Estimating density from presence/absence data in clustered populations

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Estimating density from presence/absence data in clustered populations

Ekström, Magnus, 1966- (author): Swedish University of Agricultural Sciences, Sweden

Sandring, Saskia (author): Swedish University of Agricultural Sciences

Grafström, Anton (author): Swedish University of Agricultural Sciences

Esseen, Per-Anders (author): Umeå universitet,Institutionen för ekologi, miljö och geovetenskap

Jonsson, Bengt Gunnar (author): Mittuniversitetet

Ståhl, Göran (author): Swedish University of Agricultural Sciences

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(creator_code:org_t)

2021
2021
English.

Related links:: https://site.uit.no/...; show more...; https://urn.kb.se/re...; show less...

Conference paper (other academic/artistic)

Abstract Subject headings

1. Inventories of plant populations are fundamental in ecological research and monitoring, butsuch surveys are often prone to field assessment errors. Presence/ absence (P/A) samplingmay have advantages over plant cover assessments for reducing such errors. However, thelinking between P/A data and plant density depends on model assumptions for plant spatialdistributions. Previous studies have shown, for example, how that plant density can beestimated under Poisson model assumptions on the plant locations. In this study, newmethods are developed and evaluated for linking P/A data with plant density assuming thatplants occur in clustered spatial patterns.2. New theory was derived for estimating plant density under Neyman–Scott-type cluster models such as the Matérn and Thomas cluster processes. Suggested estimators, correspondingconfidence intervals and a proposed goodness-of-fit test were evaluated in a Monte Carlosimulation study assuming a Matérn cluster process. Furthermore, the estimators were applied to plant data from environmental monitoring in Sweden to demonstrate their empiricalapplication.3. The simulation study showed that our methods work well for large enough sample sizes.The judgment of what is ’large enough’ is often difficult, but simulations indicate that asample size is large enough when the sampling distributions of the parameter estimators aresymmetric or mildly skewed. Bootstrap may be used to check whether this is true. Theempirical results suggest that the derived methodology may be useful for estimating densityof plants such as Leucanthemum vulgare and Scorzonera humilis.4. By developing estimators of plant density from P/A data under realistic model assumptions about plants’ spatial distributions, P/A sampling will become a more useful tool forinventories of plant populations. Our new theory is an important step in this direction.

Subject headings

LANTBRUKSVETENSKAPER -- Lantbruksvetenskap, skogsbruk och fiske -- Skogsvetenskap (hsv//swe)
AGRICULTURAL SCIENCES -- Agriculture, Forestry and Fisheries -- Forest Science (hsv//eng)

Keyword

matematisk statistik
Mathematical Statistics

Publication and Content Type

vet (subject category)
kon (subject category)

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By the author/editor: Ekström, Magnus, ...; Sandring, Saskia; Grafström, Anton; Esseen, Per-Ande ...; Jonsson, Bengt G ...; Ståhl, Göran

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AGRICULTURAL SCIENCES: AGRICULTURAL SCI ...; and Agriculture Fore ...; and Forest Science

By the university: Umeå University

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