Tropical rainforests are the most diverse terrestrial systems with innumerable species interactions. Humans are disturbing these ecosystems in a multitude of ways, often simultaneously (e.g. one forest can suffer from deforestation, predator loss, hunting and invasive species). Research to date has focused on how individual threats affect particular species, but we have a poor understanding of how multiple threats interact to reshape wildlife communities (diversity and food-web metrics). Given that most remaining forests face multiple threats, this enormous knowledge gap limits our ability to effectively manage protected areas (PAs).

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Urgent problem - Nowhere are these issues more important than the tropical rainforest landscapes of Australia and Southeast Asia, which are home to a billion people and four global biodiversity conservation hotspots. In Australia, fragmented rainforest cover <1% the land area – a >70% decline from historic levels – but contain >50% of plants and 35-40% of mammal and bird species. Meanwhile, Southeast Asia faces the highest global deforestation rates with fragmented PAs surrounded by agriculture and large human populations.

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A pressing conservation issue is the decline of wildlife inside PAs. The key threats facing wildlife are habitat fragmentation, hunting, and invasive species, and these vary substantially among PAs. Consequently, ostensibly similar fragmented PAs experience drastically different outcomes, including being defaunated or overrun with pests or invasive species (Fig 2 & 3). This PA-specificity suggests contingent, interacting, and/or non-linear processes. Crucially, multiple threats routinely precipitate rapid losses in native mammals. If we are going to prevent extinctions, we need to assess the combined effects of threats on wildlife communities.

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Australian rainforests have seen >20 recent mammal extinctions and most are linked to multiple threats. However, scientists have only begun to examine how threats interact to accelerate extinctions, in particular how fire elevates invasive predator impacts and forest fragmentation induces native predator losses, which in turn magnifies impacts from smaller invasive predators. Another pressing issue is the combined effects from multiple invasive species that plague the same PA (feral cats, foxes, pigs, and deer). Addressing such 3-way interactions in Australia requires big data that spans entire wildlife communities in many landscapes.

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Efficiency – Many millions of dollars are spent annually implementing wildlife surveys, and the newest and richest method for mammals is camera traps (CT) that passively document all terrestrial species >1 kg. However, single surveys in isolation offer little guidance on dynamics and are rarely tied to management decisions. To address this, new approaches are needed for cross-site analyses of CT data, which can provide far greater insights than any single study. This new approach would also leverage troves of existing wildlife data that is underutilised.

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Aims – The ECL develops a novel cross-site analytical approach to study the interactive effects from multiple threats on rainforest wildlife communities. We will apply this approach in Australia using new data collected in the Wet Tropics of Queensland World Heritage Sites, including pre-existing data from Australian collaborators. We will also compare and contrast key drivers and interaction strengths among Australian, Southeast Asian, and global datasets. In this way, we can address fundamental questions in wildlife ecology and also produce applied management guidance.

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Innovation - Untangling impacts of interacting threats on mammal communities requires a comparative framework and ‘big data’ (many landscape-scale datasets of mammal communities). Camera trap (CT) surveys are ideal for this but have not been systematically assembled for cross-site comparisons within Australia or Southeast Asia, with the exception of the ECLs work. The ECL addresses this in two ways: first by developing a novel meta-regression approach to compare wildlife communities using CT data from different sites (in collaboration with a USA statistician). Second, by developing a meta-structural equation modelling (metaSEM) approach for CT data, in close collaboration with the lead statistician authoring the metaSEM R-package (based in Singapore, see Feasibility).

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Benefit – The results will provide scientists and managers with clear guidance about the state of wildlife and mammal communities, the threats driving specific changes, and the importance of interacting effects. The analyses will be used to model the benefit of alternative conservation strategies, e.g. should we deal with (i) hunting, (ii) invasive predators, or (iii) invasive herbivores? And when managers should focus on reducing the biggest single threat, versus if reducing a combination of threats at the same time can produce outsized improvements.

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Objectives:

• (i) Advance fundamental knowledge on ecological impacts from multiple threats;

• (ii) innovate new statistical approaches for multi-site analyses of wildlife communities,

• (iii) boost the value of expensive wildlife surveys, (iv) produce the largest wildlife community dataset in Australian rainforests,

• (v) build a collaborative network to share data across Australian institutions,

• (vi) communicate research outcomes to government, NGOs, and PAs managers to improve threatened species conservation and train these groups to use new approaches.

 

Conceptual framework - Wildlife ecology and ecological cascades (EC) 

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Conserving tropical forests requires understanding how they function. Mammal community food webs are maintained through a delicate balance of connections between predators, prey, competitors, and symbionts. Disturbances can disassemble food webs by altering diversity, species population sizes, and species interactions. Ecological cascades (ECs) research tracks how changes to one species produce indirect, often cryptic, ‘knock-on’ effects on other species and the ecosystem. The secondary and tertiary consequences of losing a single species (e.g. apex predator) can outweigh the initial direct effects. For example, a 50% reduction of predators may allow herbivore densities to double, which in turn strongly suppress plants. ECs can also reshape ecosystem processes such as carbon sequestration, fire dynamics, and even disease dynamics. Even in diverse tropical rainforests, changes to a single keystone species can cause food webs to collapse, reducing wildlife diversity and altering tree communities (Fig 1).

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ECL research has extended ECs to situations when forest-dwelling pest animals crop-raid (e.g. pigs foraging in farms) and increase their densities within forests (Luskin et al. 2017b in Nature Comms3). Food-subsidized animals then overconsume native plants and degrade the ecosystem (Fig 1 & 2; Jia+ et al & Luskin+ 2018 in PNAS).

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There are diverse types of ECs, for example hunting herbivorous versus omnivorous game species (e.g. pigs, deer) produces the opposite effect as predators declines (Fig 1). ECs also depend on the ecology of wildlife species involved. For example, hunting seed-dispersing animals (e.g. primates, birds) produces different ECs than hunting seed-predating animals (e.g. pigs or rodents). The removal or addition of keystone species, such as native or feral pigs that disturb soils and vegetation, can produce magnified ECs relative to changes in more benign species (e.g. civets; Dunn et al 2022, Dehaudt et al 2022). 

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A key lesson in Australia is that negative effects from ECs are magnified by invasive species. There is a preponderance of work showing that invasive predators in Australia cause trophic cascades. Likewise, feral pigs (Sus scofa, hereafter ‘pigs’) in Australian rainforests (Fig 3C) are a particularly egregious example, costing billions in economic losses in Australia alone36, a topic we have studied in depth (Luskin et al 2014, 2017b, 2019). ECL work shows that pigs even alter rainforest tree diversity and negative density dependence in tree recruitment (Figs 2, 3 & 4).

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Australian rainforests have dramatically contracted in the Pleistocene while Southeast Asia rainforests have been comparatively stable. Work by Betts et al (2019, Science) shows that sites with Pleistocene disturbances like glaciation filtered out sensitive species from communities so that contemporary fragmentation has a comparatively lower impact on diversity relative to more climatically-stable environments. The resulting hypothesis is that Australian mammal communities are more resilient to contemporary fragmentation than those in Southeast Asia or globally.

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Taken together, fragmentation, predator loss, crop-raiding, hunting/culling, and invasive species each produce distinct changes to wildlife communities, and these outcomes differ in Australia versus other regions.