suvarna's Journal

Please fix your locality resolution (or locality accuracy or locality error). Too large an accuracy, or missing accuracy, means that the data are not incorporated into checklists for the smaller nature reserves and places, and cannot be used for conservation planning and red listing purposes.

Ideally we like it to be 2-5m accuracy, but often one is uncertain, or does not know quite where one was, in which case it might be 100s of metres. but please if you genuinely dont know exactly where you were dont make them too precise, even if it is to the nearest km or two.
You need to enter this in when you add your observations. It shows up as a circle showing the area in which you were where you are uncertain as to exactly where the point should be. You can enter the value directly in metres for the radius of the circle.
Please see how to enter these when uploading you data in this tutorial: https://vimeo.com/167431843

Here is your list of observations without Locality accuracy recorded:
https://www.inaturalist.org/observations?place_id=any&subview=table&user_id=suvarna&verifiable=any&acc=false

To fix it, please click Edit (up top) and type in the value in the "Acc (m)" box, and/or adjust the circle around your locality in the map. While at it please give a decent locality name (the Googlemap names are atrociously vague) - but be careful not to press "search" after entering the name as that will corrupt your coordinates.
and save ...

If you have lots, you will need to batch edit it: please see instructions here: https://forum.inaturalist.org/t/batch-updating-location-accuracy/11421 (Thanks Peter).

((please note: the app should record your locality accuracy automatically, if you take the photographs with the app. It wont if you add the photographs afterwards, in which case it needs to be manually inserted))

A hearty congratulations to all who have participated in the CNC2024 - from city champions + bioblitz organizers to observers who spent many hours in the field, then sorting through the copious images taken before uploading and the identifiers who spent many hours sharing their knowledge and raising the number of species recorded during the 4-day global event.

The City of Cape Town featured #10 for the number of observations made and #8 for the number of species recorded on the global leaderboard. See here for more global results.

We have much to celebrate as the southern African community as 36 cities, representing 9 African countries participated in the CNC 2024 (compared to 31 cities, representing 6 African countries in CNC 2023). A total of 136, 234 observations were made by 2,980 observers. Thus far 10,093 species have been identified by 1465 identifiers with this number increasing as more identifications are made with time. The number of casual observations has decreased to 9.1% from 12.5% last year implying that participants are focussing on wild species (ie. neither captive nor cultivated).

The most observed species in Africa was Osteospermum moniliferum (Bietou) with 715 observations.

Ranked in number of people participated:

1. South Africa*: 2778
2. Mozambique (Maputo): 28
3. Kenya (Nairobi + Kajiado): 22
4. Namibia (Windhoek + Katima Mulilo): 22
5. Botswana: 12
6. Malawi (Lilongwe): 10
7. Madagascar (Antananarivo): 9
8. Eswatini (Hhohho + Lubombo +Manzini):4
9. Gabon (Bakoumba): 2

Ranked in number of observations made:

1. South Africa*: 118,676
2. Botswana: 1,523
3. Namibia (Windhoek + Katima Mulilo): 1,302
4. Eswatini (Hhohho + Lubombo +Manzini): 776
5. Mozambique (Maputo): 389
6. Madagascar (Antananarivo): 321
7. Malawi (Lilongwe): 302
8. Gabon (Bakoumba): 274
9. Kenya (Nairobi + Kajiado): 153

Ranked in number of species recorded:

1. South Africa*: 9,028
2. Botswana: 571
3. Namibia (Windhoek + Katima Mulilo): 517
4. Eswatini (Hhohho + Lubombo +Manzini): 415
5. Mozambique (Maputo): 207
6. Malawi (Lilongwe): 177
7. Madagascar (Antananarivo): 160
8. Kenya (Nairobi + Kajiado): 110
9. Gabon (Bakoumba): 108

• Since 25 South African cities participated, the results will be featured per province as a separate journal entry.

Number of people participated:

1. Western Cape (Weskus, Cape Town, Overstrand, Garden Route): 1,551
2. KwaZulu-Natal (KZN South Coast, eThekwini, KZN Midlands, Dolphin Coast, Zululand): 496
3. Gauteng (Joburg, Tshwane): 342
4. Eastern Cape (Nelson Mandela Bay, Albany CoE, Buffalo City, Pondoland, Umzimvubu): 237
5. Limpopo (Waterberg Capricorn, Thohoyandou): 69
6. Mpumalanga (Wakkerstroom, Mbombela): 52
7. North West (Mahikeng, Potchefstroom): 36
8. Free State (Bloemfontein): 19
9. Northern Cape (Nieuwoudville): 5

Number of observations made:

1. Western Cape (Weskus, Cape Town, Overstrand, Garden Route): 64,025
2. KwaZulu-Natal (KZN South Coast, eThekwini, KZN Midlands, Dolphin Coast, Zululand): 23,031
3. Eastern Cape (Nelson Mandela Bay, Albany CoE, Buffalo City, Pondoland, Umzimvubu): 15,742
4. Gauteng (Joburg, Tshwane): 8,907
5. Limpopo (Waterberg Capricorn, Thohoyandou): 2,518
6. North West (Mahikeng, Potchefstroom): 1,818
7. Mpumalanga (Wakkerstroom, Mbombela): 1,595
8. Northern Cape (Nieuwoudville): 756
9. Free State (Bloemfontein): 302

Number of species recorded:

1. Western Cape (Weskus, Cape Town, Overstrand, Garden Route): 4,893
2. KwaZulu-Natal (KZN South Coast, eThekwini, KZN Midlands, Dolphin Coast, Zululand): 3,521
3. Eastern Cape (Nelson Mandela Bay, Albany CoE, Buffalo City, Pondoland, Umzimvubu): 2,703
4. Gauteng (Joburg, Tshwane): 1,582
5. Limpopo (Waterberg Capricorn, Thohoyandou): 890
6. Mpumalanga (Wakkerstroom, Mbombela): 731
7. North West (Mahikeng, Potchefstroom): 472
8. Northern Cape (Nieuwoudville): 245
9. Free State (Bloemfontein): 139

Number of identifiers:

1. Western Cape (Weskus, Cape Town, Overstrand, Garden Route): 934
2. KwaZulu-Natal (KZN South Coast, eThekwini, KZN Midlands, Dolphin Coast, Zululand): 542
3. Eastern Cape (Nelson Mandela Bay, Albany CoE, Buffalo City, Pondoland, Umzimvubu): 448
4. Gauteng (Joburg, Tshwane): 340
5. Mpumalanga (Wakkerstroom, Mbombela): 196
6. Limpopo (Waterberg Capricorn, Thohoyandou): 167
7. North West (Mahikeng, Potchefstroom): 107
8. Northern Cape (Nieuwoudville): 60
9. Free State (Bloemfontein): 50

While we understand that a proportion of observations are not of good photo quality to ascertain identification to species level, with time those keen on surveys can only improve their photography skills. We encourage our identifiers to share tips and tricks for their respective taxon groups and produce videos and crib notes that we share via our YouTube channel. Also, assist us by marking observations recorded in gardens as cultivated/ captive.

Our participation in CNC annually brings much fun being in nature, while feeding foundational biodiversity data to our national datasets, especially that of endemic, threatened, and protected species.
More importantly, CNC data is being analyzed by local government agencies responsible for managing and reporting on biodiversity at the municipal scale.

The South African Red List Plants and Animals Project produced 473 Threatened species

405 Plant species
33 Bird species
12 Mammal species
5 Reptile species
6 Amphibian species
5 Ray finned fish species

Note that these are records as per the South African Red List Plants and Animals Project which does not have all taxonomic groups listed.

The NEMBA Alien Species South Africa Project produced 265 Invasive species

242 Invasive Plant species
7 Invasive Bird species
5 Invasive Fish species
4 Invasive Insect species
2 Invasive Mammal species
2 Invasive Mollusk species

The CREW Programme provides in-person iNaturalist training to students based at HEIs across South Africa. Upon completion of the training, a project is set up to track student participation over the year. The student with the most observations is then awarded.

Participation in CNC 2024 is as follows:

Tshwane University of Technology (Environmental Management): 184 observations; 84 species
Highest observer: @ayanda_moiponi (92 observations)

North West University (Mahikeng campus): 120 observations, 53 species
Highest observer: @maeka (34 observations)

Tshwane University of Technology (Nature Conservation): 2 observations; 2 species
Highest observer: @nomthandazo6 (2 observations)

Mangasutho University of Technology (Nature Conservation): 3 observations; 2 species
Highest observer: @reply1 (2 observations)

Sadly no participation from students at the University of Johannesburg

Searching all comments: https://www.inaturalist.org/comments?q=silky%20nest
your own comments: https://www.inaturalist.org/comments?for_me=true&q=silkypuff
also: https://www.inaturalist.org/comments?commit=Search&q=robin 1

Observations without any ID: &iconic_taxa=unknown(includes Bacteria)&identified=false

Observations identified by a particular user (e.g. myself): &ident_user_id=suvarna

OBSCURED DATA: (observations and identify)
no positional data: https://www.inaturalist.org/observations?acc=false
above: https://www.inaturalist.org/observations?acc_above=10000
below: https://www.inaturalist.org/observations?acc_below=3
also: &acc_below_or_unknown

NO LOCALITIES: &geo=false

user private: https://www.inaturalist.org/observations?geoprivacy=private
user obscured: https://www.inaturalist.org/observations?geoprivacy=obscured
user obscured or private: https://www.inaturalist.org/observations?geoprivacy=obscured_private
taxon private: https://www.inaturalist.org/observations?taxon_geoprivacy=private
taxon obscured: https://www.inaturalist.org/observations?user_id=kueda&taxon_geoprivacy=obscured

NO DATE
https://www.inaturalist.org/observations/identify?quality_grade=casual&verifiable=false&photos=true&captive=false&geo=true&taxon_id=517449

PROJECTS:
projects in a place: (restricted to those with a centroid in the place)
https://www.inaturalist.org/projects/browse?place_id=botswana

YOUR STATS: https://www.inaturalist.org/stats/2018/you
SITE USAGE STATS: https://www.inaturalist.org/stats

For more: https://www.inaturalist.org/journal/tonyrebelo/17377-filter-cribsheet