Back

Habitat remediation followed by managed connectivity reduces unwanted changes in evolutionary trajectory of high extirpation risk populations

Lamka, G. F.; Willoughby, J. R.

2023-12-12 evolutionary biology
10.1101/2023.11.03.565519 bioRxiv
Show abstract

As we continue to convert green spaces into roadways and buildings, connectivity between populations and biodiversity will continue to decline. In threatened and endangered species, this trend is particularly concerning because the cessation of immigration can cause increased inbreeding and loss of genetic diversity, leading to lower adaptability and higher extirpation probabilities in these populations. Unfortunately, monitoring changes in genetic diversity from management actions such as assisted migration and predicting the extent of introduced genetic variation that is needed to prevent extirpation is difficult and costly in situ. Therefore, we designed an agent-based model to link population-wide genetic variability and the influx of unique alleles via immigration to population stability and extirpation outcomes. These models showed that management of connectivity can be critical in restoring at-risk populations and reducing the effects of inbreeding depression; increased connectivity prevented extirpation for the majority of scenarios we considered (71.5% of critically endangered populations and 100% of endangered and vulnerable populations). However, the rescued populations were more similar to the migrant source population (average FST range 0.05 - 0.10) compared to the historical recipient population (average FST range 0.23 - 0.37). This means that these management actions not only recovered the populations from the effects of inbreeding depression, but they did so in a way that changed the evolutionary trajectory that was predicted and expected for these populations prior to the population crash. This change was most extreme in populations with the smallest population sizes, which are representative of critically endangered species that could reasonably be considered candidates for restored connectivity or translocation strategies. Understanding how these at-risk populations change in response to varying management interventions has broad implications for the long-term adaptability of these populations and can improve future efforts for protecting locally adapted allele complexes when connectivity is restored.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

1
Evolutionary Applications
91 papers in training set
Top 0.1%
37.5%
2
Molecular Ecology
304 papers in training set
Top 0.2%
22.7%
50% of probability mass above
3
Philosophical Transactions of the Royal Society B
51 papers in training set
Top 0.5%
6.4%
4
Proceedings of the Royal Society B: Biological Sciences
341 papers in training set
Top 3%
2.5%
5
Conservation Genetics
15 papers in training set
Top 0.1%
2.1%
6
Frontiers in Ecology and Evolution
60 papers in training set
Top 2%
2.1%
7
Evolution Letters
71 papers in training set
Top 1.0%
1.9%
8
Journal of Heredity
35 papers in training set
Top 0.1%
1.9%
9
Ecology and Evolution
232 papers in training set
Top 2%
1.8%
10
Diversity and Distributions
26 papers in training set
Top 0.2%
1.3%
11
Global Change Biology
69 papers in training set
Top 1%
1.3%
12
Conservation Biology
14 papers in training set
Top 0.2%
1.2%
13
eLife
5422 papers in training set
Top 51%
1.0%
14
Scientific Reports
3102 papers in training set
Top 73%
0.8%
15
PLOS Genetics
756 papers in training set
Top 14%
0.8%
16
The American Naturalist
114 papers in training set
Top 2%
0.8%
17
PLOS ONE
4510 papers in training set
Top 69%
0.7%
18
Evolution
199 papers in training set
Top 2%
0.7%
19
Frontiers in Plant Science
240 papers in training set
Top 5%
0.7%
20
BMC Biology
248 papers in training set
Top 6%
0.6%
21
Nature Communications
4913 papers in training set
Top 65%
0.6%
22
Methods in Ecology and Evolution
160 papers in training set
Top 3%
0.5%
23
Molecular Ecology Resources
161 papers in training set
Top 1%
0.5%
24
Biological Conservation
43 papers in training set
Top 0.9%
0.5%