Scaling participation in payments for ecosystem services programs

<div><p>Payments for ecosystem services programs have become common tools but most have failed to achieve wide-ranging conservation outcomes. The capacity for scale and impact increases when PES programs are designed through the lens of the potential participants, yet this has received little attention in research or practice. Our work with small-scale marine fisheries integrates the social science of PES programs and provides a framework for designing programs that focus <i>a priori</i> on scaling. In addition to payments, desirable non-monetary program attributes and ecological feedbacks attract a wider range of potential participants into PES programs, including those who have more negative attitudes and lower trust. Designing programs that draw individuals into participating in PES programs is likely the most strategic path to reaching scale. Research should engage in new models of participatory research to understand these dynamics and to design programs that explicitly integrate a broad range of needs, values, and modes of implementation.</p></div

Participation probabilities based on (A) attitudes toward participation, (B) trust that facilitating conditions implement the program exists, and (C) fisher’s dependence on the resource for the livelihood.

<p>Participation probabilities based on (A) attitudes toward participation, (B) trust that facilitating conditions implement the program exists, and (C) fisher’s dependence on the resource for the livelihood.</p

Scaling participation in payments for ecosystem services programs - Fig 1

<p>(A) A TURF-reserve program compensates Chilean fishing associations annually for setting aside a portion of their formal fishing grounds as a no-take reserve. The fishing association conducts anti-poaching surveillance. A third-party video-monitoring system monitors the no-take reserve for any contract breach. Baselines and control sites are established and biodiversity is monitored to document outcomes. (B) Some of the over 700 TURFs along the coastline of Chile showing coverage of all bioregions. Our study was conducted in the Central bioregion.</p

TURF-reserve program characteristics and levels evaluated.

<p>Levels in bold were empirically identified as the most desirable program conditions from the fishers’ perspectives.</p

Scaling participation in payments for ecosystem services programs - Fig 2

<p>(A) Predicted probability of approving a TURF-reserve program between the most and least desirable program, based on fisher preferences or program characteristics and outcomes. Payments have a positive effect on approval for both programs, but approval differs drastically, with the undesirable program never reaching majority (50%) approval. The effect of contract length on approval for undesirable (B) and desirable (C) programs reveals a tradeoff (highlighted in green): the probability of accepting an unfavorable 10-year contract at US$2,750 per year (probability = 0.39) in an otherwise desirable program is higher than the probability of accepting a favorable 2-year contract at the same payment level (probability = 0.26) in an otherwise undesirable program.</p

Single molecule sequencing of the M13 virus genome without amplification

<div><p>Next generation sequencing (NGS) has revolutionized life sciences research. However, GC bias and costly, time-intensive library preparation make NGS an ill fit for increasing sequencing demands in the clinic. A new class of third-generation sequencing platforms has arrived to meet this need, capable of directly measuring DNA and RNA sequences at the single-molecule level without amplification. Here, we use the new GenoCare single-molecule sequencing platform from Direct Genomics to sequence the genome of the M13 virus. Our platform detects single-molecule fluorescence by total internal reflection microscopy, with sequencing-by-synthesis chemistry. We sequenced the genome of M13 to a depth of 316x, with 100% coverage. We determined a consensus sequence accuracy of 100%. In contrast to GC bias inherent to NGS results, we demonstrated that our single-molecule sequencing method yields minimal GC bias.</p></div

Read length distribution after length and repeat filters (blue bars) and after alignment (red bars).

<p>Read length distribution after length and repeat filters (blue bars) and after alignment (red bars).</p

Sample preparation and sequencing process for single molecule sequencing of biological samples.

<p>Sample preparation and sequencing process for single molecule sequencing of biological samples.</p

Coverage depth distribution.

<p>(A) Coverage depth for each base on M13 reference. The average coverage depth is 316x±96x. (B) Coverage rate as a function of coverage depth.</p

M13 genome sequencing statistics.

<p>M13 genome sequencing statistics.</p