Categories
Climate precipitation

Does Northern Hemisphere volcanic eruptions influence Sahelian rainfall?

In a recent study in Nature Climate Change Haywood and colleagues demonstrate how volcanic eruptions can influence Sahelian precipitation. Sadly the article is not open access, but from the abstract it seems like they are providing further evidence that aerosols are important for rainfall in the Sahel. In this context I also recommend the study by Huang which shows how black carbon also is a player in this game.

Haywood and colleagues suggest that sporadic volcanic eruptions in the Northern Hemisphere cause Sahelian drought. Using de-trended observations from 1900 to 2010, they show that three of the four driest Sahelian summers were preceded by substantial Northern Hemisphere volcanic eruptions. They used a state-of-the-art coupled global atmosphere–ocean model to simulate both episodic volcanic eruptions and geoengineering by continuous deliberate injection into the stratosphere. In either case, large asymmetric stratospheric aerosol loadings concentrated in the Northern Hemisphere were a harbinger of Sahelian drought whereas those concentrated in the Southern Hemisphere induce a greening of the Sahel.

Categories
Africa cattle Climate livestock

Cattle and Climate in Africa

Map of cattle in Africa in the 1960s and 2000s
Estimated cattle (heads per square kilometre) density around 1960 (upper left), 2000 (upper right) and difference (2000–1960, bottom) relative to the mean.

The role of cattle in developing countries is as a source of high-quality food, as draft animals, and as a source of manure and fuel. Cattle represent important contribution to household incomes, and in drought prone areas they can act as an insurance against weather risk. So far, no studies have addressed how historical variations in temperature and rainfall have influenced cattle populations in Africa. The focus of this study is to assess the historical impact of climate variability on national cattle holdings. We reconstruct the cattle density and distribution for two time periods; 1955–1960 and 2000–2005. Based on estimates from FAO and official numbers, we generated a time series of cattle densities from 1961–2008, and compared these data with precipitation and temperature anomalies for the same period. We show that from 1961–2008 rainfall and temperature have been modulating, and occasionally controlling, the number of cattle in Africa.

Lunde and Lindtjørn (2013) Cattle and climate in Africa: How climate variability has influenced national cattle holdings from 1961–2008. PeerJ 1:e55 http://dx.doi.org/10.7717/peerj.55
Categories
Climate climate change

How do we evaluate the impacts of climate change?

Working on a malaria model, where one of the abilities is to evaluate the impact of climate change, I have twisted my brain to understand how we should evaluate the impacts of a warmer planet. Sea level rise, fair enough; low lying land might potentially become flooded; the nature of precipitation might influence energy production; ice free Arctic might allow ships to take a shorter route. How climate influence human and livestock health is a more complicated question, and I believe we need to make some assumptions to evaluate the consequences.

When assessing how climate might change in the future, climate modellers have made assumptions, and work from the thinking that if emissions of green house constitutes continue as today, the planet will become X degrees warmer. If we cut emissions today, the temperatures will only increase by Y degrees. To understand how human health is influenced by a changing climate my personal opinion is that impact modellers should adopt the thinking from the climate community, and develop standardized scenarios about population growth, how housing improves (or not), how health systems change, irrigation, … The scenarios needs to be structured on grids, like the climate models. By having this type of standardized scenarios, we will be able to estimate the uncertainty of the impact models, and potentially draw some conclusions about how climate influence human and animal populations.

The 2010 paper by Gething et al. is a good example of how real world projections might become wrong when the society develops along with climate change. A malaria model using a scenario suggesting Europe and the Americas improved housing and health systems would probably come up with the same results as they find in their paper, but very few models take such changes into consideration. This type of scenarios become even more relevant as it seems like we are moving towards adaptation, while emissions carry on like before.

Categories
publishing

First experience with PeerJ

I have been mentioning PeerJ in a couple of posts lately. It is a new journal with an interesting concept, so we wanted to try it out. In the beginning of March we submitted a paper where we describe how climate have influenced national cattle holdings in Africa the past 40 years or so. This is our experience with the journal. After a few hours, an editor had been assigned, and after 19 days, two reviewers had read and commented the paper. The comments were written in a nice language, and the tone of editor, Jianhua Xu, was very pleasant as well. We responded to the reviewers’ comments, and one day later the paper was accepted. In my opinion, this is the speed journals should have. No delays because the manuscript is laying on a desk somewhere in the world. About six hours after acceptance, I was contacted by the Department of Publishing Operations, requesting some information, allowing us to do final corrections. If PeerJ manages to keep this speed, yet another reason to consider this newcomer.

Categories
publishing

How many read PeerJ

The new open access journal, PeerJ, has been accepting publications since December 2012. So far 46 articles have been published. The ideas behind the journal are brilliant; low costs for the authors, fast peer-review, and they do not evaluate the impact of the articles, only quality. Up till now articles have been published in batches, three so far, and a rough estimate tells us that about 10% of the submitted articles have been published. According to the PeerJ website, they expect an acceptance rate of about 70% once the journal is fully up and running. There seems however to be a delay about 20 days from acceptance till the final article is published, which might be fixed when PeerJ Preprints is up and running (Figure 1). I believe most authors want their paper out once it has been accepted.

acceptToPubl
Time from acceptance to publication in PeerJ according to publication batch

Another issue is the visibility of the articles. So far, it seems like very few people are aware of the journal, and probably not many has made the habit to visit the journal. The median number of unique views per day per article is currently 9.85, way too low in my opinion, but I guess the journal needs one or two years before such numbers make sense. The most read article has however 589 views per day,while the first article fronted by PeerJ has 188 unique views per day so it is indeed possible to attract readers to single articles. Figure 2 is showing the density of article views per day for the 46 first article. Anyway, I welcome this journal and their thinking, and hope more people will embrace it.

Density of unique views per day for the 46 first articles in PeerJ
Density of unique views per day for the 46 first articles in PeerJ

 

Edit: It would be interesting to compare the start-up of PeerJ with Scientific Reports. It seems like they published about the same number of articles the first month, but unfortunately SREP does not not show the number of accesses for articles published in 2011.

Categories
malaria

Malaria in the real world should not be oversimplified

A new study in Scientific Reports show that diurnal temperature fluctuations are important for a correct description of the dynamics of malaria in the real world. This is a nice addition to the previous work by Paaijmans, and once again it has been shown malaria models should not be oversimplified. Although we are getting closer to understanding how temperature influence malaria transmission, there are still many unresolved questions. In the srep article the authors also show how indoor temperature differ from outdoor temperature, and how this change malaria transmission. I totally agree this is an important factor, even though I do not agree on the functional form of the indoor-outdoor temperature relationship (see MJ article). Anyway, nice work, nicely written. Discussion is a must-read.

Categories
malaria OMaWa

Validating the malaria model

A dynamic model of some malaria-transmitting anopheline mosquitoes of the Afrotropical region. II. Validation of species distribution and seasonal variations

Background
The first part of this study aimed to develop a model for Anopheles gambiae s.l. with separate parametrization schemes for Anopheles gambiae s.s. and Anopheles arabiensis. The characterizations were constructed based on literature from the past decades. This part of the study is focusing on the model’s ability to separate the mean state of the two species of the An. gambiae complex in Africa. The model is also evaluated with respect to capturing the temporal variability of An. arabiensis in Ethiopia. Before conclusions and guidance based on models can be made, models need to be validated.

Methods
The model used in this paper is described in part one (Malaria Journal 2013, 12:28). For the validation of the model, a data base of 5,935 points on the presence of An. gambiae s.s. and An. arabiensis was constructed. An additional 992 points were collected on the presence An. gambiae s.l.. These data were used to assess if the model could recreate the spatial distribution of the two species. The dataset is made available in the public domain. This is followed by a case study from Madagascar where the model’s ability to recreate the relative fraction of each species is investigated. In the last section the model’s ability to reproduce the temporal variability of An. arabiensis in Ethiopia is tested. The model was compared with data from four papers, and one field survey covering two years.

Results
Overall, the model has a realistic representation of seasonal and year to year variability in mosquito densities in Ethiopia. The model is also able to describe the distribution of An. gambiae s.s. and An. arabiensis in sub-Saharan Africa. This implies this model can be used for seasonal and long term predictions of changes in the burden of malaria. Before models can be used to improving human health, or guide which interventions are to be applied where, there is a need to understand the system of interest. Validation is an important part of this process. It is also found that one of the main mechanisms separating An. gambiae s.s. and An. arabiensis is the availability of hosts; humans and cattle. Climate play a secondary, but still important, role.

Malaria Journal 2013, 12:78

Categories
Climate malaria OMaWa

Using climate models in malaria models

Weather is important for transmission of malaria. The simplest way to measure the current weather is to walk outside and feel whether it is cold or hot, and see if it is sunny, cloudy, or rainy. Weather and climate models always start with a measurement of the current weather. Rather than relying on the perceived conditions, the weather models need accurate observations of the current weather. Such observations can be derived from satellites measuring the temperature, pressure, winds, and vapour content of the atmosphere. In addition, weather balloons can be used to correct the satellite derived observations. Once the current weather has been measured, these observations can be used as initial conditions in climate and weather models, and weather can be foretasted up to ten days ahead. With additional information about the temperature, density and salinity of the ocean, weather can be projected a season ahead. If you add volcanoes, variability of the sun, and greenhouse gasses, it is possible to estimate historical and future weather and climate.

 

Independent on which time period is of interest, these forecasts, or projections, have to be cover the entire Earth, and the forecasts involves solving millions of equations which demands computational resources. To keep the cost down, the global models are often run with a coarse resolution, dividing the Earth into squares of 250 km x 250 km. In regions where the land is flat for several thousand kilometres, and there is no ocean nearby, these coarse resolutions may be good enough to simulate the weather. Once a mountain, coastline, different land use, or soil types are present, the coarse global models represents the weather poorly. To aid this problem, one can use regional climate models (RCMs).

 

Regional climate models work by increasing the resolution of the global models in a smaller area, a domain, of interest. Such domain might cover southern Africa, Ethiopia, or western Africa, and resolve the terrain down to one by on km. The global climate model determines the large scale winds, temperatures, pressure, and humidity entering the smaller domain. The regional climate model can then resolve the local impact on weather from land use, orography, soil types etc., giving weather and climate information at much finer resolutions that what is feasible using a global model.

Categories
publishing

Discovery of new Monkey

Only a few months after the discovery of a new species of monkey has been identified in Africa, yet a new species hit the surface. It was during a visit to the deep forests  of DR Congo, close to the Lomami river (the same area as the previous discovery) we ran into a colony of the newly discovered species. The colony consisted of one individual. Unfortunately all documentation in form of photography were lost in the river on the journey back to Kinshasha, so you have to rely on our research notes, analysis done in the field, and our memory. We hope the new journal PeerJ will accept our publication based on the limited material.

Summary of Materials and Methods

A notebook, a faint memory, a lost camera, and a standard RGBA test.

Results
Pigmentation

Before loosing the camera, we were able to carry out a RGBA test accurately describing the pigmentation of the monkey.

Hair: 5494d2ff
Skin: d9e9f9ff
Ear skin: ffd4aaff
These are rather unusual colours, and might result from our research assistant being obsessed with camera filters, and suffering from loss of short time memory thus being unable to recall if any filters were applied at the time of taking the pictures. Since the ear skin has reasonable colours, we conclude he did not apply any filters, and that the RGBA analysis show the true colours.

Behaviour and anatomy

The most stunning feature of this new monkey is the lack of knees, quite unusual for monkeys which are known to spend considerable time in trees. The head is disproportionally large, and it surprised us how the neck was able to support the weight of the massive cranium. The torso is water drop shaped, and resembles the one of a penguin. Given that the monkey is living close to a river, and the obscure anatomy, we speculate this monkey is spending most its time in water, where supporting the weight of the head would not be a problem, and the lack of knees would be beneficial for swimming performance. At the time of observation it was however sitting quietly, and alone, at the river bank, playing with some research equipment our assistant had forgotten when taking water samples the previous day.

Conclusions
We have discovered a single water living, blue monkey in DR Congo. Probably it is mainly feeding  on fish, but this needs to be confirmed by an expensive research project, hopefully lasting several years. Since there are some weaknesses regarding the documentation, we hope naming the new species after the founders of PeerJ, Binfield and Hoyt, will ease the review process. We propose the monkey should be named Aquavivens toybin, or Aquavivens toJbin since toybin already has a twitter account.

 

#PeerJMonkey

Categories
malaria OMaWa

Malaria model has been published

A dynamic model of some malaria-transmitting anopheline mosquitoes of the Afrotropical region. I. Model description and sensitivity analysis

Background
Most of the current biophysical models designed to address the large-scale distribution of malaria assume that transmission of the disease is independent of the vector involved. Another common assumption in these type of model is that the mortality rate of mosquitoes is constant over their life span and that their dispersion is negligible. Mosquito models are important in the prediction of malaria and hence there is a need for a realistic representation of the vectors involved.
Results
We construct a biophysical model including two competing species, Anopheles gambiae s.s. and Anopheles arabiensis. Sensitivity analysis highlight the importance of relative humidity and mosquito size, the initial conditions and dispersion, and a rarely used parameter, the probability of finding blood. We also show that the assumption of exponential mortality of adult mosquitoes does not match the observed data, and suggest that an age dimension can overcome this problem.
Conclusions
This study highlights some of the assumptions commonly used when constructing mosquito-malaria models and presents a realistic model of An. gambiae s.s. and An. arabiensis and their interaction. This new mosquito model, OMaWa, can improve our understanding of the dynamics of these vectors, which in turn can be used to understand the dynamics of malaria.

 

Malaria Journal 2013, 12:28

A dynamic model of some malaria-transmitting anopheline mosquitoes of the Afrotropical region. I. Model description and sensitivity analysis