The lethal and sub-lethal consequences of entomopathogenic nematode infestation and exposure for adult pine weevils, Hylobius abietis (Coleoptera: Curculionidae)

Entomopathogenic nematodes (EPN) frequently kill their host within 1–2 days, and interest in EPN focuses mainly on their lethality. However, insects may take longer to die, or may fail to die despite being infected, but little is known about the effects of EPN infection on insects, other than death. Here we investigate both lethal and sub-lethal effects of infection by two EPN species, Steinernema carpocapsae and Heterorhabditis downesi, on adults of the large pine weevil, Hylobius abietis. Following 12 h nematode–weevil contact in peat, S. carpocapsae killed a significantly higher proportion of weevils (87–93%) than H. downesi (43–57%) at all concentrations tested. Less than 10% of weevils were dead within 2 days, and weevils continued to die for up to 10 days after exposure (LT50 of 3 days or more). In a separate experiment, live weevils dissected 6 days after a 24 h exposure to nematodes on filter paper harbored encapsulated and dead nematodes, showing that weevils could defend themselves against infection. Some live weevils also harbored live nematodes 6 days after they had been removed from the nematode infested medium. Feeding by weevils was not affected by infection with, or exposure to, either species of EPN. We discuss these results in relation to the use of EPN in biological control against H. abietis.

Uptake of agri-environmental schemes in the Less-Favoured Areas of Greece: The role of corruption and farmers' responses to the financial crisis

Vine-growing in the Less-Favoured Areas of Greece is facing multiple challenges that might lead to its abandonment. In an attempt to maintain rural populations, Rural Development Schemes have been created that offer the opportunity to rural households to maintain or expand their farming businesses including vine-growing. This paper stems from a study that used data from a cross-sectional survey of 204 farmers to investigate how farming systems and farmers’ perception of corruption, amongst other socio-economic factors, affected their decisions to continue vine-growing through participation in Rural Development Schemes, in three remote Less-Favoured Areas of Greece. The Theory of Planned Behaviour was used to frame the research problem with the assumption being that an individual’s intention to participate in a Scheme is based on their prior beliefs about it. Data from the survey were reduced and simplified by the use of non-linear principal component analysis. The ensuing variables were used in selectivity corrected ordered probit models to reveal farmers’ attitudes towards viticulture and rural development. It was found that economic factors, perceived corruption and farmers’ attitudes were significant determinants on whether to participate in the Schemes. The research findings highlight the important role of perceived corruption and the need for policies that facilitate farmers’ access to decision making centres.

Combining 3D and 2D for less constrained periocular recognition

Periocular recognition has recently become an active topic in biometrics. Typically it uses 2D image data of the periocular region. This paper is the first description of combining 3D shape structure with 2D texture. A simple and effective technique using iterative closest point (ICP) was applied for 3D periocular region matching. It proved its strength for relatively unconstrained eye region capture, and does not require any training. Local binary patterns (LBP) were applied for 2D image based periocular matching. The two modalities were combined at the score-level. This approach was evaluated using the Bosphorus 3D face database, which contains large variations in facial expressions, head poses and occlusions. The rank-1 accuracy achieved from the 3D data (80%) was better than that for 2D (58%), and the best accuracy (83%) was achieved by fusing the two types of data. This suggests that significant improvements to periocular recognition systems could be achieved using the 3D structure information that is now available from small and inexpensive sensors.