Factors affecting detection probability in plant distribution studies

Chen, Guoke; Kéry, Marc; Zhang, Jin Long; Ma, Keping

doi:10.1111/j.1365-2745.2009.01560.x

Cited by 102 publications

(131 citation statements)

References 28 publications

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“…If the goal of the survey is to initiate a long-term demography study, incomplete detection could lead to such work being done on a nonrandom subset of the population. These issues are not new: field biologists know they can miss plants and recent work documents the extent of detection problems across species [11]. However it has been challenging for plant biologists to go from general knowledge of the issue to incorporating detection in their own work.…”

Section: Discussionmentioning

confidence: 99%

“…For example, in contrast to the near 100% detection of flowering orchids, the probability of initial detection of vegetative plants was approximately 0.8 [17], [18]. In a Chinese forest, detection of the presence or absence of different trees and shrubs varied from 0.09 to 0.34 [11]. Variation in detection among observers can also be important: detection probabilities varied from 0.09 to 1.0 among 12 observers searching for an exotic plant [12].…”

Section: Introductionmentioning

confidence: 97%

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Detection and Plant Monitoring Programs: Lessons from an Intensive Survey of Asclepias meadii with Five Observers

et al. 2012

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Monitoring programs, where numbers of individuals are followed through time, are central to conservation. Although incomplete detection is expected with wildlife surveys, this topic is rarely considered with plants. However, if plants are missed in surveys, raw count data can lead to biased estimates of population abundance and vital rates. To illustrate, we had five independent observers survey patches of the rare plant Asclepias meadii at two prairie sites. We analyzed data with two mark-recapture approaches. Using the program CAPTURE, the estimated number of patches equaled the detected number for a burned site, but exceeded detected numbers by 28% for an unburned site. Analyses of detected patches using Huggins models revealed important effects of observer, patch state (flowering/nonflowering), and patch size (number of stems) on probabilities of detection. Although some results were expected (i.e. greater detection of flowering than nonflowering patches), the importance of our approach is the ability to quantify the magnitude of detection problems. We also evaluated the degree to which increased observer numbers improved detection: smaller groups (3–4 observers) generally found 90 – 99% of the patches found by all five people, but pairs of observers or single observers had high error and detection depended on which individuals were involved. We conclude that an intensive study at the start of a long-term monitoring study provides essential information about probabilities of detection and what factors cause plants to be missed. This information can guide development of monitoring programs.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 97%

Detection and Plant Monitoring Programs: Lessons from an Intensive Survey of Asclepias meadii with Five Observers

et al. 2012

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“…However, this relationship is not always observed. There is a large number of non-environmental controls of abundance, including biotic interactions such as predation or interspecific competition (Holt et al, 2002;Van Horne, 1983), dispersal limitation (Holt et al, 2002;Pulliam, 2006;Verbek et al, 2010) and different species detectability among habitats, seasons, weather conditions (Gu and Swihart, 2004;Pearce and Ferrier, 2001) and observers (Chen et al, 2009). This can lead to the population of a species reaching high values of abundance within low probability of occurrence areas.…”

Section: Introductionmentioning

confidence: 99%

Occurrence and abundance models of threatened plant species: Applications to mitigate the impact of hydroelectric power dams

Guarino

Barbosa

Waechter

2012

Ecological Modelling

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In situ and ex situ plant conservation Environmental assessment Model validation a b s t r a c t Species occurrence and abundance models are important tools that can be used in biodiversity conservation, and can be applied to predict or plan actions needed to mitigate the environmental impacts of hydropower dams. In this study our objectives were: (i) to model the occurrence and abundance of threatened plant species, (ii) to verify the relationship between predicted occurrence and true abundance, and (iii) to assess whether models based on abundance are more effective in predicting species occurrence than those based on presence-absence data. Individual representatives of nine species were counted within 388 randomly georeferenced plots (10 m × 50 m) around the Barra Grande hydropower dam reservoir in southern Brazil. We modelled their relationship with 15 environmental variables using both occurrence (Generalised Linear Models) and abundance data (Hurdle and Zero-Inflated models). Overall, occurrence models were more accurate than abundance models. For all species, observed abundance was significantly, although not strongly, correlated with the probability of occurrence. This correlation lost significance when zero-abundance (absence) sites were excluded from analysis, but only when this entailed a substantial drop in sample size. The same occurred when analysing relationships between abundance and probability of occurrence from previously published studies on a range of different species, suggesting that future studies could potentially use probability of occurrence as an approximate indicator of abundance when the latter is not possible to obtain. This possibility might, however, depend on life history traits of the species in question, with some traits favouring a relationship between occurrence and abundance. Reconstructing species abundance patterns from occurrence could be an important tool for conservation planning and the management of threatened species, allowing scientists to indicate the best areas for collection and reintroduction of plant germplasm or choose conservation areas most likely to maintain viable populations.

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“…It has been pointed out that detection probability should be considered to correctly estimate population properties such as the occurrence rate or survival rate, even if the observed objects are plants (Kéry, 2004; Chen et al, 2009; Chen et al, 2013). The present study had only one observation for each survey year.…”

Section: Methodsmentioning

confidence: 99%

“…However, the quadrat size was rather small (5 m × 5 m) and the whole of each quadrat was explored, so I expected that the detection probability should be near to one and therefore “detection/nondetection” was regarded as “presence/absence” in this study. Chen et al (2009) showed that the detection probability asymptotically approaches one with larger survey efforts.…”

Section: Methodsmentioning

confidence: 99%

Changes in understory species occurrence of a secondary broadleaved forest after mass mortality of oak trees under deer foraging pressure

Itô

2016

PeerJ

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The epidemic of mass mortality of oak trees by Japanese oak wilt has affected secondary deciduous broadleaved forests that have been used as coppices in Japan. The dieback of oak trees formed gaps in the crown that would be expected to enhance the regeneration of shade-intolerant pioneer species. However, foraging by sika deer Cervus nippon has also affected forest vegetation, and the compound effects of both on forest regeneration should be considered when they simultaneously occur. A field study was conducted in Kyôto City, Japan to investigate how these compound effects affected the vegetation of the understory layer of these forests. The presence/absence of seedlings and saplings was observed for 200 quadrats sized 5 m ×5 m for each species in 1992, before the mass mortality and deer encroachment, and in 2014 after these effects. A hierarchical Bayesian model was constructed to explain the occurrence, survival, and colonization of each species with their responses to the gaps that were created, expanded, or affected by the mass mortality of Quercus serrata trees. The species that occurred most frequently in 1992, Eurya japonica, Quercus glauca, and Cleyera japonica, also had the highest survival probabilities. Deer-unpalatable species such as Symplocos prunifolia and Triadica sebifera had higher colonization rates in the gaps, while the deer-palatable species Aucuba japonica had the smallest survival probability. The gaps thus promoted the colonization of deer-unpalatable plant species such as Symplocos prunifolia and Triadica sebifera. In the future, such deer-unpalatable species may dominate gaps that were created, expanded, or affected by the mass mortality of oak trees.

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Factors affecting detection probability in plant distribution studies

Cited by 102 publications

References 28 publications

Detection and Plant Monitoring Programs: Lessons from an Intensive Survey of Asclepias meadii with Five Observers

Detection and Plant Monitoring Programs: Lessons from an Intensive Survey of Asclepias meadii with Five Observers

Occurrence and abundance models of threatened plant species: Applications to mitigate the impact of hydroelectric power dams

Changes in understory species occurrence of a secondary broadleaved forest after mass mortality of oak trees under deer foraging pressure

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