Dynamic design of ecological monitoring networks for non‐Gaussian spatio‐temporal data

Wikle, Christopher K.; Royle, J. Andrew

doi:10.1002/env.718

Cited by 41 publications

(37 citation statements)

References 39 publications

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“…Monitoring programs range from continent-wide, multispecies programs, such as the North American Breeding Bird Survey (Link & Sauer 1998;Sauer et al 2003), to programs focused on a single species at a single site (e.g., Knox 1997). They include programs that integrate data with sophisticated mathematical models (Wikle & Royle 2005) and programs that simply attempt to determine whether or not a species is present at a given site (Manley et al 2005). Some primarily rely on mark-recapture data (Freedberg & Bowne 2006), others use data from harvests (Tolimieri & Levin 2005), and still others use remote sensing (Robinson et al 2001).…”

Section: Introductionmentioning

confidence: 99%

Current Trends in Plant and Animal Population Monitoring

Marsh

Trenham

2008

Conservation Biology

171

129

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Animal and plant population monitoring programs are critical for identifying species at risk, evaluating the effects of management or harvest, and tracking invasive and pest species. Nevertheless, monitoring activities are highly decentralized, which makes it difficult for researchers or conservation planners to get a good general picture of what real-world monitoring programs actually entail. We used a Web-based survey to collect information on population monitoring programs. The survey focused on basic questions about each program, including motivations for monitoring, types of data being collected, spatiotemporal design of the program, and reasons for choosing that design. We received responses from 311 people involved in monitoring of various species and used these responses to summarize ongoing monitoring efforts. We also used responses to determine whether monitoring strategies have changed over time and whether they differed among monitoring agencies. Most commonly, monitoring entailed collection of count data at multiple sites with the primary goal of detecting trends. But we also found that goals and strategies for monitoring appeared to be diversifying, that area-occupied and presence-absence approaches appeared to be gaining in popularity, and that several other promising approaches (monitoring to reduce parameter uncertainty, risk-based monitoring, and directly linking monitoring data to management decisions) have yet to become widely established. We suggest that improved communication between researchers studying monitoring designs and those who are charged with putting these designs into practice could further improve monitoring programs and better match sampling designs to the objectives of monitoring programs. Resumen: Los programas de monitoreo de poblaciones de animales y plantas son críticos para la identificación de especies en riesgo, la evaluación de efectos del manejo o cosecha y el seguimiento de especies plaga e invasoras. Sin embargo, las actividades de monitoreo están muy descentralizadas, lo que dificulta que los investigadores o los planificadores de conservación tengan un buena imagen general de lo que significan los programas de monitoreo en el mundo real. Utilizamos un muestreo basado en laRed para colectar información sobre programas de monitoreo de poblaciones. El muestreo se concentró en preguntas básicas sobre cada programa, y las razones para seleccionar ese diseño. Recibimos respuesta de 311 personas involucradas en el monitoreo de varias especies, y utilizamos estas respuestas para resumir los esfuerzos de monitoreo actuales. También utilizamos las respuestas para determinar sí las estrategias de monitoreo han cambiado en el tiempo y sí difieren entre agencias de monitoreo. En general, el monitoreo implicó la colecta de datos de conteo en múltiples sitios con el objetivo primario de detectar tendencias. Pero también encontramos que las metas y estrategias de monitoreo eran diversas, y que los enfoques delárea ocupada y de presencia-ausencia ‡Current address: 648Trends in Pop...

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Section: Introductionmentioning

confidence: 99%

Current Trends in Plant and Animal Population Monitoring

Marsh

Trenham

2008

Conservation Biology

171

129

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“…count data (Wikle and Royle 2005). There is much more to learn about the choice of design criterion for estimating and predicting Histogram of q d values from 64 randomly selected designs (gray) and the optimal design (black), each design containing 20 randomly selected transects to be flown over Glacier Bay National Park in the upcoming survey year.…”

Section: Discussionmentioning

confidence: 99%

“…These dynamics are often ignored when developing spatial survey designs (Wikle and Royle 2005). These dynamics are often ignored when developing spatial survey designs (Wikle and Royle 2005).…”

Section: Introductionmentioning

confidence: 99%

“…We distinguish dynamic survey designs from the traditional statistical notion of adaptive sampling (sensu Thompson 1990), although the two concepts are related. However, dynamic survey designs have been applied to few long-term ecological monitoring programs (e.g., Wikle and Royle 2005, Hooten et al 2009, 2012, Evangelou and Zhu 2012. However, dynamic survey designs have been applied to few long-term ecological monitoring programs (e.g., Wikle and Royle 2005, Hooten et al 2009, 2012, Evangelou and Zhu 2012.…”

Section: Introductionmentioning

confidence: 99%

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Monitoring dynamic spatio‐temporal ecological processes optimally

Williams

Hooten

Womble

et al. 2018

Ecology

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Population dynamics vary in space and time. Survey designs that ignore these dynamics may be inefficient and fail to capture essential spatio-temporal variability of a process. Alternatively, dynamic survey designs explicitly incorporate knowledge of ecological processes, the associated uncertainty in those processes, and can be optimized with respect to monitoring objectives. We describe a cohesive framework for monitoring a spreading population that explicitly links animal movement models with survey design and monitoring objectives. We apply the framework to develop an optimal survey design for sea otters in Glacier Bay. Sea otters were first detected in Glacier Bay in 1988 and have since increased in both abundance and distribution; abundance estimates increased from 5 otters to >5,000 otters, and they have spread faster than 2.7 km/yr. By explicitly linking animal movement models and survey design, we are able to reduce uncertainty associated with forecasting occupancy, abundance, and distribution compared to other potential random designs. The framework we describe is general, and we outline steps to applying it to novel systems and taxa.

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“…Interestingly, Hoeting et al (2000) and Wintle and Bardos (2006) obtained similar results with their simulated data refl ecting plant and mammal distributions. Both static and dynamic designs have advantages and disadvantages (MacKenzie and Royle 2005, Wikle and, but an appropriate allocation of sampling eff ort between fi xed and roving units may contribute to combining several monitoring and mapping objectives (Hooten et al 2009). First, our results revealed considerable among-species variation in this minimum sample size.…”

Section: Discussionmentioning

confidence: 99%

Optimising long‐term monitoring projects for species distribution modelling: how atlas data may help

Aizpurua

Paquet²,

Brotons

et al. 2014

Ecography

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29how they change over time may provide key information to guide eff ective landscape and conservation planning. Dynamic species distribution mapping may, therefore, be considered as an essential component of a biodiversity monitoring project (Brotons et al. 2007(Brotons et al. , K é ry et al. 2013. In any monitoring project, sampling units are, however, sparsely distributed over the region of interest, which is inconvenient for a straightforward mapping of species distributions.Species distribution modelling is an increasingly used technique (Rodr í guez et al. 2007) that can produce distribution maps based on monitoring data (Brotons et al. 2006). With these models, environmental variables describing the habitat conditions in the sampling units are related to records of species presence. Th ese models are used to predict the species distribution beyond the sampling units in areas where species occurrence is unknown (Ara ú jo and Guisan 2006, Elith et al. 2010. Th e use of models to predict species distributions is of key signifi cance for biodiversity conservation (Guisan et al. 2013). Among several applications, models Long-term biodiversity monitoring data are mainly used to estimate changes in species occupancy or abundance over time, but they may also be incorporated into predictive models to document species distributions in space. Although changes in occupancy or abundance may be estimated from a relatively limited number of sampling units, small sample size may lead to inaccurate spatial models and maps of predicted species distributions. We provide a methodological approach to estimate the minimum sample size needed in monitoring projects to produce accurate species distribution models and maps. Th e method assumes that monitoring data are not yet available when sampling strategies are to be designed and is based on external distribution data from atlas projects. Atlas data are typically collected in a large number of sampling units during a restricted timeframe and are often similar in nature to the information gathered from long-term monitoring projects. Th e large number of sampling units in atlas projects makes it possible to simulate a broad gradient of sample sizes in monitoring data and to examine how the number of sampling units infl uences the accuracy of the models. We apply the method to several bird species using data from a regional breeding bird atlas. We explore the eff ect of prevalence, range size and habitat specialization of the species on the sample size needed to generate accurate models. Model accuracy is sensitive to particularly small sample sizes and levels off beyond a suffi ciently large number of sampling units that varies among species depending mainly on their prevalence. Th e integration of spatial modelling techniques into monitoring projects is a cost-eff ective approach as it off ers the possibility to estimate the dynamics of species distributions in space and over time. We believe our innovative method will help in the sampling design of future monitoring projects ai...

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Dynamic design of ecological monitoring networks for non‐Gaussian spatio‐temporal data

Cited by 41 publications

References 39 publications

Current Trends in Plant and Animal Population Monitoring

Current Trends in Plant and Animal Population Monitoring

Monitoring dynamic spatio‐temporal ecological processes optimally

Optimising long‐term monitoring projects for species distribution modelling: how atlas data may help

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