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The state of sea trout in 1251 Norwegian watercourses was assessed based on a scoring system for human pressures, abundance data, and local knowledge.Over 16,000 km of rivers and lakes were available to sea trout in these watercourses, spanning from the temperate to Arctic regions.Sea trout were classified to be in a good or very good state in fewer than 25% of the watercourses and in a poor or very poor state in almost 40%. Twenty‐nine watercourses had lost their sea trout populations.Salmon lice from aquaculture salmon farms had by far the largest adverse effect on sea trout among the human impact factors, both in the number of watercourses (83%) and river area affected (60%), and the total effect on sea trout abundance.Agriculture and hydropower production also had strong adverse impacts (35% and 19% of watercourses), but substantially lower than that caused by salmon lice. Culverts related to road crossings and other habitat alterations also had impacts on sea trout in many watercourses (27%).Exploitation of sea trout has been reduced in Norway in recent years, both in the marine and freshwater fisheries. Yet, the exploitation pressure was moderate or high in almost 14% of the watercourses where the state of sea trout was poor or very poor, suggesting a high potential for overexploitation in these.The state of sea trout was best in the northern sparsely populated areas. However, distribution of watercourses with sea trout in a poor or very poor state was more linked to aquaculture, agriculture, and hydropower production than human population density.The developed approach for large‐scale mapping of state and pressures, which is vital for prioritizing management measures, may inspire other nations in their conservation effort for this important species. [ABSTRACT FROM AUTHOR]

The main aim of this paper is to address consequences of climate warming on loss of habitat and genetic diversity in the enigmatic tropical alpine giant rosette plants using the Ethiopian endemic Lobelia rhynchopetalum as a model. We modeled the habitat suitability of L. rhynchopetalum and assessed how its range is affected under two climate models and four emission scenarios. We used three statistical algorithms calibrated to represent two different complexity levels of the response. We analyzed genetic diversity using amplified fragment length polymorphisms and assessed the impact of the projected range loss. Under all model and scenario combinations and consistent across algorithms and complexity levels, this afro-alpine flagship species faces massive range reduction. Only 3.4% of its habitat seems to remain suitable on average by 2,080, resulting in loss of 82% ( CI 75%-87%) of its genetic diversity. The remaining suitable habitat is projected to be fragmented among and reduced to four mountain peaks, further deteriorating the probability of long-term sustainability of viable populations. Because of the similar morphological and physiological traits developed through convergent evolution by tropical alpine giant rosette plants in response to diurnal freeze-thaw cycles, they most likely respond to climate change in a similar way as our study species. We conclude that specialized high-alpine giant rosette plants, such as L. rhynchopetalum, are likely to face very high risk of extinction following climate warming. [ABSTRACT FROM AUTHOR]

Aim Previous research on how climatic niches vary across species ranges has focused on a limited number of species, mostly invasive, and has not, to date, been very conclusive. Here we assess the degree of niche conservatism between distant populations of native alpine plant species that have been separated for thousands of years. Location European Alps and Fennoscandia. Methods Of the studied pool of 888 terrestrial vascular plant species occurring in both the Alps and Fennoscandia, we used two complementary approaches to test and quantify climatic-niche shifts for 31 species having strictly disjunct populations and 358 species having either a contiguous or a patchy distribution with distant populations. First, we used species distribution modelling to test for a region effect on each species' climatic niche. Second, we quantified niche overlap and shifts in niche width (i.e. ecological amplitude) and position (i.e. ecological optimum) within a bi-dimensional climatic space. Results Only one species (3%) of the 31 species with strictly disjunct populations and 58 species (16%) of the 358 species with distant populations showed a region effect on their climatic niche. Niche overlap was higher for species with strictly disjunct populations than for species with distant populations and highest for arctic-alpine species. Climatic niches were, on average, wider and located towards warmer and wetter conditions in the Alps. Main conclusion Climatic niches seem to be generally conserved between populations that are separated between the Alps and Fennoscandia and have probably been so for 10,000-15,000 years. Therefore, the basic assumption of species distribution models that a species' climatic niche is constant in space and time-at least on time scales 104 years or less-seems to be largely valid for arctic-alpine plants. [ABSTRACT FROM AUTHOR]

Maximum entropy (MaxEnt) modelling, as implemented in the Maxent software, has rapidly become one of the most popular methods for distribution modelling. Originally, MaxEnt was described as a machine-learning method. More recently, it has been explained from principles of Bayesian estimation. MaxEnt offers numerous options (variants of the method) and settings (tuning of parameters) to the users. A widespread practice of accepting the Maxent software's default options and settings has been established, most likely because of ecologists' lack of familiarity with machine-learning and Bayesian statistical concepts and the ease by which the default models are obtained in Maxent. However, these defaults have been shown, in many cases, to be suboptimal and exploration of alternatives has repeatedly been called for. In this paper, we derive MaxEnt from strict maximum likelihood principles, and point out parallels between MaxEnt and standard modelling tools like generalised linear models (GLM). Furthermore, we describe several new options opened by this new derivation of MaxEnt, which may improve MaxEnt practice. The most important of these is the option for selecting variables by subset selection methods instead of the ℓ1-regularisation method, which currently is the Maxent software default. Other new options include: incorporation of new transformations of explanatory variables and user control of the transformation process; improved variable contribution measures and options for variation partitioning; and improved output prediction formats. The new options are exemplified for a data set for the plant species Scorzonera humilis in SE Norway, which was analysed by the standard MaxEnt procedure in a previously published paper. We recommend that thorough comparisons between the proposed alternative options and default procedures and variants thereof be carried out. [ABSTRACT FROM AUTHOR]

We provide the first comparative multispecies analysis of spatial genetic structure and diversity in the circumpolar Arctic using a common strategy for sampling and genetic analyses. We aimed to identify and explain potential general patterns of genetic discontinuity/connectivity and diversity, and to compare our findings with previously published hypotheses., We collected and analyzed 7707 samples of 17 widespread arctic-alpine plant species for amplified fragment length polymorphisms ( AFLPs). Genetic structure, diversity and distinctiveness were analyzed for each species, and extrapolated to cover the geographic range of each species. The resulting maps were overlaid to produce metamaps., The Arctic and Atlantic Oceans, the Greenlandic ice cap, the Urals, and lowland areas between southern mountain ranges and the Arctic were the strongest barriers against gene flow. Diversity was highest in Beringia and gradually decreased into formerly glaciated areas. The highest degrees of distinctiveness were observed in Siberia., We conclude that large-scale general patterns exist in the Arctic, shaped by the Pleistocene glaciations combined with long-standing physical barriers against gene flow. Beringia served as both refugium and source for interglacial (re)colonization, whereas areas further west in Siberia served as refugia, but less as sources for (re)colonization. [ABSTRACT FROM AUTHOR]

We explored the applied use of distribution modelling as a tool for making spatial predictions of occurrences of the red-listed vascular plant species Scorzonera humilis in a study area in southeast Norway. Scorzonera is typical of extensively managed semi-natural grasslands. A Maxent model was trained on all known records of the species, accurately georeferenced and gridded to fine resolution (grid cells of 25×25 m). Model performance was assessed on the training data by data-splitting (by which some records were set off for evaluation) and on independent evaluation data collected in the field. Of the eight predictor variables used in the modelling, distance to roads and to arable land were most important followed by land-cover class and altitude. Judged from the area under curve (AUC), the model was good to excellent and a significant, positive relationship was found between relative probabilities of occurrence predicted by the model and true probability of presence provided by the independently collected evaluation data. The model was used together with the evaluation data to estimate presence of Scorzonera humilis in 0.7% of the grid cells in the study area. The grid cells in which the model predicted highest probability for Scorzonera to be present had a true probability of presence of ca 12%, i.e. 17×higher than in an average cell. The present study demonstrates that, even when only simple predictor variables are available, spatial prediction modelling contributes important knowledge about rare species such as prevalence estimates, spatial prediction maps and insights into the species' autecology. Spatial prediction modelling also makes cost-efficient monitoring of rare species possible. However, it is pointed out that these benefits require evaluation of the model on independently sampled evaluation data. [ABSTRACT FROM AUTHOR]

Question: How can statistical modelling tools (GLMM) and GIS be used as an aid in understanding complex ecological patterns? This general question was approached by using bryophyte demography data as an example. More specifically, we asked what is the contribution of terrain shape to explaining the performance and fate of plant individuals, controlling for all other known relationships? Location: Norway. Methods: Information on demography was obtained for 140 populations of the perennial clonal bryophyte Hylocomium splendens in Norway spruce forests during an 11-year period (1992-2002). Performance (size and branching pattern) was recorded for mature segments and fate was recorded for growing points. Positions of each of the more than 30 000 recorded bryophyte ramets were coupled with (micro-) topographic characteristics (slope and convexity) derived from fine-scale digital elevation models in a GIS framework. Carefully planned sequences of generalised linear mixed models (GLMM) were performed to test predictions from a conceptual path model. Results: We demonstrate strong dependence of size on branching, fate and on vertical position in the bryophyte carpet, and an effect of vertical position on branching pattern. Micro-topography contributed to explaining plant performance by four different mechanisms: (1) a direct effect of slope on the segment's vertical position in the carpet; (2-3) direct effects of both slope and convexity on fates of individuals via controls on risk of burial; and (4) an indirect effect of convexity on branching pattern via a direct effect on size. No indication of a direct effect of terrain on branching was found. Conclusions: Our study exemplifies the usefulness of GLMM for disentangling complex ecological relationships. Specifically, we recognise micro-topography as a potentially important factor for plant demography in general and for performance and fate of individuals in particular. [ABSTRACT FROM AUTHOR]

Aim The main aims of this study are: (1) to test if temperature and related parameters are the primary determinants of the regional distribution of macrofungi (as is commonly recognized for plants); (2) to test if the success of modelling fungal distribution patterns depends on species and distribution characteristics; and (3) to explore the potential of using herbarium data for modelling and predicting fungal species’ distributions. Location The study area, Norway, spans 58–71° N latitude and 4–32° E longitude, and embraces extensive ecological gradients in a small area. Methods The study is based on 1020 herbarium collections of nine selected species of macrofungi and a set of 75 environmental predictor variables, all recorded in a 5 × 5-km grid covering Norway. Primarily, generalized linear model (GLM; logistic regression) analyses were used to identify the environmental variables that best accounted for the species’ recorded distributions in Norway. Second, Maxent analyses (using variables identified by GLM) were used to produce predictive potential distribution maps for these species. Results Variables relating to temperature and radiation were most frequently included in the GLMs, and between 24.8% and 59.8% of the variation in single-species occurrence was accounted for. The fraction of variation explained by the GLMs ranged from 41.6% to 59.8% for species with restricted distributions, and from 24.8% to 39.3% for species with widespread/scattered and intermediate distributions. The two-step procedure of GLM followed by Maxent gave predictions with very high values for the area under the curve (0.927–0.997), and maps of potential distribution were generally credible. Main conclusions We show that temperature is a key factor governing the distribution of macrofungi in Norway, indicating that fungi may respond strongly to global warming. We confirm that modelling success depends partly on species and distribution characteristics, notably on how the distribution relates to the extent of the study area. Our study demonstrates that the combination of GLM and Maxent may be a fruitful approach for biogeography. We conclude that herbarium data improve insight into factors that control the distributions of fungi, of particular value for research on fleshy fungi (mushrooms), which have largely cryptic life cycles. [ABSTRACT FROM AUTHOR]

Aim To assess the scale of variation for major environmental gradients in Norway. To obtain a step-less model for this variation and to use this model to evaluate the extent to which the consensus expert classification of Norway into vegetation regions can be predicted from environmental variables. To discuss the potential of step-less models for understanding natural variation at regional scales, for stratification and for predictive modelling of species distributions and land-cover types. Location The mainland of Norway. Methods Fifty-four climatic, topographical, hydrological and geological variables were recorded for grid cells with spatial resolution (grain size) of 1 × 1, 5 × 5 and 10 × 10 km, spanning the entire mainland of Norway. Principal components analyses (PCA) were used to summarize variation in three primary data matrices and three random subsets of these. Results The first four principal components explained between 75% and 85% of the variation in the data sets. All PCAs revealed four consistent environmental gradients, in order of decreasing importance: (1) regional variation (gradient) from coast to inland and from oceanic/humid to continental areas; (2) regional variation from north to south and from high to low altitudes; (3) regional variation from north to south and from inland to coast, related to solar radiation; and (4) topographic (terrain relief) variation on finer scales than (1–3). The first two PCA axes corresponded to the two bioclimatic gradients used in expert classifications of Norway into biogeographical regions: vegetation sections (from highly oceanic to slightly continental) and vegetation zones (from nemoral to alpine). Main conclusions Our PCA analyses substantiate the current view of bioclimatic regional vegetation variation in Norway, provide an explicit characterization of this variation in terms of climatic variables, and show that environmental variability can be reproduced as GIS layers in step-less models. These models have the potential to become important tools for future predictive modelling within resource management, conservation planning and biogeographical (and other ecological) research. [ABSTRACT FROM AUTHOR]

What are the relative contribution of temperature and solar irradiance as types of energy deliveries for species richness at the ecosystem level? In order to reveal this question in lake ecosystems, we assessed zooplankton species richness in 1891 Norwegian lakes covering a wide range in latitude, altitude, and lake area. Geographical variables could largely be replaced by temperature-related variables, e.g. annual monthly maximum temperature or growth season. Multivariate analysis (PCA) revealed that not only maximum monthly temperature, but also energy input in terms of solar radiation were closely associated with species richness. This was confirmed by stepwise, linear regression analysis in which lake area was also found to be significant. We tested the predictive power of the “metabolic scaling laws” for species richness by regressing Ln of species richness over the inverse of the air temperature (in Kelvin), corrected for the activation energy (eV) as predicted by the Boltzmann constant. A significant, negative slope of 0.78 for ln richness over temperature, given as 1/kT, was found, thus slightly higher than the range of slopes predicted from the scaling law (0.60–0.70). Temperature basically constrained the upper bound of species number, but it was only a modest predictor of actual richness. Both PCA-analysis and linear regression models left a large unexplained variance probably due to lake-specific properties such as catchment influence, lake productivity, food-web structure, immigration constraints or more stochastic effects. [ABSTRACT FROM AUTHOR]

Pelagic crustacean zooplankton were collected from 336 Norwegian lakes covering a wide range of latitude, altitude, lake area, mean depth, production (as chlorophyll a), and fish community structure. Mean zooplankton species richness during the ice-free season was generally low at high latitudes and altitudes. Further, lower species richness was recorded in western lakes, possibly reflecting constraints on migration and dispersal. However, despite obvious spatial limitations, geographic boundaries were only weak predictors of mean zooplankton richness. Similarly, lake surface area did not contribute positively to mean richness such as seen in other ecosystem surveys. Rather, intrinsic factors such as primary production and fish community (planktivore) structure were identified by regression analysis as the major predictors of zooplankton diversity, while a positive correlation was observed between species richness and total zooplankton biomass. However, in spite of a large number of variables included in this study, the predictive power of multiple regression models was modest (<50% variance explained), pointing to a major role for within-lake properties, as yet unidentified intrinsic forces, stochasticity, or dispersal as constraints on zooplankton diversity in these lakes. [ABSTRACT FROM AUTHOR]

Spatial patterns of important population or individual characteristics are expected to reflect structuring ecosystem processes to the extent that populations with strikingly different spatial patterns most likely have been structured by different processes. Few studies of spatial pattern in plant assemblages, bryophyte assemblages in particular, still exist and pattern has only vaguely been linked with process. In this study we describe fine-scale spatial variation in size and the occurrence of terminated (non-branching) segments in 21 Norwegian populations of the dominant boreal forest moss Hylocomium splendens, in search for general patterns of spatial structure. All Hylocomium splendens segments in the investigated plots were followed for a 10-year period; their size (dry mass, estimated from in situ measurements) and fate (terminated or ramifying) were recorded annually. The spatial structure of size and terminating segments at scales from 0.5 to 16 cm was described for each population as fractal dimension profiles, derived from semi-variograms. For about one half of the populations size and terminating segments could be assigned to a specific spatial pattern, the predicted outcome of one of three main structuring processes: (i) negative spatial dependence (fractal dimension F>3.0) on the scale of individuals (below 2 cm), indicative of negative interactions; (ii) positive spatial dependence (F<3.0) on the scale of individuals, indicative of positive interactions; and (iii) positive spatial dependence on broader (4–8 cm) scales, indicative of structuring by environmental factors or patchy disturbance. Patterns (i) and (iii) were observed both for size and terminated segments more often than expected. Fractal dimension profiles for size obtained separately for each year revealed temporal patterns of spatial structure that tended to be invariant over years. Negative spatial dependence of size, possibly due to large size difference between buried segments and other segments during self thinning, was typical of populations rapidly growing in number. Positive spatial dependence with a range of influence by the spatial process of 4–8 cm was observed in plots with sparse bryophyte cover and high cover of deciduous litter, probably due to accumulation of litter in depressions between shoots or groups of shoots. The main finding of this study is that different populations of the same species in the same type of ecosystem can be spatially structured in different ways. This accords with a model for the studied system as consisting of a mosaic of cells, of spatial extent of a few cm or larger, intergrading in space and temporally dynamic, the population characteristics of each cell being shaped by several structuring processes that vary, temporally and spatially, in their relative importance. [ABSTRACT FROM AUTHOR]

Question: Does the understorey vegetation of Norwegian boreal forests change in relation to broad-scale, long-term changes? Location: Norway. Methods: Permanently marked 1 -m² vegetation plots from 17 monitoring reference areas in forests dominated by Picea abies (11 areas, 620 plots) and Betula spp. (six areas, 300 plots) were analysed twice, at the start in 1988-1997 and 5 yr later (1993-2002). Species subplot frequency data were analysed separately for each area by univariate and multivariate statistical methods; 5-yr changes in single species abundances, species number per plot and species composition were tested. Results: Two distinct patterns of change were found: 1. Abundance of several vascular plant species decreased in SE Norwegian Picea forests, most noticeably of species with a preference for richer soils, such as Oxalis acetosella. 2. Abundance of many bryophyte species as well as bryophyte species number per plot increased in forests of both types over most of Norway. Conclusions: The pattern of vascular plant changes is probably a time-delayed response of long-lived, mainly clonal, populations to acidified soils resulting from deposition of long-distance airborne pollutants. The pattern bryophyte changes, with reference to the close link between climatic conditions for growth and abundance changes for Hylocomium splendens established in previous demographic studies, is related to climatic conditions favourable for bryophyte growth. We conclude that many forest understorey plants are sensitive indicators of environmental change, and that the concept used for intensive monitoring of Norwegian forests enables early detection of changes in vegetation brought about by broad- scale, regional, impact factors. [ABSTRACT FROM AUTHOR]