Detecting northern peatland vegetation patterns at ultra-high spatial resolution

Peer reviewe

State-wide calculation of terrain-visualisations and automatic map generation for archaeological objects

Airborne laser scanning (ALS) became very popular in the last two decades for archaeological prospection. With the state-wide availability of ALS-data in Lower Saxony, Germany, about 48,000 km2;, we needed flexible and scalable approaches to process the data. First, we produced a state-wide digital terrain model (DTM) and some visualisations of it to use it in standard GIS software. Some of these visualisations are available as web maps and used for prospection also by volunteers. In a second approach, we automatically generate maps for all known archaeological objects. This is mainly used for the documentation of the 130,000 known objects in Lower Saxony, but also for object-by-object revision of the database. These Maps will also be presented in the web portal "Denkmalatlas Niedersachsen", an open data imitative of the state Lower Saxony.In the first part of this paper, we show how the state-wide DTM and its visualisations can be calculated using tiles. In the second part, we describe the automatic map generation process. All implementations were done with ArcGIS and its scripting interface ArcPy

Describing complex interactions of social-ecological systems for tipping point assessments: an analytical framework

Humans play an interconnecting role in social-ecological systems (SES), they are part of these systems and act as agents of their destruction and regulation. This study aims to provide an analytical framework, which combines the concept of SES with the concept of tipping dynamics. As a result, we propose an analytical framework describing relevant dynamics and feedbacks within SES based on two matrixes: the “tipping matrix” and the “cross-impact matrix.” We take the Southwestern Amazon as an example for tropical regions at large and apply the proposed analytical framework to identify key underlying sub-systems within the study region: the soil ecosystem, the household livelihood system, the regional social system, and the regional climate system, which are interconnected through a network of feedbacks. We consider these sub-systems as tipping elements (TE), which when put under stress, can cross a tipping point (TP), resulting in a qualitative and potentially irreversible change of the respective TE. By systematically assessing linkages and feedbacks within and between TEs, our proposed analytical framework can provide an entry point for empirically assessing tipping point dynamics such as “tipping cascades,” which means that the crossing of a TP in one TE may force the tipping of another TE. Policy implications: The proposed joint description of the structure and dynamics within and across SES in respect to characteristics of tipping point dynamics promotes a better understanding of human-nature interactions and critical linkages within regional SES that may be used for effectively informing and directing empirical tipping point assessments, monitoring or intervention purposes. Thereby, the framework can inform policy-making for enhancing the resilience of regional SES

Describing complex interactions of social-ecological systems for tipping point assessments: an analytical framework

Humans play an interconnecting role in social-ecological systems (SES), they are part of these systems and act as agents of their destruction and regulation. This study aims to provide an analytical framework, which combines the concept of SES with the concept of tipping dynamics. As a result, we propose an analytical framework describing relevant dynamics and feedbacks within SES based on two matrixes: the “tipping matrix” and the “cross-impact matrix.” We take the Southwestern Amazon as an example for tropical regions at large and apply the proposed analytical framework to identify key underlying sub-systems within the study region: the soil ecosystem, the household livelihood system, the regional social system, and the regional climate system, which are interconnected through a network of feedbacks. We consider these sub-systems as tipping elements (TE), which when put under stress, can cross a tipping point (TP), resulting in a qualitative and potentially irreversible change of the respective TE. By systematically assessing linkages and feedbacks within and between TEs, our proposed analytical framework can provide an entry point for empirically assessing tipping point dynamics such as “tipping cascades,” which means that the crossing of a TP in one TE may force the tipping of another TE. Policy implications: The proposed joint description of the structure and dynamics within and across SES in respect to characteristics of tipping point dynamics promotes a better understanding of human-nature interactions and critical linkages within regional SES that may be used for effectively informing and directing empirical tipping point assessments, monitoring or intervention purposes. Thereby, the framework can inform policy-making for enhancing the resilience of regional SES

Diverging climate trends in Mongolian taiga forests influence growth and regeneration of Larix sibirica

Central and semiarid north-eastern Asia was subject to twentieth century warming far above the global average. Since forests of this region occur at their drought limit, they are particularly vulnerable to climate change. We studied the regional variations of temperature and precipitation trends and their effects on tree growth and forest regeneration in Mongolia. Tree-ring series from more than 2,300 trees of Siberian larch (Larix sibirica) collected in four regions of Mongolia’s forest zone were analyzed and related to available weather data. Climate trends underlie a remarkable regional variation leading to contrasting responses of tree growth in taiga forests even within the same mountain system. Within a distance of a few hundred kilometers (140–490 km), areas with recently reduced growth and regeneration of larch alternated with regions where these parameters remained constant or even increased. Reduced productivity could be correlated with increasing summer temperatures and decreasing precipitation; improved growth conditions were found at increasing precipitation, but constant summer temperatures. An effect of increasing winter temperatures on tree-ring width or forest regeneration was not detectable. Since declines of productivity and regeneration are more widespread in the Mongolian taiga than the opposite trend, a net loss of forests is likely to occur in the future, as strong increases in temperature and regionally differing changes in precipitation are predicted for the twenty-first century

Microtopographic drivers of vegetation patterning in blanket peatlands recovering from erosion

Blanket peatlands are globally rare, and many have been severely eroded. Natural recovery and revegetation (‘self-restoration’) of bare peat surfaces are often observed but are poorly understood, thus hampering the ability to reliably predict how these ecosystems may respond to climatic change. We hypothesised that morphometric/topographic-related microclimatic variables may be key controls on successional pathways and vegetation patterning in self-restoring blanket peatlands. We predicted the occurrence probability of four common peatland plant species (Calluna vulgaris, Eriophorum vaginatum, Eriophorum angustifolium, and Sphagnum spp.) using a digital surface model (DSM) generated from drone imagery at a pixel size of 20 cm, a suite of variables derived from the DSM, and an ensemble learning method (random forests). All four species models provided accurate fine-scale predictions of habitat suitability (accuracy > 90%, area under curve (AUC) > 0.9, recall and precision > 0.8). Mean elevation (within a 1 m radius) was often the most influential variable. Topographic position, wind exposure, and the heterogeneity or ruggedness of the surrounding surface were also important for all models, whilst light-related variables and a wetness index were important in the Sphagnum model. Our approach can be used to improve prediction of future responses and sensitivities of peatland recovery to climatic changes and as a tool to identify areas of blanket peatlands that may self-restore successfully without management intervention