Why ‘blended finance’ could help transitions to sustainable landscapes: Lessons from the Unlocking Forest Finance project

There is a momentum towards finding financing solutions for halting deforestation at the landscape level for the benefit of climate, biodiversity and delivery of ecosystem services. The Unlocking Forest Finance (UFF) project has, between 2013 and 2018, worked on the development of innovative financing mechanisms for sustainable landscapes in three sub-national Amazon regions of Brazil (Acre and Mato Grosso) and Peru (San Martín). This paper describes the approach of the UFF project as a case study of sustainable landscape financing, and portrays the key evolutions during the process. Relying on a reflection and consultation process among project partners, the paper then derives a set of lessons for sustainable landscape finance. It illustrates the current mismatch between the demand side of private ‘impact’ investors (i.e., those who look for social and environmental impact of investments beyond financial return) and the supply side of sustainable land use investments on the ground. The paper discusses how ‘blended finance’ models that combine funding from commercial, public, and philanthropic sources could contribute to financing sustainable landscapes

GPS receivers for georeferencing of spatial variability of soil attributes Receptores GPS para georreferenciamento da variabilidade espacial de atributos do solo

The characterization of the spatial variability of soil attributes is essential to support agricultural practices in a sustainable manner. The use of geostatistics to characterize spatial variability of these attributes, such as soil resistance to penetration (RP) and gravimetric soil moisture (GM) is now usual practice in precision agriculture. The result of geostatistical analysis is dependent on the sample density and other factors according to the georeferencing methodology used. Thus, this study aimed to compare two methods of georeferencing to characterize the spatial variability of RP and GM as well as the spatial correlation of these variables. Sampling grid of 60 points spaced 20 m was used. For RP measurements, an electronic penetrometer was used and to determine the GM, a Dutch auger (0.0-0.1 m depth) was used. The samples were georeferenced using a GPS navigation receiver, Simple Point Positioning (SPP) with navigation GPS receiver, and Semi-Kinematic Relative Positioning (SKRP) with an L1 geodetic GPS receiver. The results indicated that the georeferencing conducted by PPS did not affect the characterization of spatial variability of RP or GM, neither the spatial structure relationship of these attributes.<br>A caracterização da variabilidade espacial dos atributos do solo é indispensável para subsidiar práticas agrícolas de maneira sustentável. A utilização da geoestatística para caracterizar a variabilidade espacial desses atributos, como a resistência mecânica do solo à penetração (RP) e a umidade gravimétrica do solo (UG), é, hoje, prática usual na agricultura de precisão. O resultado da análise geoestatística é dependente da densidade amostral e de outros fatores, como o método de georreferencimento utilizado. Desta forma, o presente trabalho teve como objetivo comparar dois métodos de georreferenciamento para a caracterização da variabilidade espacial da RP e da UG, bem como a correlação espacial dessas variáveis. Foi implantada uma malha amostral de 60 pontos, espaçados em 20 m. Para as medições da RP, utilizou-se de penetrógrafo eletrônico e, para a determinação da UG, utilizou-se de trado holandês (profundidade de 0,0-0,1 m). As amostras foram georreferenciadas, utilizando-se do método de Posicionamento por Ponto Simples (PPS), com de (retirar) receptor GPS de navegação, e Posicionamento Relativo Semicinemático, com receptor GPS geodésico L1. Os resultados indicaram que o georreferenciamento realizado pelo PPS não interferiu na caracterização da variabilidade espacial da RP e da UG, assim como na estrutura espacial da relação dos atributos