Seed dispersal by Martu peoples promotes the distribution of native plants in arid Australia.

Commensal relationships between wild plants and their dispersers play a key ecological and evolutionary role in community structure and function. While non-human dispersers are often considered critical to plant recruitment, human dispersers have received much less attention, especially when it comes to non-domesticated plants. Australia, as a continent historically characterized by economies reliant on non-domesticated plants, is thus a key system for exploring the ecological role of people as seed dispersers in the absence of agriculture. Here, we utilize a controlled observation research design, employing ecological surveys and ethnographic observations to examine how seed dispersal and landscape burning by Martu Aboriginal people affects the distribution of three preferred plants and one (edible, but non-preferred) control species. Using an information theoretic approach, we find that the three preferred plants show evidence of human dispersal, with the strongest evidence supporting anthropogenic dispersal for the wild bush tomato, Solanum diversiflorum.

First Peoples' knowledge leads scientists to reveal 'fairy circles' and termite linyji are linked in Australia.

In the past, when scientists encountered and studied 'new' environmental phenomena, they rarely considered the existing knowledge of First Peoples (also known as Indigenous or Aboriginal people). The scientific debate over the regularly spaced bare patches (so-called fairy circles) in arid grasslands of Australian deserts is a case in point. Previous researchers used remote sensing, numerical modelling, aerial images and field observations to propose that fairy circles arise from plant self-organization. Here we present Australian Aboriginal art and narratives, and soil excavation data, that suggest these regularly spaced, bare and hard circles in grasslands are pavement nests occupied by Drepanotermes harvester termites. These circles, called linyji (Manyjilyjarra language) or mingkirri (Warlpiri language), have been used by Aboriginal people in their food economies and for other domestic and sacred purposes across generations. Knowledge of the linyji has been encoded in demonstration and oral transmission, ritual art and ceremony and other media. While the exact origins of the bare circles are unclear, being buried in deep time and Jukurrpa, termites need to be incorporated as key players in a larger system of interactions between soil, water and grass. Ecologically transformative feedbacks across millennia of land use and manipulation by Aboriginal people must be accounted for. We argue that the co-production of knowledge can both improve the care and management of those systems and support intergenerational learning within and across diverse cultures.

A Quantized Representation of Intertemporal Choice in the Brain.

Value [4][5] is typically modeled using a continuous representation (i.e., a Real number). A discrete representation of value has recently been postulated [6]. A quantized representation of probability in the brain was also posited and supported by experimental data [7]. Value and probability are inter-related via Prospect Theory [4][5]. In this paper, we hypothesize that intertemporal choices may also be quantized. For example, people may treat (or discount) 16 days indifferently to 17 days. To test this, we analyzed an intertemporal task by using 2 novel models: quantized hyperbolic discounting, and quantized exponential discounting. Our work here is a re-examination of the behavioral data previously collected for an fMRI study [8]. Both quantized hyperbolic and quantized exponential models were compared using AIC and BIC tests. We found that 13/20 participants were best fit to the quantized exponential model, while the remaining 7/20 were best fit to the quantized hyperbolic model. Overall, 15/20 participants were best fit to models with a 5-bit precision (i.e., 25 = 32 steps). In conclusion, regardless of hyperbolic or exponential, quantized versions of these models are better fit to the experimental data than their continuous forms. We finally outline some potential applications of our findings.

A Quantized Representation of Probability in the Brain.

Conventional and current wisdom assumes that the brain represents probability as a continuous number to many decimal places. This assumption seems implausible given finite and scarce resources in the brain. Quantization is an information encoding process whereby a continuous quantity is systematically divided into a finite number of possible categories. Rounding is a simple example of quantization. We apply this information theoretic concept to develop a novel quantized (i.e., discrete) probability distortion function. We develop three conjunction probability gambling tasks to look for evidence of quantized probability representations in the brain. We hypothesize that certain ranges of probability will be lumped together in the same indifferent category if a quantized representation exists. For example, two distinct probabilities such as 0.57 and 0.585 may be treated indifferently. Our extensive data analysis has found strong evidence to support such a quantized representation: 59/76 participants (i.e., 78%) demonstrated a best fit to 4-bit quantized models instead of continuous models. This observation is the major development and novelty of the present work. The brain is very likely to be employing a quantized representation of probability. This discovery demonstrates a major precision limitation of the brain's representational and decision-making ability.