Passionate about Nigerian birds and butterflies… BDI interviews citizen scientist Abubakar S. Ringim

Abubakar Surajo Ringim obtained his MSc in Conservation Biology from the University of Dar es Salaam. He is a keen bird atlaser and BioMAPper and he is actively involved with the Nigerian Bird Atlas Project (NiBAP). We met Abubakar at a bird atlas and Virtual Museum workshop at the A.P. Leventis Ornithological Research Institute (APLORI) in Jos, Nigeria back in November 2017. APLORI is the only field station dedicated to ornithological research and conservation training in West Africa. The Institute contributes directly to knowledge infrastructure, especially in West African countries, while also providing a unique base from which to set up long-term ecological research projects. APLORI is a key partner in the Nigerian Bird Atlas.

Abubakar Surajo Ringim out in the field

How did you become a citizen scientist? What was the catalyst that got you going?

I became a citizen scientist because of my strong passion for biodiversity conservation. The major catalysts that keep me going is the amazing support that I get from APLORI, especially with the Nigeria Bird Atlas Project in order to achieve bird conservation in Nigeria.

What has been the highlight for you?

Every part of citizen science is cool and amazing for me, but birds and butterflies are definitely my favourite.

How has being a citizen scientist changed your view of the world?

Before starting my citizen science journey, I was engaged locally in collecting data on biodiversity for my own research. But ever since getting involved in citizen science projects my enthusiasm for biodiversity conservation has sky rocketed, mainly because of the Virtual Museum. The Virtual Museum has really opened my eyes to the power of citizen science in mapping the distribution of species for conservation.

The beautiful granite hills that surround APLORI

What does the term “citizen scientist” mean to you?

It means everything to me. It has helped me so much and it has given me a lot of encouragement, skills, knowledge and respect for the natural world.

What are you still hoping to achieve? This might be in terms of species, coverage, targets …

I hope to cover as many grid cells and record as many species as possible. I also hope to make some amazing discoveries through my observations. My main goal is to map the distributions of butterflies in Nigeria.

Vanessula milca buechneri – Lady’s Maid butterfly – LepiMAPped by Abubakar on the Obudu Cattle Ranch near Cross River National Park, Nigeria

What resources have been the most helpful? (And how can they be made better?)

For me, the Virtual Museum is a fantastic resource! It would be nice if the website could be a bit more user friendly/intuitive. This would certainly help in mapping species distribution, awareness raising and species conservation at local or national levels.

How do you react to the statement that “Being a citizen scientist is good for my health, both physical and mental!”?

I totally agree, it has been proven that time spent in nature, e.g. listening to bird songs and looking at plants helps to improve one’s mental health and reduces stress. Bird atlasing and BioMAPping also helps to keep one physically active as you walk countless steps snapping and mapping birds, butterflies, spiders etc.

What do you see as the role which citizen science plays in biodiversity conservation? What is the link?

It plays an absolutely critical role, because in conservation we often have limited time, funds and expertise to provide data on biodiversity. Citizen science is especially important now as we are losing biodiversity at an alarming rate globally. Citizen scientist play a vital role in providing scientists with data which can be used in environmental policy and decision-making.

Diplacodes luminans Barbet Percher – OdonataMAPped by Abubakar near Bunkure, Nigeria

BDInsight – July 2019

It has been an exciting few months at the BDI. From our first bird ringing expedition to the birth of PanGoPod Alpha, and everything in between. We are grateful to the awesome citizen scientist community in South Africa, and the rest of Africa, for continuing to be ambassadors for biodiversity.

Upcoming event: Winter Warmer BioMAP Record Refresher July 2019. Oh the weather outside might be frightful, but biomapping makes it all very delightful! Please help us to refresh the records in the Virtual Museum by revisiting your regular stomping grounds or favourite patches and snapping and mapping any and all critters that you might come across. Up to date data and species distribution maps are the key ingredients to successful biodiversity monitoring and conservation!

Bird Ringing Expedition

Fynbos Estate, a very special place, lies tucked away in the Paardeberg. It is just an hour’s drive north of Cape Town and it is a nature lover’s paradise! A tranquil and beautiful spot, it really feels like a home away from home. We are extremely thankful to the team at Fynbos Estate for welcoming us on their farm and for providing us with the first field testing site of PanGoPod Alpha (more on this later).

Earlier this year we had our first bird ringing expedition on the farm. We were five bird ringers on this pioneer expedition. From the perspective of the bird ringer, Fynbos Estate is paradise. There are lots and lots of distinct ringing sites, in a variety of habitats, providing a nice diversity of bird species.

The Fynbos Estate property has two sections. The lower section is agricultural, and they produce fantastic organic wines under the label Dragonridge. The winery is artisanal, and the wines are made using traditional and time-honoured methods. The farm uses no chemicals, which means the birdlife in the area is amazing. The upper section of the property is the Simson-Simons Nature Reserve, and consists of marvellous fynbos on the slopes and summit of the Paardeberg.

We also ringed at some other sites. During the pioneering expedition we teamed up with the ringers of the Tygerberg Ringing Group. On one of these joint events, we ringed at the confluence of the Diep and Mosselbank Rivers, on the farm Goedeontmoeting.

In total, the pioneering expedition processed a total of 375 birds of 27 species at Fynbos Estate itself. 136 birds were ringed at the two satellite ringing sites and we collected lots of valuable data on moult. For more information on how you can join in on one of these awesome bird ringing expeditions see

Karoo Gariep Nature Reserve

The Karoo Gariep Nature Reserve lies almost exactly halfway between Johannesburg and Cape Town along the N1. New Holme Guest Farm lies in the reserve, 7 km off the N1. This is the perfect spot to break the long journey between the cities. The food is amazing, the biodiversity is awesome and the hospitality of PC Ferreira and his family is world-class.

So we are very excited to welcome PC to the BDI family. PC has a passion for nature conservation and wants to share his love for the Karoo with the world. We have started a project at New Holme to renovate accommodation within the Karoo Gariep Nature Reserve. This is planned to be available for travellers in summer, starting this coming summer (2019), and after that it will be used by BDI researchers through the remainder of the year. Watch BDInsight for exciting unfolding information.

PanGoPod – Just Roll Up

In June this year we celebrated the launch of PanGoPod Alpha, our first eco-friendly, off-grid, mobile home! From its infant stage as a steel structure to a fully-fledged eco-home, the PanGoPod was incubated over a few months at our premises in Unit 4, Gunner’s Park in Epping, Cape Town. Pete Laver and Hendrik Louwrens hand raised PanGoPod Alpha, putting in many long hours, blood, sweat and some tears to produce an absolutely stunning and high-quality eco-home.

The PanGoPod is an attempt to prototype alternative housing that meets people’s basic needs, is healthy to live in, and has a relatively low impact on the environment. We also think that the PanGoPod will help us get researchers into remote locations where biodiversity research is needed.

We are so grateful to a long list of people, without whom this dream project would not have been possible. We would like to give a big thank you to our handful of private investors who have taken a chance on us as we try to blaze a tiny home trail in South Africa. Elbie Pretorius from Alexander Forbes has been instrumental in the initial stages of the process.

We want to thank Mano Caldis from CIA Property Specialists, who persuaded the owners of Gunner’s Park that it was a good idea to rent this space to us – a brand-new non-profit company. Mitchell Walker from Futurecon construction has been incredibly supportive throughout this process, from supplying the PanGoPod’s light steel frame to helping with some of the structural design elements. Mitchell has also gone out of his way to provide advice on almost every aspect of the build.

Robert Burger and Dennis Leeds from InTempo Trailers have gone above and beyond in manufacturing a beast of a trailer for us to transport PanGoPod Alpha. They also helped with additional associated engineering projects. Keith Watkins from Brights Hardware Store has been a massive help in sourcing materials and tools for the build. Keith even delivered items personally when we needed a rush order.

The team from Inov8 have been awesome neighbours at Gunner’s Park, dropping in to check on our progress and provide advice on a regular basis. They also created some super cool BDI and PanGoPod insignias for us (see the photo below). Caroline Wright of Caroline Wright Interiors gave us amazing advice on the interior design of the space. She also made up fabulous cushions for us (Romo and Hertex fabrics) which tie the space together, making it feel like a home.

Diana and Johan from Fynbos Estate have been ever supportive – they have provided a wonderful base for our bird ringing expeditions, and now they are providing a beautiful site for PanGoPod Alpha’s field testing. It has been so great to meet people like them who have a real passion for conserving the environment and promoting biodiversity research.

Lesego Gaotshetse helped paint and spruce up the pod in the lead up to the mini launch. Many people gave invaluable advice along the way, including Seppie Geldenhuys, Andrew and Tania Hood from Crafteeze, Dominic van Schouwen, Peter Rose, Eugene Moll, and Leal Wright. It is the collective effort of all these awesome folks mentioned (and the many who have gone unmentioned) that makes this exciting venture both possible and worthwhile.

Namaqua BioBASH

A group of enthusiastic citizen scientists went on a biomapping adventure to the Namaqualand region in the Northern Cape. On Wednesday, June 12th, a team of six citizen scientists (Jerome Ainsley, Chris Cheetham, Tino Herselman, Salome Willemse, Les Underhill, and Karis Daniel) gathered in Handvol Gruis guesthouse near Calvinia for a 5-day BioBash. The aim of a BioBash is to gather as much biodiversity data as possible for areas that we have no species distribution data.

Gathering biodiversity data in far flung places like this would not be possible without the incredible help from citizen scientists! The dedication and love that goes into BioBASH events like these are awesome to see. Biodiversity conservation relies on the efforts of caring citizens, aka ambassadors for biodiversity, across the country. Every record counts. Thank you!

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A Rainbow of Landscapes – PART ONE

Biodiversity can be assessed at several levels. We can look at genetic diversity at species level, we can look at the diversity among different species, or we can look at the diversity of natural systems in which different species interact – this is known as ecosystems. We can look at broader groupings of ecosystems, and finally we can look at the biodiversity of the planet as a whole. Someday, we may even be able to look further than that – we may find life on other planets and may one day be able to speak of the living diversity of the milky way as a whole and of other galaxies. But for now, let’s look at diversity on a level we can appreciate at a visual level – that of landscapes. Landscapes are formed through the interaction of living and non-living elements. South Africa is blessed with an incredible diversity of landscapes, all on a relatively small part of the planet.

As a country, South Africa is mostly high and dry! High, in that most of the country consists of a central plateau, with relatively narrow coastal plains surrounding it. Dry, in that more than half of the country gets less than 500 mm (20″) of precipitation per year, on average. Thus, South African landscapes tend to be mountainous, rocky, and rather barren. But there are savannas, grasslands and forest patches as well.

Let’s consider the central plateau first. This vast plateau stretches throughout all of South Africa’s nine provinces. Towards the south and west, it is a semi-desert region known as the Karoo – which in itself consists of several different vegetation zones. The northern and eastern Karoo is grassier, while the southern and western regions are characterized by succulents and shrubby plants. The typical Karoo is a flat, high plain, with widespread flat-topped hills. The hills are remnants of an even higher plateau most of which has eroded away over millions of years. The Karoo is ancient, and has sedimentary rocks dating back to over 300 million years in which fascinating fossils are found of our own ancient ancestors, the so-called ‘mammal-like reptiles’ or proto-mammals. These rocks are remnants of sediments kilometers in depth that were deposited when the Karoo was a vast inland sea! Over time the inland sea dried up as the landscape was uplifted by thousands of meters through the process of plate tectonics.

The amazing Karoo landscape – photo taken by Megan Loftie-Eaton at Garingboom Guest Farm

Though barren looking, the Karoo has extremely interesting wildlife, and a wealth of succulent plant species. In dry years, the rocks and open patches of soil are evident, but a season of good rain transforms the landscape into a lush and green plant paradise. In the past the Karoo abounded with herds of large mammals, like springbok and black wildebeest, but their numbers were decimated through over-hunting by humans. Today the Karoo is known mainly for its big herds of domestic sheep. There is little cultivation in the Karoo as the average rainfall is so low and erratic. Small wild animals still remain, some of them being quite rare and threatened like the riverine rabbit.

Riverine Rabbit Bunolagus monticularis – photographed and submitted to MammalMAP by Trevor and Margaret Hardaker

The northern-central portion of the plateau is lower in elevation, and hotter. This basin extends into Botswana to form the Kalahari Desert. Not a true desert; it is a region of dry and sparse savanna woodland and deep, mostly reddish sandy soils. There are some extensive and occasionally very tall sand dunes in the driest parts of the Kalahari. The Kgalagadi Transfrontier Park, between Botswana and South Africa, comprises an area of over 3,6 million hectares which is one of very few conservation areas of this magnitude left in the world!

A typical Kalahari scene – a herd of springbok grazing in the riverbed

The park is known for its large herds of springbok, gemsbok and blue wildebeest. Rivers, lined with large Camel Thorn trees, only flow in years of exceptional rainfall. But plants like the succulent Tsamma melons, and a variety of tubers growing in the deep sand, store water that can be exploited by animals and humans. The San People, or Bushmen, thrived in this region for thousands of years as hunter-gatherers with a truly minimal impact on the environment, but their traditional way of life is threatened by the advancement of our modern 21st century lifestyles.

The red sand of the Kalahari – photo by Victor Loftie-Eaton

To the north and east, the plateau receives higher rainfall. The central regions, most of which are in the Free State Province, are high, cold grasslands. Much of this is farmland now, but there are still pristine areas. These high grasslands are known as the “highveld”. A typical highveld landscape is vast and flat, with tall grass waving in the wind. Trees are only found on the occasional rocky hills, or along the banks of rivers and streams. Towards the eastern Free State, western KwaZulu-Natal, and the country of Lesotho, the plateau rises up into the highest mountains in southern Africa, the Drakensberg Mountains. The Drakensberg consists of volcanic rocks that poured out of huge cracks in the Earth’s crust about 200 million years ago. The highest peaks exceed 3,000 m (10 000 ft) in height. They are truly spectacular, with sheer, dark grey, basalt cliffs over a kilometer in vertical height in many places. The annual rainfall here is very high, over 1 000 mm/40″ per year. Despite the high rainfall, there are few forests, because of the dry and cold winters and frequent fires. The Drakensberg has some of the prettiest flowers to be found in South Africa, and a host of endemic species.

Monks Cowl, Drakensberg Mountains, KwaZulu-Natal Province – photo by Megan Loftie-Eaton

Grasslands are the most threatened habitats in South Africa and worldwide. Much of South Africa’s grasslands have been lost to agriculture or forestry. This has been very harmful to the ecology and biodiversity in these areas. Grasslands are not just grass! They contain a wealth of other plant species: soft herbs and low shrubs, succulents, orchids and other flowering plant species, some with underground bulbs. Just after the first spring rains, when almost everything bursts into flower, these grasslands are fabulously colourful. They also support large numbers of wildlife, including the big and remarkable giant girdled lizard or sungazer, numerous mammals and a great variety of birds, including some endemic lark species. The marshy grasslands host elusive birds like cranes, flufftails and many others. The draining of wetlands as well as pollution from mining and other human activities have placed a lot of stress on these ecosystems and its wildlife.

North of the Magaliesberg range (Gauteng and North-West Province), and to the west of the northern Drakensberg, the ‘highveld’ gives way to ‘bushveld’, which is a savanna landscape of grass dotted with trees. Most of the trees are thorn trees, such as the flat-crowned Umbrella Thorn, which is typical of much of the savannas of Africa. Other typical bushveld trees include Silver Cluster-leaf, Red Bushwillow, Buffalo Thorn, Karee, and Marula. A particular feature of the bushveld are the many isolated rocky hills. These are often inhabited by rock hyraxes, small rodent-like creatures that are actually relics of a primitive kind of hoofed mammal that was once very diverse in Africa and included species as large as small horses! The rocky hills have unique plant life including many succulents, huge examples of which are the Aloes and Tree Euphorbias.

Tree Euphorbia or Naboom Euphorbia ingens – photographed and submitted to TreeMAP by Christopher Willis

In PART TWO of this blog series we keep traveling through the rainbow of landscapes that is South Africa. Watch this space!

This blog was written by guest blogger by Willem van der Merwe. Willem is a wildlife artist based in Polokwane, South Africa. He says, “my aim is simply to express the beauty and wonder that is in Nature, and to heighten people’s appreciation of plants, animals and the wilderness. I’m fascinated by wild things from all over the world.”

Atlas maps: choice of grid scale

Traditionally, we have used the quarter-degree grid scale to generate distribution maps in biodiversity atlases. In southern Africa, this convention started with the Bird Atlas of Natal, published in 1980, four decades ago. There is no explanation in the book as to why Digby Cyrus and Nigel Robson, the project team and co-authors, chose this grid scale. It was adopted by almost all subsequent biodiversity atlas projects.

The butterfly species which is used to illustrate this blog is the Common Dotted Border Mylothris agathina. The photo shows the “dotted border”. There is a total of 3,290 records of this species in the LepiMAP section of the Virtual Museum. This record was made by citizen scientist Vincent Parker on 27 June 2019, from the Humansdorp district of the Eastern Cape. The record is curated at


This blog explores a range of alternative grid scales. But, as distribution maps go, it is a restricted range.  These are all simple presence-absence distribution maps for the butterfly species, Common Dotted Border Mylothris agathina, featured above. If this species of butterfly was recorded anywhere within a grid cell, the grid cell is shaded. The species might have been recorded only once, or multiple times; this is not shown in any way. If the species was not recorded, the grid cell is not shaded. These maps do not attempt to show relative abundance. They are analogous to the “on-off” distribution maps in field guides, which are generally reproduced at much the same size as postage stamps.

The blog steadily works its way inwards from two extremes. The first map presented uses a 60 minute grid and the second uses a one minute grid. Then it goes to 30 and three, etc.

This is the distribution map for the Common Dotted Border, on a one-degree grid scale (or 60 minutes). If the species was recorded at least once, anywhere within the grid cell, it is shaded. (If there is a photographic Virtual Museum record, the grid cell is shaded green; if there are only specimen records, the shading is dark grey.)

At first glance, the next map looks blank. You need to look at it carefully. The distribution of the Common Dotted Border is shown on a one-minute grid:


This map, using the one-minute grid, is essentially marking the exact points at which Common Dotted Borders have been recorded. But the individual dots are so small that, unless there is a cluster of them, they are hard to see. Below is the one-minute grid scale map for just KwaZulu-Natal. With this enlarged  map, the individual points are visible.

Do either of these maps give an accurate impression of the “truth”? In this case, the “truth” is the overall set of places where this butterfly occurs. The one-minute grid in KZN represents “truth” in the sense that this species has occurred in every one of these tiny grid cells (assuming of course that they have been accurately documented). But we also know that, if we went and looked for it, we would find this species in many (or even most) of the little gaps between the points where it has been seen and reported. In technical terms, the one-minute map is riddled with false negatives, places where the species does occurs but where it has not (yet) been recorded. So, although the one-minute grid cell map is telling the truth, it is not telling the whole truth! It does not show all the places where the species occurs.

The trick now is to argue that if a species is recorded at a point, it probably also occurs in the “neighbourhood” of that point. But as soon as we start implementing this gimmick, we introduce false positives. These are places where the species does not occur, but where the distribution map shows it as present. On the grid maps we are considering in this blog, “neighbourhood” is defined in a precise way. Every point belongs to a grid cell, and that grid cell is its “neighbourhood”. If we define neighbourhoods in this way, using a one-degree (60-minute) grid, then just a single record within the grid cell results in the entire degree square being shaded. In the KwaZulu-Natal map, there is only one record of Common Dotted Border in degree cell 2730 (which has 27°S and 30°E in its northwest corner). This is the cell that straddles the border between KwaZulu-Natal and Mpumalanga. This record is on the eastern edge of the one-degree cell. On the map above with the one-minute grid, the “neighbourhood” of the point, the one-degree cell 2730, is shaded. This strategy undoubtedly introduces false positives. Defining the “neighbourhood” as a whole degree cell is just too big.

Let us step down to a 30-minute grid (or we could talk about a half-degree grid cell, but grasp that there are four half-degree grid cells in a one-degree grid cell):

The general impression given by this map is of a species with a continuous distribution. Lots and lots of gaps between individual records have been filled in.  The species is now characterized by having a distribution through most of the savanna in the north and along the southern coastal areas, continuing northwards along the west coast to about Velddrif and the estuary of the Berg River. There might be lots of false positives, with the “neighbourhood” system pushing the species into areas where it does not occur. At the same time, there are unlikely to be any false negatives! If the distribution of the Common Dotted Border really is continuous, this map might not be far from reality!

The map below is on a three-minute grid. With the map produced at this resolution, the points of occurrence of the Common Dotted Border are now easily visible.

Like the one-minute grid, this map clearly also suffers from false negatives. The true distribution is certainly far more “continuous” than this. It is not clear whether the areas with intriguing patterns of records (such as across Limpopo and Mpumalanga in northern South Africa) are due to “biological factors” or “distribution of citizen scientists”. It is possible to disentangle these factors, and for many serious researchers this map would be fascinating. They would be looking at in conjunction with maps showing relief, vegetation types and human population density.

Next up is the traditional map, made on a fifteen-minute grid, also known as the quarter-degree grid:

Compared with the distribution map on the 30-minute grid, this map is beginning to suggest a somewhat fragmented distribution. Look, for example, at the distribution in the savanna regions of Limpopo and Mpumalanga. The gaps are not random,  but seem to occur in patches. By looking at this map,  we cannot tell whether these are real, or represent regional variation in observer effort.

Here is the distribution map made with a five-minute grid. This is the grid scale in use by the Second Southern African Bird Atlas Project, where the cells are known as pentads. There are nine pentads in a quarter-degree grid cell. 

The pentad scale probably keeps the impact of false positives to a manageable level. But most people would look at this and say: “With a bit of effort, a lot of the little gaps could be covered.” So there are false negatives too. Maybe, this choice of grid represents a balance between the false negatives and the false positives.

The Appendix to this blog presents maps on a few more grid scales.

There are many other strategies for producing maps. But that is a topic for another blog. For example, you could put a circular disc around each point and define “neighbourhood” in this way. Define the distribution as the total area covered by discs. You can then experiment with what happens when you vary the diameter of the disc. There are also families of statistical methods, which use “explanatory variables” such as altitude, rainfall and temperature. These methods try to uncover the ranges of values of these variables at the points where the species occurs, and then extrapolate the distribution to the full set of points with these values for the explanatory variables. The bottom line is that no matter what you do, you end up with false positives  and false negatives.

This has been a fascinating blog to produce. We have not done exercises like this before, and I had no idea which grid cell would be the “best” choice. The reality is that it is impossible to choose. To make a choice, we would need to know the true distribution. But that is precisely what we are trying to find!

This exercise has been done on a single species. So this is a sample of size one, an anecdote, and it is dangerous to draw conclusions from an anecdote. We would probably need a sample of at least 20 or 30 carefully chosen species. The species should be chosen by lepidopterists who know the species from fieldwork experience. One of the main criteria would be to select a range of species, from species with distributions known to be near-continuous to those with highly fragmented distributions.

The choice also depends on the application for which you need the distribution maps. Your selection depends on whether you are the author of a field guide (and need a simple map), a biogeographer or macroecologist (and want to look at patterns of distribution on a continental scale), a Red List evaluator (and require an estimate of the area of the range of the species so as to allocate a threat status) or an environmental impact assessor (needing to know whether a species occurs at a particular plot of land earmarked for development). There are many other categories of users who all have specific desires for their distribution maps.

Finally, this exercise has also been a bit unfair to the Virtual Museum data. The data were assembled with mapping at a quarter-degree grid in mind. It is a bit shabby now to plot maps at finer scales, but it is interesting that quarter-degree grid patterns are not in evidence at all.

Perhaps the take-home message for Virtual Museumers is this. Please do not hesitate to submit repeat records for a species in the same quarter-degree grid cell, but try to get them spread over the grid cell.


And just for completeness sake, here are maps at a series of intermediate grid scales to those presented above.

10 minute grid:

20 minute grid:

40 minute grid:

And finally, here is the distribution map at the two minute grid:

Overall, in this blog, maps have been presented at these grid scales: 1, 2, 3, 5, 10, 15, 20, 30, 40 and 60 minutes.




Longevities of shrikes, bush-shrikes and helmet-shrikes

Southern Boubou

The shrikes, bush-shrikes and helmet-shrikes were formerly all classed together in one family, but have been split into separate bird families (shrikes, bush-shrikes) and the helmet-shrikes have been moved into the Vangidae family. After a brief description of each of these groups, the ringing numbers and longevities will be presented.

The true shrikes (family Laniidae) are predatory passerines – the family name derives from the Latin word for “butcher”, referring to their feeding habits. Shrikes are known for catching insects and small vertebrates and impaling these on thorns, barbed-wire fences, or other sharp points. This allows them to tear the prey into smaller pieces, and serves as a cache for feeding on later. Most shrike species are found in Eurasia and Africa, although two species occur in North America.

birdpix 82579
Common Fiscal

The bush-shrikes (family Malaconotidae) are insectivorous species are found in Africa, in scrub or open woodland. They are similar in habits to shrikes, hunting insects and other small prey from a perch on a bush. The bush-shrikes are either colourful species or largely black; some species are quite secretive. The bush-shrikes include the Brubru, puffbacks, tchagras and boubous.

Southern Boubou
Southern Boubou, greatest longevity in southern Africa of the “shrike” groups

The helmet-shrikes are now separated from that group into the family Vangidae. These African birds are found in scrub or open woodland. They are similar in feeding habits to shrikes, hunting insects and other small prey from a perch on a bush or tree. They are colourful species with the distinctive crests or other head ornaments, such as wattles, from which they get their name. Helmet-shrikes are noisy and sociable birds, some of which breed in loose colonies.

White Helmet-shrike



Relative to commonly ringed birds in southern Africa, few shrikes have been ringed over the last 7 decades. The highest ringing totals are for the widespread Common Fiscal, with over 7000 ringed. This species also has the highest recapture number although the Southern Boubou has a slightly higher recapture rate (12.6%). The Southern Boubou has the highest longevity record in the SAFRING database, at 16 years.

Table – ringing data for shrikes from the SAFRING database, extracted 5/7/2019.

Species Latin Ringed / retraps / recovered Longevity Ringno
Lesser Grey Shrike Lanius minor 350 / 3 / 0 0y 0m 8d CV38328
Common Fiscal Lanius collaris 7129 / 834 / 89 12y 7m 2d BB73315
Red-backed Shrike Lanius collurio 2431 / 144 / 8 7y 6m 0d 58219185
Southern Boubou Laniarius ferrugineus 2458 / 309 / 23 16y 0m 16d 4A13311
Swamp Boubou Laniarius bicolor 103 / 10 / 1 2y 7m 23d BB70663
Crimson-breasted Shrike Laniarius atrococcineus 1214 / 79 / 6 8y 2m 17d 494589
Southern Puffback Dryoscopus cubla 2246 / 205 / 9 8y 0m 21d BD13331
Southern Tchagra Tchagra tchagra 229 / 20 / 1 5y 0m 3d CC73515
Three-streaked Tchagra Tchagra australis 1965 / 169 / 6 7y 0m 19d CV50705
Black-crowned Tchagra Tchagra senegala 309 / 24 / 1 3y 1m 29d 469906
Marsh Tchagra Tchagra minuta 12 / 1 / 0 0y 11m 23d BE46526
Olive Bush Shrike Telophorus olivaceus 578 / 34 / 0 9y 8m 24d BB95191
Orange-breasted Bush Shrike Telophorus sulfureopectus 617 / 57 / 1 6y 11m 15d BE33105
Black-fronted Bush Shrike Telophorus nigrifrons 7 / 0 / 0
Gorgeous Bush Shrike Telophorus quadricolor 176 / 13 / 0 4y 4m 5d CV28603
Bokmakierie Telophorus zeylonus 1311 / 118 / 13 8y 1m 16d 4A50927
Grey-headed Bush Shrike Malaconotus blanchoti 310 / 17 / 1 4y 0m 10d 460954
Long-tailed Shrike Corvinella melanoleuca 916 / 84 / 2 2y 2m 23d D44690
Yellow-spotted Nicator Nicator gularis 135 / 6 / 0 3y 9m 29d 4H53721
White-tailed Shrike Lanioturdus torquatus 158 / 9 / 0 4y 10m 10d BH49364
White Helmet-shrike Prionops plumatus 1226 / 9 / 0 5y 0m 29d BC33931
Red-billed Helmet-shrike Prionops retzii 107 / 1 / 0
Chestnut-fronted Helmet-shrike Prionops scopifrons 28 / 0 / 0
White-crowned Shrike Eurocephalus anguitimens 429 / 22 / 1 6y 1m 25d 594922
Brubru Nilaus afer 287 / 15 / 1 8y 6m 5d BC26973
Fulleborn’s Black Boubou Laniarius fuelleborni 10 / 1 / 0

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How to create a species distribution map in the Virtual Museum

Today, we provide the recipe for creating a species distribution map for a butterfly, the Painted Lady Vanessa cardui, directly off the current and live data in the LepiMAP database. You don’t need to login to access the maps. They are available to you, free of charge, anywhere in the world — AND the recipe is the same for ALL projects in the Virtual Museum.

Step ONE: Go to the Virtual Museum

Step TWO: Click on the LepiMAP logo (or any other project logo from which you want to extract a map)

Step THREE: Down the left-hand side menu on your screen, click on “Maps”. As in the picture below:

Step FOUR: Type any part of the scientific or common name into the search box to activate the name search. Then click on “Request summary” – you can get a distribution map for the whole of Africa too.

Our server searches the LepiMAP database to find the all the records of Vanessa cardui, and then creates the distribution map and displays it for you. This takes a few seconds. Once the map is displayed you can right click on it and select “save image as…”

On the distribution maps, the turquoise circles represent Virtual Museum records, uploaded by citizen scientists, and the orange squares represent mainly specimen records. When you look at the map, you can immediately see why we launched LepiMAP. It is instantly clear that there are lots of grid cells where the Painted Lady must occur, but for which we do not have records yet. Help us to refresh the data in the Virtual Museum.

You can make a difference for biodiversity conservation by uploading your photos to the Virtual Museum. The instructions on how to go about uploading photos to the Virtual Museum are here.


Virtual Museum: open for refreshments!

As you drive your new car out of the showroom, its value drops dramatically, and then keeps on dropping. It’s not quite as bad with the Virtual Museum. But, from the time it is uploaded, the “value” of every record does slowly decrease. A record in the Virtual Museum has three components: species, place and date. The record is evidence that a particular species was recorded at the place on the date. But, as that date recedes into the past, the record becomes less and less valuable as evidence that the species STILL occurs at the site. The record needs to be “refreshed”.

This blog aims to answer two questions. (1) How do I find when a species was last recorded at a place? (2) What is the rate at which a record loses value through time, and how often does it need to be “refreshed”?

We first need to define what we mean by a “place”. For Virtual Museum purposes this is a  “quarter degree grid cell” (QDGC).  These are almost exactly square on the equator, about 27 km north to south and 27 km east to west. At the northern and southern limits of Africa, about 35°N and 35°S, a QDGC is still 27 km north-south, but has shrunk to 23 km east-west. Not quite square, which is why we talk about “cells”. There is nothing magic about the choice of the QDGC as “place”. But this unit of area has long been used in biodiversity mapping in Africa, especially southern Africa. There are about 2,000 QDGCs in South Africa, and about 50,000 in Africa as a whole. If you define the “place” as some smaller unit, then you have to worry about refreshing records in an even bigger number of places. The QDGC represents a convenient trade-off between a fine grid and a manageable number of grid cells.

So the first question boils down to: “How do I find when a species was last recorded in a quarter degree grid cell?” The blog will help you find the six-character code for grid cells south of the equator in Africa. The trick described there is to google the name of the place and ask for the coordinates (eg search for “Kuruman coordinates”, to try to find coordinates in the format of decimal degrees (Kuruman is 27.450°S 23.433°E) and then follow the instructions in the blog to find the code for the QDGC (2723AD)).

To get a list of the scorpions of Kuruman, the incantation is

and you will find that (at the time of writing this blog) one species is listed, Pseudolychas ochraceus, photographed on 8 November 2018 (see

But the focus of this blog will be on QDGC 2528CA, which covers central Pretoria, and the area northwards just west of the N1 (“Pretoria North”). It is an area characterized by rapid and relatively recent urban sprawl:

This map is available at

The map is the same no matter what you put for “vm=” in the incantation. This section of this blog is going to focus on the reptiles for this grid cell, so I chose vm=reptilemap.

Below the map is a list of the 78 species of reptile recorded here. The top 14 lines look like this:

The columns are self-explanatory. For the purpose of this blog, only one is important: “Last recorded”. This gives the date of the newest record of the species in the grid cell. The dates, quite frankly, are alarming! In row 8, the last record of Boomslang was in 1990. That is three decades ago. Does this snake still occur here?  It almost certainly does, in spite of the pressures of development. But it still needs to be formally “refreshed” and confirmed by the submission of a new photographic record.

In this list of 14 species, the oldest date in the “last recorded” column is for the Dusky Worm Lizard. There are two records of this reptile, the most “recent” from 1911. This highlights the fact that the ReptileMAP database includes all the museum specimen data, going back to the year dot, assembled for the SARCA project. These old museum records are really valuable in pointing out what species we should be on the lookout for now.

The “youngest” record is for the Southern Tree Agama, last “refreshed” on 10 February 2016 (curated at There are 18 records of this species in this QDGC; you can see them by clicking on “Records” at the end of the line when you have this “live” on your screen (it won’t work on this screenshot).

Here are the last eight species on the list of 78 for QDGC  2528CA, Pretoria North:

It tells us that Puff Adder was last refreshed on 10 September 2018, less than a year ago. This is the most recent of 59 records, and can be found at

The bottom row is key. It tells us that there are a total of 1,271 reptile records for this QDGC. That is a lot of records. Then come two dates. The top date, with the single asterisk, is the median of the 78 “Last recorded” dates. So half the species were last seen before 14 December 1988, and half the species after that date. 1988 is a long time ago. There is a massive need to refresh the reptiles in this QDGC.

How do some of the other sections of the Virtual Museum compare on this criterion? To get the dragonflies and damselflies from OdonataMAP, the incantation used above changes to

The map is the same as the map above,  but the species list looks like this:

There are only 10 species. The median date of the most recent records is 4 February 2017, which is excellent. The Little Wisp has a “Last recorded” date in 1999. This is a specimen record: – it has no photograph. It is a candidate to be “refreshed”. (The lower date, with two asterisks, 22 November 2016, is the median date for all 16 records.)

Here is the LepiMAP incantation:

It shows that there are 2,390 records of butterflies and moths for the QDGC 2528CA, and that 178 species have been recorded here. That is awesome. But the median date for the “Last recorded” column is 8 January 2009. That is a whole decade ago. To keep this information up-to-date, there are lots of opportunities here for species to be refreshed!

For BirdPix, the incantation

shows that there are 118 records of 58 species, and that the median date of “Last recorded” is 4 September 2013. That is six years ago. There is a general need even here for refreshment. Please explore these ideas for the QDGCs and species groups that interest you. The pattern of the incantation to the website always has this format:

You need to change lepimap to the section that interests you, the 2528CA to the quarter degree grid cell which you want to explore.

The recommended fieldwork strategy in the QDGC is to have a target list of “long-in-the-tooth” species that you want to refresh, but to grab every opportunity that comes your way. You can pre-empt the need to refresh species by keeping the entire data base “young”.

It would be fantastic to be able to produce “up-to-date” distribution maps for species using data from, say, the most recent three years. Here is an amazingly encouraging pair of maps:

The top map shows the distribution of the Common Dotted Border, using 2,483 records since 1 January 1980. It includes historical data from museums and private collections assembled during the SABCA project. In QDGCs with only historical data, the shading is grey. If there is photographic Virtual Museum data,  the shading is green. The bottom map is based on 555 Virtual Museum records submitted in three-and-bit years since 1 January 2016. The lower map is inevitably sparser, but it is identical in overall pattern. This is a remarkable achievement by the citizen scientists of Team LepiMAP!

These two maps illustrate the value of keeping the database refreshed!

(The inset illustration of this butterfly is one of the most recent submissions of a Common Dotted Border. The photograph was taken on 29 June 2019 by Neil Thomson in the Waterberg,  Namibia – see It is one of three records of the species from QDGC 2017AD, and is a bit to the north of the two Namibian records shown on the maps.)

Now we need to tackle the second question. How quickly does a record lose value? It would need a workshop of biodiversity experts to provide a good answer, but here is a first stab at this. Suppose a record has value 100% at the time when it is made. The “value” is the strength of the evidence that  the species occurs at this date and place. After three years the value might be 80%.  After five years, the value might drop to 50%, after 10 years to 10% and after 20 years, the record might have no value at all. In other words, the fact that a species was recorded in this grid cell 20 years ago is useless as evidence that I can still expect it to persist there.  These suggestions can be turned into a graph, with the gaps between the values above joined by straight lines:

Not everyone would agree with this precise curve, but the general shape is likely to be right. In an era with unprecedented rates of development and climate change, records of biodiversity need to be “refreshed” at regular intervals to provide ongoing evidence of the persistence of a species at a locality. For the Virtual Museum, we would love records to be refreshed before three years have elapsed. This would enable us to generate up-to-date distribution maps, such as the one above for Common Dotted Border.

The Virtual Museum is open for refreshments.


The birth of the PanGoPod

Last Saturday, 22 June 2019, Les Underhill and I were lucky enough to join in for the very special occasion of handing over the keys of PanGoPod Alpha to its first residents, two French students that have been helping Dieter Oschadleus with bird ringing on Fynbos Estate. The day might have been grey, rainy and cold, but it did not dampen our spirits. We forgot the champagne too, but with a glass of delicious Grapetizer each, we celebrated the housewarming of the brand new PanGoPod.

All smiles as we celebrated the birth of PanGoPod Alpha

From its infant stage as a steel structure to a fully fledged eco-home, the PanGoPod was incubated over a few months in the shelter of Unit 4, Gunner’s Park in Epping, Cape Town. Pete Laver and Hendrik Louwrens hand raised PanGoPod Alpha, putting in many long hours, blood, sweat and some tears to produce an absolutely stunning and high quality eco-home.

The PanGoPod in its embryo stage

It was fantastic to see PanGoPod Alpha in its natural habitat, out in the field, at Fynbos Estate. Pete and Hendrik did an amazing job to get the PanGoPod ready and livable on site. Thank you team! The students were very excited to spend their first night in the eco-friendly, off-grid tiny home that runs off of solar panels, rainwater collection, and has a composting loo…..the ingredients for happy inhabitants and a happy Earth.

The beautiful, functional and stylish interior of PanGoPod Alpha

The PanGoPod is an attempt to prototype alternative housing that meets people’s basic needs, is healthy to live in, and has a relatively low impact on the environment. I was amazed at how cozy and well laid out the PanGoPod was. I could see myself living in one of these eco-homes very easily and having some experience with living in all sorts of field research accommodation, the PanGoPod feels like a 5-star hotel. We are very excited to roll-up and roll-out PanGoPods throughout South Africa (and even the rest of Africa, because why not?) as an eco-friendly and affordable housing alternative for field researchers, or anyone that could benefit from having an awesome off grid home like this. Details on how to order your very own PanGoPod will be available soon, so watch this space!

PanGoPod Alpha on site at Fynbos Estate

We would like to give a huge thank you to the wonderful people of Fynbos Estate for providing us with the first field testing site of the PanGoPod. For more BDI news, photos and stories follow us on InstagramTwitter or Facebook.

Quarter-degree-grid cells made simple

Lump it or leave it, quarter-degree-grid cells are entrenched in the mapping system of South Africa. In an article called “SA Mapsheet Referencing“, the government tells us that “each map of the National Map Series is identified by its unique number (e.g. 2830CB) … “. Quarter degree grid cells are also deeply entrenched in the biodiversity mapping of South Africa. The first bird atlas project in South Africa was the Bird Atlas of Natal, which collected data from  1970 to 1979. We have no idea why the coordinators of that project, Digby Cyrus and Nigel Robson, selected the quarter-degree-grid cell system, but most subsequent biodiversity mapping (= atlasing) projects in South Africa followed their lead.

Often we know (or can easily use Google to find out) the coordinates of a place, but we need to know the “code” for the quarter-degree grid cell (QDGC) the place falls into. One of the objectives of this blog is to enable us to do this.

But first we need to know how the system works. The code for a QDGC has four numbers and two letters (and only A, B, C and D are used). 2830CB is an example. First, I will attempt an explanation in words, and then use two diagrams. The four numbers, 2830, tell us which degree square we are in. 2830 is the code for the degree square with 28°S and 30°E in its northwest (top left) corner. Next divide the degree square into quarters. Call the two on the top row A and B, and the two in the bottom row C and D. Top left is A, top right is B, bottom left is C and bottom right is D. So the C in 2830CB tells us that this QDGC is in the bottom left corner of the degree square; call it section C. Repeat the process one more time. Split each quarter degree square into four, and label them A and B, C and D, in the same way. So the B in 2830CB points us to the top right quarter of section C. It’s a messy explanation, and there must have been far simpler ways to do this. But we are stuck with this “official” system, and we have to come to  grips with  it!

In diagrams, it is far easier to explain. These are the official diagrams.

This is degree square 2830.

This diagram shows how degree square 2830 is divided firstly into four quarters, and how the first level of letters works. Then the bottom left quarter, section C, is subdivided for the second time, and quarter-degree-grid cell 2830CB is shaded. Easy.  Now that you have seen the diagrams, read the explanation in words again!

There are 16 quarter-degree-grid cells in a degree square. But the lines that demarcate the grid are at 15′ (fifteen minute) intervals. and 15′ = a quarter of a degree. So it is a quarter-degree grid, and we talk about quarter-degree-grid cells (where you are free to hyphenate in any way you choose!).

Suppose now you want the Virtual Museum‘s list of the Lepidoptera, the butterflies and moths, which have been  recorded in QDGC 2830CB. The incantation you need to do this is

When you go to this website, the information you get looks like this, but it is bigger:

2830CB turns out to be in rural KwaZulu-Natal. The village called Tugela Ferry is in the southeastern corner. This website provides a map of the quarter-degree-grid cell, and a list of the species of Lepidoptera recorded. There are 16 so far. Unpacking the rich amount of information on this page is going to be the topic of another blog. This incantation works for all grid cells and for all the sections of the Virtual Museum. The two places where you need to make changes are in green:

You need to customise the project, and chose the QDGC (called a “locus” in the incantation).

But this is the rub. Suppose I want a list of the scorpions of Calvinia. How on earth do I find the code for the QDGC that Calvinia falls into? You start by googling “Calvinia coordinates”. You get an embarrassment of riches – the answer comes in three formats: 31°28′30″S 19°46′22″E / 31.47500°S 19.77278°E / -31.47500; 19.77278. The easiest one to work with is the second one, in decimal degrees. Calvinia is 31.475 degrees south and 19.773 degrees east. Split these numbers into whole degrees and the decimals (i.e. 31 and 0.475, and 19 and 0.773, rounding off to three decimal places). Combine the degrees (31 and 19) into a string of four numbers. We are in degree square 3119. Next I take a piece of paper, and do this scribble:

The fractions are in decimals (and NOT minutes). The left hand edge is the north-south part. The north-south fraction is 0.475, which lies between 0.25 and 0.5. So Calvinia is in one of the cells along the second row of the scribble (AC, AD, BC, BD). The east-west fraction is 0.773, which is bigger than 0.75 (along the top edge). So Calvinia is in the fourth column. The intersection of second row and fourth column is BD. So the code for Calvinia’s QDGC is 3119BD. Let’s give this a whirl for scorpions. The incantation is

It delivers this information

Gosh, there is only a single record of a scorpion recorded from this grid cell in ScorpionMAP. Fieldwork is needed!

What QDGC lies one to the west (left) of 3119BD Calvinia? The quickest way to find this is to go back to the scribble. It is 3119BC. But what QDGC lies one to the east. It is beyond the edge of the  scribble; it is in the next degree square, one to the east of 3119. This must be degree square 3120. Looking at relative positions of the QDGCs in the scribble, the cell to the east of letter code BD must have code AC. So the QDGC one to the east of 3119BD  is 3120AC. There MUST have been an easier way to do this business of giving codes to the QDGCs!

The paragraphs that follow deal mainly with the complications of being in the northern hemisphere. Most readers can skim to the end.

A Norwegian geographer, Ragnvald Larsen, visited Africa. He thought our quarter degree grid cell system was the best thing since sliced bread, and devised a way to apply it to the whole world. If you google “QDGC”, the second item is his enthusiastic blog post. The first item is a Wikipedia article, in which the author(s) think of the QDGCs as “tiles” that cover the earth’s surface. This is quite a nice concept.

But there are two problems. The first problem gets really serious when you reach about 60°N or 60°S. Quarter-degree-grid cells are not really “squares”. In the north-south direction, every QDGC is 27.4 km long. On the equator, they are also 27.4 km wide. They shrink in width as you go north or south, because the lines of longitude get closer together, and converge at the poles:

This is what a QDGC looks like in northern Greenland at 83°N! In the far north, and south, QDGCs get narrower and narrower because the lines of longitude all converge to meet at the poles. It would be unthinkable to do a bird atlas in northern Europe using quarter-degree-grid cells. In this extreme example, in northern Greenland, the QDGC is still 27.4 km north to south, but a sliver of land 4 km wide from east to west.

But at the northern and southern ends of Africa, for example at Cape Agulhas, they are only a little narrower, at 23.0 km. So, throughout Africa, QDGCs are, for all practical purposes, approximately square. But as you go farther north, or south, they get narrower and narrower. It would be unthinkable to do a bird atlas in Europe using quarter-degree-grid cells. In Finland, for example, they would still be 27.4 km north to south, but slivers of land only a few kilometres wide from east to west.

The second problem is that codes like 3119BD assume that the 31 is south and the 19 is east. The system makes no provision for north or for west, and does not admit to the fact the east and west longitudes can be three digit numbers, as they are in Australia! Rene Navarro devised a universal system. As an example, have a look at record, a butterfly from Ethiopia. It’s in grid cell which he has called NE_010037BC. This means that it is 10°N and 37°E. Looking at the scribble above, the BC means that the record is between 10.25°N and 10.5°N and 37.5°E and 37.75°E. (It is agony to think about it, but the actual layout of the scribble in the northern hemisphere, and in the western hemisphere has to be different. If you are north and east, like in Ethiopia, AA needs to be in the bottom left corner, because north is increasing from bottom to top. If you are north and west, like in Senegal, AA needs to be in the bottom right corner, because both north and west are increasing in the opposite direction to what it does in the south and east! It’s messy.)

For  some light relief at the end of this blog, here is the butterfly from Ethiopia mentioned above. It is curated at and was recorded in grid cell NE_010037BC. It is a Citrus Swallowtail Papilio demodocus, submitted to LepiMAP by Tesfu Tujuva on 9 April 2019. This butterfly has a range throughout Africa south of the Sahara Desert, and then extends northeast through the Horn of Africa as far as Oman in the Arabian Peninsula. Go to to see where this QDGC is, and to find out whether other species of butterflies and moths have been  recorded here.

The QDGC system has proved exceptionally valuable for the purpose of generating maps of the distribution of species in southern Africa. We would love the maps to be on a finer scale, but for most groups of species (except the birds), the quarter degree grid system is the best we can achieve with the available data. It is likely to prove useful throughout Africa. This is why we have extended the naming system so that it can be used throughout the continent (and even worldwide).

From the official mapping perspective, we have no idea who invented the system for naming the quarter-degree-grid cells. But it has been in use for almost a century, since the first QDGC maps were produced by the part of government known at the time as “Trig Survey.” The system has stood the test of time. We have no choice but to get to grips with it.

Exploring data: the median and the mean, and everything in between

Here is the assignment for this blog. “Write a report on the progress being made in the Western Cape by the BirdPix section of the Virtual Museum.” The report needs to communicate to the citizen scientists who participate in the project. It needs to provide them with insights into how well the project is doing.

This map shows one aspect of progress. It provides the number of records submitted to BirdPix per quarter degree grid cell. There are lots and lots of numbers. This is not anecdote; this is real data, from which recommendations need to be made.

I could write something like this.  One long paragraph could start “Grid cell 3018DA Kliprand in the far north has 32 records,” … later on it would say … “grid cell 3318CD Cape Town has 1322 records,” …  and it would end by saying … “grid cell 3420CC at Cape Agulhas has 67 records.” This paragraph would fill up a few pages with utterly boring and useless text. It is just providing essentially the same information as is presented a lot more effectively in the map. What is needed is some sort of a summary of the data. I need to convey the overall picture, and not get bogged down in detail.

In general terms, the first task of any statistician is to summarize lots of numbers down to a tiny handful of numbers. The message in the data cannot be accessed by reading every number, or by simply eye-balling the data. There are just too many numbers to absorb. To extract succinct stories out of data is the role of the statistician, .

Now this blog is supposed to be a tutorial, and not a full scale data analysis, so I will illustrate the ideas with a subset of the Western Cape; this map goes from Langebaan to Cape Town, and inland.

The first thing to determine is the sample size, the number of numbers. This is 23. The statistician would write n=23. Statisticians have a convention that they reserve the letter n for sample size. Woe and betide any statistician who comes along and uses n for any other purpose. Mathematics is full of these little conventions and rules; if you know these secret codes, equations can often be understood far more quickly.

The sample of size 23 is big enough not to be trivial.  But it is small enough to be manageable. Here are the numbers, copied row by row off the map: 20 430 2 43 13 9 12 67 57 93 64 33 16 72 258 484 44 59 1322 1022 132 54 86. These are the numbers of BirdPix records per gridcell.

The first (and obvious) thing to try is the mean,  also called the average. We have known how to calculate this since we were schoolkids. Add the numbers together, and divide by the number of numbers. In this case, it is 4392/23=191.0. So the mean is 191.0 records per grid cell. We do this bit of trivial arithmetic, and move on to the next task. But, hey, let’s stop and look at this more carefully. Does 191.0 make sense? Does it really communicate what is going on in the sample? A little thought shows that the mean is doing a ghastly job of summarizing the data. Only five of the 23 values are larger than the mean: 258, 430, 484, 1022 and 1322. And the remaining 18 are smaller than the mean. The arithmetic is perfectly correct, but somehow it doesn’t make sense. The mean does not really communicate where the “middle” of the data really lies.

Statisticians have a strategy for dealing with this problem. They simply sort the data, and pick the number in the middle. When they are sorted the 23 numbers look like this: 2 9 12 13 16 20 33 43 44 54 57 59 64 67 72 86 93 132 258 430 484 1022 1322. The number in the middle is 59. There are 11 numbers which are smaller than 59 and 11 which are larger. This number in the middle has a technical name. It is called the median.

We are trying to communicate how well BirdPix is doing. In this situation, the median, 59 records per grid, communicates the reality far better than the mean, 119.0, does. The mean is biased, pulled upwards by the two grid cells with more than 1000 records. In contrast, the median is unfazed by “outliers”. If the largest number in the dataset was 13220 instead of 1322, the impact on the mean would be dramatic (it would change to 708.3), but there would be no impact on the median. The number in the middle remains 59. There is a technical term for this property of the median. In their jargon, statisticians say that it is robust against outliers.

There is a formula for finding the “rank” of the median. Once the numbers are sorted, the median has rank (n+1)/2. With n=23 numbers the median has rank (23+1)/2 = 12. It is the 12th largest number.

This works fine when the sample size is an odd number. But if n is even, there’s a problem. Suppose n=24. The the median has rank (24+1)/2 = 12½. The trick is to use the average of the pair of numbers in the middle of the sorted sample as the median. The median would be defined as the average of the 12th and 13th largest numbers in the sample of 24 numbers.

We now go back to our sample of 23 sorted numbers: 2 9 12 13 16 20 33 43 44 54 57 59 64 67 72 86 93 132 258 430 484 1022 1322.

The smallest number is 2, the largest number is 1322, and the median, the number  in the middle, is 59. A more subtle question is to ask to what extent the numbers are concentrated around the median, or are they spread out towards the two extremes. One clever way to get a handle on this is to compute the medians of the top half  and the bottom half of the data.  In broad brush terms, the “lower median” will be a quarter of the way from the smallest number, so it gets called the lower quartile, and the “upper median” will be a quarter of the way from the largest number, so it gets called the upper quartile.

There are various ways of doing this. The right way is to take this set of numbers  as the bottom half of the data: 2 9 12 13 16 20 33 43 44 54 57 59. Note that it includes the median, 59. There are now 12 numbers. 12 is an even number. So we need to find the middle pair of  numbers; they are 20 and 33. Their average is 26.5. This is the lower quartile. The top half of the data also contains 12 numbers, because the median is used again: 59 64 67 72 86 93 132 258 430 484 1022 1322. The middle pair is 93 and 132, and their average is 112.5. This is the upper quartile.

The grid cell for Hopefield (3318AB) has only two records. Here is one of them. Black Stork Ciconia nigra submitted to BirdPix by Linda and Eddie du Plessis. This record is curated at


Our sample size of 23 is not exactly divisible by 4, so the rest of this paragraph is only approximately true. But as the sample size n gets bigger, it gets closer and closer to the truth.  A quarter of the sample lies between the upper quartile and the largest number, and a quarter lies between the lower quarter and the smallest number. So that means the remaining half of the sample lies between the lower quartile and the upper quartile. Half the sample is greater than the median and half the sample is less than the median. So these five numbers, smallest number, lower quartile, median, upper quartile and largest number provide a neatly interpretable summary of the numbers in our sample. We call them the five-number summary. However large n is, this strategy crunches the sample down to just five numbers. These provide real insight. But it is rare for them to be presented in a paper and actually called the five-number summary. Usually, they are plotted in a particular style, and that graphic is universally called the box-and-whisker plot. One of the next blogs in this series is  devoted to the box-and-whisker plot! And that blog will also reveal the person who invented this crazy name.

So for the small sample of n=23, a statistician would write the five number summary using this notation: (2, 26.5, 59, 112.5, 1322). Now that you are initiated into the secrets of unpacking and interpreting this, we know: (1) all the numbers lie between 2 and 1322, (2) half the numbers lie between 26.5 and 112.5, (3) half the numbers are smaller than 59 and half the numbers are greater than 59.

The grid cell for Hopefield (3318AB) has only two records. Here is second of the two. Steppe Buzzard Buteo buteo submitted to BirdPix by Mark Stanton. The record is curated at


Just for the record, for the Western Cape as a whole, confining ourselves to the 200 grid cells with at least one record, the five-number summary is (1, 7, 25, 58.5, 1322). Interpretation: (1) all the numbers lie between 1 and 1322, (2) half the numbers lie between 7 and 58.5, (3) half the numbers are smaller than 25 and half the numbers are greater than 25. (And there are 62 grid cells without data!) This summary becomes interesting when it is put alongside the summaries for the other nine provinces, and that is what the box-and-whisker plot, coming to you in a blog soon, will achieve. The simple recommendation out of this analysis is that vastly more data are needed before we can claim that BirdPix has a comprehensive dataset for the Western Cape.

The mean and the median seem to be very different animals. Try this exercise. The trimmed mean is calculated by finding the mean after the smallest and largest values in the sample (2 and 1322 in our small dataset) have been eliminated. The trimmed mean is 146.1. we can repeat the process. Chop off the two largest and two smallest  numbers, and find the mean of the remaining 19 numbers: the 2-trimmed mean is 107.2. Keep going. If the sample size is odd, you ultimately are left with a single number, which is the median. If the sample size is even, ultimately you reach a point were you need to take the average of two  numbers, which is also the median. So the mean and the median are the two ends of a spectrum. The trimmed mean is a real strategy for describing the “middle” of the data,  in situations where there are only occasional outliers.

When should you use the mean  and  when should you use the median? There are no strict  rules. The median is always good, and it has a simple interpretation. The mean works fine if the sample has no outliers. If the mean and the median are close together, then the mean will be fine.  In fact the mean is then preferred. This is because a vast amount of sophisticated statistical theory has been built up around the mean, and so it has become the dominant way to measure the “middle” of a sample. But,  beware, as in the example used here, the mean is often misleading.

The blog draws heavily on the textbook IntroSTAT. If you are impatient to move faster than these blogs on “data and statistics” do, then you can download the whole book. It is an amazingly small file (1.6MB).

Karis Daniel  produced the maps.