Pernilla Christensen

National Inventory of Landscapes in Sweden (NILS) - scope, design, and experiences from establishing a multiscale biodiversity monitoring system

The landscape-level and multiscale biodiversity monitoring program National Inventory of Landscapes in Sweden (NILS) was launched in 2003. NILS is conducted as a sample-based stratified inventory that acquires data across several spatial scales, which is accomplished by combining aerial photo interpretation with field inventory. A total of 631 sample units are distributed across the land base of Sweden, of which 20% are surveyed each year. By 2007 NILS completed the first 5-year inventory phase. As the reinventory in the second 5-year phase (2008–2012) proceeds, experiences and insights accumulate and reflections are made on the setup and accomplishment of the monitoring scheme. In this article, the emphasis is placed on background, scope, objectives, design, and experiences of the NILS program. The main objective to collect data for and perform analyses of natural landscape changes, degree of anthropogenic impact, prerequisites for natural biological diversity and ecological processes at landscape scale. Different environmental conditions that can have direct or indirect effects on biological diversity are monitored. The program provides data for national and international policy and offers an infrastructure for other monitoring program and research projects. NILS has attracted significant national and international interest during its relatively short time of existence; the number of stakeholders and cooperation partners steadily increases. This is constructive and strengthens the incentive for the multiscale monitoring approach.

Long-term decline of vole populations in northern Sweden: A test of the destructive sampling hypothesis

Abstract Time series data on cyclic vole populations in 1971–1999 in northern Sweden show a long-term decline in numbers from the early 1970s to the late 1990s. We tested the destructive sampling hypothesis predicting that previously unsampled (new) plots in remote areas would yield higher density indices than the density level of permanent plots in the early 1970s. In autumn 1999 we sampled both permanent (treatment) plots and new (control) plots. Density was not higher on new than on permanent sampling plots for any of the predominant vole species, Clethrionomys glareolus, C. rufocanus, and Microtus agrestis. It appears unlikely that destructive sampling has caused the observed decline in vole numbers.

Habitat preferences of Clethrionomys rufocanus in boreal Sweden

A long-term decline of vole populations in boreal Sweden, especially of the grey-sided vole (Clethrionomys rufocanus Sund.), has been revealed by snap-trapping in 1971–2004. We identified important habitats for the grey-sided vole by mapping the distribution of cumulated number of reproductive females in 1971–1978, prior to the major decline in the 1980s. Mean abundance of C. rufocanus was higher in the western (inland) than eastern (coastland) part of the study area. As the inland appeared to represent the most, as far as we know, pristine, abundant part of the population, we based identification of high quality habitats on inland data only. Four habitats were more important than others and yielded nearly 86% of the reproductive females in spring: (1) forests of dry, (2) moist and (3) wet/hydric dwarf-shrub type, in addition to (4) forest/swamp complexes rich in dwarf-shrubs. The latter three habitats were used more frequently than expected from their occurrence in the landscape. Still, the variation in density of reproductive females within patches of the same habitat was frequently high. This suggested that habitat composition in the surrounding landscape, perhaps may have affected local vole density at the patch scale. Clear-cut sampling plots appeared to be low-frequently used by reproductive females, but also by males and immatures. In conclusion, our study indicated the importance of also studying habitat at a larger scale than that of the patch to get a deeper understanding on how habitat influences local and regional densities and population dynamics of C. rufocanus.

Using Optical Satellite Data and Airborne Lidar Data for a Nationwide Sampling Survey

A workflow for combining airborne lidar, optical satellite data and National Forest Inventory (NFI) plots for cost efficient operational mapping of a nationwide sample of 5x 5 km squares in the National Inventory of Landscapes in Sweden (NILS) landscape inventory in Sweden is presented. Since the areas where both satellite data and lidar data have a common data quality are limited, and impose a constraint on the number of available NFI plots, it is not feasible to perform classifications in a single step. Instead a stratified approach where canopy cover and canopy height are first predicted from lidar data trained with NFI plots is proposed. From the lidar predictions a forest stratum is defined as grid cells with more than 3m mean tree height and more than 10% vertical canopy cover, the remaining grid cells are defined as open land. Both forest and open land are then classified into broad vegetation classes using optical satellite data. The classification of open land is trained with aerial photo interpretation and the classification of the forest stratum is trained with a new set of NFI plots. The result is a rational procedure for nationwide sample based vegetation characterization.

Using statistical power analysis as a tool when designing a monitoring program: experience from a large-scale Swedish landscape monitoring program.

The National Inventory of Landscapes in Sweden (NILS) is a large-scale, sample-based monitoring program that combines aerial photointerpretation with field inventory to follow landscape-scale biophysical conditions and changes. A statistical power analysis was conducted before the NILS program began in 2003 with the aim to determine an appropriate sampling effort and compare some design alternatives. The chosen sampling effort was then evaluated in a second power analysis conducted just before the first 5-year re-inventory rotation started. The latter power analysis revealed which magnitude of actual change might be detected within the future for different central monitoring variables. This article reports results from these power analyses and discusses our experiences in using power analysis as a tool for designing large-scale monitoring programs. The results showed that even quite small changes in the more common variables, such as land cover types and more common plant species, can be detected on the national scale. However, on the regional scale, or for less common variables, changes will be more difficult to detect. The power analyses have revealed the size level of changes that will be possible to detect. The results have also generated incentives for further improvements of NILS, e.g., input to the modification and revision of the variable content, flow and hierarchy, and incentives for launching other complementary monitoring programs connected to NILS. They have also created a basis for a better and more user-oriented communication of results from NILS to different stakeholders.

Changes in vegetation cover and composition in the Swedish mountain region.

Climate change, higher levels of natural resource demands, and changing land use will likely lead to changes in vegetation configuration in the mountain regions. The aim of this study was to determine if the vegetation cover and composition have changed in the Swedish region of the Scandinavian Mountain Range, based on data from the long-term landscape biodiversity monitoring program NILS (National Inventory of Landscapes in Sweden). Habitat type and vegetation cover were assessed in 1740 systematically distributed permanent field plots grouped into 145 sample units across the mountain range. Horvitz–Thompson estimations were used to estimate the present areal extension of the alpine and the mountain birch forest areas of the mountain range, the cover of trees, shrubs, and plants, and the composition of the bottom layer vegetation. We employed the data from two subsequent 5-year monitoring periods, 2003–2007 and 2008–2012, to determine if there have been any changes in these characteristics. We found that the extension of the alpine and the mountain birch forest areas has not changed between the inventory phases. However, the total tree canopy cover increased in the alpine area, the cover of graminoids and dwarf shrubs and the total cover of field vegetation increased in both the alpine area and the mountain birch forest, the bryophytes decreased in the alpine area, and the foliose lichens decreased in the mountain birch forest. The observed changes in vegetation cover and composition, as assessed by systematic data in a national and regional monitoring scheme, can validate the results of local studies, experimental studies, and models. Through benchmark assessments, monitoring data also contributes to governmental policies and land-management strategies as well as to directed cause and effect analyses.