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2019 Project Implementation Review (PIR) PA Mgmt for BD Resilience

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2019 Project Implementation Report 2019 Project Implementation Review (PIR) PA Mgmt for BD Resilience Basic Data ............................................................................................................................................... 2 Overall Ratings ........................................................................................................................................ 3 Development Progress ............................................................................................................................ 4 Implementation Progress ...................................................................................................................... 46 Critical Risk Management ..................................................................................................................... 48 Adjustments .......................................................................................................................................... 49 Ratings and Overall Assessments ........................................................................................................ 50 Gender .................................................................................................................................................. 58 Social and Environmental Standards .................................................................................................... 61 Communicating Impact ......................................................................................................................... 63 Partnerships .......................................................................................................................................... 68 Annex - Ratings Definitions ................................................................................................................... 73 Page 1 of 73 2019 Project Implementation Report A. Basic Data Project Information UNDP PIMS ID 5152 GEF ID 5080 Title Transforming Management of Protected Area/Landscape Complexes to Strengthen Ecosystem Resilience Country(ies) Peru, Peru UNDP-GEF Technical Team Ecosystems and Biodiversity Project Implementing Partner Government Joint Agencies (not set or not applicable) Project Type Full Size Project Description 1. The proposed project aims to transform the management of vulnerable ecosystems in Peru's mountain ecosystems to alleviate the direct and indirect impacts of climate change (CC) on globally significant biodiversity and ecosystem functionality. This will be achieved through a three-pronged approach: development of management systems (monitoring and early warning systems, management decision making tools and sustainable financing) in order to optimize readiness at national level to address the anticipated implications of CC on mountain ecosystems; expanding and strengthening PAs in landscapes that are particularly sensitive to climate change, in order to protect refugia and corridors and to build readiness to address specific CC impacts; and promoting sustainable land management in the landscape immediately surrounding these PAs in order to anticipate the increased threats that current land uses may pose to biodiversity and ecosystem functions. This is necessary to reduce pressures on the ecosystem, in order to render them more resilient to the expected impacts of climate change. Project Contacts UNDP-GEF Regional Technical Adviser Mr. Lyes Ferroukhi ([email protected]) Programme Associate Ms. Maria Lukina-Lebedeva (maria.lukina- [email protected]) Project Manager Michael Valqui ([email protected]) CO Focal Point Mr. James Leslie ([email protected]) GEF Operational Focal Point Ms. Martha Cuba Villafuerte ([email protected]) Project Implementing Partner José Carlos Nieto ([email protected]) Other Partners (not set or not applicable) Page 2 of 73 2019 Project Implementation Report B. Overall Ratings Overall DO Rating Moderately Satisfactory Overall IP Rating Moderately Satisfactory Overall Risk Rating Moderate Page 3 of 73 2019 Project Implementation Report C. Development Progress Description Objective to enhance the resilience of vulnerable ecosystems to the impacts of climate change in PAs and surrounding landscapes , and thereby to secure their biodiversity and ecosystem functionality and derivative ecosystem services including greenhouse gas sequestration and emissions reduction Description of Indicator Baseline Level Midterm target End of project Level at 30 June 2018 Cumulative progress since level target level project start MODIFIED INDICATOR: MODIFIED BASELINE: (not set or not MODIFIED The loss of forest cover for 2016 is (official According to the official applicable) TARGET: information from the PNCBMCC-MINAM): information from the O1. Reductions in the rates of Habitat / Annual loss (ha) PNCBMCC-MINAM, the loss of loss of principal habitat types / Total loss over project Habitat / Total loss PY: 11,558ha forest cover for our two (Peruvian yungas (PY), South period (without project) over project period landscapes for 2017 was larger Amazonian moist forest (with project) / Net SAMF: 23,322ha PY / 9,933 / 49,655 than for 2016 in the three (SAMF), and Central Andean avoided loss due to CAP: 28ha biomes: Puna (CAP), generating SAMF / 21,280 / 106,400 project benefits for BD and avoiding the (Annex 01 – Monitoring data) loss of carbon sinks CAP / 33 / 165 PY / 44,699 / 4,967 ha / 367,620 tC PY: 14 553 ha Total / 31,246 / 156,230 SAMF / 95,760 / For the landscapes the loss is: SAMF: 27 927 ha OLD INDICATOR: 10,640 ha / YESI: 24,329ha 1,083,790 tC CAP: 139 ha O1. Reductions in the rates of OLD BASELINE: PUMA: 10,579ha loss of principal habitat types in CAP/ 149 / 17 ha / Habitat / Annual loss (ha) the landscapes (Peruvian 513 tC / Total loss over project (Annex 02 a, b) Total: 42 619 ha yungas (PY), South Amazonian period (without project) moist forest (SAMF), and Total / 140,607 / Central Andean Puna (CAP), 15,623 ha / PY / 11,952 / 59,760 It is worth mentioning that at a national level These increases in the generating benefits for BD and 1,451,924 tC the annual deforestation rate increased from deforestation rates can be avoiding the loss of carbon SAMF / 20,585 / 102,925 156,462ha in 2015 to 164,662ha in 2016 attributed to several factors sinks CAP / 0 / 0 external to the project's impact OLD TARGET: http://www.actualidadambiental.pe/?p=46292 as already explained in last Total / 32,537 / 162,685 Habitat / Total loss year's PIR: i) changing weather over project period (drier years correlate higher (with project) / Net probability of fires), ii) changing Page 4 of 73 2019 Project Implementation Report avoided loss due to Among the six regions with most of the policies and programs related project deforestation (85%), four are partially to land use, and increasing included in our two landscapes: Ucayali availability of funds from the PY / 53,784 / 5,976 (18%), Huánuco (11%), Madre de Dios public and private sectors to ha 1,204,762 tC (10%) and Junín (10%). However, Huánuco, invest in agriculture and other SAMF / 92,632 / Madre de Dios and Ucayali saw a reduction deforesting activities, among 10,293 ha / in their rates of forest loss from 2015 to others. 2016. 3,762,915 tC CAP/ 0 / 0 ha / 0 tC The main drivers for deforestation are land clearing for small scale agriculture, cattle It is important to consider the Total / 146,416 / ranching, as well as palm oil and small scale following about the usefulness 16,269 ha / gold mining. of this indicator to measure the 4,967,677 tC project's impact: Comment: We recommend to review this indicator because: 1. As the now available 1. The project's direct data shows there is great variability in the impact is necessarily small year to year deforestation rates, where el since the areas were the project Niño or a change of regional governments works to improve crop practices can produce changes, i.e the noise would are less than 0.05% of the total probably drown the signal of a potentially area. positive change. 2. Our intervention supporting municipal land planning, or creating new areas probably effects changes 2. The current official data that are not immediately perceivable, but severely overestimates the probably will show in 3 or more years in the deforestation rates inside future. (Annex 3). protected areas and the baseline deforestation was determined using low The same argument can be made for other, deforestation years (from 2001 also very general indicators (O3, O4, 1.1) to 2008). which probably react to dynamics hardly attributable to the project's activities as they are being implemented. 3. a time lag of several years of potential impact from our project's policy and land planning work, such as the Page 5 of 73 2019 Project Implementation Report We could seize the opportunity and discuss PDLC (local development it during the Mid term review. plans) NOTES: Specifically for protected areas with very little deforestation, the false positives are a problem, i.e. estimations of deforestation inside protected areas are consistently too high. For example, in the case of Alto Purus National Park (PNAP), the official deforestation for the area in 2015 is 314.42 ha. In contrast our deforestation data, which specifically distinguished anthropogenic and natural causes did determine deforestation attributable to human intervention to be 0 (zero) ha. However, the Project is working with SERNANP to reduce false positives without increasing the proportion of false negatives, i.e. not detecting deforestation
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