Occupancy-abundance models for predicting densities of three leaf beetles damaging the multipurpose tree Sesbania sesban in eastern and southern Africa

scientific article published on February 2006

Occupancy-abundance models for predicting densities of three leaf beetles damaging the multipurpose tree Sesbania sesban in eastern and southern Africa is …
instance of (P31):
scholarly articleQ13442814

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P356DOI10.1079/BER2005401
P698PubMed publication ID16441906

P2093author name stringSileshi G
Hailu G
Mafongoya PL
P2860cites workCorrelations Between Incidence and Abundance are Expected by ChanceQ29040808
The fractal nature of nature: power laws, ecological complexity and biodiversityQ31085782
Scaling and power-laws in ecological systemsQ33214442
Species interactions can explain Taylor's power law for ecological time series.Q51198059
Spatial distribution and sampling plans for Mesoplatys ochroptera (Coleoptera: Chrysomelidae) on sesbania.Q52596378
The statistical analysis of insect counts based on the negative binomial distribution.Q52687359
A positive relationship between local abundance and regional occupancy is almost inevitable (but not all positive relationships are the same).Q52866539
Abundance-occupancy relationshipsQ55842267
Aggregation, Variance and the MeanQ56805301
Predicting abundance from occupancy: a test for an aggregated insect assemblageQ57004750
Modelling occurrence and abundance of species when detection is imperfectQ57878181
Occupancy-abundance relationships and sampling scalesQ57950483
P433issue1
P921main subjectSouthern AfricaQ27394
Sesbania sesbanQ3206585
P304page(s)61-69
P577publication date2006-02-01
P1433published inBulletin of Entomological ResearchQ15763806
P1476titleOccupancy-abundance models for predicting densities of three leaf beetles damaging the multipurpose tree Sesbania sesban in eastern and southern Africa
P478volume96

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Q31138597Quasi-Poisson vs. negative binomial regression: how should we model overdispersed count data?
Q34003670Using the negative binomial distribution to model overdispersion in ecological count data

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