| 1. |
- Adler, Sven, et al.
(författare)
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Ny design för riktade naturtypsinventeringar inom NILS och THUF
- 2020
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Den här rapporten beskriver: Ett generellt ramverk för nationella inventeringar där det går att komplettera utifrån nya behov på såväl nationell som regional nivå inom samma stickprovsdesign. Samma skattningsförfarande och skattningsalgoritmer på både nationell och regional nivå samt vid olika tätheter på stickprovet. Ett stort stickprov, med många rutor i stickprovet, vilket ger statistisk styrka vid skattningarna av t.ex. arealer, även för relativt ovanliga naturtyper. Ett balanserat stickprov, bland annat med NMD som stödunderlag, vilket ger bättre skattningar än ett icke-balanserat stickprov. Att relativt ovanliga naturtyper och naturtyper som förekommer geografiskt samlat kommer att kunna fångas upp med geografiskt riktade förtätningar. Att vanliga fenomen inventeras med ett glest stickprov. Extra stor fördel för naturtyper där många rutor går att exkludera från fältbesök genom modellering och inventering i ortofoto. En sådan naturtypsgrupp är gräsmarker, där det dessutom ännu saknas en nationell inventering. Fortsatt samarbete med NMD där de data som samlas in i de nya inventeringarna kommer att kunna bidra både som träningsdata i utvecklingen av NMD och till att verifiera NMD. Mer tids- och kostnadseffektiva inventeringar exempelvis: o Många rutor behöver aldrig besökas i fält eftersom det genom modellering och inventering i ortofoto går att utesluta att de har de eftersökta naturtyperna. Sådana rutor bidrar till en högre precision för skattningarna. o Ortofoton används för att hålla nere kostnaden för bilder och bildhantering. o De mindre 1 km × 1 km-rutorna underlättar fältlogistiken. o Den nya designen är flexibel. Det går att anpassa stickprovet efter den budget som erhålls och genom simuleringar kan vi uppskatta hur stor påverkan på skattningar en minskning eller ökning av stickprovet kan komma att ha. o Eftersom designen bygger på ett tätt, nationellt, stickprov så kommer ytterligare inventeringar kunna läggas till lövskogs- och gräsmarksinventeringarna med samordningsvinster (t.ex. inventeringar av linjeobjekt, pollinatörer och våtmarker).
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| 2. |
- Bondesson, Lennart, 1944-, et al.
(författare)
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An extension of Sampford's method for unequal probability sampling
- 2011
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Ingår i: Scandinavian Journal of Statistics. - : John Wiley & Sons. - 0303-6898 .- 1467-9469. ; 38:2, s. 377-392
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Sampford's (1967) unequal probability sampling method is extended to the case that the inclusion probabilities do not sum to an integer. In this case the sampling outcome is left open for exactly one randomly chosen unit and that unit gets a new inclusion probability. Three applications are presented. Two of them challenge traditional sampling routines. The simple Pareto sampling design, which was introduced by Rosén (1997a,b), is also extended. The extended Pareto design is shown to be close to the extended Sampford design.
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| 3. |
- Bondesson, Lennart, et al.
(författare)
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Sampling Designs with Linear and Quadratic Probability Functions
- 2014
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Ingår i: Open Journal of Statistics. - : Scientific Research Publishing. - 2161-718X .- 2161-7198. ; 4, s. 178-187
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Tidskriftsartikel (refereegranskat)abstract
- Fixed size without replacement sampling designs with probability functions that are linear or quadratic functions of the sampling indicators are defined and studied. Generality, simplicity, remarkable properties, and also somewhat restricted flexibility characterize these designs. It is shown that the families of linear and quadratic designs are closed with respect to sample complements and with respect to conditioning on sampling outcomes for specific units. Relations between inclusion probabilities and parameters of the probability functions are derived and sampling procedures are given.
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| 4. |
- Ehlers, Sarah, et al.
(författare)
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Data assimilation in stand-level forest inventories
- 2013
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Ingår i: Canadian Journal of Forest Research. - : Canadian Science Publishing. - 0045-5067 .- 1208-6037. ; 43, s. 1104-1113
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Tidskriftsartikel (refereegranskat)abstract
- The development of remote sensing methods through research and large-scale application nowadays makes it possible to obtain stand-level estimates of forest variables at short intervals and at low cost. This offers substantial possibilities to forestry practitioners, but it also poses challenges regarding how cost-efficient data acquisition strategies should be developed. For example, should cheap but low-quality data be acquired and discarded whenever new data become available or should investments be made in high-quality data that are continuously updated to last over a longer period of time? We suggest that the solution could be to establish data assimilation (DA) procedures linked to forest inventories to make appropriate use of data from several sources. With DA, old information is updated through growth forecasts and when new information becomes available it is assimilated with the old information; the different sources of information are made use of to the extent motivated by their accuracy. In this study we made a general assessment of the usefulness of DA in connection with stand-level forest inventories and we compared two different methodological approaches, the extended Kalman filter and the Bayesian method. Not surprisingly, the relative advantage of DA was found to be largest for cases where low-precision estimates of growing stock volume were obtained at short intervals and forecasts were made with accurate growth prediction models. The methodological comparison revealed a tendency of the extended Kalman filter to underestimate the variance of the estimates.
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| 5. |
- Ekström, Magnus, 1966-, et al.
(författare)
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Estimating density from presence/absence data in clustered populations
- 2020
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Ingår i: Methods in Ecology and Evolution. - : John Wiley & Sons. - 2041-210X. ; 11:3, s. 390-402
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Tidskriftsartikel (refereegranskat)abstract
- Inventories of plant populations are fundamental in ecological research and monitoring, but such surveys are often prone to field assessment errors. Presence/absence (P/A) sampling may have advantages over plant cover assessments for reducing such errors. However, the linking between P/A data and plant density depends on model assumptions for plant spatial distributions. Previous studies have shown, for example, how that plant density can be estimated under Poisson model assumptions on the plant locations. In this study, new methods are developed and evaluated for linking P/A data with plant density assuming that plants occur in clustered spatial patterns. New theory was derived for estimating plant density under Neyman-Scott-type cluster models such as the Matern and Thomas cluster processes. Suggested estimators, corresponding confidence intervals and a proposed goodness-of-fit test were evaluated in a Monte Carlo simulation study assuming a Matern cluster process. Furthermore, the estimators were applied to plant data from environmental monitoring in Sweden to demonstrate their empirical application. 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 a sample size is large enough when the sampling distributions of the parameter estimators are symmetric or mildly skewed. Bootstrap may be used to check whether this is true. The empirical results suggest that the derived methodology may be useful for estimating density of plants such as Leucanthemum vulgare and Scorzonera humilis. 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 for inventories of plant populations. Our new theory is an important step in this direction.
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| 6. |
- Ekström, Magnus, 1966-, et al.
(författare)
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Estimating density from presence/absence data in clustered populations
- 2021
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- 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.
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| 7. |
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| 8. |
- Ekström, Magnus, et al.
(författare)
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Logistic regression for clustered data from environmental monitoring programs
- 2018
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Ingår i: Ecological Informatics. - : Elsevier. - 1574-9541 .- 1878-0512. ; 43, s. 165-173
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Tidskriftsartikel (refereegranskat)abstract
- Large-scale surveys, such as national forest inventories and vegetation monitoring programs, usually have complex sampling designs that include geographical stratification and units organized in clusters. When models are developed using data from such programs, a key question is whether or not to utilize design information when analyzing the relationship between a response variable and a set of covariates. Standard statistical regression methods often fail to account for complex sampling designs, which may lead to severely biased estimators of model coefficients. Furthermore, ignoring that data are spatially correlated within clusters may underestimate the standard errors of regression coefficient estimates, with a risk for drawing wrong conclusions. We first review general approaches that account for complex sampling designs, e.g. methods using probability weighting, and stress the need to explore the effects of the sampling design when applying logistic regression models. We then use Monte Carlo simulation to compare the performance of the standard logistic regression model with two approaches to model correlated binary responses, i.e. cluster-specific and population-averaged logistic regression models. As an example, we analyze the occurrence of epiphytic hair lichens in the genus Bryoria; an indicator of forest ecosystem integrity. Based on data from the National Forest Inventory (NFI) for the period 1993-2014 we generated a data set on hair lichen occurrence on > 100,000 Picea abies trees distributed throughout Sweden. The NFI data included ten covariates representing forest structure and climate variables potentially affecting lichen occurrence. Our analyses show the importance of taking complex sampling designs and correlated binary responses into account in logistic regression modeling to avoid the risk of obtaining notably biased parameter estimators and standard errors, and erroneous interpretations about factors affecting e.g. hair lichen occurrence. We recommend comparisons of unweighted and weighted logistic regression analyses as an essential step in development of models based on data from large-scale surveys.
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| 9. |
- Esseen, Per-Anders, et al.
(författare)
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Broad-scale distribution of epiphytic hair lichens correlates more with climate and nitrogen deposition than with forest structure
- 2016
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Ingår i: Canadian Journal of Forest Research. - : Canadian Science Publishing. - 0045-5067 .- 1208-6037. ; 46:11, s. 1348-1358
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Tidskriftsartikel (refereegranskat)abstract
- Hair lichens are strongly influenced by forest structure at local scales, but their broad-scale distributions are less understood. We compared the occurrence and length of Alectoria sarmentosa (Ach.) Ach., Bryoria spp., and Usnea spp. in the lower canopy of > 5000 Picea abies (L.) Karst. trees within the National Forest Inventory across all productive forest in Sweden. We used logistic regression to analyse how climate, nitrogen deposition, and forest variables influence lichen occurrence. Distributions overlapped, but the distribution of Bryoria was more northern and that of Usnea was more southern, with Alectoria's distribution being intermediate. Lichen length increased towards northern regions, indicating better conditions for biomass accumulation. Logistic regression models had the highest pseudo R2 value for Bryoria, followed by Alectoria. Temperature and nitrogen deposition had higher explanatory power than precipitation and forest variables. Multiple logistic regressions suggest that lichen genera respond differently to increases in several variables. Warmingdecreased the odds for Bryoria occurrence at all temperatures. Corresponding odds for Alectoria and Usnea decreased in warmer climates, but in colder climates, they increased. Nitrogen addition decreased the odds for Alectoria and Usnea occurrence under high deposition, but under low deposition, the odds increased. Our analyses suggest major shifts in the broad-scale distribution of hair lichens with changes in climate, nitrogen deposition, and forest management.
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| 10. |
- Esseen, Per-Anders, et al.
(författare)
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Multiple drivers of large-scale lichen decline in boreal forest canopies
- 2022
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Ingår i: Global Change Biology. - : John Wiley & Sons. - 1354-1013 .- 1365-2486. ; 28:10, s. 3293-3309
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Tidskriftsartikel (refereegranskat)abstract
- Thin, hair-like lichens (Alectoria, Bryoria, Usnea) form conspicuous epiphyte communities across the boreal biome. These poikilohydric organisms provide important ecosystem functions and are useful indicators of global change. We analyse how environmental drivers influence changes in occurrence and length of these lichens on Norway spruce (Picea abies) over 10 years in managed forests in Sweden using data from >6000 trees. Alectoria and Usnea showed strong declines in southern-central regions, whereas Bryoria declined in northern regions. Overall, relative loss rates across the country ranged from 1.7% per year in Alectoria to 0.5% in Bryoria. These losses contrasted with increased length of Bryoria and Usnea in some regions. Occurrence trajectories (extinction, colonization, presence, absence) on remeasured trees correlated best with temperature, rain, nitrogen deposition, and stand age in multinomial logistic regression models. Our analysis strongly suggests that industrial forestry, in combination with nitrogen, is the main driver of lichen declines. Logging of forests with long continuity of tree cover, short rotation cycles, substrate limitation and low light in dense forests are harmful for lichens. Nitrogen deposition has decreased but is apparently still sufficiently high to prevent recovery. Warming correlated with occurrence trajectories of Alectoria and Bryoria, likely by altering hydration regimes and increasing respiration during autumn/winter. The large-scale lichen decline on an important host has cascading effects on biodiversity and function of boreal forest canopies. Forest management must apply a broad spectrum of methods, including uneven-aged continuous cover forestry and retention of large patches, to secure the ecosystem functions of these important canopy components under future climates. Our findings highlight interactions among drivers of lichen decline (forestry, nitrogen, climate), functional traits (dispersal, lichen colour, sensitivity to nitrogen, water storage), and population processes (extinction/colonization).
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