| 1. |
- Ekström, Magnus, 1966-, et al.
(författare)
-
Estimating density from presence/absence data in clustered populations
- 2020
-
Ingår i: Methods in Ecology and Evolution. - : John Wiley & Sons. - 2041-210X. ; 11:3, s. 390-402
-
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.
|
|
| 2. |
- Ekström, Magnus, 1966-, et al.
(författare)
-
Estimating density from presence/absence data in clustered populations
- 2021
-
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.
|
|
| 3. |
|
|
| 4. |
- Esseen, Per-Anders, et al.
(författare)
-
Multiple drivers of large-scale lichen decline in boreal forest canopies
- 2022
-
Ingår i: Global Change Biology. - : John Wiley & Sons. - 1354-1013 .- 1365-2486. ; 28:10, s. 3293-3309
-
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).
|
|
| 5. |
- Jonsson, Bengt-Gunnar, 1963-, et al.
(författare)
-
Rapid changes in ground vegetation of mature boreal forests : an analysis of Swedish national forest inventory data
- 2021
-
Ingår i: Forests. - : MDPI. - 1999-4907. ; 12:4
-
Tidskriftsartikel (refereegranskat)abstract
- The boreal forest floor vegetation is critical for ecosystem functioning and an important part of forest biodiversity. Given the ongoing global change, knowledge on broad-scale changes in the composition and abundance of different plant species and species groups is hence important for both forest conservation and management. Here, we analyse permanent plot data from the National Forest Inventory (NFI) on changes in the vegetation over a 10-year period in four regions of Sweden. To limit the direct and relatively well-known effects of forest management and associated succession, we only included mature forest stands not influenced by forestry during the 10 years between inventories, and focused on vegetation change mainly related to other factors. Results show strong decrease among many species and species groups. This includes dominant species such as Vaccinimum myrtillus and Deschampsia flexuosa as well as several forest herbs. The only species increasing are some mosses in the southern regions. Our data do not allow for a causal interpretation of the observed patterns. However, the changes probably result from latent succession in combination with climate change and nitrogen deposition, and with time lags complicating the interpretation of their relative importance. Regardless of the cause, the observed changes are on a magnitude that suggest impacts on ecosystem functioning and hence highlight the need for more experimental work.
|
|
| 6. |
- Moberg, Christina, et al.
(författare)
-
De unga gör helt rätt när de stämmer staten
- 2022
-
Ingår i: Aftonbladet. - 1103-9000.
-
Tidskriftsartikel (populärvet., debatt m.m.)abstract
- 1 620 forskare och lärare i forskarvärlden: Vi ställer oss bakom Auroras klimatkrav
|
|
| 7. |
- Mold, Jeff E., et al.
(författare)
-
Divergent clonal differentiation trajectories establish CD8(+) memory T cell heterogeneity during acute viral infections in humans
- 2021
-
Ingår i: Cell Reports. - : Elsevier BV. - 2211-1247. ; 35:8
-
Tidskriftsartikel (refereegranskat)abstract
- The CD8(+) T cell response to an antigen is composed of many T cell clones with unique T cell receptors, together forming a heterogeneous repertoire of effector and memory cells. How individual T cell clones contribute to this heterogeneity throughout immune responses remains largely unknown. In this study, we longitudinally track human CD8(+) T cell clones expanding in response to yellow fever virus (YFV) vaccination at the single-cell level. We observed a drop in clonal diversity in blood from the acute to memory phase, suggesting that clonal selection shapes the circulating memory repertoire. Clones in the memory phase display biased differentiation trajectories along a gradient from stem cell to terminally differentiated effector memory fates. In secondary responses, YFV- and influenza-specific CD8(+) T cell clones are poised to recapitulate skewed differentiation trajectories. Collectively, we show that the sum of distinct clonal phenotypes results in the multifaceted human T cell response to acute viral infections.
|
|
| 8. |
- Ståhl, Göran, et al.
(författare)
-
Presence-absence sampling for estimating plant density using survey data with variable plot size
- 2020
-
Ingår i: Methods in Ecology and Evolution. - : John Wiley & Sons. - 2041-210X. ; 11:4, s. 580-590
-
Tidskriftsartikel (refereegranskat)abstract
- Presence–absence sampling is an important method for monitoring state and change of both individual plant species and communities. With this method, only the presence or absence of the target species is recorded on plots and thus the method is straightforward to apply and less prone to surveyor judgement compared to other vegetation monitoring methods. However, in the basic setting, all plots must be equally large or otherwise it is unclear how data should be analysed. In this study, we propose and evaluate five different methods for estimating plant density based on presence–absence registrations from surveys with variable plot sizes.Using artificial plant population data as well as empirical data from the Swedish National Forest Inventory, we evaluated the performance of the proposed methods. The main analysis was conducted through sampling simulation in artificial populations, whereby bias and variance of density estimators for the different methods were quantified and compared.Both for state and change estimation of plant density, we found that the best method to handle variable plot size was to perform generalized least squares regression, using plot size as an independent variable. Methods where plots smaller than a certain threshold were excluded or their registrations recalculated were, however, almost as good. Using all registrations as if they were obtained from plots with the nominal plot size resulted in substantial bias.Our findings are important for plant population studies in a wide range of environmental monitoring programmes. In these programmes, plots are typically randomly laid out and may be located across boundaries between different land‐use or land‐cover classes, resulting in subplots of variable size. Such splitting of plots is common when large plots are used, for example, with the 100 m2 plots used in the Swedish National Forest Inventory. Our methods overcome problems to estimate plant density from presence–absence data observed in plots that vary in size.
|
|
