Optimising occupancy models and detection probability for conservation monitoring in a forest-dwelling small mammal

2019 ◽  
Author(s):  
Fraser John Combe ◽  
Jonathan S Ellis ◽  
Simone Bullion ◽  
Paul Chanin ◽  
Phillip C Wheater ◽  
...  
Keyword(s):  
Small Mammal ◽  
Detection Probability ◽  
Spatial Scales ◽  
Spatial And Temporal Variation ◽  
Sampling Effort ◽  
Occupancy Models ◽  
Effective Population ◽  
Temporal And Spatial ◽  
Elusive Species ◽  
Hazel Dormouse

The ability to determine the survey effort required to detect species presence is critical for the conservation of populations in order to monitor changes in distribution or abundance, a challenge for rare and elusive species. While designing an effective population survey may be of concern to scientists, it may also be a legal requirement for protected species. We analysed how spatial and temporal variation in sampling effort impacts detection probability in the hazel dormouse (Muscardinus avellanarius), a small mammal that naturally occurs at low density in forest habitat. We used presence and absence data from 144 sites in England, UK. We found that detection probability was strongly affected by survey intensity, with a 37.5% increase in detection probability when sampling effort was increased from 16 to 50 nest tubes per site. We also show that detection probability is highly temporally dependent; monitoring early in the year results in low detection probability (21%-53%; April-June), whilst detection dramatically increased later in the year (89%; September). Our results suggest that variation in detection probability can be complex and influenced by effects at temporal and spatial scales, and by sampling effort. We show that sampling effort can be minimised depending on seasonal variation in detection probability, however this is likely to be species and method dependent.

scholarly journals Using areas of known occupancy to identify sources of variation in detection probability of raptors: taking time lowers replication effort for surveys

2016 ◽  
Vol 3 (10) ◽  
pp. 160368 ◽  
Author(s):  
Campbell Murn ◽  
Graham J. Holloway
Keyword(s):  
Detection Probability ◽  
Spatial Scales ◽  
Survey Methods ◽  
A Priori ◽  
Low Density ◽  
Occupancy Models ◽  
Imperfect Detection ◽  
Factors Affecting ◽  
Sources Of Variation ◽  
Time Of Year

Species occurring at low density can be difficult to detect and if not properly accounted for, imperfect detection will lead to inaccurate estimates of occupancy. Understanding sources of variation in detection probability and how they can be managed is a key part of monitoring. We used sightings data of a low-density and elusive raptor (white-headed vulture Trigonoceps occipitalis ) in areas of known occupancy (breeding territories) in a likelihood-based modelling approach to calculate detection probability and the factors affecting it. Because occupancy was known a priori to be 100%, we fixed the model occupancy parameter to 1.0 and focused on identifying sources of variation in detection probability. Using detection histories from 359 territory visits, we assessed nine covariates in 29 candidate models. The model with the highest support indicated that observer speed during a survey, combined with temporal covariates such as time of year and length of time within a territory, had the highest influence on the detection probability. Averaged detection probability was 0.207 (s.e. 0.033) and based on this the mean number of visits required to determine within 95% confidence that white-headed vultures are absent from a breeding area is 13 (95% CI: 9–20). Topographical and habitat covariates contributed little to the best models and had little effect on detection probability. We highlight that low detection probabilities of some species means that emphasizing habitat covariates could lead to spurious results in occupancy models that do not also incorporate temporal components. While variation in detection probability is complex and influenced by effects at both temporal and spatial scales, temporal covariates can and should be controlled as part of robust survey methods. Our results emphasize the importance of accounting for detection probability in occupancy studies, particularly during presence/absence studies for species such as raptors that are widespread and occur at low densities.

Daily Variation in Sampled Densities of Ixodes scapularis and Amblyomma americanum (Acari: Ixodidae) Nymphs at a Single Site—Implications for Assessing Acarological Risk

2022 ◽  
Author(s):  
Terry L Schulze ◽  
Robert A Jordan
Keyword(s):  
Ixodes Scapularis ◽  
Spatial Scales ◽  
Amblyomma Americanum ◽  
Full Description ◽  
Spatial And Temporal Variability ◽  
Sampling Effort ◽  
Protection Measures ◽  
Host Seeking ◽  
Sampling Protocols ◽  
Temporal And Spatial

Abstract The public health challenge posed by tick-borne disease (TBD) has increased efforts to characterize the spatial and temporal distribution of ticks and associated pathogens to better focus tick control strategies and personal protection measures. We describe variability in nymphal Ixodes scapularis Say and Amblyomma americanum (L.) density derived from daily drag sampling at a single location in New Jersey over 4 yr and explore how observed differences in daily collections might affect the estimation of acarological risk. We found significant variability in the density of host-seeking nymphs that could suggest substantially different rates of human-tick encounters depending on sampling date, habitat, and ambient weather conditions. The spatial and temporal variability in the distribution of 2 sympatric tick species with different host preferences and questing strategies, suggests that to produce results that are comparable among sites across the area sampled, surveillance efforts may be limited to shorter collection seasons, fewer sites or less sampling effort (fewer plots or fewer visits) per site, and a geographic scope that minimizes the potential temporal and spatial biases indicated here. Our results illustrate that evaluation of models of tick distribution or relative acarological risk based on surveillance data requires a full description of the diversity of habitats sampled and the conditions under which sampling is performed. The array of factors that affect tick host-seeking and that could bias interpretation of sampling results emphasizes the need to standardize sampling protocols and for more caution when interpreting tick sampling data collected over large temporal and spatial scales.

scholarly journals Using citizen-science data to identify local hotspots of species occurrence

2014 ◽  
Author(s):  
Eric J. Ward ◽  
Kristin N Marshall ◽  
Todd Hass ◽  
Scott F. Pearson ◽  
Gerald Joyce ◽  
...  
Keyword(s):  
Spatial Scales ◽  
Puget Sound ◽  
Range Shift ◽  
Anthropogenic Activity ◽  
Occupancy Models ◽  
Science Data ◽  
Seabird Species ◽  
Nearshore Ecosystems ◽  
Temporal And Spatial ◽  
Spatial Patchiness

Seabirds have been identified and used as indicators of ecosystem processes such as climate change, and anthropogenic activity in nearshore ecosystems around the globe. Temporal and spatial trends have been documented at large spatial scales, but few studies have examined fine scale spatial patterns, by species or functional group, because . In this paper, we apply spatial occupancy models to assess the spatial patchiness and interannual trends of 18 seabird species in the Puget Sound region (Washington state, USA). Our dataset, the Puget Sound Seabird Survey, is unique in that represents a seven year study, collected in winter months (October – April), and is collected at an extremely fine spatial scale (62 sites in the current analysis). Despite historic declines of seabirds in the region over the last 50 years, results from our study are optimistic, suggesting increases in probabilities of occurrence for 14 of the 18 species included. We found support for declines in occurrence for white-winged scoters, brants, and 2 species of grebes. The declines of Western grebes in particular are troubling, but in agreement with other recent studies that have shown support for a range shift south in recent years, to the California Current.

scholarly journals Using citizen-science data to identify local hotspots of species occurrence

2014 ◽  
Author(s):  
Eric J. Ward ◽  
Kristin N Marshall ◽  
Todd Hass ◽  
Scott F. Pearson ◽  
Gerald Joyce ◽  
...  
Keyword(s):  
Spatial Scales ◽  
Puget Sound ◽  
Range Shift ◽  
Anthropogenic Activity ◽  
Occupancy Models ◽  
Science Data ◽  
Seabird Species ◽  
Nearshore Ecosystems ◽  
Temporal And Spatial ◽  
Spatial Patchiness

Seabirds have been identified and used as indicators of ecosystem processes such as climate change, and anthropogenic activity in nearshore ecosystems around the globe. Temporal and spatial trends have been documented at large spatial scales, but few studies have examined fine scale spatial patterns, by species or functional group, because . In this paper, we apply spatial occupancy models to assess the spatial patchiness and interannual trends of 18 seabird species in the Puget Sound region (Washington state, USA). Our dataset, the Puget Sound Seabird Survey, is unique in that represents a seven year study, collected in winter months (October – April), and is collected at an extremely fine spatial scale (62 sites in the current analysis). Despite historic declines of seabirds in the region over the last 50 years, results from our study are optimistic, suggesting increases in probabilities of occurrence for 14 of the 18 species included. We found support for declines in occurrence for white-winged scoters, brants, and 2 species of grebes. The declines of Western grebes in particular are troubling, but in agreement with other recent studies that have shown support for a range shift south in recent years, to the California Current.

Spatial and temporal variation in the structure of estuarine macroinvertebrate assemblages: implications for assessing the health of estuaries

2007 ◽  
Vol 58 (9) ◽  
pp. 866 ◽  
Author(s):  
A. J. Hirst ◽  
R. Kilpatrick
Keyword(s):  
Human Impacts ◽  
Spatial Scales ◽  
Reference Points ◽  
Tidal River ◽  
Spatial And Temporal Variation ◽  
Small Scale ◽  
Spatial Differences ◽  
Spatial Replication ◽  
Temporal And Spatial ◽  
Suitable Reference

As human impacts in estuaries are often pervasive (estuary-wide) and/or pre-existing, the identification of suitable reference points, from which to assess the extent of impacts, is problematic. One solution is to compare potentially degraded estuaries with estuaries deemed to be largely unmodified by human activities. However, there is a perception that individual estuaries are too spatially and temporally dynamic to allow valid comparisons to be made using such an approach. We tested this idea for a commonly used indicator, benthic macroinvertebrates, using a factorial design incorporating both temporal and spatial scales between and within three adjacent meso-tidal river estuaries in northern Tasmania. Variation in macroinvertebrate assemblage structure was analysed using permutational multivariate analysis of variance. Most variance occurred within estuaries (68–82% variance) relative to spatial differences between estuaries (24–14%) corresponding with a strong upstream estuarine gradient and small-scale spatial patchiness. Seasonal variation accounted for 9–4% of total variance indicating that temporal differences were relatively insignificant when contrasted against spatial variability within and between estuaries. We suggest that with sufficient spatial replication at the within estuary-scale, entire estuaries may act as whole reference systems, allowing studies to examine potential impacts within estuaries with spatially diffuse, pre-existing human impacts.

Larval Feeding: Mechanisms, Rates, and Performance in Nature

2018 ◽  
Keyword(s):  
Marine Invertebrates ◽  
Spatial Scales ◽  
Size Spectrum ◽  
Larval Feeding ◽  
Natural Habitats ◽  
Feeding Mechanism ◽  
Temporal And Spatial ◽  
And Performance ◽  
Bioenergetics Models ◽  
Many Particles

Larvae of many marine invertebrates must capture and ingest particulate food in order to develop to metamorphosis. These larvae use only a few physical processes to capture particles, but implement these processes using diverse morphologies and behaviors. Detailed understanding of larval feeding mechanism permits investigators to make predictions about feeding performance, including the size spectrum of particles larvae can capture and the rates at which they can capture them. In nature, larvae are immersed in complex mixtures of edible particles of varying size, density, flavor, and nutritional quality, as well as many particles that are too large to ingest. Concentrations of all of these components vary on fine temporal and spatial scales. Mechanistic models linking larval feeding mechanism to performance can be combined with data on food availability in nature and integrated into broader bioenergetics models to yield increased understanding of the biology of larvae in complex natural habitats.

Humans and the Environment

2013 ◽  
Keyword(s):  
Spatial Scales ◽  
Empirical Studies ◽  
Human Action ◽  
Cultural Practice ◽  
Environmental Archaeology ◽  
Archaeological Data ◽  
Temporal And Spatial ◽  
Global And Local ◽  
The Relationship ◽  
The Way

The environment has always been a central concept for archaeologists and, although it has been conceived in many ways, its role in archaeological explanation has fluctuated from a mere backdrop to human action, to a primary factor in the understanding of society and social change. Archaeology also has a unique position as its base of interest places it temporally between geological and ethnographic timescales, spatially between global and local dimensions, and epistemologically between empirical studies of environmental change and more heuristic studies of cultural practice. Drawing on data from across the globe at a variety of temporal and spatial scales, this volume resituates the way in which archaeologists use and apply the concept of the environment. Each chapter critically explores the potential for archaeological data and practice to contribute to modern environmental issues, including problems of climate change and environmental degradation. Overall the volume covers four basic themes: archaeological approaches to the way in which both scientists and locals conceive of the relationship between humans and their environment, applied environmental archaeology, the archaeology of disaster, and new interdisciplinary directions.The volume will be of interest to students and established archaeologists, as well as practitioners from a range of applied disciplines.

scholarly journals 8-Day and Daily Maximum and Minimum Air Temperature Estimation via Machine Learning Method on a Climate Zone to Global Scale

2021 ◽  
Vol 13 (12) ◽  
pp. 2355
Author(s):  
Linglin Zeng ◽  
Yuchao Hu ◽  
Rui Wang ◽  
Xiang Zhang ◽  
Guozhang Peng ◽  
...  
Keyword(s):  
Spatial Scale ◽  
Air Temperature ◽  
Spatial Scales ◽  
Model Performance ◽  
Global Scale ◽  
Scale Model ◽  
Validation Dataset ◽  
Daily Maximum ◽  
Climate Zone ◽  
Temporal And Spatial

Air temperature (Ta) is a required input in a wide range of applications, e.g., agriculture. Land Surface Temperature (LST) products from Moderate Resolution Imaging Spectroradiometer (MODIS) are widely used to estimate Ta. Previous studies of these products in Ta estimation, however, were generally applied in small areas and with a small number of meteorological stations. This study designed both temporal and spatial experiments to estimate 8-day and daily maximum and minimum Ta (Tmax and Tmin) on three spatial scales: climate zone, continental and global scales from 2009 to 2018, using the Random Forest (RF) method based on MODIS LST products and other auxiliary data. Factors contributing to the relation between LST and Ta were determined based on physical models and equations. Temporal and spatial experiments were defined by the rules of dividing the training and validation datasets for the RF method, in which the stations selected in the training dataset were all included or not in the validation dataset. The RF model was first trained and validated on each spatial scale, respectively. On a global scale, model accuracy with a determination coefficient (R2) > 0.96 and root mean square error (RMSE) < 1.96 °C and R2 > 0.95 and RMSE < 2.55 °C was achieved for 8-day and daily Ta estimations, respectively, in both temporal and spatial experiments. Then the model was trained and cross-validated on each spatial scale. The results showed that the data size and station distribution of the study area were the main factors influencing the model performance at different spatial scales. Finally, the spatial patterns of the model performance and variable importance were analyzed. Both daytime and nighttime LST had a significant contribution in the 8-day Tmax estimation on all the three spatial scales; while their contribution in daily Tmax estimation varied over different continents or climate zones. This study was expected to improve our understanding of Ta estimation in terms of accuracy variations and influencing variables on different spatial and temporal scales. The future work mainly includes identifying underlying mechanisms of estimation errors and the uncertainty sources of Ta estimation from a local to a global scale.

scholarly journals Sequential modelling of the Earth’s core magnetic field

2020 ◽  
Vol 72 (1) ◽  
Author(s):  
Guillaume Ropp ◽  
Vincent Lesur ◽  
Julien Baerenzung ◽  
Matthias Holschneider
Keyword(s):  
Magnetic Field ◽  
Prior Information ◽  
Spatial Scales ◽  
Model Parameters ◽  
International Geomagnetic Reference Field ◽  
The Earth ◽  
Temporal And Spatial ◽  
Different Sources ◽  
Original Approach ◽  
Modelling Approach

Abstract We describe a new, original approach to the modelling of the Earth’s magnetic field. The overall objective of this study is to reliably render fast variations of the core field and its secular variation. This method combines a sequential modelling approach, a Kalman filter, and a correlation-based modelling step. Sources that most significantly contribute to the field measured at the surface of the Earth are modelled. Their separation is based on strong prior information on their spatial and temporal behaviours. We obtain a time series of model distributions which display behaviours similar to those of recent models based on more classic approaches, particularly at large temporal and spatial scales. Interesting new features and periodicities are visible in our models at smaller time and spatial scales. An important aspect of our method is to yield reliable error bars for all model parameters. These errors, however, are only as reliable as the description of the different sources and the prior information used are realistic. Finally, we used a slightly different version of our method to produce candidate models for the thirteenth edition of the International Geomagnetic Reference Field.

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