Mining threats in high-level biodiversity conservation policies.

Amid a global infrastructure boom, there is increasing recognition of the ecological impacts of the extraction and consumption of construction minerals, mainly processed as concrete, including significant and expanding threats to global biodiversity. We investigated how high-level national and international biodiversity conservation policies address mining threats, with a special focus on construction minerals. We conducted a review and quantified the degree to which threats from mining these minerals are addressed in biodiversity goals and targets under the 2011-2020 and post-2020 biodiversity strategies, national biodiversity strategies and action plans, and the assessments of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. Mining appeared rarely in national targets but more frequently in national strategies. Yet, in most countries, it was superficially addressed. Coverage of aggregates mining was greater than coverage of limestone mining. We outline 8 key components, tailored for a wide range of actors, to effectively mainstream biodiversity conservation into the extractive, infrastructure, and construction sectors. Actions include improving reporting and monitoring systems, enhancing the evidence base around mining impacts on biodiversity, and modifying the behavior of financial agents and businesses. Implementing these measures could pave the way for a more sustainable approach to construction mineral use and safeguard biodiversity.

Amenazas de la minería a las políticas de alto nivel para la conservación de la biodiversidad Resumen Enmedio del auge global del desarrollo de infraestructura, hay un mayor reconocimiento de los impactos ecológicos de la extracción y consumo de materiales para construcción, procesados predominantemente como concreto. Estos materiales representan amenazas significativas y en expansión para la biodiversidad global. Investigamos cómo son abordadas las amenazas de la minería por las políticas nacionales e internacionales de alto nivel para la conservación de la biodiversidad, con enfoque especial en los minerales para construcción. Realizamos una revisión exhaustiva y cuantificamos el grado en el cual son abordadas las amenazas de la extracción de estos minerales en los objetivos y metas para la biodiversidad bajo estrategias 2011­2020 y post 2020, las estrategias y planes de acción nacionales para la biodiversidad, y las evaluaciones de la Plataforma Intergubernamental Científico­normativa sobre Diversidad Biológica y Servicios de los Ecosistemas. La minería raramente apareció en los objetivos nacionales, pero fue más frecuente en las estrategias nacionales. Sin embargo, fue abordada superficialmente en la mayoría de los países. La cobertura de minería de agregados fue mayor que la cobertura de la minería de caliza. Describimos ocho componentes clave, adaptados para una amplia gama de actores, para incorporar eficazmente la conservación de la biodiversidad en los sectores extractivo, desarrollo de infraestructura y construcción. Las acciones incluyen la mejora de los sistemas de informes y monitoreo, el reforzamiento de la base de evidencias en torno a los impactos de la minería sobre la biodiversidad y la modificación del comportamiento de los agentes financieros y comerciales. La implementación de estas medidas podría allanar el camino para un enfoque más sostenible en el uso de minerales para la construcción y la salvaguarda de la biodiversidad.

Modeling the Brazilian Cerrado land use change highlights the need to account for private property sizes for biodiversity conservation.

Simulating future land use changes can be an important tool to support decision-making, especially in areas that are experiencing rapid anthropogenic pressure, such as the Cerrado-Brazilian savanna. Here we used a spatially-explicit model to identify the main drivers of native vegetation loss in the Cerrado and then extrapolate this loss for 2050 and 2070. We also analyzed the role of property size in complex Brazilian environmental laws in determining different outcomes of these projections. Our results show that distance to rivers, roads, and cities, agricultural potential, permanent and annual crop agriculture, and cattle led to observed/historical loss of vegetation, while protected areas prevented such loss. Assuming full adoption of the current Forest Code, the Cerrado may lose 26.5 million ha (± 11.8 95% C.I.) of native vegetation by 2050 and 30.6 million ha (± 12.8 95% C.I.) by 2070, and this loss shall occur mainly within large properties. In terms of reconciling conservation and agricultural production, we recommend that public policies focus primarily on large farms, such as protecting 30% of the area of properties larger than 2500 ha, which would avoid a loss of more than 4.1 million hectares of native vegetation, corresponding to 13% of the predicted loss by 2070.

A Conceptual Framework to Integrate Biodiversity, Ecosystem Function, and Ecosystem Service Models.

Global biodiversity and ecosystem service models typically operate independently. Ecosystem service projections may therefore be overly optimistic because they do not always account for the role of biodiversity in maintaining ecological functions. We review models used in recent global model intercomparison projects and develop a novel model integration framework to more fully account for the role of biodiversity in ecosystem function, a key gap for linking biodiversity changes to ecosystem services. We propose two integration pathways. The first uses empirical data on biodiversity-ecosystem function relationships to bridge biodiversity and ecosystem function models and could currently be implemented globally for systems and taxa with sufficient data. We also propose a trait-based approach involving greater incorporation of biodiversity into ecosystem function models. Pursuing both approaches will provide greater insight into biodiversity and ecosystem services projections. Integrating biodiversity, ecosystem function, and ecosystem service modeling will enhance policy development to meet global sustainability goals.

Identifying priority regions and territorial planning strategies for conserving native vegetation in the Cerrado (Brazil) under different scenarios of land use changes.

The Cerrado biome covers approximately 20% of Brazil and it is crucial for the Water, Food, Energy, and Ecosystems (WFEE) nexus. Thus, in recent years, large areas of the undisturbed Cerrado have been converted into farmland. In this biome, according to the Brazilian Forest Code, farmers need to keep 20% of native vegetation (Legal Reserves - LRs). By exploring combined and isolated impacts of different scenarios of LR and Protected area (PA) arrangements, this study evaluated the importance of complementarity between LR compliance and the amount of PAs (including Conservation Units - CUs and Indigenous Lands - ILs) to reduce deforestation and conserve native vegetation in the Cerrado. Seven scenarios were investigated: a scenario that considers the current PA and the LR values foreseen in the Native Vegetation Protection Law - NVPL; three scenarios focused on production; and three focused on conservation. Considering the trend of the current scenario, the estimated loss of native vegetation will be 30% (30.6 million ha) by 2070. According to the model simulations, for two periods (2050 and 2070), the LR Elimination scenario (LRE) would cause a greater loss of native vegetation than the PA Elimination (PAE), and as expected, the exclusion of both (PALRE) would provide a greater loss of native vegetation. Native vegetation is concentrated mainly on agricultural properties. Taking our conservation-oriented scenarios as an example of conservation strategies, if there were no financial, practical, political, social or personal constraints, there is no doubt that the CPALRI scenario (Creation of Protected Areas and Legal Reserve Increase) is the best trajectory for conserving biodiversity. Therefore, private properties, through LRs, are essential for efficient planning of land use/cover as they ensure security in the WFEE nexus. The resulting projected scenarios are important to help decision makers in territorial planning and how to arbitrate territorial demands aiming at the rational use of the natural resources of the Cerrado.

Influence of landscape features on urban land surface temperature: Scale and neighborhood effects.

Higher land surface temperature (LST) in cities than its surrounding areas presents a major sustainability challenge for cities. Adaptation and mitigation of the increased LST require in-depth understanding of the impacts of landscape features on LST. We studied the influences of different landscape features on LST in five large cities across China to investigate how the features of a specific urban landscape (endogenous features), and neighboring environments (exogenous features) impact its LST across a continuum of spatial scales. Surprisingly, results show that the influence of endogenous landscape features (Eendo) on LST can be described consistently across all cities as a nonlinear function of grain size (gs) and neighbor size (ns) (Eendo = ßnsgs-0.5, where ß is a city-specific constant) while the influence of exogenous features (Eexo) depends only on neighbor size (ns) (Eexo = Î³-εns0.5, where γ and ε are city-specific constants). In addition, a simple relationship describing the relative strength of endogenous and exogenous impacts of landscape features on LST was found (Eendo > Eexo if ns > kgs2/5, where k is a city-specific parameter; otherwise, Eendo < Eexo). Overall, vegetation alleviates 40%-60% of the warming effect of built-up while surface wetness intensifies or reduces it depending on climate conditions. This study reveals a set of unifying quantitative relationships that effectively describes landscape impacts on LST across cities, grain and neighbor sizes, which can be instrumental towards the design of sustainable cities to deal with increasing temperature.

Global vulnerability of soil ecosystems to erosion.

CONTEXT: Soil erosion is one of the main threats driving soil degradation across the globe with important impacts on crop yields, soil biota, biogeochemical cycles, and ultimately human nutrition. OBJECTIVES: Here, using an empirical model, we present a global and temporally explicit assessment of soil erosion risk according to recent (2001-2013) dynamics of rainfall and vegetation cover change to identify vulnerable areas for soils and soil biodiversity. METHODS: We used an adaptation of the Universal Soil Loss Equation together with state of the art remote sensing models to create a spatially and temporally explicit global model of soil erosion and soil protection. Finally, we overlaid global maps of soil biodiversity to assess the potential vulnerability of these soil communities to soil erosion. RESULTS: We show a consistent decline in soil erosion protection over time across terrestrial biomes, which resulted in a global increase of 11.7% in soil erosion rates. Notably, soil erosion risk systematically increased between 2006 and 2013 in relation to the baseline year (2001). Although vegetation cover is central to soil protection, this increase was mostly driven by changes in rainfall erosivity. Globally, soil erosion is expected not only to have an impact on the vulnerability of soil conditions but also on soil biodiversity with 6.4% (for soil macrofauna) and 7.6% (for soil fungi) of these vulnerable areas coinciding with regions with high soil biodiversity. CONCLUSIONS: Our results indicate that an increasing proportion of soils are degraded globally, affecting not only livelihoods but also potentially degrading local and regional landscapes. Similarly, many degraded regions coincide with and may have impacted high levels of soil biodiversity.

The importance of Legal Reserves for protecting the Pantanal biome and preventing agricultural losses.

Considering scenarios of future changes in land use have the potential to support policy-makers in drafting environmental laws to reconcile the demands of multiple land uses. The Pantanal, one of the largest wetlands in the world, has been undergoing rapid land use changes, and does not yet have any integrated environmental legislation on Legal Reserve for entire region (LR - minimum percentage of native vegetation required within private properties). The aim of this paper was to generate future vegetation loss scenarios for the Pantanal based on four LR values: (i) BAU: Business as usual, which considers existing laws: Native Vegetation Protection Law and State Decree; (ii) LRE: LR elimination owing to a bill recently proposed; (iii) LR50: which considers the bill proposing 50% of LR for the Pantanal; and (iv) LR80: our proposed levels of 80% of LR for the lowlands and 35% for the plateau (following values in the Amazon). Based on native vegetation loss from each scenario, we estimated the soil loss and sediment yield to rivers. Our results show that LRE would increase native vegetation loss in the Pantanal by as much as 139% when compared to the BAU, whereas increasing LR levels would reduce conversion values by 29% (LR80). Elimination of the LR would increase soil erosion and sediment production by up to 7% and 10%, respectively, compared to BAU. Based on native vegetation loss from each scenario, we estimated the soil loss and sediment yield to rivers with our data showing more than 90% of the sediment transported to the lowland originating from the plateau. The LR80 indicates a reduction in soil nutrient replacement costs of 10% compared to BAU, while in the LR50 these costs decrease by 1.5%, and in the LRE would increase of 8%. Our results show that abolishing current protections would have substantial impacts on avulsion processes, on several economic activities (tourism, fishery, cattle raising, etc.) and negative impacts for biodiversity conservation and would bring losses to agriculture in the Pantanal. Hence, our study brings clearly evidence of LR importance and need to expand it in this sensitive wetland.

Increasing capacity to produce scenarios and models for biodiversity and ecosystem services / Capacitando profissionais para o desenvolvimento de cenários e modelos em biodiversidade e serviços ecossistêmicos

Abstract: Extensive anthropogenic activities driven by the demand for agriculture and forestry products have led to dramatic reductions in biodiversity worldwide and significant changes in the provisioning of ecosystem services. These trends are expected to continue in the future as the world continues to develop without much consideration of the role that nature plays in sustaining human livelihoods. Scenarios and models can be important tools to help policy- and decision-makers foresee the impact of their decisions; thus, increasing capacity in creating such models and scenarios is of utmost importance. However, postgraduate training schools that focus on this topic are still rare. Here we present and reflect on the experience of the São Paulo School of Advanced Science on Scenarios and Modelling on Biodiversity and Ecosystem Services to Support Human Well-Being (SPSAS Scenarios). In addition, we introduce the Special Issue of Biota Neotropica that resulted from the activities taking place during the SPSAS Scenarios. In total, nine case studies emerged from the activities carried out during SPSAS Scenarios. These focused on a variety of ecosystems, their current drivers of change and expected trends, as well as on the development of alternative positive scenarios applying the recently developed Nature Futures Framework. We emphasize the need to increase capacity in scenario and modelling skills in order to address some of the existing gaps in producing policy-relevant scenarios and models for biodiversity and ecosystem services.

Resumo: Atividades antropogênicas extensas, impulsionadas pela demanda por produtos da agricultura e da silvicultura, têm levado a reduções dramáticas na biodiversidade mundial e a mudanças significativas no provimento de serviços ecossistêmicos. Estas tendências devem continuar no futuro, pois o mundo continua a se desenvolver sem muita consideração pelo papel que a natureza desempenha em sustentar a subsistência humana. Cenários e modelos são ferramentas importantes para ajudar os tomadores de decisão a preverem o impacto de suas decisões, auxiliando na definição das melhores opções para políticas de conservação e uso sustentável; portanto o aumento da capacidade para o desenvolvimento de modelos e cenários é de suma importância. Entretanto, ainda são raros os cursos de pós-graduação que foquem na capacitação de profissionais para o desenvolvimento de modelos e cenários em biodiversidade e serviços ecossistêmicos. Neste trabalho apresentamos a experiência da Escola São Paulo de Ciências Avançadas de Cenários e Modelagem em Biodiversidade e Serviços Ecossistêmicos para Apoiar o Bem-Estar Humano (SPSAS Scenarios). Adicionalmente, apresentamos neste Número Especial da Biota Neotropica os resultados dos exercícios de modelagem e cenários desenvolvidos no decorrer da SPSAS Scenarios. No total, as atividades realizadas durante o SPSAS Scenarios resultaram em nove estudos de caso. Estes se concentraram em uma diversidade de ecossistemas, nos atuais drivers de mudança e as respectivas tendências, bem como nas alternativas de desenvolvimento visando cenários mais positivos propostos recentemente no contexto da Framework Futuros para Natureza da Plataforma Intergovernamental de Biodiversidade e Serviços Ecossistêmicos (IPBES). Enfatizamos aqui a necessidade de acelerar a capacitação de profissionais que trabalhem com cenários e modelagem de forma a preencher algumas lacunas existentes na produção de cenários e modelos relevantes para a tomada de decisão em biodiversidade e serviços ecossistêmicos

Spatial and temporal dimensions of landscape fragmentation across the Brazilian Amazon.

The Brazilian Amazon in the past decades has been suffering severe landscape alteration, mainly due to anthropogenic activities, such as road building and land clearing for agriculture. Using a high-resolution time series of land cover maps (classified as mature forest, non-forest, secondary forest) spanning from 1984 through 2011, and four uncorrelated fragmentation metrics (edge density, clumpiness index, area-weighted mean patch size and shape index), we examined the temporal and spatial dynamics of forest fragmentation in three study areas across the Brazilian Amazon (Manaus, Santarém and Machadinho d'Oeste), inside and outside conservation units. Moreover, we compared the impacts on the landscape of: (1) different land uses (e.g. cattle ranching, crop production), (2) occupation processes (spontaneous vs. planned settlements) and (3) implementation of conservation units. By 2010/2011, municipalities located along the Arc of Deforestation had more than 55% of the remaining mature forest strictly confined to conservation units. Further, the planned settlement showed a higher rate of forest loss, a more persistent increase in deforested areas and a higher relative incidence of deforestation inside conservation units. Distinct agricultural activities did not lead to significantly different landscape structures; the accessibility of the municipality showed greater influence in the degree of degradation of the landscapes. Even with a high proportion of the landscapes covered by conservation units, which showed a strong inhibitory effect on forest fragmentation, we show that dynamic agriculturally driven economic activities, in municipalities with extensive road development, led to more regularly shaped, heavily fragmented landscapes, with higher densities of forest edge.

The Environmental Legacy of Modern Tropical Deforestation.

Tropical deforestation has caused a significant share of carbon emissions and species losses, but historical patterns have rarely been explicitly considered when estimating these impacts [1]. A deforestation event today leads to a time-delayed future release of carbon, from the eventual decay either of forest products or of slash left at the site [2]. Similarly, deforestation often does not result in the immediate loss of species, and communities may exhibit a process of "relaxation" to their new equilibrium over time [3]. We used a spatially explicit land cover change model [4] to reconstruct the annual rates and spatial patterns of tropical deforestation that occurred between 1950 and 2009 in the Amazon, in the Congo Basin, and across Southeast Asia. Using these patterns, we estimated the resulting gross vegetation carbon emissions [2, 5] and species losses over time [6]. Importantly, we accounted for the time lags inherent in both the release of carbon and the extinction of species. We show that even if deforestation had completely halted in 2010, time lags ensured there would still be a carbon emissions debt of at least 8.6 petagrams, equivalent to 5-10 years of global deforestation, and an extinction debt of more than 140 bird, mammal, and amphibian forest-specific species, which if paid, would increase the number of 20(th)-century extinctions in these groups by 120%. Given the magnitude of these debts, commitments to reduce emissions and biodiversity loss are unlikely to be realized without specific actions that directly address this damaging environmental legacy.

Modelling land cover change in the Brazilian Amazon: temporal changes in drivers and calibration issues.

Land cover change (LCC) models are used in many studies of human impacts on the environment, but knowing how well these models predict observed changes in the landscape is a challenge. We used nearly three decades of LCC maps to run several LCC simulations to: (1) determine which parameters associated with drivers of LCC (e.g. roads) get selected for which transition (forest to deforested, regeneration to deforested or deforested to regeneration); (2) investigate how the parameter values vary through time with respect to the different activities (e.g. farming); and (3) quantify the influence of choosing a particular time period for model calibration and validation on the performance of LCC models. We found that deforestation of primary forests tends to occur along roads (included in 95 % of models) and outside protected areas (included in all models), reflecting farming establishment. Regeneration tends to occur far from roads (included in 78 % of the models) and inside protected areas (included in 38 % of the models), reflecting the processes of land abandonment. Our temporal analysis of model parameters revealed a degree of variation through time (e.g. effectiveness of protected areas rose by 73 %, p < 0.001), but for the majority of parameters there was no significant trend. The degree to which model predictions agreed with observed change was heavily dependent on the year used for calibration (p < 0.001). The next generation of LCC models may need to embed trends in parameter values to allow the processes determining LCC to change through time and exert their influence on model predictions.

The transparency, reliability and utility of tropical rainforest land-use and land-cover change models.

Land-use and land-cover (LULC) change is one of the largest drivers of biodiversity loss and carbon emissions globally. We use the tropical rainforests of the Amazon, the Congo basin and South-East Asia as a case study to investigate spatial predictive models of LULC change. Current predictions differ in their modelling approaches, are highly variable and often poorly validated. We carried out a quantitative review of 48 modelling methodologies, considering model spatio-temporal scales, inputs, calibration and validation methods. In addition, we requested model outputs from each of the models reviewed and carried out a quantitative assessment of model performance for tropical LULC predictions in the Brazilian Amazon. We highlight existing shortfalls in the discipline and uncover three key points that need addressing to improve the transparency, reliability and utility of tropical LULC change models: (1) a lack of openness with regard to describing and making available the model inputs and model code; (2) the difficulties of conducting appropriate model validations; and (3) the difficulty that users of tropical LULC models face in obtaining the model predictions to help inform their own analyses and policy decisions. We further draw comparisons between tropical LULC change models in the tropics and the modelling approaches and paradigms in other disciplines, and suggest that recent changes in the climate change and species distribution modelling communities may provide a pathway that tropical LULC change modellers may emulate to further improve the discipline. Climate change models have exerted considerable influence over public perceptions of climate change and now impact policy decisions at all political levels. We suggest that tropical LULC change models have an equally high potential to influence public opinion and impact the development of land-use policies based on plausible future scenarios, but, to do that reliably may require further improvements in the discipline.

Predictive modelling of contagious deforestation in the Brazilian Amazon.

Tropical forests are diminishing in extent due primarily to the rapid expansion of agriculture, but the future magnitude and geographical distribution of future tropical deforestation is uncertain. Here, we introduce a dynamic and spatially-explicit model of deforestation that predicts the potential magnitude and spatial pattern of Amazon deforestation. Our model differs from previous models in three ways: (1) it is probabilistic and quantifies uncertainty around predictions and parameters; (2) the overall deforestation rate emerges "bottom up", as the sum of local-scale deforestation driven by local processes; and (3) deforestation is contagious, such that local deforestation rate increases through time if adjacent locations are deforested. For the scenarios evaluated-pre- and post-PPCDAM ("Plano de Ação para Proteção e Controle do Desmatamento na Amazônia")-the parameter estimates confirmed that forests near roads and already deforested areas are significantly more likely to be deforested in the near future and less likely in protected areas. Validation tests showed that our model correctly predicted the magnitude and spatial pattern of deforestation that accumulates over time, but that there is very high uncertainty surrounding the exact sequence in which pixels are deforested. The model predicts that under pre-PPCDAM (assuming no change in parameter values due to, for example, changes in government policy), annual deforestation rates would halve between 2050 compared to 2002, although this partly reflects reliance on a static map of the road network. Consistent with other models, under the pre-PPCDAM scenario, states in the south and east of the Brazilian Amazon have a high predicted probability of losing nearly all forest outside of protected areas by 2050. This pattern is less strong in the post-PPCDAM scenario. Contagious spread along roads and through areas lacking formal protection could allow deforestation to reach the core, which is currently experiencing low deforestation rates due to its isolation.

Using landscape history to predict biodiversity patterns in fragmented landscapes.

Landscape ecology plays a vital role in understanding the impacts of land-use change on biodiversity, but it is not a predictive discipline, lacking theoretical models that quantitatively predict biodiversity patterns from first principles. Here, we draw heavily on ideas from phylogenetics to fill this gap, basing our approach on the insight that habitat fragments have a shared history. We develop a landscape 'terrageny', which represents the historical spatial separation of habitat fragments in the same way that a phylogeny represents evolutionary divergence among species. Combining a random sampling model with a terrageny generates numerical predictions about the expected proportion of species shared between any two fragments, the locations of locally endemic species, and the number of species that have been driven locally extinct. The model predicts that community similarity declines with terragenetic distance, and that local endemics are more likely to be found in terragenetically distinctive fragments than in large fragments. We derive equations to quantify the variance around predictions, and show that ignoring the spatial structure of fragmented landscapes leads to over-estimates of local extinction rates at the landscape scale. We argue that ignoring the shared history of habitat fragments limits our ability to understand biodiversity changes in human-modified landscapes.

Changes in size of deforested patches in the Brazilian Amazon.

Different deforestation agents, such as small farmers and large agricultural businesses, create different spatial patterns of deforestation. We analyzed the proportion of deforestation associated with different-sized clearings in the Brazilian Amazon from 2002 through 2009. We used annual deforestation maps to determine total area deforested and the size distribution of deforested patches per year. The size distribution of deforested areas changed over time in a consistent, directional manner. Large clearings (>1000 ha) comprised progressively smaller amounts of total annual deforestation. The number of smaller clearings (6.25-50.00 ha) remained unchanged over time. Small clearings accounted for 73% of all deforestation in 2009, up from 30% in 2002, whereas the proportion of deforestation attributable to large clearings decreased from 13% to 3% between 2002 and 2009. Large clearings were concentrated in Mato Grosso, but also occurred in eastern Pará and in Rondônia. In 2002 large clearings accounted for 17%, 15%, and 10% of all deforestation in Mato Grosso, Pará, and Rondônia, respectively. Even in these states, where there is a highly developed agricultural business dominated by soybean production and cattle ranching, the proportional contribution of large clearings to total deforestation declined. By 2009 large clearings accounted for 2.5%, 3.5%, and 1% of all deforestation in Mato Grosso, Pará, and Rondônia, respectively. These changes in deforestation patch size are coincident with the implementation of new conservation policies by the Brazilian government, which suggests that these policies are not effectively reducing the number of small clearings in primary forest, whether these are caused by large landholders or smallholders, but have been more effective at reducing the frequency of larger clearings.