Aim This study determines whether the establishment of tropical protected areas (PAs) has led to a reduction in deforestation within their boundaries or whether deforestation has been displaced to adjacent unprotected areas: a process termed neighbourhood leakage. Location Sumatra, Indonesia. Methods We processed and analysed 98 corresponding LANDSAT satellite images with a c. 800 m2 resolution to map deforestation from 1990 to 2000 across 440,000 km2 on the main island of Sumatra and the smaller island of Siberut. We compared deforestation rates across three categories of land: (1) within PAs; (2) in adjacent unprotected land lying with 10 km of PA boundaries; and (3) within the wider unprotected landscape. We used the statistical method of propensity score matching to predict the deforestation that would have been observed had there been no PAs and to control for the generally remote locations in which Sumatran PAs were established. Results During the period 1990–2000 deforestation rates were found to be lower inside PAs than in adjacent unprotected areas or in the wider landscape. Deforestation rates were also found to be lower in adjacent unprotected areas than in the wider landscape. Main conclusions Sumatran PAs have lower deforestation rates than unprotected areas. Furthermore, a reduction in deforestation rates inside Sumatran PAs has promoted protection, rather than deforestation, in adjacent unprotected land lying within 10 km of PA boundaries. Despite this positive evaluation, deforestation and logging have not halted within the boundaries of Sumatran PAs. Therefore the long‐term viability of Sumatran forests remains open to question.
f Circoviruses are among the smallest and simplest of all viruses, but they are relatively poorly characterized. Here, we intensively sampled two sympatric parrot populations from Mauritius over a period of 11 years and screened for the circovirus Beak and feather disease virus (BFDV). During the sampling period, a severe outbreak of psittacine beak and feather disease, which is caused by BFDV, occurred in Echo parakeets. Consequently, this data set presents an ideal system for studying the evolution of a pathogen in a natural population and to understand the adaptive changes that cause outbreaks. Unexpectedly, we discovered that the outbreak was most likely caused by changes in functionally important regions of the normally conserved replicationassociated protein gene and not the immunogenic capsid. Moreover, these mutations were completely fixed in the Echo parakeet host population very shortly after the outbreak. Several capsid alleles were linked to the replication-associated protein outbreak allele, suggesting that whereas the key changes occurred in the latter, the scope of the outbreak and the selective sweep may have been influenced by positive selection in the capsid. We found evidence for viral transmission between the two host populations though evidence for the invasive species as the source of the outbreak was equivocal. Finally, the high evolutionary rate that we estimated shows how rapidly new variation can arise in BFDV and is consistent with recent results from other small singlestranded DNA viruses.
We consider a stochastic model for the spread of an SIR (susceptible → infective → removed) epidemic among a closed, finite population that contains several types of individuals and is partitioned into households. The infection rate between two individuals depends on the types of the transmitting and receiving individuals and also on whether the infection is local (i.e., within a household) or global (i.e., between households). The exact distribution of the final outcome of the epidemic is outlined. A branching process approximation for the early stages of the epidemic is described and made fully rigorous, by considering a sequence of epidemics in which the number of households tends to infinity and using a coupling argument. This leads to a threshold theorem for the epidemic model. A central limit theorem for the final outcome of epidemics which take off is derived, by exploiting an embedding representation.
We consider a stochastic model for the spread of an SIR (susceptible ! infective ! removed) epidemic among a closed, nite population that contains several types of individuals and is partitioned into households. The infection rate between two individuals depends on the types of the transmitting and receiving individuals and also on whether the infection is local (i.e. within a household) or global (i.e. between households). The exact distribution of the nal outcome of the epidemic is outlined. A branching process approximation for the early stages of the epidemic is described and made fully rigorous, by considering a sequence of epidemics in which the number of households tends to in nity and using a coupling argument. This leads to a threshold theorem for the epidemic model. A central limit theorem for the nal outcome of epidemics which take o is derived, by exploiting an embedding representation.
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