Forest management and future changes to ecosystem services in the Romanian Carpathians

This study investigates consequences of future changes to the provision of ecosystem services (ES) in the Romanian Carpathians. Two 2040 forest management scenarios were compared, using two indicators to describe the gains and losses of ES. Changes in landslide regulation potential were defined as changes to landslide susceptibility. High nature value grasslands characterized biodiversity support. The business as usual scenario results in a 8% lower loss of landslide regulation potential compared to the alternative scenario. It also results in a 29% higher regional net gain of landslide regulation potential. Both scenarios result in the loss of biodiversity support due to their prevalent transition of forest expansion. This type of information is crucial for informing decision makers on the locations of potential gains and losses of future development

How will land degradation neutrality change future land system patterns?:A scenario simulation study

Land degradation is a major global issue and achieving a land degradation-neutral world is one of the Sustainable Development Goals. However, striving for land degradation neutrality (LDN) is challenged by increasing claims on land resources and could result in major land use conflicts. The aim of this study is to demonstrate how LDN can be implemented in land system modelling and how achieving LDN alongside sufficient supplies of food, timber and shelter could affect future land system patterns, using the Republic of Turkey as a case study. We developed a LDN scenario with full implementation of the guidelines and a business-as-usual scenario without pursuing LDN, and compared the resulting differences in land system changes. Additionally, the influence of different elements of the LDN framework on the land use projections was tested. Our results show that although it is possible to achieve LDN in the context of increasing demands for resources and housing, it might require a considerable re-organization of the land systems. Intensification of annual cropland systems was the main driver of new land degradation, which was in the LDN scenario primarily counterbalanced by large areas of afforestation, while other land improvement options only played a minor role. To achieve a no-net-loss, about 20% of Turkey’s territory was afforested in our scenario, mainly claiming extensively used annual cropland (~70%) and grassland (~30%). All individual LDN principles had a substantial impact on the final land system patterns meaning that the final outcome is not the result of just one of the principles, it is affected by all. Our findings suggest that pursuing LDN under growing demands for land-based products could stimulate a land sparing approach which might have trade-offs with other sustainability dimensions. This highlights the need for local support and new solutions for rural areas, thereby avoiding poverty, migration and illegal use of restoration areas

An Amazon Tipping Point: The Economic and Environmental Fallout

The Amazon biome, despite its resilience, is being pushed by unsustainable economic drivers towards an ecological tipping point where restoration to its previous state may no longer possible. This is the result of self-reinforcing interactions between deforestation, climate change and fire. In this paper, we develop scenarios that represent movement towards an Amazon tipping point and strategies to avert one. We assess the economic, natural capital and ecosystem services impacts of these scenarios using the Integrated Economic-Environmental Modeling (IEEM) Platform linked with high resolution spatial land use land cover change and ecosystem services modeling (IEEM+ESM). This paper’s main contributions are developing: (i) a framework for evaluating strategies to avert an Amazon tipping point based on their relative costs, benefits and trade-offs, and; (ii) a first approximation of the economic, natural capital and ecosystem services impacts of movement towards an Amazon tipping point, and evidence to build the economic case for strategies to avert it. We find that a conservative estimate of the cumulative regional cost through 2050 of an Amazon tipping point would be US$256.6 billion in Gross Domestic Product. Policies that would contribute to averting a tipping point, including strongly reducing deforestation, investing in climate-adapted agriculture, and improving fire management, would generate approximately US$339.3 billion in additional wealth. From a public investment perspective, the returns to implementing strategies for averting a tipping point would be US$29.5 billion. Quantifying the costs, benefits and trade-offs of policies to avert a tipping point in a transparent and replicable manner can pave the way for evidence-based approaches to support policy action focusing on the design of regional strategies for the Amazon biome and catalyze global cooperation and financing to enable their implementation.Centro de Estudios Distributivos, Laborales y Sociale

Global forest management data for 2015 at a 100 m resolution

Spatially explicit information on forest management at a global scale is critical for understanding the status of forests, for planning sustainable forest management and restoration, and conservation activities. Here, we produce the first reference data set and a prototype of a globally consistent forest management map with high spatial detail on the most prevalent forest management classes such as intact forests, managed forests with natural regeneration, planted forests, plantation forest (rotation up to 15 years), oil palm plantations, and agroforestry. We developed the reference dataset of 226 K unique locations through a series of expert and crowdsourcing campaigns using Geo-Wiki (https://www.geo-wiki.org/). We then combined the reference samples with time series from PROBA-V satellite imagery to create a global wall-to-wall map of forest management at a 100 m resolution for the year 2015, with forest management class accuracies ranging from 58% to 80%. The reference data set and the map present the status of forest ecosystems and can be used for investigating the value of forests for species, ecosystems and their services

Understanding Land Cover Changes in the Italian Alps and Romanian Carpathians Combining Remote Sensing and Stakeholder Interviews

In the last two decades, socio-economic changes in Europe have had a significant effect on land cover changes, but it is unclear how this has affected mountain areas. We focus on two mountain areas: the eastern Italian Alps and the Romanian Curvature Carpathians. We classified land cover from Earth observation data after 1989 by using applied remote sensing techniques. We also analyzed socio-economic data and conducted semi-structured interviews with local stakeholders. In Italy, most of the land conversion processes followed long-term trends. In Romania, they took off with the sudden political changes after 1989. In both areas, forest expansion was the biggest, but potentially not the most consequential change. More consequential changes were urbanization in Italy and small-scale deforestation in Romania, since both increased the risk of hydro-meteorological hazards. Stakeholders’ views were an added value to the spatial analysis and vice versa. For example, stakeholders’ explanations resolved the seeming contradiction of decreased economic activity and increased urbanization (Italian site), as a consequence of secondary home building. Furthermore, spatial analysis revealed that urbanization in Romania was less significant with regard to consequences for the wider human-environment system than many stakeholders thought

Representing responses to climate change in spatial land system models

Modelling future change to land use and land cover is done as part of many local and global scenario environmental assessments. Nevertheless, there are still considerable challenges related to simulating land-use responses to climate change. Mostly, climate change is considered by changing the temperature and precipitation, affecting the spatial distribution and productivity of future land use and land cover as result of differential changes in growing conditions. Other climate change effects, such as changes in the water resources needed to support future cropland expansion and intensification, are often neglected. In this study, we demonstrate how including different types of responses to climate change influences the simulation of future changes to land use and land cover, and land management. We study the influence of including different climate change effects in land system modeling step by step. The results show that land system models need to include numerous simultaneous climate change effects, particularly when looking at adaptation options such as implementing irrigation. Otherwise, there is a risk of biased impact estimates leading either to under- or overestimation of the consequences of land use change, including land degradation. Spatial land system models therefore need to be developed accounting for a multitude of climate change impacts, uncertainties related to climate data, and an assessment of the sensitivity of the outcomes toward the decisions of modellers on representing climate change impacts

Mapping global patterns of land use decision-making

Humans have changed most of the terrestrial surface by changing land-use and land-cover. The spatial distribution and extent of land-cover changes have been studied and mapped widely, using remote sensing and geospatial technologies. Although there are numerous studies on the human decisions underlying such changes, they are limited to local case-studies. How such local-scale patterns of decision-making can be used to explain land-use change globally is unknown. Using a collection of local studies from a literature review, we studied the contextual conditions of different modes of land-use change decision-making and present global maps of the potential distribution of decision-making in land-use change. We find that decision-making in land-use can be explained, to a large extent, by the socio-economic, climatic and soil conditions of a location, captured by global data proxies of these conditions. Survival and livelihood objectives are positively associated to the spatial variation in childhood malnutrition and distance to roads, and negatively to total economic output of an area. Economic objectives on the other hand, are positively associated to total economic output, but also to the annual precipitation at the location. Similar trends are observed when looking at more detailed decision-making types: survivalist, subsistence-oriented and market-oriented smallholder decision-making types are more likely found in areas with higher poverty levels and overall lower levels of socio-economic development. The spatial distribution can be used to understand the occurrence of land-use intensification trajectories and to account for variation in decision-making in global land-use models. Finally, we provide a representation of the spread of case-studies and which contexts are poorly represented by case-studies