Inferring forest fate from demographic data: from vital rates to population dynamic models

As population-level patterns of interest in forests emerge from individual vital rates, modelling forest dynamics requires making the link between the scales at which data are collected (individual stems) and the scales at which questions are asked (e.g. populations and communities). Structured population models (e.g. integral projection models (IPMs)) are useful tools for linking vital rates to population dynamics. However, the application of such models to forest trees remains challenging owing to features of tree life cycles, such as slow growth, long lifespan and lack of data on crucial ontogenic stages. We developed a survival model that accounts for size-dependent mortality and a growth model that characterizes individual heterogeneity. We integrated vital rate models into two types of population model; an analytically tractable form of IPM and an individual-based model (IBM) that is applied with stochastic simulations. We calculated longevities, passage times to, and occupancy time in, different life cycle stages, important metrics for understanding how demographic rates translate into patterns of forest turnover and carbon residence times. Here, we illustrate the methods for three tropical forest species with varying life-forms. Population dynamics from IPMs and IBMs matched a 34 year time series of data (albeit a snapshot of the life cycle for canopy trees) and highlight differences in life-history strategies between species. Specifically, the greater variation in growth rates within the two canopy species suggests an ability to respond to available resources, which in turn manifests as faster passage times and greater occupancy times in larger size classes. The framework presented here offers a novel and accessible approach to modelling the population dynamics of forest trees

30% land conservation and climate action reduces tropical extinction risk by more than 50%

Limiting climate change to less than 2°C is the focus of international policy under the climate convention (UNFCCC), and is essential to preventing extinctions, a focus of the Convention on Biological Diversity (CBD). The post‐2020 biodiversity framework drafted by the CBD proposes conserving 30% of both land and oceans by 2030. However, the combined impact on extinction risk of species from limiting climate change and increasing the extent of protected and conserved areas has not been assessed. Here we create conservation spatial plans to minimize extinction risk in the tropics using data on 289 219 species and modeling two future greenhouse gas concentration pathways (RCP2.6 and 8.5) while varying the extent of terrestrial protected land and conserved areas from <17% to 50%. We find that limiting climate change to 2°C and conserving 30% of terrestrial area could more than halve aggregate extinction risk compared with uncontrolled climate change and no increase in conserved area

Spatial heterogeneity of habitat suitability for Rift Valley fever occurrence in Tanzania: an ecological niche modelling approach

Despite the long history of Rift Valley fever (RVF) in Tanzania, extent of its suitable habitat in the country remains unclear. In this study we investigated potential effects of temperature, precipitation, elevation, soil type, livestock density, rainfall pattern, proximity to wild animals, protected areas and forest on the habitat suitability for RVF occurrence in Tanzania. Presence-only records of 193 RVF outbreak locations from 1930 to 2007 together with potential predictor variables were used to model and map the suitable habitats for RVF occurrence using ecological niche modelling. Ground-truthing of the model outputs was conducted by comparing the levels of RVF virus specific antibodies in cattle, sheep and goats sampled from locations in Tanzania that presented different predicted habitat suitability values. Habitat suitability values for RVF occurrence were higher in the northern and central-eastern regions of Tanzania than the rest of the regions in the country. Soil type and precipitation of the wettest quarter contributed equally to habitat suitability (32.4% each), followed by livestock density (25.9%) and rainfall pattern (9.3%). Ground-truthing of model outputs revealed that the odds of an animal being seropositive for RVFV when sampled from areas predicted to be most suitable for RVF occurrence were twice the odds of an animal sampled from areas least suitable for RVF occurrence (95% CI: 1.43, 2.76, p < 0.001). The regions in the northern and central-eastern Tanzania were more suitable for RVF occurrence than the rest of the regions in the country. The modelled suitable habitat is characterised by impermeable soils, moderate precipitation in the wettest quarter, high livestock density and a bimodal rainfall pattern. The findings of this study should provide guidance for the design of appropriate RVF surveillance, prevention and control strategies which target areas with these characteristics

The commonness of rarity: Global and future distribution of rarity across land plants

A key feature of life’s diversity is that some species are common but many more are rare. Nonetheless, at global scales, we do not know what fraction of biodiversity consists of rare species. Here, we present the largest compilation of global plant diversity to quantify the fraction of Earth’s plant biodiversity that are rare. A large fraction, ~36.5% of Earth’s ~435,000 plant species, are exceedingly rare. Sampling biases and prominent models, such as neutral theory and the k-niche model, cannot account for the observed prevalence of rarity. Our results indicate that (i) climatically more stable regions have harbored rare species and hence a large fraction of Earth’s plant species via reduced extinction risk but that (ii) climate change and human land use are now disproportionately impacting rare species. Estimates of global species abundance distributions have important implications for risk assessments and conservation planning in this era of rapid global change

Contribution of spatially explicit models to climate change adaptation and mitigation plans for a priority forest habitat

Climate change will impact forest ecosystems, their biodiversity and the livelihoods they sustain. Several adaptation and mitigation strategies to counteract climate change impacts have been proposed for these ecosystems. However, effective implementation of such strategies requires a clear understanding of how climate change will influence the future distribution of forest ecosystems. This study uses maximum entropy modelling (MaxEnt) to predict environmentally suitable areas for cork oak (Quercus suber) woodlands, a socio-economically important forest ecosystem protected by the European Union Habitats Directive. Specifically, we use two climate change scenarios to predict changes in environmental suitability across the entire geographical range of the cork oak and in areas where stands were recently established. Up to 40 % of current environmentally suitable areas for cork oak may be lost by 2070, mainly in northern Africa and southern Iberian Peninsula. Almost 90 % of new cork oak stands are predicted to lose suitability by the end of the century, but future plantations can take advantage of increasing suitability in northern Iberian Peninsula and France. The predicted impacts cross-country borders, showing that a multinational strategy, will be required for cork oak woodland adaptation to climate change. Such a strategy must be regionally adjusted, featuring the protection of refugia sites in southern areas and stimulating sustainable forest management in areas that will keep long-term suitability. Afforestation efforts should also be promoted but must consider environmental suitability and land competition issues

A protocol for an intercomparison of biodiversity and ecosystem services models using harmonized land-use and climate scenarios

To support the assessments of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), the IPBES Expert Group on Scenarios and Models is carrying out an intercomparison of biodiversity and ecosystem services models using harmonized scenarios (BES-SIM). The goals of BES-SIM are (1) to project the global impacts of land-use and climate change on biodiversity and ecosystem services (i.e., nature's contributions to people) over the coming decades, compared to the 20th century, using a set of common metrics at multiple scales, and (2) to identify model uncertainties and research gaps through the comparisons of projected biodiversity and ecosystem services across models. BES-SIM uses three scenarios combining specific Shared Socio-economic Pathways (SSPs) and Representative Concentration Pathways (RCPs)-SSP1xRCP2.6, SSP3xRCP6.0, SSP5xRCP8.6-to explore a wide range of land-use change and climate change futures. This paper describes the rationale for scenario selection, the process of harmonizing input data for land use, based on the second phase of the Land Use Harmonization Project (LUH2), and climate, the biodiversity and ecosystem services models used, the core simulations carried out, the harmonization of the model output metrics, and the treatment of uncertainty. The results of this collaborative modeling project will support the ongoing global assessment of IPBES, strengthen ties between IPBES and the Intergovernmental Panel on Climate Change (IPCC) scenarios and modeling processes, advise the Convention on Biological Diversity (CBD) on its development of a post-2020 strategic plans and conservation goals, and inform the development of a new generation of nature-centred scenarios