Abstract. The open-source modeling framework MAgPIE (Model of Agricultural Production and its Impact on the Environment) combines economic and biophysical approaches to simulate spatially explicit global scenarios of land use within the 21st century and the respective interactions with the environment. Besides various other projects, it was used to simulate marker scenarios of the Shared Socioeconomic Pathways (SSPs) and contributed substantially to multiple IPCC assessments. However, with growing scope and detail, the non-linear model has become increasingly complex, computationally intensive and non-transparent, requiring structured approaches to improve the development and evaluation of the model.Here, we provide an overview on version 4 of MAgPIE and how it addresses these issues of increasing complexity using new technical features: modular structure with exchangeable module implementations, flexible spatial resolution, in-code documentation, automatized code checking, model/output evaluation and open accessibility. Application examples provide insights into model evaluation, modular flexibility and region-specific analysis approaches. While this paper is focused on the general framework as such, the publication is accompanied by a detailed model documentation describing contents and equations, and by model evaluation documents giving insights into model performance for a broad range of variables.With the open-source release of the MAgPIE 4 framework, we hope to contribute to more transparent, reproducible and collaborative research in the field. Due to its modularity and spatial flexibility, it should provide a basis for a broad range of land-related research with economic or biophysical, global or regional focus.

Abstract. The open source modeling framework MAgPIE combines economic and biophysical approaches to simulate spatially-explicit global scenarios of landuse within the 21st century and the respective interactions with the environment. Besides various other projects, it was used to simulate marker scenarios of the Shared Socio-economic Pathways (SSPs) and contributed substantially to multiple IPCC assessments. However, with growing scope and detail, the non-linear model has become increasingly complex, computational intensive, and intransparent, requiring structured approaches to improve the development and evaluation of the model. Here we provide an overview on version 4 of MAgPIE, and how it addresses these issues of increasing complexity using new technical features: modular structure, flexible detail in process dynamics, flexible spatial resolution, in-code documentation, automatized code-checking, model/output evaluation, and open accessibility. Application examples provide insights into model evaluation and region-specific analysis approaches. While this paper is focused on the general framework as such, the publication is accompanied by a detailed model documentation describing contents and equations, and by model evaluation documents giving insights into model performance for a broad range of variables. With the open source release of the MAgPIE 4 framework we hope to contribute to more transparent, reproducible and collaborative research in the field. Due to its modularity and spatial flexibility it should provide a basis for a broad range of land-related research with economic or biophysical, global or regional focus.

Estimating the investments needed to achieve the Sustainable Development Goals (SDGs) is key to mobilising the financial resources to achieve them. Despite an increasing body of research to estimate the capital and operational costs towards achieving various related SDG targets individually and collectively, an overview of the total estimated investment needs at the global scale has not been conducted since the adoption of SDGs in 2015. This study provides such an overview. Estimates for investment needs are found for nine goals: SDG 2 (zero hunger), SDG 3 (good health and well-being), SDG 4 (quality education), SGD 6 (clean water and sanitation), SDG7 (access to energy), SDG 9 (infrastructure), SDG 13 (climate action), SDG 14 (life below water), and SDG 15 (life on land). The reviewed studies vary significantly in terms of applied methodology, the assumed targets that need to be achieved, and presented estimates, but overall they indicate significantly higher investment needs to achieve all covered SDGs than previous estimates suggest. For most SDGs, annual investment needs are in the order of hundreds of billion USD annually, and for SDG6 and SDG13 estimates of a trillion or more are reported.

Tropical forests are key habitats for diverse organisms, and because of their wide global distribution, rich biodiversity, and long history of human use, they are also essential for providing a wide range of ecosystem services (ESs;Brandon, 2015; Brockerhoff et al., 2017;Gibson et al., 2011;Mori et al., 2017). Considerable attention has been devoted to tropical forests and their role as a natural climate solution for mitigating climate change. It is estimated that about 30% of all CO 2 emitted by human activities is removed from the atmosphere by these forests (Le Quéré et al., 2018). The important role of tropical forests as a carbon sink and stock has historically guided conservation pacts, programs, and policies for establishing targets associated with carbon storage and climate change mitigation. This role was important in developing several articles of the 1997 Kyoto Protocol (Swingland et al., 2002) and explicit policies for reducing emissions from deforestation and forest degradation through the REDD+ agreement (Pistorius, 2012). Several countries also set ambitious goals for restoring forests to reduce emissions or sequester carbon in the United Nations Framework Convention on Climate Change 2015 Paris Agreement. The land use, land cover change, and forestry (LULCCF) sector is included in many countries' first nationally determined contributions (NDCs) but with differing levels of specificity. Assuming full implementation of NDCs, Grassi et al. (2017) show that land use-and forests, in particular-emerges as a key component of the Paris Agreement: global land use will turn from a net anthropogenic source during 1990-2010 (1.3 ± 1.1 Gt CO 2 e yr −1 ) to a net sink of carbon by 2030 (up to −1.1 ± 0.5 Gt CO 2 e yr −1 ) and would provide a quarter of countries' planned emission reductions. Two tropical countries stand out regarding the magnitude of the LULCCF contribution: Brazil set ambitious goals of reducing greenhouse gas emissions by 43% by 2030 with