Choice of biodiversity index drives optimal fire management decisions

Preservation of biodiversity is a central goal of conservation management, yet the conditions that promote persistence may differ for the species in the community. For systems subject to stochastic disturbances such as fire, understanding which management practices promote persistence for all species in a community is complex. Before deciding on the best course of action, an objective must be specified. Yet an overarching goal of species persistence can be specified into a measureable objective many different ways. We investigated four alternative management objectives for maximizing species persistence that use common biodiversity indices: (1) attaining the minimally acceptable mix of successional vegetation states to support species' relative abundances, (2) maximizing the arithmetic mean abundance of species, (3) maximizing the geometric mean abundance of species, and (4) minimizing the average extinction risk of species. We used stochastic dynamic programming to model successional changes in vegetation in the presence of both planned and unplanned fires, and utilize an extensive data set on the occurrence of birds, reptiles, and small mammals in different successional states in semiarid Australia. We investigated the influence the choice of objective function and taxonomic focus has on the optimal fire management recommendations. We also evaluated a recent hazard reduction policy to annually burn a fixed amount of the landscape and compare results to the optimal solution. The optimal management strategy to maximize species persistence over a 100-year period is predominantly to minimize wildfires. This is because the majority of species are more likely to occur in intermediate, and late successional vegetation. However the optimal solution showed sensitivity to the objective and the species included in the analysis. These results highlight the need for careful consideration when specifying an objective to represent overarching conservation goals. Using the extinction risk objective, we show that a policy to annually burn 5% of the landscape could increase the average probability of extinction for the modelled species by 7% over the next 100 years compared to the optimal management scenario

Assessing the sensitivity of biodiversity indices used to inform fire management

Biodiversity indices are widely used to summarize changes in the distribution and abundance of multiple species and measure progress towards management targets. However, the sensitivity of biodiversity indices to the data, landscape classification and conservation values underpinning them are rarely interrogated. There are limited studies to help scientists and land managers use biodiversity indices in the presence of fire and vegetation succession. The geometric mean of species' relative abundance or occurrence (G) is a biodiversity index that can be used to determine the mix of post‐fire vegetation that maximizes biodiversity. We explored the sensitivity of G to (1) type of biodiversity data, (2) representation of ecosystem states, (3) expression of conservation values, and (4) uncertainty in species' response to landscape structure. Our case study is an area of fire‐prone woodland in southern Australia where G is used in fire management planning. We analysed three datasets to determine the fire responses of 170 bird, mammal and reptile species. G and fire management targets were sensitive to the species included in the analysis. The optimal mix of vegetation successional states for threatened birds was more narrowly defined than the optimal mix for all species combined. G was less sensitive to successional classification (i.e. number of states); although classifications of increasing complexity provided additional insights into desirable levels of heterogeneity. Weighting species by conservation status or endemism influenced the mix of vegetation states that maximized biodiversity. When a higher value was placed on threatened species the importance of late successional vegetation was emphasized. Representing variation in individual species' response to vegetation structure made it clearer when a decrease in G was likely to reflect a significant reduction in species occurrences. Synthesis and applications. Data, models and conservation values can be combined using biodiversity indices to make robust environmental decisions. Combining different types of biodiversity data using composite indices, such as the geometric mean, can improve the coverage and relevance of biodiversity indices. We recommend that evaluation of biodiversity indices for fire management verify how index assumptions align with management objectives, consider the relative merits of different types of biodiversity data, test sensitivity of ecosystem state definitions and incorporate conservation values through species weightings

Forecasting species range dynamics with process-explicit models: matching methods to applications.

Knowing where species occur is fundamental to many ecological and environmental applications. Species distribution models (SDMs) are typically based on correlations between species occurrence data and environmental predictors, with ecological processes captured only implicitly. However, there is a growing interest in approaches that explicitly model processes such as physiology, dispersal, demography and biotic interactions. These models are believed to offer more robust predictions, particularly when extrapolating to novel conditions. Many process-explicit approaches are now available, but it is not clear how we can best draw on this expanded modelling toolbox to address ecological problems and inform management decisions. Here, we review a range of process-explicit models to determine their strengths and limitations, as well as their current use. Focusing on four common applications of SDMs - regulatory planning, extinction risk, climate refugia and invasive species - we then explore which models best meet management needs. We identify barriers to more widespread and effective use of process-explicit models and outline how these might be overcome. As well as technical and data challenges, there is a pressing need for more thorough evaluation of model predictions to guide investment in method development and ensure the promise of these new approaches is fully realised

How fire interacts with habitat loss and fragmentation

Biodiversity faces many threats and these can interact to produce outcomes that may not be predicted by considering their effects in isolation. Habitat loss and fragmentation (hereafter 'fragmentation') and altered fire regimes are important threats to biodiversity, but their interactions have not been systematically evaluated across the globe. In this comprehensive synthesis, including 162 papers which provided 274 cases, we offer a framework for understanding how fire interacts with fragmentation. Fire and fragmentation interact in three main ways: (i) fire influences fragmentation (59% of 274 cases), where fire either destroys and fragments habitat or creates and connects habitat; (ii) fragmentation influences fire (25% of cases) where, after habitat is reduced in area and fragmented, fire in the landscape is subsequently altered because people suppress or ignite fires, or there is increased edge flammability or increased obstruction to fire spread; and (iii) where the two do not influence each other, but fire interacts with fragmentation to affect responses like species richness, abundance and extinction risk (16% of cases). Where fire and fragmentation do influence each other, feedback loops are possible that can lead to ecosystem conversion (e.g. forest to grassland). This is a well-documented threat in the tropics but with potential also to be important elsewhere. Fire interacts with fragmentation through scale-specific mechanisms: fire creates edges and drives edge effects; fire alters patch quality; and fire alters landscape-scale connectivity. We found only 12 cases in which studies reported the four essential strata for testing a full interaction, which were fragmented and unfragmented landscapes that both span contrasting fire histories, such as recently burnt and long unburnt vegetation. Simulation and empirical studies show that fire and fragmentation can interact synergistically, multiplicatively, antagonistically or additively. These cases highlight a key reason why understanding interactions is so important: when fire and fragmentation act together they can cause local extinctions, even when their separate effects are neutral. Whether fire-fragmentation interactions benefit or disadvantage species is often determined by the species' preferred successional stage. Adding fire to landscapes generally benefits early-successional plant and animal species, whereas it is detrimental to late-successional species. However, when fire interacts with fragmentation, the direction of effect of fire on a species could be reversed from the effect expected by successional preferences. Adding fire to fragmented landscapes can be detrimental for species that would normally co-exist with fire, because species may no longer be able to disperse to their preferred successional stage. Further, animals may be attracted to particular successional stages leading to unexpected responses to fragmentation, such as higher abundance in more isolated unburnt patches. Growing human populations and increasing resource consumption suggest that fragmentation trends will worsen over coming years. Combined with increasing alteration of fire regimes due to climate change and human-caused ignitions, interactions of fire with fragmentation are likely to become more common. Our new framework paves the way for developing a better understanding of how fire interacts with fragmentation, and for conserving biodiversity in the face of these emerging challenges