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Aim To demonstrate how the interrelations of individual movements form largescale population-level movement patterns and how these patterns are associated with the underlying landscape dynamics by comparing ungulate movements across species.Locations Arctic tundra in Alaska and Canada, temperate forests in Massachusetts, Patagonian Steppes in Argentina, Eastern Steppes in Mongolia. MethodsWe used relocation data from four ungulate species (barren-ground caribou, Mongolian gazelle, guanaco and moose) to examine individual movements and the interrelation of movements among individuals. We applied and developed a suite of spatial metrics that measure variation in movement among individuals as population dispersion, movement coordination and realized mobility. Taken together, these metrics allowed us to quantify and distinguish among different large-scale population-level movement patterns such as migration, range residency and nomadism. We then related the population-level movement patterns to the underlying landscape vegetation dynamics via long-term remote sensing measurements of the temporal variability, spatial variability and unpredictability of vegetation productivity. ResultsMoose, which remained in sedentary home ranges, and guanacos, which were partially migratory, exhibited relatively short annual movements associated with landscapes having very little broad-scale variability in vegetation. Caribou and gazelle performed extreme long-distance movements that were associated with broad-scale variability in vegetation productivity during the peak of the growing season. Caribou exhibited regular seasonal migration in which individuals were clustered for most of the year and exhibited coordinated movements. In contrast, gazelle were nomadic, as individuals were independently distributed and moved in an uncoordinated manner that relates to the comparatively unpredictable (yet broad-scale) vegetation dynamics of their landscape. Main conclusionsWe show how broad-scale landscape unpredictability may lead to nomadism, an understudied type of long-distance movement. In contrast to classical migration where landscapes may vary at broad scales but in a predictable manner, long-distance movements of nomadic individuals are uncoordinated and independent from other such individuals. Landscapes with little broad-scale variability in vegetation productivity feature smaller-scale movements and allow for range residency. Nomadism requires distinct integrative conservation strategies that facilitate long-distance movements across the entire landscape and are not limited to certain migration corridors.

Recent reviews stated that the complex and context-dependent nature of human decisionmaking resulted in ad-hoc representations of human decision in agent-based land use change models (LUCC ABMs) and that these representations are often not explicitly grounded in theory. However, a systematic survey on the characteristics (e.g. uncertainty, adaptation, learning, interactions and heterogeneities of agents) of the representation of human decision in LUCC ABMs is missing. To inform this debate we performed a quantitative review of 134 LUCC ABM papers using a standardised questionnaire with a particular focus on the characteristics and the theoretical foundation of human decision-making. Thereby, we investigated whether implementations of human decision-making in current LUCC ABMs are theory based. Additionally, we assessed to which degree key factors such as learning, interaction or economic, environmental or social influence factors are considered in human decision making sub-models. We show that most human decision sub-models are not explicitly based on a specific theory and if so they are mostly based on economic theories. In contrast, promising psychological theories such as the theory of planned behaviour are the exception. The key factors of human decision sub-models showed a huge diversity and are not strongly related to neither the characteristics of the specific studied systems (e.g. rural vs. urban or its geographic location) nor the applied theoretical paradigm. We finish by presenting approaches for consolidating and enlarging the theoretical basis for modelling human decision-making.

Animal migration is a global phenomenon, but few studies have examined the substantial withinand between-species variation in migration distances. We built a global database of 94 land migrations of large mammalian herbivore populations ranging from 10 to 1638 km. We examined how resource availability, spatial scale of resource variability and body size affect migration distance among populations. Resource availability measured as normalised difference vegetation index had a strong negative effect, predicting a tenfold difference in migration distances between low-and high-resource areas and explaining 23% of the variation in migration distances. We found a weak, positive effect of the spatial scale of resource variability but no effect of body size. Resource-poor environments are known to increase the size of mammalian home ranges and territories. Here, we demonstrate that for migratory populations as well, animals living in resource-poor environments travel farther to fulfil their resource needs.

Weise, H. (2014). Standardised and transparent model descriptions for agent-based models: Current status and prospects. ENVIRONMENTAL MODELLING AND SOFTWARE, 55, 156-163. https://doi.org/10.1016/j.envsoft.2014 Citing this paper Please note that where the full-text provided on King's Research Portal is the Author Accepted Manuscript or Post-Print version this may differ from the final Published version. If citing, it is advised that you check and use the publisher's definitive version for pagination, volume/issue, and date of publication details. And where the final published version is provided on the Research Portal, if citing you are again advised to check the publisher's website for any subsequent corrections. General rightsCopyright and moral rights for the publications made accessible in the Research Portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognize and abide by the legal requirements associated with these rights.•Users may download and print one copy of any publication from the Research Portal for the purpose of private study or research.•You may not further distribute the material or use it for any profit-making activity or commercial gain •You may freely distribute the URL identifying the publication in the Research Portal Take down policy If you believe that this document breaches copyright please contact librarypure@kcl.ac.uk providing details, and we will remove access to the work immediately and investigate your claim.

Long-term trends in photosynthetic capacity measured with the satellite-derived Normalized Difference Vegetation Index (NDVI) are usually associated with climate change. Human impacts on the global land surface are typically not accounted for. Here, we provide the first global analysis quantifying the effect of the earth's human footprint on NDVI trends. Globally, more than 20% of the variability in NDVI trends was explained by OPEN ACCESS Remote Sens. 2014, 6 5718 anthropogenic factors such as land use, nitrogen fertilization, and irrigation. Intensely used land classes, such as villages, showed the greatest rates of increase in NDVI, more than twice than those of forests. These findings reveal that factors beyond climate influence global long-term trends in NDVI and suggest that global climate change models and analyses of primary productivity should incorporate land use effects.

Enduring sustainability challenges requires a new model of collective leadership that embraces critical reflection, inclusivity and care. Leadership collectives can support a move in academia from metrics to merits, from a focus on career to care, and enact a shift from disciplinary to inter- and trans-disciplinary research. Academic organisations need to reorient their training programs, work ethics and reward systems to encourage collective excellence and to allow space for future leaders to develop and enact a radically re-imagined vision of how to lead as a collective with care for people and the planet.

Abstract. Effective disaster management is a core feature for the protection of communities against natural disasters such as floods. Disaster management organizations (DMOs) are expected to contribute to ensuring this protection. However, what happens when their resources to cope with a flood are at stake or the intensity and frequency of the event exceeds their capacities? Many cities in the Free State of Saxony, Germany, were strongly hit by several floods in the last years and are additionally challenged by demographic change, with an ageing society and out-migration leading to population shrinkage in many parts of Saxony. Disaster management, which is mostly volunteer-based in Germany, is particularly affected by this change, leading to a loss of members. We propose an agent-based simulation model that acts as a "virtual lab" to explore the impact of various changes on disaster management performance. Using different scenarios we examine the impact of changes in personal resources of DMOs, their access to operation relevant information, flood characteristics as well as differences between geographic regions. A loss of DMOs and associated manpower caused by demographic change has the most profound impact on the performance. Especially in rural, upstream regions population decline in combination with very short lead times can put disaster management performance at risk.