The impact of invasive species on social-ecological systems: Relating supply and use of selected provisioning ecosystem services

Linders, Theo E. W.; Bekele, Ketema; Schaffner, Urs; Allan, Eric; Alamirew, Tena; Choge, Simon; Eckert, Sandra; Haji, Jema; Muturi, Gabriel M.; Mbaabu, Purity Rima; Shiferaw, Hailu; Eschen, René

doi:10.1016/j.ecoser.2019.101055

Cited by 47 publications

(28 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In order to avoid the latter, we decided to only consider the value for the costliest species for each country and our estimate is to be considered as conservative. This is even more so, since other weed species impact on the quality of grazing land, but our results appear to confirm the important impact of L. camara on grazing land [Swarbrick et al 1995, in CABI (2015] and fodder availability (Shackleton et al 2017a, b) and of P. juliflora on income from livestock (Linders et al 2020).…”

Section: Reductions In Livestock-based Incomesupporting

confidence: 79%

“…Although capital is held as livestock, we only estimated income based on livestock; our estimate was based on the number of livestock held and this IAS impact is comparable to crop yield losses for farming. Although in our study the impact of IAS on livestock derived income is small compared to the other estimates, the impacts of IAS on livestock numbers and thus on capital on the household or community level can be significant (Linders et al 2020). Estimating the impacts of weeds on grasslands, and how this reduced the carrying capacity, was limited by the availability of distribution and impact data for the IAS, which restricted the number of species for which we were able to estimate impacts across the continent, and was further complicated by the frequent cooccurrence of species that makes it impossible to attribute impacts to a single species and introduces the risk of double counting of costs.…”

Section: Reductions In Livestock-based Incomementioning

confidence: 57%

See 1 more Smart Citation

Towards estimating the economic cost of invasive alien species to African crop and livestock production

et al. 2021

Self Cite

View full text Add to dashboard Cite

Background Invasive alien species (IAS) cause significant economic losses in all parts of the world. Although IAS are widespread in Africa and cause serious negative impacts on livelihoods as a result of yield losses and increased labour costs associated with IAS management, few data on the impacts are available in the literature and the magnitude and extent of the costs are largely unknown. We estimated the cost of IAS to agriculture, the most important economic sector in Africa. Methods Data on the monetary costs of IAS to mainland Africa as well as information about the presence and abundance of the most important IAS were collected through literature review and an online survey among a wide variety of stakeholders. Using this and additional data from publicly available sources we estimated yield losses and management costs due to IAS in agriculture for individual countries and the entire continent. Where the data allowed, the costs for selected IAS or crops were estimated separately. The estimates were extrapolated using production and distribution data and/or matching of agro-ecological zones. Results The total estimated annual cost of IAS to agriculture in Africa is USD 3.66 Tn. Yield losses, reductions in livestock derived income and IAS management costs, mainly labour costs, constitute the majority of the estimated cost (ca. 1, < 1 and 99 percent, respectively). The IAS causing the highest yield losses were Phthorimaea absoluta (USD 11.4 Bn) and Spodoptera frugiperda (USD 9.4 Bn). Conclusions This study reveals the extent and scale of the economic impacts of IAS in the agricultural sector in one of the least studied continents. Although the cost estimate presented here is significant, IAS also cause major costs to other sectors which could not be assessed due to data deficit. The results highlight the need for pre-emptive management options, such as prevention and early detection and rapid response to reduce huge potential future costs, as well as measures that contribute to large-scale control of widely established IAS at little cost to farmers and other affected land users, to reduce losses and improve livelihoods.

show abstract

Section: Reductions In Livestock-based Incomesupporting

confidence: 79%

Section: Reductions In Livestock-based Incomementioning

confidence: 57%

Towards estimating the economic cost of invasive alien species to African crop and livestock production

et al. 2021

Self Cite

View full text Add to dashboard Cite

show abstract

“…Of all reference points, 30% (205 points) were presence while 70% (475 points) were absence data. This share was chosen considering the previous distribution of Prosopis in the area (Linders et al 2020). Field data were collected throughout the study area and 200 m was the minimum distance among the points.…”

Section: Presence and Absence Datamentioning

confidence: 99%

Species Distribution Modelling performance and its implication for Sentinel-2-based prediction of invasive Prosopis juliflora in lower Awash River basin, Ethiopia

2021

View full text Add to dashboard Cite

Background Species Distribution Modelling (SDM) coupled with freely available multispectral imagery from Sentinel-2 (S2) satellite provides an immense contribution in monitoring invasive species. However, attempts to evaluate the performances of SDMs using S2 spectral bands and S2 Radiometric Indices (S2-RIs) and biophysical variables, in particular, were limited. Hence, this study aimed at evaluating the performance of six commonly used SDMs and one ensemble model for S2-based variables in modelling the current distribution of Prosopis juliflora in the lower Awash River basin, Ethiopia. Thirty-five variables were computed from Sentinel-2B level-2A, and out of the variables, twelve significant variables were selected using Variable Inflation Factor (VIF). A total of 680 presence and absence data were collected to train and validate variables using the tenfold bootstrap replication approach in the R software “sdm” package. The performance of the models was evaluated using sensitivity, specificity, True Skill Statistics (TSS), kappa coefficient, area under the curve (AUC), and correlation. Results Our findings demonstrated that except bioclim all machine learning and regression models provided successful prediction. Among the tested models, Random Forest (RF) performed better with 93% TSS and 99% AUC followed by Boosted Regression Trees (BRT), ensemble, Generalized Additive Model (GAM), Support Vector Machine (SVM), and Generalized Linear Model (GLM) in decreasing order. The relative influence of vegetation indices was the highest followed by soil indices, biophysical variables, and water indices in decreasing order. According to RF prediction, 16.14% (1553.5 km2) of the study area was invaded by the alien species. Conclusions Our results highlighted that S2-RIs and biophysical variables combined with machine learning and regression models have a higher capacity to model invasive species distribution. Besides, the use of machine learning algorithms such as RF algorithm is highly essential for remote sensing-based invasive SDM.

show abstract

“…This is, in part, owing to the context-dependent impacts of invaders (see section 2) and because environmental change can alter the balance of positive and negative effects (McLaughlan et al 2014). For instance, disturbed river banks and roadsides in Africa favor proliferation of the invasive tree, Prosopis juliflora (Shiferaw et al 2019), which increases local income from wood sales, but reduces habitat suitable for livestock and results in lower income from cattle sales (Linders et al 2020). The predicted future effect of interactions among climate, socioeconomic factors, and invasions on plant biodiversity hotspots constitutes the greatest threat in emerging economies located in megadiverse regions of the Southern Hemisphere (Seebens et al 2015).…”

Section: Changes To Ecosystem Services and Human Well-beingmentioning

confidence: 99%

Four priority areas to advance invasion science in the face of rapid environmental change

et al. 2021

View full text Add to dashboard Cite

Unprecedented rates of introduction and spread of non-native species pose burgeoning challenges to biodiversity, natural resource management, regional economies, and human health. Current biosecurity efforts are failing to keep pace with globalization, revealing critical gaps in our understanding and response to invasions. Here, we identify four priority areas to advance invasion science in the face of rapid global environmental change. First, invasion science should strive to develop a more comprehensive framework for predicting how the behavior, abundance, and interspecific interactions of non-native species vary in relation to conditions in receiving environments and how these factors govern the ecological impacts of invasion. A second priority is to understand the potential synergistic effects of multiple co-occurring stressors – particularly involving climate change – on the establishment and impact of non-native species. Climate adaptation and mitigation strategies will need to consider the possible consequences of promoting non-native species, and appropriate management responses to non-native species will need to be developed. The third priority is to address the taxonomic impediment. The ability to detect and evaluate invasion risks is compromised by a growing deficit in taxonomic expertise, which cannot be adequately compensated by new molecular technologies alone. Management of biosecurity risks will become increasingly challenging unless academia, industry, and governments train and employ new personnel in taxonomy and systematics. Fourth, we recommend that internationally cooperative biosecurity strategies consider the bridgehead effects of global dispersal networks, in which organisms tend to invade new regions from locations where they have already established. Cooperation among countries to eradicate or control species established in bridgehead regions should yield greater benefit than independent attempts by individual countries to exclude these species from arriving and establishing.

show abstract

The impact of invasive species on social-ecological systems: Relating supply and use of selected provisioning ecosystem services

Cited by 47 publications

References 52 publications

Towards estimating the economic cost of invasive alien species to African crop and livestock production

Towards estimating the economic cost of invasive alien species to African crop and livestock production

Species Distribution Modelling performance and its implication for Sentinel-2-based prediction of invasive Prosopis juliflora in lower Awash River basin, Ethiopia

Four priority areas to advance invasion science in the face of rapid environmental change

Contact Info

Product

Resources

About