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Uncontrolled fires place considerable burdens on forest ecosystems, compromising our ability to meet conservation and restoration goals. A poor understanding of the impacts of fire on ecosystems and their biodiversity exacerbates this challenge, particularly in tropical regions where few studies have applied consistent analytical techniques to examine a broad range of ecological impacts over multiyear time frames. We compiled 16 y of data on ecosystem properties (17 variables) and biodiversity (21 variables) from a tropical peatland in Indonesia to assess fire impacts and infer the potential for recovery. Burned forest experienced altered structural and microclimatic conditions, resulting in a proliferation of nonforest vegetation and erosion of forest ecosystem properties and biodiversity. Compared to unburned forest, habitat structure, tree density, and canopy cover deteriorated by 58 to 98%, while declines in species diversity and abundance were most pronounced for trees, damselflies, and butterflies, particularly for forest specialist species. Tracking ecosystem property and biodiversity datasets over time revealed most to be sensitive to recurrent high-intensity fires within the wider landscape. These megafires immediately compromised water quality and tree reproductive phenology, crashing commercially valuable fish populations within 3 mo and driving a gradual decline in threatened vertebrates over 9 mo. Burned forest remained structurally compromised long after a burn event, but vegetation showed some signs of recovery over a 12-y period. Our findings demonstrate that, if left uncontrolled, fire may be a pervasive threat to the ecological functioning of tropical forests, underscoring the importance of fire prevention and long-term restoration efforts, as exemplified in Indonesia. [ABSTRACT FROM AUTHOR]

Reliable estimates of wildlife mortality due to wildlife-vehicle collisions are key to understanding its impact on wildlife populations and developing strategies to prevent or reduce collisions. Standardised approaches for monitoring roadkill are needed to derive robust and unbiased estimates of mortality that are comparable across different study systems and ecological contexts. When designing surveys, there is a trade-off between survey frequency (and hence logistical effort and financial cost) and carcass detection. In this regard, carcass persistence (the period a carcass remains detectable before being removed by decomposition or scavengers) is important; the longer a carcass persists, the greater the likelihood it will be detected with lower survey effort by conducting more infrequent surveys. Using multi-taxon carcass data collected over a month of repeated driven surveys, combined with five covariates (species functional group, body weight, carcass position on road, carcass condition [either flattened or not after impact], and rainfall prior to each survey), we explored the drivers of carcass persistence with the overall aim of providing information to optimise the design of carcass surveys along linear infrastructure. Our methodological approach included a survival analysis to determine carcass persistence, linear regressions to test the effect of covariates, a subsampling analysis (using field data and a simulation exercise) to assess how the proportion of carcasses detected changes according to survey frequency, and an analysis to compare the costs of surveys based on study duration, transect length and survey frequency. Mean overall carcass persistence was 2.7 days and was significantly correlated with position on road and within-functional group body weight. There was no evidence for a significant effect of rainfall, while the effect of carcass condition was weakly non-significant. The proportion of carcasses detected decreased sharply when survey intervals were longer than three days. However, we showed that survey costs can be reduced by up to 80% by conducting non-daily surveys. Expanding on the call for a standardised methodology for roadkill surveys, we propose that carcass persistence be explicitly considered during survey design. By carefully considering the objectives of the survey and characteristics of the focal taxa, researchers can substantially reduce logistical costs. In addition, we developed an R Shiny web app that can be used by practitioners to compare survey costs across a variety of survey characteristics. This web app will allow practitioners to easily assess the trade-off between carcass detection and logistical effort. • In roadkill studies there is a trade-off between survey cost and the number of carcasses detected. • Carcass persistence can be used to inform optimal roadkill survey design. • Survey costs can be reduced by 80% by conducting non-daily surveys based on different level of carcass persistence. • We developed an online R Shiny web app to compare costs across different survey scenarios. [ABSTRACT FROM AUTHOR]