Predicting landscape-scale biodiversity recovery by natural tropical forest regrowth.

Natural forest regrowth is a cost-effective, nature-based solution for biodiversity recovery, yet different socioenvironmental factors can lead to variable outcomes. A critical knowledge gap in forest restoration planning is how to predict where natural forest regrowth is likely to lead to high levels of biodiversity recovery, which is an indicator of conservation value and the potential provisioning of diverse ecosystem services. We sought to predict and map landscape-scale recovery of species richness and total abundance of vertebrates, invertebrates, and plants in tropical and subtropical second-growth forests to inform spatial restoration planning. First, we conducted a global meta-analysis to quantify the extent to which recovery of species richness and total abundance in second-growth forests deviated from biodiversity values in reference old-growth forests in the same landscape. Second, we employed a machine-learning algorithm and a comprehensive set of socioenvironmental factors to spatially predict landscape-scale deviation and map it. Models explained on average 34% of observed variance in recovery (range 9-51%). Landscape-scale biodiversity recovery in second-growth forests was spatially predicted based on socioenvironmental landscape factors (human demography, land use and cover, anthropogenic and natural disturbance, ecosystem productivity, and topography and soil chemistry); was significantly higher for species richness than for total abundance for vertebrates (median range-adjusted predicted deviation 0.09 vs. 0.34) and invertebrates (0.2 vs. 0.35) but not for plants (which showed a similar recovery for both metrics [0.24 vs. 0.25]); and was positively correlated for total abundance of plant and vertebrate species (Pearson r = 0.45, p = 0.001). Our approach can help identify tropical and subtropical forest landscapes with high potential for biodiversity recovery through natural forest regrowth.

Predicción de la Recuperación de la Biodiversidad a Escala de Paisaje según la Regeneración Natural del Bosque Tropical Resumen La regeneración natural del bosque es una solución rentable para la recuperación de la biodiversidad basada en la naturaleza, sin embargo, los diferentes factores socioambientales pueden derivar en resultados variables. Cómo predecir la ubicación en donde la regeneración natural del bosque recuperará los niveles de biodiversidad, los cuales son un indicador del valor de la conservación y un suministro potencial de diferentes servicios ambientales, es un vacío de conocimiento importante en la planeación de la restauración forestal. Buscamos predecir y mapear la recuperación a escala de paisaje de la riqueza de especies y la abundancia total de vertebrados, invertebrados y plantas en bosques tropicales y subtropicales de segundo crecimiento para guiar la planeación de la restauración. Primero, realizamos un metaanálisis mundial para cuantificar la medida a la que se desvió la recuperación de la riqueza y la abundancia total de especies en los bosques de segundo crecimiento de los valores de biodiversidad en los bosques antiguos referenciales en el mismo paisaje. Después, utilizamos un algoritmo de aprendizaje automático y un conjunto integral de factores socioambientales para predecir espacialmente la desviación a escala de paisaje para después mapearla. Los modelos explicaron en promedio el 34% de la varianza observada en la recuperación (rango de 9-51%). La recuperación de la biodiversidad a escala de paisaje en los bosques de segundo crecimiento pudo predecirse espacialmente con base en los factores socioambientales del paisaje (demografía humana, uso y cobertura del suelo, alteraciones naturales y antropogénicas, productividad del ecosistema, tipo de topografía y de suelo); fue significativamente más alta para la riqueza de especies que para la abundancia total de vertebrados (desviación media pronosticada ajustada al rango de 0.09 versus 0.34) e invertebrados (0.2 versus 0.35) pero no para las plantas (las cuales mostraron una recuperación similar para ambas medidas [0.24 versus 0.25]); y tuvo una correlación positiva para la abundancia de especies de plantas y vertebrados (Pearson r =0.45, p=0.001). Nuestra estrategia puede ayudar a identificar los paisajes de bosques tropicales y subtropicales con un potencial alto para la recuperación de la biodiversidad por medio de la regeneración natural del bosque.

Planning forest restoration within private land holdings with conservation co-benefits at the landscape scale.

Forest loss is mainly due to the conversion of forest to agriculture, mostly in private lands. Forest restoration is a global priority, yet restoration targets are ambitious and budget-limited. Therefore, assessing the outcome of alternative decisions on land-use within private lands is paramount to perform cost-effective restoration. We present a novel framework that incorporates spatial planning for forest restoration within private lands with conservation co-benefits at the landscape scale. As a case study, we used three real landscapes of 10.000 ha with differing amounts of forest cover in the Atlantic Forest region of Brazil, and three hypothetical animal species with different dispersal abilities. We estimated the total amount of forest that landholders must restore to comply with the Native Vegetation Protection Law, which requires landholders to reforest 20% of their land within a 20-year time frame. We compared the cost-effectiveness of five restoration strategies based on the improvement in habitat availability and restoration costs. The most cost-effective strategy depends on a landscape's initial amount of forest cover and the species of concern. We revealed that spatial planning for restoration in private lands increased habitat availability up to 12 times more than random restoration, which was always the least cost-effective strategy. Cost-effective large-scale restoration in Brazil depends on public policies that assist landholders to comply with the law and on prioritizing areas for restoration within private lands. We show that by adding habitat availability as target in spatial prioritization, benefits for biodiversity can be hastened at low additional cost, even in real world scenarios with severe spatial constraints. Despite constraints, spatially planned restoration for law compliance in Brazil increased landscape permeability by creating corridors and stepping stones. Our framework should be used to plan restoration in Brazilian private lands and can be customized for other regions worldwide.

Global restoration opportunities in tropical rainforest landscapes.

Over 140 Mha of restoration commitments have been pledged across the global tropics, yet guidance is needed to identify those landscapes where implementation is likely to provide the greatest potential benefits and cost-effective outcomes. By overlaying seven recent, peer-reviewed spatial datasets as proxies for socioenvironmental benefits and feasibility of restoration, we identified restoration opportunities (areas with higher potential return of benefits and feasibility) in lowland tropical rainforest landscapes. We found restoration opportunities throughout the tropics. Areas scoring in the top 10% (i.e., restoration hotspots) are located largely within conservation hotspots (88%) and in countries committed to the Bonn Challenge (73%), a global effort to restore 350 Mha by 2030. However, restoration hotspots represented only a small portion (19.1%) of the Key Biodiversity Area network. Concentrating restoration investments in landscapes with high benefits and feasibility would maximize the potential to mitigate anthropogenic impacts and improve human well-being.