Vanilla distribution modeling for conservation and sustainable cultivation in a joint land sparing/sharing concept

Vanilla, an expensive but popular spice used in many industries, faces problems related to its supply. Some of these problems are due to the fact that vanilla cultivation is based on clonal material of a single species (Vanilla planifolia) and is dominated by just a few countries located outside the native grow- ing areas of aromatic vanilla species, which is the neotropics. Despite the economic importance of this crop, relatively little attention has been paid to its wild relatives, in particular with respect to their biology, ecol- ogy, and potential use. We hypothesized that species distribution models (SDMs) can identify suitable areas for both the conservation and cultivation of vanilla crop wild relatives (CWRs), following a joint land sparing/land sharing (SPASHA) approach, thus offering alternative sourcing areas and production meth- ods. This is the first study that explored the use of ensemble SDMs to provide applicable land use maps related to the conservation and sustainable cultivation of wild vanilla species in Costa Rica, contributing to a solution for the problems related to current vanilla production systems. We focused on four aromatic vanilla CWRs, native to Costa Rica, to make land use policy recommendations for this country, and more specifically for the biological corridor Osa and its surroundings within our study region Area de Conser- vacio n Osa (ACOSA). The resulting distribution maps, with a mean AUC of 0.89, reflected their current potential distribution (ranging from unsuitable to suitable) in Costa Rica. Combining them with recent land use and conservation area maps of our study region, we defined (1) areas for vanilla conservation and (2) areas for sustainable vanilla cultivation within agroforestry systems. These land use recommendations can now be integrated within the National Bio-Corridor Program (PNCB) that aims at making biological corridors more productive by proposing alternative income generation for local communities living within these areas. Our approach can be applied to identify priority areas for implementing the SPASHA approach on other vanilla CWRs and in more regions across its native growing ranges, given the availabil- ity of land use maps and enough occurrence records to build accurate SDMs.UCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Agroalimentarias::Jardín Botánico Lankester (JBL

Efectos del cambio climático en la distribución de 20 especies de aves de la región amazónica del Perú

OBJETIVO El objetivo del estudio es evaluar los efectos del cambio climático en la distribución de las poblaciones silvestres de 20 especies de aves. ÁREA DE ESTUDIO El área de estudio es el bosque de las regiones Amazónicas de Huánuco, Amazonas, Junín, Loreto, Madre de Dios, Pasco, San Martín y Ucayali. SELECCIÓN DE LAS 20 ESPECIES Inicialmente, se colectaron los puntos de presencia de todas las especies de aves en la Amazonía peruana según eBird/Clements Checklist (Clements et al., 2019). Los puntos de presencia fueron obtenidos de las siguientes bases de datos: GBIF (Global Biodiversity Information Facility; www.gbif.org), e Inventario Nacional Forestal y de Fauna Silvestre del SERFOR. Luego de colectar los datos, se procedió con la selección de las especies para el modelamiento de acuerdo a los siguientes criterios: (i) que las especies estén amenazadas según el Libro Rojo de la Fauna Silvestre Amenazada del Perú (SERFOR, 2018), (ii) que existan como mínimo 15 puntos de presencia, y (iii) que por lo menos la mitad de los puntos de presencia se encuentren ubicados en la Amazonía. Las siguientes 20 especies cumplieron los criterios y fueron utilizadas para el modelamiento

Climate change impact on cultivated and wild cacao in Peru and the search of climate change-tolerant genotypes

Aim: Cacao (Theobroma cacao L.) is expected to be vulnerable to climate change. The objectives of this study were to (a) assess the future impact of climate change on cacao in Peru and (b) identify areas where climate change-tolerant genotypes are potentially present. Location: Peru Methods: Drawing on 19,700 and 1,200 presence points of cultivated and wild cacao, respectively, we modelled their suitability distributions using multiple en semble models constructed based on both random and target group selection of pseudo-absence points and different resolutions of spatial filtering. To estimate the uncertainty of future predictions, we generated future projections for all the ensem ble models. We investigated the potential emergence of novel climates, determined expected changes in ecogeographical zones (zones representative for particular sets of growth conditions) and carried out an outlier analysis based on the environmental variables most relevant for climate change adaptation to identify areas where climate change-tolerant genotypes are potentially present. Results: We found that the best modelling approaches differed between cultivated and wild cacao and that the resolution of spatial filtering had a strong impact on future suitability predictions, calling for careful evaluation of the effect of model selection on modelling results. Overall, our models foresee a contraction of suitable area for cultivated cacao while predicting a more positive future for wild cacao in Peru. Ecogeographical zones are expected to change in 8%–16% of the distribution of cultivated and wild cacao. We identified several areas where climate change-tolerant genotypes may be present in Peru. Main conclusions: Our results indicate that tolerant genotypes will be required to facilitate the adaptation of cacao cultivation under climate change. The identified cacao populations will be target of collection missions

Efectos del cambio climático en la distribución de 20 especies forestales maderables de la región amazónica del Perú

OBJETIVO: El objetivo del estudio es evaluar los efectos del cambio climático en la distribución de las poblaciones silvestres de 20 especies de árboles. ÁREA DE ESTUDIO: El área de estudio es el bosque de las regiones amazónicas de Huánuco, Amazonas, Junín, Loreto, Madre de Dios, Pasco, San Martín y Ucayali. SELECCIÓN DE LAS 20 ESPECIES : Inicialmente, se colectaron los puntos de presencia de todas las especies de árboles en la Amazonía peruana, según la lista nacional de Perú (Brako & Zarucchi, 1993). Los puntos de presencia fueron obtenidos de las siguientes bases de datos: GBIF (Global Biodiversity Information Facility; www.gbif.org), BIEN (Botanical Information and Ecology Network; http://biendata.org/), Inventario Nacional Forestal y de Fauna Silvestre del SERFOR, y la Base de Datos Espaciales del Organismo de Supervisión de los Recursos Forestales y de Fauna Silvestre (OSINFOR). Luego de colectar los datos, se procedió con la selección de las especies para el modelamiento de acuerdo a los siguientes criterios: (i) que las especies tengan un grado de amenaza según el Decreto Supremo Nº 043-2006-AG AG o estén identificadas como especies forestales de acuerdo a la Resolución Ejecutiva N°118-2019-MINAGRI-SERFOR-DE, (ii) que existan como mínimo 15 puntos de presencia, y (iii) que por lo menos la mitad se encuentren ubicados en la Amazonía. Las siguientes 20 especies cumplieron los criterios y fueron utilizadas para el modelamiento

Food tree species selection for nutrition-sensitive forest landscape restoration in Burkina Faso

Modern food systems push agriculture to focus on a small number of commercial crops, while there is a very large diversity of untapped edible plants that could be used to address food security and nutrition. Poor and monotonous diets are closely linked to the complex burden of multiple forms of malnutrition and dietary risk. In some contexts, such as West Africa, micronutrient deficiency risks are particularly pronounced. Hence, there is an urgent need to provide people with healthy diets supported by sustainable food systems. Within this context, using nutrition-sensitive forest landscape restoration to combat environmental degradation could contribute towards ensuring the year-round availability of nutritious tree-based food

Diversity for Restoration (D4R): guiding the selection of tree species and seed sources for climate-resilient restoration of tropical forest landscapes

1. At the start of the UN Decade of Ecosystem Restoration (2021–2030), the restoration of degraded ecosystems is more than ever a global priority. Tree planting will make up a large share of the ambitious restoration commitments made by countries around the world, but careful planning is needed to select species and seed sources that are suitably adapted to present and future restoration site conditions and that meet the restoration objectives. 2. Here we present a scalable and freely available online tool, Diversity for Restoration (D4R), to identify suitable tree species and seed sources for climate-resilient tropical forest landscape restoration. 3. The D4R tool integrates (a) species habitat suitability maps under current and future climatic conditions; (b) analysis of functional trait data, local ecological knowledge and other species characteristics to score how well species match the restoration site conditions and restoration objectives; (c) optimization of species combinations and abundances considering functional trait diversity or phylogenetic diversity, to foster complementarity between species and to ensure ecosystem multifunctionality and stability; and (d) development of seed zone maps to guide sourcing of planting material adapted to present and predicted future environmental conditions. We outline the various elements behind the tool and discuss how it fits within the broader restoration planning process, including a review of other existing tools. 4. Synthesis and applications. The Diversity for Restoration tool enables non-expert users to combine species traits, environmental data and climate change models to select tree species and seed sources that best match restoration site conditions and restoration objectives. Originally developed for the tropical dry forests of Colombia, the tool has now been expanded to the tropical dry forests of northwestern Peru–southern Ecuador and the countries of Burkina Faso and Cameroon, and further expansion is underway. Acknowledging that restoration has a wide range of meanings and goals, our tool is intended to support decision making of anyone interested in tree planting and seed sourcing in tropical forest landscapes, regardless of the purpose or restoration approachISSN:0021-8901ISSN:1365-266

Tropical and subtropical Asia's valued tree species under threat

Tree diversity in Asia's tropical and subtropical forests is central to nature-based solutions. Species vulnerability to multiple threats, which affects the provision of ecosystem services, is poorly understood. We conducted a region-wide, spatially explicit vulnerability assessment (including overexploitation, fire, overgrazing, habitat conversion, and climate change) of 63 socio-economically important tree species selected from national priority lists and validated by an expert network representing 20 countries. Overall, 74% of the most important areas for conservation of these trees fall outside of protected areas, with species severely threatened across 47% of their native ranges. The most imminent threats are overexploitation and habitat conversion, with populations being severely threatened in an average of 24% and 16% of their distribution areas. Optimistically, our results predict relatively limited overall climate change impacts, however, some of the study species are likely to lose more than 15% of their habitat by 2050 because of climate change. We pinpoint specific natural forest areas in Malaysia and Indonesia (Borneo) as hotspots for on-site conservation of forest genetic resources, more than 82% of which do not currently fall within designated protected areas. We also identify degraded lands in Indonesia (Sumatra) as priorities for restoration where planting or assisted natural regeneration will help maintain these species into the future, while croplands in Southern India are highlighted as potentially important agroforestry options. Our study highlights the need for regionally coordinated action for effective conservation and restoration

Vulnerability mapping of 100 priority tree species in Central Africa to guide conservation and restoration efforts

Climate change and other anthropogenic threats are increasingly imperilling the diverse biomes of Central Africa, which are globally important for biodiversity, carbon storage and people's livelihoods. The objectives of this paper were to: (i) map the vulnerability of 100 socio-ecologically important priority tree species in Central Africa to climate change, fire, habitat conversion, overexploitation, overgrazing and (ii) propose a spatially explicit strategy to guide restoration and conservation actions. We performed ensemble distribution modelling to predict the present and future distributions of the 100 species, assembled other anthropogenic threat exposure layers, assessed species' sensitivities to the five threats based on their trait profiles, and constructed species-specific vulnerability maps by combining the species' exposure and sensitivity. The results show that these 100 species are vulnerable to the five threats, with an average of 34% of their distribution ranges under high to very high vulnerability and 60% under medium to high vulnerability to at least one threat. Many species identified as most vulnerable in this study are not considered as threatened by the IUCN Red List, suggesting a need to update their conservation status, potentially through integration of the vulnerability mapping methodology we used here. We generated both species-specific maps and summary maps including all 100 species identifying priority areas for a) in-situ conservation, b) ex-situ conservation, and c) active planting or assisted natural regeneration. We present an online platform to enable easy access to the vulnerability and the conservation and restoration priority maps for decision makers and support conservation and restoration planning across Central Africa

Site-specific scaling of remote sensing-based estimates of woody cover and aboveground biomass for mapping long-term tropical dry forest degradation status

Remote sensing-based approaches are important for evaluating ecosystem degradation and the efficient planning of ecosystem restoration efforts. However, the large majority of remote sensing-based degradation assessments are trend-based, implying that they can only detect degradation that occurred after medium or high-resolution satellite imagery became available. This makes them less suitable to map long-term degradation in ecosystems that have been under high human pressure since before. The main goal of this study was to develop a robust operational approach to map forest degradation status in heterogeneous landscapes with a long-standing degradation history to inform the planning of restoration interventions. We hereby use the tropical dry forests of Lambayeque, Peru, as a case study. Instead of using a trend-based assessment, we evaluated forest degradation status by comparing current woody cover (WC) and aboveground biomass (AGB) estimates obtained from remote sensing imagery with benchmark values consisting of the 95th percentile WC and AGB values inside environmentally homogenous land capability classes. Using boosted regression tree models and a combination of optical (Sentinel-2) and synthetic aperture radar (Sentinel-1) data of different seasons, we mapped WC and AGB, using training data obtained through very high-resolution imagery and field measurements. Further, we aimed at assessing (i) whether the inclusion of Sentinel-1 data improves mapping accuracy in comparison to using only Sentinel-2 data, and (ii) whether the use of multi-seasonal data improves accuracy in comparison to single-season data. Models combining multi-seasonal Sentinel-1 and Sentinel-2 data resulted in the most accurate WC predictions (mean absolute error (MAE): 16%; MAE normalized by dividing by the inter-quartile range of training data: 26%) and AGB predictions (MAE: 28.6 t/ha; normalized MAE: 65%), but differences in predictive accuracy with single season models or models using only Sentinel-2 data were small. The most accurate models estimated an average WC of 41% and an average AGB of 23.4 t/ha. Average WC and AGB reduction due to degradation was 35% and 36%, respectively, indicating that these forests are highly degraded. The site-specific scaling of WC and AGB allows to efficiently estimate forest degradation status irrespective of the time when this degradation occurred, and to express degradation status against site-specific benchmarks. On the condition that there are still some areas that are sufficiently undegraded to be used as a benchmark, the approach can be used to prioritize forest restoration actions and inform targets for restoration in heterogeneous landscapes suffering the impacts of undocumented long-term degradation