The earth is undergoing climatic changes and the model predictions for the high-arctic climate are particularly dramatic [1]. This underscores the urgency for achieving a better understanding of how climate affects ecological processes like herbivory, predation and pollination [2]. The major controls of such processes are the population size of the functional group (e.g. herbivores, predators or pollinators) and the activity level of the individuals. A particularly strong response to climatic conditions can be expected in high-arctic arthropods since they are poikilothermic and because the abiotic conditions of the High Arctic are generally close to the minimum requirements for locomotion [3]. The seasonal emergence of adult arctic arthropods (i.e. their phenological development) is determined mainly by the timing of snowmelt [4–7], whereas their activity pattern is a function of body temperature. The microclimatic conditions that determine body temperature in arthropods is an integration of a suite of weather variables (e.g. radiation, precipitation and wind speed) in addition to temperature [8–11]. Hence, the magnitude of arthropod-related ecological processes in the High Arctic depends on several potentially uncorrelated components of climate. We have previously shown that high-arctic arthropods have advanced their emergence phenology in recent years in response to earlier timing of snowmelt [12]. This shift in phenology may expose arthropods to a time of the season with different weather conditions and may therefore affect their level of activity.

Capture rates from passive traps like pitfall traps integrate arthropod density and activity levels [13] and therefore provides a proxy for the magnitude of the ecological processes in which the organisms are involved. For instance, the capture rate of wolf spiders is related to their level of activity as well as their density. As such it is a correlate of the predation pressure by wolf spiders. Likewise, the capture rate of pollinators provides a proxy for the magnitude of pollination. The effect of weather on activity patterns is immediate whereas the physiological processes controlling density involves emergence and mortality. Hence, the time scale of fluctuations in activity is likely to be shorter than the time scale of fluctuations in density. Previous work from seasonal environments has shown that these two factors can be separated statistically [14]. Here, we extend this technique by applying generalized additive models [15]. Using this modelling approach, it is possible to separate the variation in capture rate due to a component which varies over a short time scale (activity) from variation due to a component which varies over a longer time scale (density) without a priori assumptions about its exact shape. We aim at elucidating broader patterns in the relation between climate and arthropod ecology, and therefore we take a higher taxon approach. We addressed the following questions: Which meteorological variable most strongly influences the locomotory performance of different taxa of flying and surface-dwelling arthropods in a high-arctic location? What is the relative influence of weather parameters and capture date on capture numbers of these taxa?

Our analyses demonstrated that the temporal variation in capture rates of high-arctic arthropods from pitfall and window traps consisted of two components indicating the effects of density and activity. By using generalized additive modelling to separate variation in capture rates, we found one component that was unimodally related to capture date and one that was a function of short-term weather fluctuations through the season. Air temperature was the most important weather variable followed by solar radiation. The influence of temperature was most pronounced on the taxa of flying arthropods like Lepidoptera and Diptera, which is consistent with previous findings [14]. The surface-dwelling taxa like the spiders (Linyphiidae and Lycosidae) responded most strongly to variation in solar radiation. Solar radiation is probably a better predictor of near-surface temperatures than ambient air temperature two metres above the ground. Although, capture rates may be influenced by factors other than density and activity, such as seasonally-determined changes in behaviour related specifically to reproduction, our flexible non-linear functions would have included such effects in the function of capture date. When we reran the entire analysis using Gaussian curves to model the seasonal development the same weather variables were identified as the most important in eight of twelve cases. The deviation between the model approaches could arise if the seasonal development does not follow a Gaussian curve. Alternatively, the spline function of the GAM could have captured some of the variation due to variation in activity levels, but with the degrees of freedom in the spline (i.e. the flexibility of the curve) set at a constant and low level this is rather unlikely. The good correspondence between the two methods lends further support to the conclusion that the identified weather variables are indeed affecting the activity level of the individual species groups.

Species-specific responses may be hidden by pooling multiple species in larger taxonomic units. However, we found no bimodality in the seasonal capture of the taxa included in this study which could suggest that individual species within a taxon occurred during different parts of the season. Also, since flying and surface-dwelling arthropods responded to different components of climate, general differences in the environmental conditions experienced by these two groups may be more important than behavioural differences between species within taxa. Clearly, this higher taxon approach precludes a detailed understanding of the species-environment interactions. However, since our aim here is to elucidate broader patterns in the relation between climate and arthropod ecology, we refer to these interactions simply as arthropod-related ecological processes. It is possible that sampling with shorter time intervals would have identified a stronger influence of weather variables on activity of the arthropods. However, without increasing the number of traps this would also have reduced the sample size from each sampling and thereby reduced the statistical power of the analyses. Indeed we are confident that by using data from ten seasons we identified the most important weather variable for the activity level of each taxon.

Our non-linear statistical modelling approach also made it possible to quantify the relative importance of density and activity. It has long been acknowledged that passive traps like pitfall traps provide biased estimates of density, because differences in activity levels between trapping periods are difficult to control for [22]. It has stimulated the development of alternative sampling techniques to provide unbiased estimates of population density [23, 24]. However, in some cases no alternative sampling technique is feasible. Indeed, some organisms are simply too small and fragile for applying mark recapture techniques or too mobile, cryptic or non-randomly distributed to allow for counting using a transect approach. In these cases, parallel data on dominating meteorological variables make it possible to control for the effect of differences in locomotory performance among trapping periods. Also, capture rates in passive traps may actually provide a proxy for the rate of ecological processes involving arthropods.

We found that the non-linear component of the general additive models representing density explained more of the variation than did the weather variables representing locomotory performance. This indicates that the magnitude of arthropod-related ecological processes is currently more influenced by phenological changes than by short-term fluctuations in weather. However, the dynamics of the two most important weather variables (temperature and solar radiation) differed markedly across the season and therefore a change in the timing of the phenology of the species groups could also increase the importance of weather on locomotory performance. The summer peak of incoming solar radiation occurred almost two months earlier than the summer peak in average air temperature (Fig. 2). Since taxa of flying arthropods are mostly sensitive to variation in air temperature and taxa of surface-dwelling arthropods are mostly sensitive to variation in solar radiation, changes in phenological timing may have opposite effects on these two groups of organisms. We have previously shown that arthropod phenology at Zackenberg is more closely linked to timing of snowmelt than to temperature for the taxa included in this study [7]. Consequently, in species where the activity level is most sensitive to temperature, an advancement of the timing of snowmelt would result in an unchanged or decreased contribution to ecological processes, depending on the magnitude of the parallel temperature increase. In contrast, species where the activity level is mostly influences by solar radiation would probably contribute more to ecological processes by an advancement of their emergence, because they would be present during a period with higher levels of solar radiation.

We were able to statistically separate the variation in capture rates of high-arctic arthropods into a non-linear component of capture date (density) and a linear component of weather (activity). Consistent with previous findings, air temperature best explained variation in the activity level of flying insects. An advancement of the phenology in this group due to earlier snowmelt will make individuals appear earlier in the season, but parallel temperature increases could mean that individuals are exposed to similar temperatures. Hence, the effect of climatic changes on the activity pattern in this group may be unchanged. In contrast, we found that solar radiation is a better proxy of activity levels than air temperature in surface-dwelling arthropods. An advancement of the phenology may expose surface-dwelling arthropods to higher levels of solar radiation, which suggest that their locomotory performance is enhanced and their contribution to ecological processes is increased. Therefore, the integrated effect of climatic changes on ecological processes depends on the change in both temperature and timing of snowmelt and may vary between processes involving surface-dwelling and flying arthropods.