Positive Interactions Drive Bat Distribution in a Remote Oceanic Archipelago (Azores, Portugal)

One of the fundamental interests in ecology is understanding which factors drive species’ distribution. We aimed to understand the drivers of bat distribution and co-occurrence patterns in a remote, insular system. The two bat species known to occur in the Azores archipelago were used as a model. Echolocation calls were recorded at 414 point-locations haphazardly distributed across the archipelago. Calls were analysed and assigned to each species. Binominal generalised linear models were adjusted using different descriptors at two scales: archipelago and island. The presence of the co-occurring species was included at both scales. The results show that island isolation, habitat and climate play an essential role on the archipelago and island scales, respectively. However, the positive interaction between bat species was the most critical driver of species’ distribution at the island scale. This high co-occurrence pattern at the island scale may result from both species’ maximising foraging profit in a region where prey abundance may be highly variable. However, further research is necessary to clarify the mechanisms behind this positive interaction. Both species are threatened and lack specific management and protection measures. Maintaining this positive interaction between the two species may prove to be fundamental for their conservation.

A COLLECTIVE RESERVING MODEL WITH CLAIM OPENNESS

The present paper introduces a simple aggregated reserving model based on claim count and payment dynamics, which allows for claim closings and re-openings. The modelling starts off from individual Poisson process claim dynamics in discrete time, keeping track of accident year, reporting year and payment delay. This modelling approach is closely related to the one underpinning the so-called double chain-ladder model, and it allows for producing separate reported but not settled and incurred but not reported reserves. Even though the introduction of claim closings and re-openings will produce new types of dependencies, it is possible to use flexible parametrisations in terms of, for example, generalised linear models (GLM) whose parameters can be estimated based on aggregated data using quasi-likelihood theory. Moreover, it is possible to obtain interpretable and explicit moment calculations, as well as having consistency of normalised reserves when the number of contracts tend to infinity. Further, by having access to simple analytic expressions for moments, it is computationally cheap to bootstrap the mean squared error of prediction for reserves. The performance of the model is illustrated using a flexible GLM parametrisation evaluated on non-trivial simulated claims data. This numerical illustration indicates a clear improvement compared with models not taking claim closings and re-openings into account. The results are also seen to be of comparable quality with machine learning models for aggregated data not taking claim openness into account.

Exploring relationships between drought and epidemic cholera in Africa using generalised linear models

Background Temperature and precipitation are known to affect Vibrio cholerae outbreaks. Despite this, the impact of drought on outbreaks has been largely understudied. Africa is both drought and cholera prone and more research is needed in Africa to understand cholera dynamics in relation to drought. Methods Here, we analyse a range of environmental and socioeconomic covariates and fit generalised linear models to publicly available national data, to test for associations with several indices of drought and make cholera outbreak projections to 2070 under three scenarios of global change, reflecting varying trajectories of CO2 emissions, socio-economic development, and population growth. Results The best-fit model implies that drought is a significant risk factor for African cholera outbreaks, alongside positive effects of population, temperature and poverty and a negative effect of freshwater withdrawal. The projections show that following stringent emissions pathways and expanding sustainable development may reduce cholera outbreak occurrence in Africa, although these changes were spatially heterogeneous. Conclusions Despite an effect of drought in explaining recent cholera outbreaks, future projections highlighted the potential for sustainable development gains to offset drought-related impacts on cholera risk. Future work should build on this research investigating the impacts of drought on cholera on a finer spatial scale and potential non-linear relationships, especially in high-burden countries which saw little cholera change in the scenario analysis.

Poverty Diagnostics in the Philippines: Assessing Impacts of Programs through Generalised Linear Models (GLMs)

<p>The Philippines is a country where a quarter to one-third of the population is poor. Although the nation has managed to lower poverty incidence in some years, its booming population increases the poor population dramatically. This is why alleviating poverty is a pinnacle program in the country. In aid of poverty alleviation endeavor, this study focuses on assessing which programs had been effective in alleviating poverty given other family characteristics. Aside from descriptive methods, employing Generalised Linear Models (GLMs) and categorical data analysis are the focus in analysing the effects of existing intervention programs on status of improvement and income of families. In addition, varying effects of programs depending on values of other covariates are also analysed. Descriptive analysis and modeling are applied on the panel data of families. Intervention programs namely scholarship, Comprehensive Agrarian Reform Program (CARP) and government housing or other housing financing program (GHFP) have been run together with other family characteristics to describe improvement in welfare and income. Interaction effects, between access to intervention programs and other aspects of the family, have been derived to give a richer picture of the phenomenon. The study has come to conclude that the programs are indeed effective in improving lives of families, with some effects varying on some levels of other explanatory variables.</p>

Poverty Diagnostics in the Philippines: Assessing Impacts of Programs through Generalised Linear Models (GLMs)

<p>The Philippines is a country where a quarter to one-third of the population is poor. Although the nation has managed to lower poverty incidence in some years, its booming population increases the poor population dramatically. This is why alleviating poverty is a pinnacle program in the country. In aid of poverty alleviation endeavor, this study focuses on assessing which programs had been effective in alleviating poverty given other family characteristics. Aside from descriptive methods, employing Generalised Linear Models (GLMs) and categorical data analysis are the focus in analysing the effects of existing intervention programs on status of improvement and income of families. In addition, varying effects of programs depending on values of other covariates are also analysed. Descriptive analysis and modeling are applied on the panel data of families. Intervention programs namely scholarship, Comprehensive Agrarian Reform Program (CARP) and government housing or other housing financing program (GHFP) have been run together with other family characteristics to describe improvement in welfare and income. Interaction effects, between access to intervention programs and other aspects of the family, have been derived to give a richer picture of the phenomenon. The study has come to conclude that the programs are indeed effective in improving lives of families, with some effects varying on some levels of other explanatory variables.</p>

Silky sifaka (Propithecus candidus) use sleep sites for thermoregulation, food access and predator avoidance

Primate sleeping site selection is influenced by multiple ecological factors including predation avoidance, thermoregulation, and food access. To test these hypotheses, we studied the sleeping trees used by a group of wild silky sifakas (Propithecus candidus) in Marojejy National Park, Madagascar. During this ten-month study, the group slept in 828 sleeping trees from approximately 35 genera. In support of thermoregulation, generalised linear models revealed that as temperature decreased, the number of individuals sleeping together significantly increased and they slept at further distances from the trunk. As rainfall increased, sleep site height significantly increased. Weinmannia was the most frequented tree genus, despite low abundance, accounting for 29% of all sleeping trees. In support of food access, 94.8% of sleeping trees were food trees. Weinmannia is among the most highly preferred food trees. The group slept at a mean height of 16.0 m near the top of tall trees which averaged 19.5 m. Sleep trees were significantly taller than trees in botanical plots within the sifaka’s home range. They never slept in the same trees on consecutive nights, and sleeping heights were significantly higher than daytime heights which is consistent with predation avoidance. Social sleeping in groups of two or three individuals (62.9%) was more common than solitary sleeping (37.1%). At such heights, huddling may increase vigilance and lessen the risk of predation by the fossa (Cryptoprocta ferox) while also reducing heat loss. These patterns suggest that silky sifaka sleep site choice is influenced by thermoregulation and food access in addition to predation avoidance. We suggest that understanding sleep site use can assist in conservation of species like silky sifakas by enabling researchers to find new groups, protect habitats with key tree species, and inform reforestation efforts.

Factors Influencing the Awareness and Adoption of Borehole-Garden Permaculture in Malawi: Lessons for the Promotion of Sustainable Practices

Using wastewater accumulating around rural waterpoints to irrigate community gardens, borehole-garden permaculture (BGP) presents a method of sustainable water management. BGP also presents public health benefits through the removal of stagnant water around boreholes, key Malaria breeding grounds, and through providing year-round food to supplement diets. By analysing a dataset of over 100,000 cases, this research examines the awareness and adoption of BGP across Malawi. Generalised linear models identified significant variables influencing BGP awareness and uptake revealing that socioeconomic, biophysical and waterpoint-specific variables influenced both the awareness and adoption of BGP. BGP had low uptake in Malawi with only 2.4% of communities surveyed practising BGP while 43.0% of communities were aware of BGP. Communities in areas with unreliable rainfall and high malaria susceptibility had low BGP awareness despite BGP being particularly beneficial to these communities. This work suggests that future work in the promotion of BGP should focus their efforts within these areas. Furthermore, this work highlights the value of community networks in knowledge sharing and suggests that such social capital could be further used by NGOs and the Government of Malawi in the promotion of BGP and other sustainable practices.

Trends in amyloidosis in spondyloarthritis: results from the Spanish National Inpatient Registry over a 17-year period (1999–2015)—TREND-EspA study

ObjectiveTo assess the incidence of amyloidosis and trends therein in patients with spondyloarthritis (SpA) over a long period (17 years).MethodsAn observational retrospective population-based matched cohort study was conducted. All the admissions of patients with SpA, including ankylosing spondylitis (AS), psoriatic arthritis (PsA), arthritis associated with inflammatory bowel disease (SpA-IBD) and reactive arthritis (ReA), reported between 1999 and 2015, were analysed and a control group matched by age, sex and year of admission was selected. Incidence rates for amyloidosis were calculated. Generalised linear models were used for trend analysis and unconditional logistic regression for calculating crude and adjusted ORs (AOR) to assess the association between amyloidosis and SpA.ResultsThe study database contained data on 107 140 admissions in each group. Between 1999 and 2015, 792 patients in the SpA cohort (0.7% of all admissions) had a diagnosis of amyloidosis versus 68 in the non-SpA cohort (0.1%) (p<0.001). From 1999 to 2015, incidence rates of amyloidosis tended to decrease in the SpA cohort (−4.63%/year overall), while they increased in the Non-SpA cohort (+10.25%/year overall). We found strong associations of amyloidosis with all SpAs (AOR 10.4; 95% CI 8.2 to 13.3) and with each type studied (AORs 10.05 (7.84 to 12. 88) for AS, 9.5 (7.3 to 12.4) for PsA, 22.9 (16.6 to 31.7) for SpA-IBD and 10.1 (6.1 to 16.7) for ReA).ConclusionsIncidence of amyloidosis among patients with SpA has strongly decreased in Spain. Amyloidosis is most strongly associated with SpA-IBD while the strength of association with PsA and ReA is similar to that with AS.

Integral projection models

Integral projection models (IPMs) allow projecting the behaviour of a population over time using information on the vital processes of individuals, their state, and that of the environment they inhabit. As with matrix population models (MPMs), time is treated as a discrete variable, but in IPMs, state and environmental variables are continuous and are related to the vital rates via generalised linear models. Vital rates in turn integrate into the population dynamics in a mechanistic way. This chapter provides a brief description of the logic behind IPMs and their construction, and, because they share many of the analyses developed for MPMs, it only emphasises how perturbation analyses can be performed with respect to different model elements. The chapter exemplifies the construction of a simple and a more complex IPM structure with an animal and a plant case study, respectively. Finally, inverse modelling in IPMs is presented, a method that allows population projection when some vital rates are not observed.