and fungal communities across North China Plain in two contrasting seasons (summer versus winter). Although we found that microbial alpha (number of phylotypes) and beta (changes in community composition) diversities differed significantly between summer and winter, space rather than season explained more of the spatiotemporal variation of soil microbial alpha and beta diversities. Environmental covariates explained some of microbial spatiotemporal variation observed, with fast-changing environmental covariates—climate variables, soil moisture, and available nutrient—likely being the main factors that drove the seasonal variation found in bacterial and fungal beta diversities. Using random forest modeling, we further identified a group of microbial exact sequence variants (ESVs) as indicators of summer and winter seasons and for which relative abundance was associated with fast-changing environmental variables (e.g., soil moisture and dissolved organic nitrogen). Together, our empirical field study’s results suggest soil microbial seasonal variation could arise from the changes of fast-changing environmental variables, thus providing integral support to the large emerging body of snapshot studies related to microbial biogeography. IMPORTANCE Both space and time are key factors that regulate microbial community, but microbial temporal variation is often ignored at a large spatial scale. In this study, we compared spatial and seasonal effects on bacterial and fungal diversity variation across an 878-km transect and found direct evidence that space is far more important than season in regulating the soil microbial community. Partitioning the effect of season, space and environmental variables on microbial community, we further found that fast-changing environmental factors contributed to microbial temporal variation.

Predicting fish species richness and habitat relationships using Bayesian hierarchical multispecies occupancy models

2020 ◽  
Vol 77 (3) ◽  
pp. 602-610
Author(s):  
Shannon White ◽  
Evan Faulk ◽  
Caleb Tzilkowski ◽  
Andrew Weber ◽  
Matthew Marshall ◽  
...  
Keyword(s):  
Species Richness ◽  
Fish Community ◽  
Fish Assemblages ◽  
Similar Species ◽  
Occupancy Models ◽  
Imperfect Detection ◽  
Modeling Framework ◽  
Bayesian Hierarchical ◽  
Recreation Area ◽  
Species Occupancy

Understanding how stream fishes respond to changes in habitat availability is complicated by low occurrence rates of many species, which in turn reduces the ability to quantify species–habitat relationships and account for imperfect detection in estimates of species richness. Multispecies occupancy models have been used sparingly in the analysis of fisheries data, but address the aforementioned deficiencies by allowing information to be shared among ecologically similar species, thereby enabling species–habitat relationships to be estimated for entire fish communities, including rare species. Here, we highlight the utility of hierarchical multispecies occupancy models for the analysis of fish community data and demonstrate the modeling framework on a stream fish community dataset collected in the Delaware Water Gap National Recreation Area, USA. In particular, we demonstrate the ability of the modeling framework to make inferences at the species-, guild-, and community-levels, thereby making it a powerful tool for understanding and predicting how environmental variables influence species occupancy probabilities and structure fish assemblages.

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