What birds do we have, where are they, why are they there, how many are there and what threats to they face?

The Birds of Tanzania: An Atlas of Distribution and Seasonality

The earliest handbooks did not include maps, just mention of the few localities from where specimens had been collected and these were often very few indeed. One of the earliest regional handbooks to incorporate maps was The Birds of the Belgian Congo (Chapin 1932) which used maps for some species to show continental as well as regional distribution. Museum specimens carried details of their origins and as collections were enlarged such data were used to create distribution maps by “joining up the dots”. Mackworth-Praed & Grant (1952-1973) used this method in their African Handbook of Birds, the maps being rather small and generally little more than thumbprints in the margins of the text. Meanwhile, in Europe mapping based on far larger collections was becoming more sophisticated, the first grid based book on bird distributions was The Atlas of Breeding Birds in Britain and Ireland (Sharrock 1976) to which nearly 15,000 people contributed. The predecessor to this monumental work using amateur enthusiasts to collect records was an Atlas of the British Flora (Perring & Walters 1962). Although a handful of other flora had been mapped using grids by individual botanists working in limited areas.

Since the 1960s many countries (and far smaller units) across the world have created grid based bird atlases using a variety of scales to suit the size of the country, region or county being mapped and the number of observers available to meet the required target. Blakers et al. (1984) used 1 degree squares (approx 10,000km²) for their Australian Atlas while Webster (1997) used a 1km² grid for a far smaller area of less than 120km².

In Africa bird Atlases have been published as coarse as 1 degree for the Sudan (Nikolaus 1987) and as fine as 1/8th of a degree for Swaziland (Parker 1994). However, at the 5th Pan-African Ornithological Congress it was agreed that to ensure conformity across the continent the basic recording unit should be the 1/2º x 1/2º square (Ash & Pomeroy 1981). This recommendation has been followed by many countries and within the east-central Afrotropics atlases have been published for Kenya (Lewis & Pomeroy 1989), Uganda (Carswell et al. 2005), Malawi (Dowsett-Lemaire & Dowsett 2006 ) and Zambia (Dowsett et al. 2008) all based around the quarter degree square with local variations as different opportunities have arisen.

The East African Natural History Society established a mapping scheme for East Africa in the late 70s. It soon became apparent that coverage in Kenya was far in advance of Uganda and Tanzania and the emphasis shifted to efforts in individual
countries.

In Tanzania initial mapping was based upon the now standard quarter degree square but the first field cards designed in 1985 included for monthly data and an abundance code. The rational for the former was the requirement for seasonality records and that most observers were resident and thus able to contribute regular data. Gathering abundance data in such large areas is problematic but it was felt at the time that an effort should be made in this regard and this has proved useful in identifying sites of importance for waterbirds where conservation values relate to numbers (Wetlands International (2006).

Ideally an Atlas will cover a fixed time period to allow comparisons with future surveys, highlighting any population changes and establishing trends. By incorporating a year field the Tanzania Atlas allows for this and population trends in reporting rates have already been used for conservation purposes (Morrison 2008, Baker 2008).

The 1/2º x 1/2º square covers approximately 2,500km2, too large an area when trying to evaluate species ecological limits but covering even these 353 squares in Tanzania is a huge undertaking given the limited human resources available. Using a smaller unit such as the 1/4º x 1/4º would have been quite impossible. However the introduction of hand held GPS units in the mid 90s allowed far greater levels of accuracy and the use of altitude in helping to define the range of a species. Bird observations are now collected within 500m of a georeferenced point and where possible a vegetation profile is created that will allow useful analysis between bird species and preferred habitats. This will be especially useful as ground-truthed data for analysis with satellite derived variables at the scale of 1km².

Initially the locality field was used simply to define the square but this as evolved to allow site based species list for individual forests, lakes, protected areas etc. Creating species lists, abundancy codes and viability codes for protected areas has been further enhanced by adding a field to the database that allows ready access of data for any designated National Park or Game Reserve.

Initially no allowance was made for day dates but these have been added to allow analysis of migration patterns. No specific field for counts was incorporated in the early years of the project but these are now deemed of importance, especially for waterbirds (Baker 1996, Baker & Baker 2002, Delaney et al. 2009), adding yet another field to the database.

An example from the database and an explanation for each field is given in Table 1.

At the time of writing there are 862,000 records entered on the database. 30,699 of these are breeding season records and 9,842 are egg months, the ultimate goal for breeding season definition. These records have come from almost 500 contributors and include some literature data deemed accurate enough to place within an Atlas square.

Early maps were simple scattergrams using MSexcel (Baker 1996). However, since 2004 GIS maps have been produced in ARCGIS using 90m SRTM data to show elevation bands. More recent maps use the 30m SRTM data, providing new insights into altitudinal limits.

The example maps (Map1-7)used in this paper are based around the distribution of the Ashy Starling Cosmopsarus unicolor which is endemic to Tanzania yet often locally common and quite widespread. It is an easy bird to find and identify allowing some confidence when discussing NEGATIVE DATA.