Spatial conservation prioritisation under global threats

摘要: Species extinction is one of the world’s major environmental problems. Biodiversity conservation planning aims to provide tools and knowledge assist solving this problem. Historically, has accounted for threats from human activity at a local scale (e.g. land conversion or hunting). However, emergence global-scale demands novel techniques. Here, I develop new global biodiversity in two emerging areas: changing climate migratory species under sea level rise. Climate change affecting, will affect, every place world. Researchers interested predicting managing impact on have generally focused predictions future ranges determine actions priorities. predicted shifts are expected be very uncertain because issues such as dispersal distances, population dynamics interactions with other species. To overcome these problems surrounding prediction range shifts, would need detailed distribution models based great deal data each It thus not practical apply techniques prioritisation, where uncertainty too predict distributions all In thesis, tackle problem by incorporating stability effectiveness habitat climatic refugia into analyses change. Sea rise most prominent consequences change: mean between 75 200 cm 2100. This coastal species, which shorebirds particularly sensitive exemplar. These birds undertake annual long distance flights their Arctic breeding grounds coasts around Most interrupt journeys rest feed, staging areas can constitute significant bottlenecks. The dependency entire bottlenecks cause much higher loss than when simply calculated summing total loss. previous studies impacts typically taken latter approach. For spatially explicit modelling clearly required solve Underpinning my thesis spend scarce resources wisely. international organizations World Wildlife Fund, Conservation International, Nature Conservancy) developed priorities guide expenditure scale. Such prioritisations influence allocation 1.5 billion USD annually. Despite this, no existing prioritisation schemes consider Chapter 2, examine robustness eight statistically analyse prioritizing criteria correlate robustness. discover that invest high endemic richness irreplaceability more robust climate. At same time, investment intact regions proved less individual realistic priority setting due limitations. 3, resource algorithm incorporates ecological ecoregions allocating funds way changes optimal schedule investments both temporally. maximise resilience change, analysis concludes funding increased located tropics and/or mid-elevation habitats, conditions remain relatively stable. many dynamic over time space, presents serious challenges target continually moving. Past research assumed ecosystem equal sum an assumption invalid if changing. 4, explicitly model network structure assemblage using East Asian-Australasian Flyway (EAAF). Using model, estimate carrying capacity graph theoretic framework. flyway we connectedness considering extent alone. also find variation among taxa explained identity sites acting networks 5, design efforts along routes shorebirds. objective after assemblage. efficient directing effort suffer greatest impact. resulting preliminary subject iterative improvement our improves. highlights importance understanding connectivity My work discovered biodiversity, namely allocate face problems, shown solutions frequently counterintuitive.