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Conservation of biodiversity and natural resources in a changing climate requires understanding what controls ecosystem resilience to disturbance. This understanding is especially important in the fire-prone Mediterranean systems of the world. The fire frequency in these systems is sensitive to climate, and recent climate change has resulted in more frequent fires over the last few decades. However, the sensitivity of postfire recovery and biomass/fuel load accumulation to climate is less well understood than fire frequency despite its importance in driving the fire regime. In this study, we develop a hierarchical statistical framework to model postfire ecosystem recovery using satellite-derived observations of vegetation as a function of stand age, topography, and climate. In the Cape Floristic Region (CFR) of South Africa, a fire-prone biodiversity hotspot, we found strong postfire recovery gradients associated with climate resulting in faster recovery in regions with higher soil fertility, minimum July (winter) temperature, and mean January (summer) precipitation. Projections using an ensemble of 11 downscaled Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCMs) suggest that warmer winter temperatures in 2080-2100 will encourage faster postfire recovery across the region, which could further increase fire frequency due to faster fuel accumulation. However, some models project decreasing precipitation in the western CFR, which would slow recovery rates there, likely reducing fire frequency through lack of fuel and potentially driving local biome shifts from fynbos shrubland to nonburning semidesert vegetation. This simple yet powerful approach to making inferences from large, remotely sensed datasets has potential for wide application to modeling ecosystem resilience in disturbance-prone ecosystems globally.

Societal Impact Statement: Madagascar is famous for its unique forests and their fauna. Most of the island is covered by flammable grassy ecosystems long considered to be of human origin and threatening the remaining forests. Yet new studies show that many plants and animals of the grassy systems are unique to Madagascar and restricted to these open habitats. Open grassy ecosystems have markedly different management requirements from forests and bring different contributions to society. We argue that the grassy ecosystems can benefit Madagascar if understood and managed wisely using expanded knowledge bases that also include collaboration with locals. Summary: Until recently, nearly all research and interests in Madagascar focused on forested habitats. To help place Madagascar's grassy ecosystems in context, we provide a summary of the origin, development, and evolution of open tropical, C4 grassy ecosystems elsewhere, especially those from Africa; we summarize similarities and differences with the distribution of C3 and C4 grasses in the Malagasy landscape, their plant traits, and inferences on the evolutionary legacy of grasses. We also discuss the animal communities that use and have coevolved in these grassy systems; to help resolve controversies over the pre‐settlement extent of grassy ecosystems, we suggest a variety of complementary geochemical, palaeobotanical, and molecular genetic tools that have been effectively used elsewhere to untangle forest/grassy ecosystem mosaics and the ecological and evolutionary processes that influence them. Many of these tools can and should be employed in Madagascar to fully understand the spatio‐temporal dynamics of open, grassy, and closed forest systems across the island; as regards conservation, we discuss the ecosystem services provided by grassy systems, which are too often ignored in general, not only as a biome, vis‐à‐vis forests, but also for their global importance as a carbon sink and role they play in water management and providing goods to local villagers. We conclude by outlining the necessary research to better manage open ecosystems across Madagascar without threatening endangered forest ecosystems. [ABSTRACT FROM AUTHOR]

Turnover, or change in the composition of species over space and time, is one of the primary ways to define beta diversity. Inferring what factors impact beta diversity is not only important for understanding biodiversity processes but also for conservation planning. At present, a popular approach to understanding the drivers of compositional turnover is through generalized dissimilarity modelling (GDM). We argue that the current GDM approach suffers several limitations and provide an alternative modelling approach that remedies these issues.We propose using generative spatial random effects models implemented in a Bayesian framework. We offer hierarchical specifications to yield full regression and spatial predictive inference, both with associated full uncertainties. The approach is illustrated by examining dissimilarity in three datasets: tree survey data from Panama's Barro Colorado Island (BCI), plant occurrence data from southwest Australia and plant abundance surveys from the Greater Cape Floristic Region (GCFR) of South Africa. We select a best model using out‐of‐sample predictive performance.We find that the form of the best model differs across the three datasets, but our models provide performance ranging from comparable to significant improvement over GDMs. Within the GCFR, the spatial random effects play a more important role in the modelling than all the environmental variables.We have proposed a model that provides several improvements to the current GDM framework. This includes advantages such as a flexible spatially varying mean function, spatial random effects that capture dependence unaccounted for by explanatory variables, and spatially heterogeneous variance structure. All these features are offered in a model that can adequately handle a large incidence of total dissimilarity through 'one‐inflation', as would be expected from highly biodiverse areas with steep turnover gradients. [ABSTRACT FROM AUTHOR]

Land-use history as a predictor of invasive alien plant distributions has received little study, especially across large spatial and temporal scales. Here we evaluate the importance of land-use history and other environmental characteristics as predictors of the distributions of a suite important invasive woody plant species in the northeastern United States. Using historical aerial photographs, we delineated 69 years (1934–2003) of land-use change across a typically heterogeneous 95 km2 landscape. We randomly surveyed over 500 sites for six invasive plant species. We found that land use history patterns strongly affected presence and abundance of the invasive plants as a group, but affected some species more than others. Generally, past agricultural use favored invasive species, whereas intact forest blocks discouraged them. Current land-use trends toward residential/commercial development favor disturbance-adapted species like Celastrus orbiculatus (asiatic bittersweet) and will probably slow the spread of post-agricultural specialists such as Berberis thunbergii (Japanese barberry).

For most of the 20th century, the hypothesis was accepted that Madagascar's extensive grass‐dominated ecosystems were of anthropogenic origin, carved out of pristine forests after a mere two millennia of human settlement. We tested an alternative hypothesis that these C4 grassy ecosystems were part of the general Late Miocene expansion of tropical grassy biomes, using diverse data from published sources (Bond et al. 2008). Joseph and Seymour (2021) criticised this paper, which they see as seminal to subsequent studies on the grasslands. Here we respond to their critique of our study. We also briefly note diverse studies since 2008 pointing to the ancient origin of Madagascar's C4 grasses and the ecosystems they dominate. We conclude with key research needs that will help promote open‐minded research on these long neglected grassy biomes. The answers would be of considerable scientific and public interest but may also contribute to enlightened management of forest/grassland mosaics. [ABSTRACT FROM AUTHOR]