Mads C. Forchhammer

Aarhus University, Aarhus, Central Jutland, Denmark

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Publications (74)458.73 Total impact

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    ABSTRACT: Although many studies have examined the phenological mismatches between interacting organisms, few have addressed the potential for mismatches between phenology and seasonal weather conditions. In the Arctic, rapid phenological changes in many taxa are occurring in association with earlier snowmelt. The timing of snowmelt is jointly affected by the size of the late winter snowpack and the temperature during the spring thaw. Increased winter snowpack results in delayed snowmelt, whereas higher air temperatures and faster snowmelt advance the timing of snowmelt. Where inter-annual variation in snowpack is substantial, changes in the timing of snowmelt can be largely uncoupled from changes in air temperature. Using detailed long-term data on the flowering phenology of four arctic plant species from Zackenberg, Greenland, we investigate whether there is a phenological component to the temperature conditions experienced prior to and during flowering. In particular, we assess the role of timing of flowering
    Ecology 08/2014; 96(3). DOI:10.1890/14-0338.1 · 4.66 Impact Factor
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    ABSTRACT: The high arctic is undergoing a faster change in climate than most other regions of the planet, with already observed ecological consequences. Combined with the characteristics of high-arctic ecosystems, such as low species redundancy, high seasonality and weather extremes, shifts in individual species performance and phenology may lead to altered interaction dynamics through trophic mismatch and cascades. An ecosystem approach is therefore desirable in the attempt to understand the multidimensional impacts of climate. Here, we present ecosystem-wide trend analyses of a long-term dataset on terrestrial and limnic biota with focus on the distribution of observed trends and associated variation across the eco-system. We used 114 time series drawn from 11 abiotic variables, 19 terrestrial and 7 limnic biotic species/taxa and compared temporal trends, changes and abrupt shifts in the variation within and across the two biota. A total of 36 % of the time series analysed showed a significant trend during the study period with a higher frequency of trends occurring within performance variables. Overall, the changes tended to be negative, indicating advances in phenology but reduced species performance. General sys-tem variance was also higher in the limnic biota than in the terrestrial biota, both exhibiting increasing variance up through the trophic system. Overall, our results suggest that multiple biotic responses to the climatic changes in this high-arctic ecosystem are not synchronised across trophic levels and may differ qualitatively and quantitatively between terrestrial and limnic biota.
    Polar Biology 08/2014; 37(8):1073-1082. DOI:10.1007/s00300-014-1501-2 · 1.59 Impact Factor
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    Jacob Nabe-Nielsen · Jakob Tougaard · Jonas Teilmann · Klaus Lucke · Mads C. Forchhammer ·
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    ABSTRACT: Animals often alternate between searching for food locally and moving over larger distances depending on the amount of food they find. This ability to switch movement strategy can have large implications on the fate of individuals and populations, and a mechanism that allows animals to find the optimal balance between alternative movement strategies is therefore selectively advantageous. Recent theory suggests that animals are capable of switching movement mode depending on heterogeneities in the landscape, and that different modes may predominate at different temporal scales. Here we develop a conceptual model that enables animals to use either an area-concentrated food search behavior or undirected random movements. The model enables animals to increase their food intake by fine-tuning the relative contribution of the two types of behavior. In contrast to most models of optimal foraging, our model does not assume food to be distributed in large, well-defined patches, and our focus is on how animals should move rather than on which patch is most profitable. We demonstrate how the model, which builds on the animals’ ability to remember the profitability and location of previously visited areas, is capable of producing home ranges and of generating realistic movement patterns for the harbor porpoise, both at fine and intermediate temporal scales.
    Oikos 09/2013; 122(9):1307-1316. DOI:10.1111/j.1600-0706.2013.00069.x · 3.44 Impact Factor
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    ABSTRACT: Advancing phenology in response to global warming has been reported across biomes, raising concerns about the temporal uncoupling of trophic interactions. Concurrently, widely reported flower visitor declines have been linked to resource limitations. Phenological responses in the Arctic have been shown to outpace responses from lower latitudes and recent studies suggest that differences between such responses for plants and their flower visitors could be particularly pronounced in the Arctic. The evidence for phenological uncoupling is scant because relevant data sets are lacking or not available at a relevant spatial scale. Here, we present evidence of a climate-associated shortening of the flowering season and a concomitant decline in flower visitor abundance based on a long-term, spatially replicated (1996-2009) data set from high-Arctic Greenland. A unique feature of the data set is the spatial and temporal overlap of independent observations of plant and insect phenology. The shortening of the flowering season arose through spatial variation in phenological responses to warming. The shorter flowering seasons may have played a role in the observed decline in flower visitor abundance. Our results demonstrate that the dramatic climatic changes currently taking place in the Arctic are strongly affecting individual species and ecological communities, with implications for trophic interactions.
    Nature Climate Change 08/2013; 3(8):759–763. DOI:10.1038/nclimate1909 · 14.55 Impact Factor
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    ABSTRACT: Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km(2) to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally, these data should be sampled to reflect variation in the underlying environment across large spatial extents, and at fine spatial resolution. Simplified ecosystems where there are relatively few interacting species and sometimes a wealth of existing ecosystem monitoring data (e.g. arctic, alpine or island habitats) offer settings where the development of modelling tools that account for biotic interactions may be less difficult than elsewhere.
    Biological Reviews 02/2013; 88:15-30. DOI:10.1111/j.1469-185X.2012.00235.x · 9.67 Impact Factor
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    ABSTRACT: Alpine and arctic lemming populations appear to be highly sensitive to climate change, and when faced with warmer and shorter winters, their well-known high-amplitude population cycles may collapse. Being keystone species in tundra ecosystems, changed lemming dynamics may convey significant knock-on effects on trophically linked species. Here, we analyse long-term (1988-2010), community-wide monitoring data from two sites in high-arctic Greenland and document how a collapse in collared lemming cyclicity affects the population dynamics of the predator guild. Dramatic changes were observed in two highly specialized lemming predators: snowy owl and stoat. Following the lemming cycle collapse, snowy owl fledgling production declined by 98 per cent, and there was indication of a severe population decline of stoats at one site. The less specialized long-tailed skua and the generalist arctic fox were more loosely coupled to the lemming dynamics. Still, the lemming collapse had noticeable effects on their reproductive performance. Predator responses differed somewhat between sites in all species and could arise from site-specific differences in lemming dynamics, intra-guild interactions or subsidies from other resources. Nevertheless, population extinctions and community restructuring of this arctic endemic predator guild are likely if the lemming dynamics are maintained at the current non-cyclic, low-density state.
    Proceedings of the Royal Society B: Biological Sciences 09/2012; 279(1746):4417-4422. DOI:10.1098/rspb.2012.1490 · 5.05 Impact Factor
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    ABSTRACT: Snow cover plays a major role in the climate, hydrological and ecological systems of the Arctic and other regions through its influence on the surface energy balance (e.g. reflectivity), water balance (e.g. water storage and release), thermal regimes (e.g. insulation), vegetation and trace gas fluxes. Feedbacks to the climate system have global consequences. The livelihoods and well-being of Arctic residents and many services for the wider population depend on snow conditions so changes have important consequences. Already, changing snow conditions, particularly reduced summer soil moisture, winter thaw events and rain-on-snow conditions have negatively affected commercial forestry, reindeer herding, some wild animal populations and vegetation. Reductions in snow cover are also adversely impacting indigenous peoples’ access to traditional foods with negative impacts on human health and well-being. However, there are likely to be some benefits from a changing Arctic snow regime such as more even run-off from melting snow that favours hydropower operations. KeywordsSnow–Arctic–Climate–Albedo–Hydrology–Ecology–Biogeochemical cycling–Geochemical processes–Forestry–Infrastructure–Tourism–Indigenous cultures–Human health
    AMBIO A Journal of the Human Environment 12/2011; 40:32-45. DOI:10.1007/s13280-011-0213-x · 2.29 Impact Factor
  • E. Post · P. Boving · S. M. Cahoon · J. Kerby · T. Hoye · M. Forchhammer · P. Sullivan · J. M. Welker ·
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    ABSTRACT: The study of phenology is a unifying discipline in ecology. Although studied most commonly as a response to environmental variation such as climate change, phenology is a conceptually powerful integrator of ecological dynamics across levels of biological organization. Here, we will present data from two long-term study sites in Greenland, where spring is advancing rapidly due to recent warming. Our results highlight important features of phenology as an integrator of ecological dynamics in the Arctic, from variation at the plant species level in time and space, to species interactions across trophic levels between plants and herbivores, to the importance of phenology in ecosystem carbon exchange. Beyond its role as a response variable and integrator of ecological dynamics, we suggest phenology is an important driver of ecological response to climate change.
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    Snow, Water, Ice and Permafrost in the Arctic (SWIPA): Climate Change and the Cryosphere, 11/2011: chapter 4: pages 4 1–4 58; Oslo: Arctic Monitoring and Assessment Programme., ISBN: 978-82-7971-071-4
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    D.K. Kristensen · E. Kristensen · M.C. Forchhammer · A. Michelsen · N.M. Schmidt ·
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    ABSTRACT: The use of stable isotopes in diet analysis usually relies on the different photosynthetic pathways of C3 and C4 plants, and the resulting difference in carbon isotope signature. In the Arctic, however, plant species are exclusively C3, and carbon isotopes alone are therefore not suitable for studying arctic herbivore diets. In this study, we examined the potential of both stable carbon and nitrogen isotopes to reconstruct the diet of an arctic herbivore, here the muskox (Ovibos moschatus (Zimmermann, 1780)), in northeast Greenland. The isotope composition of plant communities and functional plant groups was compared with those of muskox faeces and shed wool, as this is a noninvasive approach to obtain dietary information on different temporal scales. Plants with different root mycorrhizal status were found to have different δ15N values, whereas differences in δ13C, as expected, were less distinct. As a result, our examination mainly relied on stable nitrogen isotopes. The interpretation of stable isotopes from faeces was difficult because of the large uncertainty in diet–faeces fractionation, whereas isotope signatures from wool suggested that the muskox summer diet consists of around 80% graminoids and up to 20% willows. In conclusion, the diet composition of an arctic herbivore can indeed be inferred from stable isotopes in arctic areas, despite the lack of C4 plants.
    Canadian Journal of Zoology 09/2011; 89(10):892-899. DOI:10.1139/z11-073 · 1.30 Impact Factor
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    Niels M. Schmidt · Claudia Baittinger · Johannes Kollmann · Mads C. Forchhammer ·
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    ABSTRACT: Dendroclimatological reconstructions may be influenced by intraspecific variation in radial growth caused by plant gender and ecotypic differentiation. We examined the growth response of the High Arctic Salix arctica to interannual variation in snow precipitation in Zackenberg, NE Greenland. Tree ring examinations revealed a consistent response of annual radial growth in this dwarf shrub to variation in the amount of snow precipitation across gender and across three distinct vegetation types. Annual growth, however, differed between vegetation types. These results are discussed with respect to an improved understanding of the factors limiting the growth of S. arctica, which can be used for future reconstructions of climatic conditions, especially in remote High Arctic regions.
    Arctic Antarctic and Alpine Research 11/2010; 42(4):471-475. DOI:10.1657/1938-4246-42.4.471 · 1.52 Impact Factor
  • Jacob Nabe-Nielsen · Richard M Sibly · Mads C Forchhammer · Valery E Forbes ·
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    ABSTRACT: Background / Purpose: The shape, distribution and size of habitat patches affects the long-term dynamics of populations. This can only be studied using simulation modelling.Landscape fragmentation causes reduced equilibrium population sizes and slower return from disturbances, particularly in short-dispersing species. Main conclusion: The spatial configurations of landscapes influence the long-term conservation of species, and has the largest effect on short-dispersing species and species that depend on resources in multiple patch types.
    24th International Congress for Conservation Biology 2010 meeting; 07/2010
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    ABSTRACT: The effects of landscape modifications on the long-term persistence of wild animal populations is of crucial importance to wildlife managers and conservation biologists, but obtaining experimental evidence using real landscapes is usually impossible. To circumvent this problem we used individual-based models (IBMs) of interacting animals in experimental modifications of a real Danish landscape. The models incorporate as much as possible of the behaviour and ecology of four species with contrasting life-history characteristics: skylark (Alauda arvensis), vole (Microtus agrestis), a ground beetle (Bembidion lampros) and a linyphiid spider (Erigone atra). This allows us to quantify the population implications of experimental modifications of landscape configuration and composition. Starting with a real agricultural landscape, we progressively reduced landscape complexity by (i) homogenizing habitat patch shapes, (ii) randomizing the locations of the patches, and (iii) randomizing the size of the patches. The first two steps increased landscape fragmentation. We assessed the effects of these manipulations on the long-term persistence of animal populations by measuring equilibrium population sizes and time to recovery after disturbance. Patch rearrangement and the presence of corridors had a large effect on the population dynamics of species whose local success depends on the surrounding terrain. Landscape modifications that reduced population sizes increased recovery times in the short-dispersing species, making small populations vulnerable to increasing disturbance. The species that were most strongly affected by large disturbances fluctuated little in population sizes in years when no perturbations took place. Traditional approaches to the management and conservation of populations use either classical methods of population analysis, which fail to adequately account for the spatial configurations of landscapes, or landscape ecology, which accounts for landscape structure but has difficulty predicting the dynamics of populations living in them. Here we show how realistic and replicable individual-based models can bridge the gap between non-spatial population theory and non-dynamic landscape ecology. A major strength of the approach is its ability to identify population vulnerabilities not detected by standard population viability analyses.
    PLoS ONE 01/2010; 5(1):e8932. DOI:10.1371/journal.pone.0008932 · 3.23 Impact Factor
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    ABSTRACT: The climate effects research program in Zackenberg in high arctic Greenland got a counterpart in Nuuk in low arctic West Greenland in 2007. The programme NuukBasic is described and, for the first time, results will presented from several of the monitoring components (Table 1). In particular, we focus on changes in plant phenology, vegetation greenness, graded effects of UVB radiation and lake ecology. Results are compared and contrasted concurrent changes at the high arctic site Zackenberg in Northeast Greenland.Biological Monitoring elements in NuukBasis
  • M. C. Forchhammer · T. V. Callaghan · E. Post ·
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    ABSTRACT: It is well established that climate affects organisms in a wide range of different ways, including their distributions and, indeed, their performance (i.e. changes in growth, survival and reproduction). However, establishing whether species respond to changes in climate is not necessarily equal to establishing whether species performance is also affected. This argument also applies when climate effects are considered across trophic levels, such as consumer-resources interactions. For example, a phenological response of a plant may have no effect on its performance but may indeed have significant effects on herbivores. Here we emphasize and exemplify how the choice of a ``biological currency'' of climate change effects may be highly informative in one aspect but apparently useless in another. We do this by using the comprehensive data collected on plant species, large herbivore and their interactions at Zackenberg and Kangerlussuaq in Greenland.
  • T. T. Høye · N. M. Schmidt · M. C. Forchhammer · P. S. Bøving · E. Post ·
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    ABSTRACT: Seasonal timing of reproduction (phenology) is highly responsive to global warming, especially in the Arctic. Here, we present a comparative analysis of multi-annual observational data on phenological dynamics across trophic levels from Zackenberg, North-East Greenland (a High Arctic site) and Kangerlussuaq, West Greenland (a Low Arctic site). Both sites have experienced considerable warming and our analyses indicate that rates of change in plant phenological responses may differ between sites, related to different proximal drivers at the two sites. We also present parallel data on interacting organisms (pollinators and mammalian herbivores) to evaluate the risks and effects of trophic mismatch at these two sites.
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    ABSTRACT: At the close of the Fourth International Polar Year, we take stock of the ecological consequences of recent climate change in the Arctic, focusing on effects at population, community, and ecosystem scales. Despite the buffering effect of landscape heterogeneity, Arctic ecosystems and the trophic relationships that structure them have been severely perturbed. These rapid changes may be a bellwether of changes to come at lower latitudes and have the potential to affect ecosystem services related to natural resources, food production, climate regulation, and cultural integrity. We highlight areas of ecological research that deserve priority as the Arctic continues to warm.
    Science 10/2009; 325(5946):1355-8. DOI:10.1126/science.1173113 · 33.61 Impact Factor
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    ABSTRACT: Variation in carrying capacity and population return rates is generally ignored in traditional studies of population dynamics. Variation is hard to study in the field because of difficulties controlling the environment in order to obtain statistical replicates, and because of the scale and expense of experimenting on populations. There may also be ethical issues. To circumvent these problems we used detailed simulations of the simultaneous behaviours of interacting animals in an accurate facsimile of a real Danish landscape. The models incorporate as much as possible of the behaviour and ecology of skylarks Alauda arvensis, voles Microtus agrestis, a ground beetle Bembidion lampros and a linyphiid spider Erigone atra. This allows us to quantify and evaluate the importance of spatial and temporal heterogeneity on the population dynamics of the four species. Both spatial and temporal heterogeneity affected the relationship between population growth rate and population density in all four species. Spatial heterogeneity accounted for 23-30% of the variance in population growth rate after accounting for the effects of density, reflecting big differences in local carrying capacity associated with the landscape features important to individual species. Temporal heterogeneity accounted for 3-13% of the variance in vole, skylark and spider, but 43% in beetles. The associated temporal variation in carrying capacity would be problematic in traditional analyses of density dependence. Return rates were less than one in all species and essentially invariant in skylarks, spiders and beetles. Return rates varied over the landscape in voles, being slower where there were larger fluctuations in local population sizes. Our analyses estimated the traditional parameters of carrying capacities and return rates, but these are now seen as varying continuously over the landscape depending on habitat quality and the mechanisms of density dependence. The importance of our results lies in our demonstration that the effects of spatial and temporal heterogeneity must be accounted for if we are to have accurate predictive models for use in management and conservation. This is an area which until now has lacked an adequate theoretical framework and methodology.
    BMC Ecology 07/2009; 9(1):18. DOI:10.1186/1472-6785-9-18 · 2.36 Impact Factor
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    Ditte K Hendrichsen · Chris J Topping · Mads C Forchhammer ·
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    ABSTRACT: Statistical autoregressive analyses of direct and delayed density dependence are widespread in ecological research. The models suggest that changes in ecological factors affecting density dependence, like predation and landscape heterogeneity are directly portrayed in the first and second order autoregressive parameters, and the models are therefore used to decipher complex biological patterns. However, independent tests of model predictions are complicated by the inherent variability of natural populations, where differences in landscape structure, climate or species composition prevent controlled repeated analyses. To circumvent this problem, we applied second-order autoregressive time series analyses to data generated by a realistic agent-based computer model. The model simulated life history decisions of individual field voles under controlled variations in predator pressure and landscape fragmentation. Analyses were made on three levels: comparisons between predated and non-predated populations, between populations exposed to different types of predators and between populations experiencing different degrees of habitat fragmentation. The results are unambiguous: Changes in landscape fragmentation and the numerical response of predators are clearly portrayed in the statistical time series structure as predicted by the autoregressive model. Populations without predators displayed significantly stronger negative direct density dependence than did those exposed to predators, where direct density dependence was only moderately negative. The effects of predation versus no predation had an even stronger effect on the delayed density dependence of the simulated prey populations. In non-predated prey populations, the coefficients of delayed density dependence were distinctly positive, whereas they were negative in predated populations. Similarly, increasing the degree of fragmentation of optimal habitat available to the prey was accompanied with a shift in the delayed density dependence, from strongly negative to gradually becoming less negative. We conclude that statistical second-order autoregressive time series analyses are capable of deciphering interactions within and across trophic levels and their effect on direct and delayed density dependence.
    BMC Ecology 06/2009; 9(1):10. DOI:10.1186/1472-6785-9-10 · 2.36 Impact Factor
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Publication Stats

3k Citations
458.73 Total Impact Points


  • 1993-2014
    • Aarhus University
      • • Department of Bioscience
      • • Arctic Research Centre ARC
      • • Department of Ecology and Genetics
      Aarhus, Central Jutland, Denmark
  • 2013
    • University of Veterinary Medicine Hannover
      Hanover, Lower Saxony, Germany
  • 2011-2013
    • Greenland Institute of Natural Resources
      Nuuk, Sermersooq, Greenland
  • 2008-2010
    • Roskilde University
      • Centre for Integrated Population Ecology (CIPE)
      Roskilde, Zealand, Denmark
  • 2006-2009
    • Marine Environmental Research Institute
      Blue Hills, Connecticut, United States
  • 2002-2008
    • Pennsylvania State University
      • Department of Biology
      University Park, MD, United States
  • 2001-2008
    • IT University of Copenhagen
      København, Capital Region, Denmark
  • 1999-2002
    • University of Cambridge
      • Department of Zoology
      Cambridge, England, United Kingdom
  • 1997-2002
    • University of Oslo
      • • Centre for Ecological and Evolutionary Synthesis
      • • Department of Biosciences
      Kristiania (historical), Oslo, Norway
  • 2000
    • National Environmental Engineering Research Institute
      Ajni, Maharashtra, India