Patterns of Rotifer Diversity in the Chihuahuan Desert

Desert aquatic systems are widely separated, lack hydrologic connections, and are subject to drought. However, they provide unique settings to investigate distributional patterns of micrometazoans, including rotifers. Thus, to understand rotifer biodiversity we sampled 236 sites across an array of habitats including rock pools, springs, tanks, flowing waters, playas, lakes, and reservoirs in the Chihuahuan Desert of the USA (n = 202) and Mexico (n = 34) over a period of >20 years. This allowed us to calculate diversity indices and examine geographic patterns in rotifer community composition. Of ~1850 recognized rotifer species, we recorded 246 taxa (~13%), with greatest diversity in springs (n = 175), lakes (n = 112), and rock pools (n = 72). Sampling effort was positively related to observed richness in springs, lakes, rivers, and tanks. Nestedness analyses indicated that rotifers in these sites, and most subsets thereof, were highly nested (support from 4 null models). Distance was positively correlated with species composition dissimilarity on small spatial scales. We predicted species richness for unsampled locations using empirical Bayesian kriging. These findings provide a better understanding of regional rotifer diversity in aridlands and provide information on potential biodiversity hotspots for aquatic scientists and resource managers.

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Responses of Vertebrate Wildlife to Oil and Natural Gas Development: Patterns and Frontiers

Current Landscape Ecology Reports ◽

10.1007/s40823-021-00065-0 ◽

2021 ◽

Author(s):

A. D. Chalfoun

Keyword(s):

Natural Gas ◽

Anthropogenic Activities ◽

Spatial Scales ◽

Habitat Type ◽

Population Level ◽

Low Frequencies ◽

Natural Gas Development ◽

The Usa ◽

Oil And Natural Gas

Abstract Purpose of Review Anthropogenic activities can lead to the loss, fragmentation, and alteration of wildlife habitats. I reviewed the recent literature (2014–2019) focused on the responses of avian, mammalian, and herpetofaunal species to oil and natural gas development, a widespread and still-expanding land use worldwide. My primary goals were to identify any generalities in species’ responses to development and summarize remaining gaps in knowledge. To do so, I evaluated the directionality of a wide variety of responses in relation to taxon, location, development type, development metric, habitat type, and spatiotemporal aspects. Recent Findings Studies (n = 70) were restricted to the USA and Canada, and taxonomically biased towards birds and mammals. Longer studies, but not those incorporating multiple spatial scales, were more likely to detect significant responses. Negative responses of all types were present in relatively low frequencies across all taxa, locations, development types, and development metrics but were context-dependent. The directionality of responses by the same species often varied across studies or development metrics. Summary The state of knowledge about wildlife responses to oil and natural gas development has developed considerably, though many biases and gaps remain. Studies outside of North America and that focus on herpetofauna are lacking. Tests of mechanistic hypotheses for effects, long-term studies, assessment of response thresholds, and experimental designs that isolate the effects of different stimuli associated with development, remain critical. Moreover, tests of the efficacy of habitat mitigation efforts have been rare. Finally, investigations of the demographic effects of development across the full annual cycle were absent for non-game species and are critical for the estimation of population-level effects.

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Archaeal ammonia oxidizers respond to soil factors at smaller spatial scales than the overall archaeal community does in a high Arctic polar oasis

Canadian Journal of Microbiology ◽

10.1139/cjm-2015-0669 ◽

2016 ◽

Vol 62 (6) ◽

pp. 485-491 ◽

Cited By ~ 3

Author(s):

Samiran Banerjee ◽

Nabla Kennedy ◽

Alan E. Richardson ◽

Keith N. Egger ◽

Steven D. Siciliano

Keyword(s):

Community Structure ◽

Spatial Scales ◽

Archaeal Community ◽

Diversity Indices ◽

High Arctic ◽

Total Carbon ◽

Spatial Dependency ◽

Edaphic Factors ◽

Total Carbon Content ◽

Arctic Soils

Archaea are ubiquitous and highly abundant in Arctic soils. Because of their oligotrophic nature, archaea play an important role in biogeochemical processes in nutrient-limited Arctic soils. With the existing knowledge of high archaeal abundance and functional potential in Arctic soils, this study employed terminal restriction fragment length polymorphism (t-RFLP) profiling and geostatistical analysis to explore spatial dependency and edaphic determinants of the overall archaeal (ARC) and ammonia-oxidizing archaeal (AOA) communities in a high Arctic polar oasis soil. ARC communities were spatially dependent at the 2–5 m scale (P < 0.05), whereas AOA communities were dependent at the ∼1 m scale (P < 0.0001). Soil moisture, pH, and total carbon content were key edaphic factors driving both the ARC and AOA community structure. However, AOA evenness had simultaneous correlations with dissolved organic nitrogen and mineral nitrogen, indicating a possible niche differentiation for AOA in which dry mineral and wet organic soil microsites support different AOA genotypes. Richness, evenness, and diversity indices of both ARC and AOA communities showed high spatial dependency along the landscape and resembled scaling of edaphic factors. The spatial link between archaeal community structure and soil resources found in this study has implications for predictive understanding of archaea-driven processes in polar oases.

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Synchrony of frond dynamics among patches of the clonal seaweed Mazzaella parksii (Rhodophyta) at local spatial scale

Journal of the Marine Biological Association of the United Kingdom ◽

10.1017/s0025315404010148h ◽

2004 ◽

Vol 84 (5) ◽

pp. 883-886 ◽

Cited By ~ 1

Author(s):

Ricardo Scrosati

Keyword(s):

Spatial Scale ◽

Seasonal Changes ◽

Pacific Coast ◽

Spatial Scales ◽

Sampling Effort ◽

Confidence Limits ◽

Seasonal Trends ◽

Intertidal Seaweed ◽

The Mean

This study investigated the synchrony of frond dynamics among patches of the intertidal seaweed Mazzaella parksii (=M. cornucopiae; Rhodophyta: Gigartinales) at local spatial scale. At Prasiola Point (Pacific coast of Canada), the mean synchrony of the seasonal changes in frond density among seven permanent, 100-cm2 quadrats was significant (mean Pearson's r=0·73, with 0·65–0·81 as 95% confidence limits) between 1993 and 1995. This indicates that predicting seasonal trends for non-monitored patches at local spatial scale can be done relatively well based on observations on a limited number of quadrats. The identification of the spatial scales at which seaweed populations covary synchronously will permit minimizing sampling effort while retaining the ability to make valid predictions for non-monitored sites.

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Growth rings across the Tree of Life: demographic insights from biogenic time series data

10.1093/oso/9780198838609.003.0004 ◽

2021 ◽

pp. 77-96

Author(s):

Margaret E. K. Evans ◽

Bryan A. Black ◽

Donald A. Falk ◽

Courtney L. Giebink ◽

Emily L. Schultz

Keyword(s):

Time Series ◽

Time Series Data ◽

Spatial Scales ◽

Ocean Dynamics ◽

Individual Growth ◽

Series Data ◽

Rate Variation ◽

Sampling Effort ◽

Growth Rings ◽

Demographic Processes

Biogenic time series data can be generated in a single sampling effort, offering an appealing alternative to the slow process of revisiting or recapturing individuals to measure demographic rates. Annual growth rings formed by trees and in the ear bones of fish (i.e. otoliths) are prime examples of such biogenic time series. They offer insight into not only the process of growth but also birth, death, movement, and evolution, sometimes at uniquely deep temporal and large spatial scales, well beyond 5–30 years of data collected in localised study areas. This chapter first reviews the fundamentals of how tree-ring and otolith time series data are developed and analysed (i.e. dendrochronology and sclerochronology), then surveys growth rings in other organisms, along with microstructural or microcompositional variation in growth rings, and other records of demographic processes. It highlights the answers to demographic questions revealed by these time series data, such as the influence of environmental (atmospheric or ocean) conditions, competition, and disturbances on demographic processes, and the genetic versus plastic basis of individual growth and traits that influence growth. Lastly, it considers how spatial networks of biogenic, annually resolved time series data can offer insights into the importance of macrosystem atmospheric and ocean dynamics on multispecies, trophic dynamics. The authors encourage demographers to integrate the complementary information contained in biogenic time series data into population models to better understand the drivers of vital rate variation and predict the impacts of global change.

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Unimodal Relationships of Understory Alpha and Beta Diversity along Chronosequence in Coppiced and Unmanaged Beech Forests

Diversity ◽

10.3390/d12030101 ◽

2020 ◽

Vol 12 (3) ◽

pp. 101 ◽

Cited By ~ 3

Author(s):

Sándor Bartha ◽

Roberto Canullo ◽

Stefano Chelli ◽

Giandiego Campetella

Keyword(s):

Beta Diversity ◽

Management Practices ◽

Multiple Scales ◽

Forest Succession ◽

Spatial Scales ◽

Alpha Diversity ◽

Structural Diversity ◽

Diversity Indices ◽

Alpha And Beta Diversity ◽

Coppice Management

Patterns of diversity across spatial scales in forest successions are being overlooked, despite their importance for developing sustainable management practices. Here, we tested the recently proposed U-shaped biodiversity model of forest succession. A chronosequence of 11 stands spanning from 5 to 400 years since the last disturbance was used. Understory species presence was recorded along 200 m long transects of 20 × 20 cm quadrates. Alpha diversity (species richness, Shannon and Simpson diversity indices) and three types of beta diversity indices were assessed at multiple scales. Beta diversity was expressed by a) spatial compositional variability (number and diversity of species combinations), b) pairwise spatial turnover (between plots Sorensen, Jaccard, and Bray–Curtis dissimilarity), and c) spatial variability coefficients (CV% of alpha diversity measures). Our results supported the U-shaped model for both alpha and beta diversity. The strongest differences appeared between active and abandoned coppices. The maximum beta diversity emerged at characteristic scales of 2 m in young coppices and 10 m in later successional stages. We conclude that traditional coppice management maintains high structural diversity and heterogeneity in the understory. The similarly high beta diversities in active coppices and old-growth forests suggest the presence of microhabitats for specialist species of high conservation value.

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The genus Rhinoglena (Rotifera, Monogononta, Ephiphanidae) in North America, with the description of two new species

Zootaxa ◽

10.11646/zootaxa.4290.1.6 ◽

2017 ◽

Vol 4290 (1) ◽

pp. 113 ◽

Cited By ~ 1

Author(s):

HENDRIK SEGERS ◽

ELIZABETH J. WALSH

Keyword(s):

New Species ◽

North America ◽

Literature Review ◽

Chihuahuan Desert ◽

Identification Key ◽

Close Relative ◽

Generic Diagnosis ◽

Aquatic Habitats ◽

Two New Species ◽

The Usa

Based on material from aquatic habitats in the northern Chihuahuan Desert and a literature review, we present an account on the occurrence of genus Rhinoglena in North America. Two new species are described, and the presence of Rhinoglena frontalis in the USA is confirmed. Of the two new species, R. texana n. sp. is a close relative of R. frontalis, whereas R. ovigera n. sp. is unique by being oviparous, in contrast to all other Rhinoglena which are viviparous. This prompts a revision of the generic diagnosis of Rhinoglena to accommodate the new species. An identification key to the known species of the genus is provided.

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A Habitat-Based Framework for Communicating Natural Resource Condition

ISRN Ecology ◽

10.5402/2012/384892 ◽

2012 ◽

Vol 2012 ◽

pp. 1-13 ◽

Cited By ~ 1

Author(s):

Tim J. B. Carruthers ◽

Shawn L. Carter ◽

Todd R. Lookingbill ◽

Lisa N. Florkowski ◽

Jane M. Hawkey ◽

...

Keyword(s):

Natural Resource ◽

Spatial Scales ◽

Good Condition ◽

Washington Dc ◽

General Audience ◽

Resource Managers ◽

Resource Condition ◽

Terrestrial Habitats ◽

Temporal And Spatial ◽

Forest Habitats

Progress in achieving desired environmental outcomes needs to be rigorously measured and reported for effective environmental management. Two major challenges in achieving this are, firstly, how to synthesize monitoring data in a meaningful way at appropriate temporal and spatial scales and, secondly, how to present results in a framework that allows for effective communication to resource managers and scientists as well as a broader general audience. This paper presents a habitat framework, developed to assess the natural resource condition of the urban Rock Creek Park (Washington, DC, USA), providing insight on how to improve future assessments. Vegetation and stream GIS layers were used to classify three dominant habitat types, Forest, Wetland, and Artificial-terrestrial. Within Rock Creek Park, Forest habitats were assessed as being in good condition (67% threshold attainment of desired condition), Wetland habitats to be in fair condition (49% attainment), and Artificial-terrestrial habitats to be in degraded condition (26% attainment), resulting in an assessed fair/good condition (60% attainment; weighted by habitat area) for all natural resources in Rock Creek Park. This approach has potential to provide assessment of resource condition for diverse ecosystems and provides a basis for addressing management questions across multiple spatial scales.

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Understanding Spatial Heterogeneity of COVID-19 Pandemic Using Shape Analysis of Growth Rate Curves

10.1101/2020.05.25.20112433 ◽

2020 ◽

Cited By ~ 1

Author(s):

Anuj Srivastava ◽

Gerardo Chowell

Keyword(s):

Public Health ◽

Growth Rate ◽

Shape Analysis ◽

Spatial Scales ◽

Transmission Dynamics ◽

Public Health Decision ◽

Health Decision Making ◽

Health Decision ◽

The Usa ◽

Level Analysis

AbstractThe growth rates of COVID-19 across different geographical regions (e.g., states in a nation, countries in a continent) follow different shapes and patterns. The overall summaries at coarser spatial scales that are obtained by simply averaging individual curves (across regions) obscure nuanced variability and blurs the spatial heterogeneity at finer spatial scales. We employ statistical methods to analyze shapes of local COVID-19 growth rate curves and statistically group them into distinct clusters, according to their shapes. Using this information, we derive the so-called elastic averages of curves within these clusters, which correspond to the dominant incidence patterns. We apply this methodology to the analysis of the daily incidence trajectory of the COVID-pandemic at two spatial scales: A state-level analysis within the USA and a country-level analysis within Europe during mid-February to mid-May, 2020. Our analyses reveal a few dominant incidence trajectories that characterize transmission dynamics across states in the USA and across countries in Europe. This approach results in broad classifications of spatial areas into different trajectories and adds to the methodological toolkit for guiding public health decision making at different spatial scales.HighlightsCoarsely summarizing epidemic data collected at finer spatial scales can result in a loss of heterogenous spatial patterns that exist at finer scales. For instance, the average curves may give the impression that the epidemic’s trajectory is declining when, in fact, the trajectory of the epidemic is increasing in certain areas.Shape analysis of COVID-19 growth rate curves discovers significant heterogeneity in epidemic spread patterns across spatial areas which can be statistically clustered into distinct groups.At a higher level, clustering spatial patterns into distinct groups helps discern broad trends, such as rapid growth, leveling off, and slow decline in epidemic growth curves resulting from local transmission dynamics. At a finer level, it helps identify temporal patterns of multiple waves that characterize rate curves for different clusters.Quantitative methods for characterizing the spatial-temporal dynamics of evolving epidemic emergencies provide an objective framework to understand transmission dynamics for public health decision making.

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An integrated model of seasonal changes in stock composition and abundance with an application to Chinook salmon

PeerJ ◽

10.7717/peerj.11163 ◽

2021 ◽

Vol 9 ◽

pp. e11163

Author(s):

Cameron Freshwater ◽

Sean C. Anderson ◽

Terry D. Beacham ◽

Wilf Luedke ◽

Catarina Wor ◽

...

Keyword(s):

Chinook Salmon ◽

Seasonal Changes ◽

Anthropogenic Impacts ◽

Spatial Scales ◽

Integrated Model ◽

Seasonal Abundance ◽

Distribution Data ◽

Sampling Effort ◽

Catch Per Unit Effort ◽

Marine Habitats

Population-specific spatial and temporal distribution data are necessary to identify mechanisms regulating abundance and to manage anthropogenic impacts. However the distributions of highly migratory species are often difficult to resolve, particularly when multiple populations’ movements overlap. Here we present an integrated model to estimate spatially-stratified, seasonal trends in abundance and population composition, using data from extensive genetic sampling of commercial and recreational Chinook salmon (Oncorhynchus tshawytscha) fisheries in southern British Columbia. We use the model to estimate seasonal changes in population-specific standardized catch per unit effort (a proxy for abundance) across six marine regions, while accounting for annual variability in sampling effort and uncertain genetic stock assignment. We also share this model as an R package stockseasonr for application to other regions and species. Even at the relatively small spatial scales considered here, we found that patterns in seasonal abundance differed among regions and stocks. While certain locations were clearly migratory corridors, regions within the Salish Sea exhibited diverse, and often weak, seasonal patterns in abundance, emphasizing that they are important, year-round foraging habitats. Furthermore, we found evidence that stocks with similar freshwater life histories and adult run timing, as well as relatively proximate spawning locations, exhibited divergent distributions. Our findings highlight subtle, but important differences in how adult Chinook salmon use marine habitats. Down-scaled model outputs could be used to inform ecosystem-based management efforts by resolving the degree to which salmon overlap with other species of concern, as well as specific fisheries. More broadly, variation in stock-specific abundance among regions indicates efforts to identify mechanisms driving changes in size-at-maturity and natural mortality should account for distinct marine distributions.

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Using Disaster Outcomes to Validate Components of Social Vulnerability to Floods: Flood Deaths and Property Damage across the USA

Sustainability ◽

10.3390/su12156006 ◽

2020 ◽

Vol 12 (15) ◽

pp. 6006

Author(s):

Beth Tellman ◽

Cody Schank ◽

Bessie Schwarz ◽

Peter D. Howe ◽

Alex de Sherbinin

Keyword(s):

Social Vulnerability ◽

Spatial Scales ◽

Sociodemographic Factors ◽

Property Damage ◽

Socioeconomic Variables ◽

Coastal Flood ◽

Rural Counties ◽

Vulnerability Indicators ◽

The Usa ◽

Flood Intensity

Social vulnerability indicators seek to identify populations susceptible to hazards based on aggregated sociodemographic data. Vulnerability indices are rarely validated with disaster outcome data at broad spatial scales, making it difficult to develop effective national scale strategies to mitigate loss for vulnerable populations. This paper validates social vulnerability indicators using two flood outcomes: death and damage. Regression models identify sociodemographic factors associated with variation in outcomes from 11,629 non-coastal flood events in the USA (2008–2012), controlling for flood intensity using stream gauge data. We compare models with (i) socioeconomic variables, (ii) the composite social vulnerability index (SoVI), and (iii) flood intensity variables only. The SoVI explains a larger portion of the variance in death (AIC = 2829) and damage (R2 = 0.125) than flood intensity alone (death—AIC = 2894; damage—R2 = 0.089), and models with individual sociodemographic factors perform best (death—AIC = 2696; damage—R2 = 0.229). Socioeconomic variables correlated with death (rural counties with a high proportion of elderly and young) differ from those related to property damage (rural counties with high percentage of Black, Hispanic and Native American populations below the poverty line). Results confirm that social vulnerability influences death and damage from floods in the USA. Model results indicate that social vulnerability models related to specific hazards and outcomes perform better than generic social vulnerability indices (e.g., SoVI) in predicting non-coastal flood death and damage. Hazard- and outcome-specific indices could be used to better direct efforts to ameliorate flood death and damage towards the people and places that need it most. Future validation studies should examine other flood outcomes, such as evacuation, migration and health, across scales.

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