One of our most prolific contributors to the ALA is Reiner Richter, a wildlife photographer from Victoria. He has been taking nature photographs as a hobby for many years and has submitted over 13,000 fantastic sightings to the ALA.
Reiner uses the ALA to assist with identification for species that he is less familiar with.
“If I know what the genus might be I will search for species within that genera that are nearby using the mapping tools,” Reiner said.
He also uses the ALA to find gaps in data then embarks on expeditions to fill them. A couple of years ago, he noticed a gap between Lakes Entrance and Orbost and upon searching there, he found a population of Austrocnemis splendida, a small damselfly that is quite rare in the state.
While searching for and photographing species, Reiner has made some interesting discoveries. His rediscovery of a Micraspis flavovittata, a ladybeetle thought to be extinct, garnered some attention in the mainstream media. From the unique markings, he knew on sight that this was a new species for him personally. Not finding an image of such a species anywhere on the web, he passed it on to experts, starting with Museum Victoria. He is hopeful that this species can get listed as critically endangered as a result.
One of the things Reiner finds most rewarding is to photograph fungi in winter.
“Many strange fungi remain unidentified as the kingdom is vast and there are few experts in the field, so relatively few species have been described,” Reiner said.
Please contact us if you would like to share how you use the ALA.
The scatterplot function links the sampled values of any two environmental variables on a species (or genus etc) with the map. Points on the scatterplot represent the environment found at each occurrence record, as given by the environmental variables of the two axes of the scatterplot.
The scatterplot (environmental space) and the map (geographic space) are linked. Dragging a rectangle over an area of the scatterplot to enclose occurrence points will highlight the corresponding points on the map. You can also define an active area on the map and have all occurrences within that area highlighted on the scatterplot.
From the menu option, select ‘Tools’ and then ‘Scatterplot’.
The scatterplot requires a minimum of three parameters – a species or taxonomic group and two environmental variables.
Any legend permits modification of the display of the associated layer. In the scatterplot tool, this means that both the points (occurrences) in both the map (geographic) and environmental (scatterplot) space. To activate the legend in the scatterplot, click on the ‘Species display setting’ button. This will create a floating legend that will permit rendering the points in both spaces on the basis of selected legend properties. For example, in the image at the top of the page, under the facet dropdown box on the legend, “Institution” was selected and the Apply button pressed. After a little while (for many points) the points on the scatterplot and the map will be coloured according to the institution facet.
For more detailed information on Scatterplot faceting »
A case study on using the scatterplot tool to investigate the distribution of Banksia integrifolia in Australia, is given by Dr Ben Raymond of the Australian Antarctic Division, Hobart.
Read the Case Study »
For Step 4, we are now using the general window for any type of environmental/contextual layer selection. If you tick the box next to “Display possible environments“, the scatterplot will be shaded (from dark meaning a small area of that environmental combination – to light meaning a large area of that environmental combination) to display what environmental combinations are possible – and not all are, thankfully.
In the context of the scatterplot, it is likely that you will want to use the ‘Add from search‘ box and either enter part of the name of the layer or its short name (e.g., Bio01 for “Temperature – annual mean”) and then check the box on the left of the name to select it. Ditto with the second layer. At the bottom of the window, you will see the number of layers selected and this should equal 2 before clicking on the next key (bottom right).
An alternative is to import the names of the two layers from a file – and this can be done from the top dropdown box. The names of the two selected layers can of course also be exported using the ‘Export set’ button at the bottom of the table. You can then re-import the list using the import option from the top dropdown box.
Once you have entered the name of the primary taxa (Eucalyptus camaldulensis), the (primary) occurrences are mapped.
The background taxa group is the genus Eucalyptus. This gives us a good indication of what environments the genus covers and what portion of that environment is covered by E. camaldulensis. These occurrences are only mapped on the scatterplot in orange in the background. The E. camaldulensis is shown by blue points. If the highlight records in the active area was selected, then those records would be ringed with a red circle.
In the worked example, we will use temperature (Temperature – annual mean (Bio01)) and precipitation (Precipitation – annual (Bio12)) as the two environmental variables to define the environment. Once these two variables have been added, the scatterplot is generated. As there is a large number of occurrences (Eucalyptus has over 240,000 records), processing can take up to a minute or so. The distribution of Eucalyptus (orange dots) covers a significant portion of the scatterplot, thereby indicating that the genus can handle a wide range of temperature and rainfall conditions. The majority of the distribution is below 2,500mm rainfall, with two higher rainfall extensions at low and high temperature. To learn more about the environment used by the genus, make it the primary taxa.
Eucalyptus camaldulensis is located toward the bottom of the scatterplot distribution and clearly follows the outline of the genus ‘envelope’ on the low precipitation end, but over a broad range of temperature. This suggests that E. camaldulensis is stereotypic of low rainfall adapted eucalyptus. However, it covers mean annual temperatures from 12°C to nearly 30°C – a very impressive range!
Let’s look at some of the outliers to see where they occur. First, the low temperature end. Drag a rectangle over the lower end occurrences on the scatterplot. This highlights the corresponding points on the map, near Cressy in Tasmania and Macedon in Victoria. The former is low altitude, but further south than the higher altitude Macedon.
Let’s do the same at the high temperature end to see where these occurrences are located. Drag the rectangle on the scatterplot and then examine the highlighted occurrences on the map. Not unexpectedly – the high temperature occurrences are found in the extreme north of Australia.
Note that the range of temperature and rainfall values of the rectangle are listed above the scatterplot. In this case, a mean annual temperature range of 25.6130°C to 28.0974°C and rainfall between 285.996mm and 485.908mm. Also note that there are 20 records selected
The selected occurrences could be used to create two new mapped layers – an ‘IN-group’ containing only those 20 occurrences and an ‘OUT-group’ containing all the rest. This option can be useful for filtering/separating out a subset of occurrences for further analysis in say the spatial prediction model. Also note that there are 73 occurrences that have one or two missing environmental values of temperature or rainfall. If an IN/OUT groups are created these occurrences are added to the OUT-group by default. If you click the checkbox saying ‘Select records with missing values’, then the corresponding occurrences will be highlighted on the map and added to the IN-group. In all cases, these occurrences are located off the terrestrial temperature and rainfall surfaces; they occur in the ocean. This may be due to the resolution of the surfaces or of the coastline or just inaccurate occurrence locations.
Next, let’s consider why E. camaldulensis doesn’t occur in a few environments on the scatterplot.
There is a hole in the distribution of E. camaldulensis at around 25°C and 600mm that is filled by other eucalypt species (shown by the orange Eucalyptus background points) so that environment exists in nature. But why are there no occurrences here? There are at least four possibilities:
The same situation doesn’t occur with the ‘dent’ in the environment at around 14°C and 2500mm. Obviously that environment doesn’t exist in Australia (at least not represented by the environmental layers we have chosen) – and it is therefore not surprising that no eucalypts are to be found. The eucalyptus background covers much of the potential environmental range indicating the ubiquity of the genus. The grey-scale of the ‘display possible environments in area’ indicate the size of the corresponding mapped areas, with black representing only a small area with this environment in Australia, and reversely white, a large area. For example, there are only small areas of Australia with extreme rainfall (around Tully in Northern Queensland), and a large area of very low rainfall. This can be examined further by examining the environmental layers: Temperature – annual mean (Bio01) and Precipitation – annual (Bio12).
Mean annual temperature and annual rainfall were chosen because these variables were very likely to constrain the spatial distribution of eucalyptus. You may wish to use the Prediction Tool (MaxEnt) to find out which environmental variables best seem to control the distribution of Eucalyptus camaldulensis.
By Lee Belbin, Geospatial Team Leader
This post has been written and produced by Emilie Ens from Macquarie University, Sydney.
Over the last couple of years the ALA has been working with the Yugul Mangi Rangers and Macquarie University ecologists to build cross-cultural biodiversity knowledge of SE Arnhem Land. Additionally the collaboration has helped develop Indigenous content in the ALA website and raise awareness nationally, about Indigenous science and biodiversity management. The team has just published a paper called “Putting Indigenous Conservation Policy into practice delivers biodiversity and cultural benefits“.
In July 2016, the team held a regional woman’s biodiversity and cultural knowledge sharing workshop at Ngilipitji in eastern Arnhem Land. Thirty five women attended from the three ranger groups in the region (Yugul Mangi Rangers from Ngukurr, Yirralka Rangers from Yirrkala and Numbirindi Rangers from Numbulwar) as well as the Ngukurr Yangbala (Young) Rangers. Ngilipitji was chosen as a mid-way point for the groups and because it lies close to the border of the Laynhapuy Indigenous Protected Area (managed by the Yirralka Rangers) and the proposed SE Arnhem Land Indigenous Protected Area (managed by the Yugul Mangi and Numbirindi Rangers under the Northern Land Council) and is considered a “shared management” zone.
The team conducted biodiversity surveys over three days and nights in an area that according to ALA data, had not been surveyed in the past. We set up 70 Elliot, 15 Cage, 6 Pitfall, 15 Funnel and 12 camera traps over three sites (Rocky hill, Bottom spring, Top spring) to detect mammals and reptiles. We conducted one night search around the outstation for geckoes, did plenty of fishing and made opportunistic sightings of species. Despite the remoteness of this Country, surprisingly we only found 4 skinks (Carlia munda, Cryptoblepharus metallicus), 5 geckoes (Gehyra australis, Heteronotia binoei), 2 water rats (Hydromys chrysogaster), 2 dingoes (Canis lupus dingo), 3 crows (Corvus orru), 8 Black Bream (Hephaestus fluiginosus) and freshwater crocodile’s (Crocodylus johnsoni) eyes shining at night in the creek. One feral cat, 2 cane toads and evidence of feral buffalo and pig were also seen. We found no frogs, small mammals, large reptiles or turtles. The lack of animal sightings was suggested as due to the weather being cold and at times windy and raining. However the presence of feral animals and possibility of past damaging late dry season wild fires were also discussed as possible causes.
At each site we did plant collections, pressed specimens and are still processing and identifying the species. However about 50 species were recorded, all were commonly known. Some lively knowledge exchange occurred around the plant species. The common medicinal plant Eucalyptus tetrodonta was called bambuja by the SE Arnhem mob and gadayka by the NE Arnhem ladies. All grasses were called wiji in Marra, mulmu in Yolngu matha and notho in Ngandi languages. The large Acacias (Acacia auriculiformis and A. aulacocarpa) were described as dukul in Ngandi, Ritharrngu and Ngalakan (SE Arnhem languages) and dhurrtji in Yolngu matha (NE Arnhem). Despite being relatively close in proximity, there were clear differences in language words for plants between SE and NE Arnhem Land.
In addition to exchange of language names and uses knowledge, senior Ngandi woman Cherry Wulumirr Daniels also facilitated cultural leadership and kinship discussions throughout the camp with her usual passion and command of everyone’s attention. On the last night, the Yirralka Rangers shared with everyone a cultural song and dance (manikay) about Ngilipitji that was recorded by their family members. They also taught the group a range of other songs and dances that often had environmental themes. This was followed by cultural performances and lessons from the Numbirindi Rangers and Ngukurr mob.
After the camp the Yirralka Rangers came to Ngukurr, many for the first time, and participated in an ALA workshop led by Rebecca Pirzl with input from Julie Roy, Yugul Mangi senior woman ranger. We downloaded the camera trap photos and shared all photos and videos with each other.
All the ladies had a fantastic time learning from each other and experiencing Country that many had never been to before. Although we only found a few animal species and common plant species, they were all significant records due to the lack of surveys in this area in the past. The knowledge exchange was deemed a success with annual exchanges and the need for more cross-cultural biodiversity surveys discussed.
Banbai nation people at Wattleridge Indigenous Protected Area in northern New South Wales are working with Michelle McKemey at the University of New England to develop season and fire calendars.
The calendars represent annual seasonal changes as well as biocultural factors that indicate the right, and wrong, time to burn. They are developed using results of ecological experiments, literature reviews, observations and cultural knowledge gathered through interviews. For more information read WINBA = FIRE, the Wattleridge IPA Fire and Seasons Calendar. The development of the WINBA = FIRE, Wattleridge Fire and Seasons calendar has been supported by the Firesticks Project.
The ALA is working with Michelle and her Indigenous collaborators to test an ALA prototype for an online interactive Indigenous seasonal calendar. This online platform will visualise and reflect the Indigenous knowledge contained within seasonal calendars and the context for which they were developed. The project will also create some opportunities for two-way sharing by linking to other biodiversity information contained in the ALA.
This work is part ALA’s Indigenous Ecological Knowledge plan which is exploring the role of various information management platforms in bridging the boundaries between traditional Indigenous knowledge and western science.